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PROCESS PLANNING FOR SHAPE DEPOSITION MANUFACTURING

a dissertation submitted to the department of mechanical engineering and the committee on graduate studies of stanford university in partial fulfillment of the requirements for the degree of doctor of philosophy

By Krishnan Ramaswami January 1997

c Copyright 2000 by Krishnan Ramaswami

All Rights Reserved

ii

I certify that I have read this dissertation and that in my opinion it is fully adequate, in scope and quality, as a dissertation for the degree of Doctor of Philosophy.

Friedrich B. Prinz (Principal Adviser)


Kosuke Ishii


David Beach

Approved for the University Committee on Graduate Studies:

iii

Abstract

Solid Freeform Fabrication (SFF) refers to a class of rapid manufacturing process that builds parts by incremental material deposition and fusion of thin 2-1/2 dimensional layers. Over this past decade, SFF has taken the manufacturing industry to new heights.

However, parts produced by SFF processes exhibit a stair-step surface

texture due to the presence of 2-1/2 dimensional layers and exhibit limited material properties. These issues are addressed by a modified SFF process called Shape Deposition Manufacturing. Shape Deposition Manufacturing (SDM) is a novel layered manufacturing process in which multi-material structures with embedded components can be fabricated. In SDM, the layers are truly three dimensional in nature and are built using a combination of material addition and material removal processes. The need for an automated and robust process planner is more in the case of SDM as it attempts to build fully functional parts directly from CAD models. This thesis focuses on the process planning issues in Shape Deposition Manufacturing. The major issues in process planning for SDM involves the generation of 3-D layers and generation of deposition and CNC cutter paths for these 3-D layers. In SDM, the CAD model is decomposed into 3-D layers of varying thickness based upon both geometric and material criteria.

The layers are further decomposed

into manufacturable volumes called compacts. Silhouette edges and silhouette loops are identified to help the decomposition of models into 3-D layers and compacts. Unlike techniques used in existing SFF methods which divide models into equally spaced slices, the present algorithm decomposes models into compacts which are iv

not necessarily planar and equally spaced. Solely based on geometric evaluations a feasible sequence of material addition and removal processes is found for these compacts. Each compact is deposited to the near-net shape using material deposition techniques. Deposition paths are generated for the 2-D cross-section obtained by the XY projection of the compact. The compact is then machined to the required shape through a series of CNC cutting operations. The absence of fixturing problems and tool accessibility problems helps in fully automating the generation of CNC cutter paths. Several parts of varying complexity were built using this process planner and the results will be discussed.

v

Acknowledgements I take this opportunity to express my sincere appreciation to my adviser Prof. Fritz Prinz for his support and guidance in pursuing this research. He kept me free of financial worries and provided the much needed encouragement over the last four years. He provided an excellent research atmosphere that was very helpful in the successful completion of this work. I would like to thank Prof. Kincho Law for serving as the chair of my thesis committee. I would also like to thank the other members of my thesis committee, Prof. David Beach, Prof. Kos Ishii and Prof. Paul Losleben for their valuable comments and useful suggestions. Thanks are also due to Prof. Yasushi Yamaguchi of Univ. of Tokyo for many exciting and useful discussions. I am grateful to my former colleagues of the Engineering Design Research Center at Carnegie Mellon University and the current colleagues of the Rapid Prototyping Lab at Stanford University for their support and encouragement in the course of this research. In particular, I would like to thank Dr. Levent Gürsöz for the inspiring conversations during the initial stages of this work, and Dr. Robert Merz for his valuable suggestions on different aspects of this work. I would also like to thank Sylvia Walters for efficiently handling all the administrative details. I want to thank my friends in the different parts of this country for their support and friendship. In particular, my friends in Pittsburgh and Bay area deserve special credit for making me feel at home by providing an enjoyable social atmosphere. Finally, I wish to express my special thanks to my father and the other members of my family for their support and encouragement during the course of this work.

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Contents Abstract

iv

Acknowledgements

vi

1 Introduction

1

1.1

Problem Statement . . . . . . . . . . . . . . . . . . . . . . . . . . . .

1

1.2

Solid Freeform Fabrication . . . . . . . . . . . . . . . . . . . . . . . .

2

1.2.1

Review of SFF processes . . . . . . . . . . . . . . . . . . . . .

3

1.2.2

Limitations of SFF . . . . . . . . . . . . . . . . . . . . . . . .

6

1.3

Present Work . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

7

1.4

Thesis Outline . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

8

2 Shape Deposition Manufacturing

11

2.1

The SDM Process . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

11

2.2

Process planning . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

14

2.3

Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

18

3 Spatial Decomposition

20

3.1

Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

20

3.2

Overview . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

22

3.2.1

Definitions . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

22

3.2.2

Basic concepts . . . . . . . . . . . . . . . . . . . . . . . . . . .

23

3.2.3

Related work . . . . . . . . . . . . . . . . . . . . . . . . . . .

26

3.2.4

Requirements . . . . . . . . . . . . . . . . . . . . . . . . . . .

27

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3.3

Algorithm . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

28

3.4

Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

36

4 Deposition Path Generation

38

4.1

Deposition Methods in SDM . . . . . . . . . . . . . . . . . . . . . . .

39

4.2

Generation of deposition paths . . . . . . . . . . . . . . . . . . . . . .

40

4.2.1

Types of deposition paths . . . . . . . . . . . . . . . . . . . .

41

Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

49

4.3

5 CNC Cutter Path Generation

50

5.1

Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

50

5.2

Rough Cutting . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

51

5.3

Two Dimensional Profile cutting . . . . . . . . . . . . . . . . . . . . .

55

5.4

Offset of TwoD Profiles . . . . . . . . . . . . . . . . . . . . . . . . . .

55

5.5

Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

59

6 3-D Cutter Path Generation

60

6.1

Finishing operation . . . . . . . . . . . . . . . . . . . . . . . . . . . .

60

6.2

Collision Free Paths . . . . . . . . . . . . . . . . . . . . . . . . . . . .

66

6.2.1

Collision types

. . . . . . . . . . . . . . . . . . . . . . . . . .

66

6.2.2

Collision Detection and Avoidance . . . . . . . . . . . . . . .

66

Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

68

6.3

7 Software Issues

70

7.1

Terminology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

70

7.2

CAD system requirements . . . . . . . . . . . . . . . . . . . . . . . .

71

7.3

CAD System Comparison . . . . . . . . . . . . . . . . . . . . . . . .

74

7.4

Implementation issues . . . . . . . . . . . . . . . . . . . . . . . . . .

76

8 Applications 8.1 8.2

79

Geometrically complex parts . . . . . . . . . . . . . . . . . . . . . . .

80

8.1.1

IMS-T2 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

80

Next generation metal tooling . . . . . . . . . . . . . . . . . . . . . .

82

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8.2.1 8.3

GM Injection molding Tool . . . . . . . . . . . . . . . . . . .

83

Non-conventional parts . . . . . . . . . . . . . . . . . . . . . . . . . .

84

8.3.1

Parts with interacting geometric features . . . . . . . . . . . .

84

8.3.2

Conformable, Embedded Electro-mechanical parts . . . . . . .

87

8.3.3

Assembled mechanisms . . . . . . . . . . . . . . . . . . . . . .

89

9 Conclusions and Future work

91

9.1

Contributions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

91

9.2

Future work . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

95

A Kinematic Transformations

99

A.1 Coordinate systems . . . . . . . . . . . . . . . . . . . . . . . . . . . . 100 A.2 Kinematic equations . . . . . . . . . . . . . . . . . . . . . . . . . . . 101 Bibliography

104

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List of Figures 1.1

THE WORKING PRINCIPLE OF SFF . . . . . . . . . . . . . . . . . . . . . . . .

3

2.1

THE SDM PROCESS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

12

2.2

A SCHEMATIC OF THE SDM SETUP . . . . . . . . . . . . . . . . . . . . . . .

13

2.3

DIFFICULTIES WITH CONVENTIONAL CAD/CAM PROCESSES . . . . . . . . . . . .

15

2.4

PROCESS PLANNING STEPS IN SDM . . . . . . . . . . . . . . . . . . . . . .

17

3.1

SEQUENCE OF OPERATIONS

. . . . . . . . . . . . . . . . . . . . . . . . . .

21

3.2

TYPES OF SURFACES

. . . . . . . . . . . . . . . . . . . . . . . . . . . . .

22

3.3

SILHOUETTE EDGES AND LOOPS . . . . . . . . . . . . . . . . . . . . . . . .

23

3.4

PART AND ITS SUPPORT . . . . . . . . . . . . . . . . . . . . . . . . . . . .

24

3.5

COMPACT DECOMPOSITION OF THE PART . . . . . . . . . . . . . . . . . . . . .

24

3.6

COMPACT DECOMPOSITION OF THE SUPPORT . . . . . . . . . . . . . . . . . . .

25

3.7

CYCLIC ORDERING

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

28

3.8

COMPACT DECOMPOSITION USING INFINITE SWEEP

. . . . . . . . . . . . . . . .

29

3.9

FIRST THREE STAGES OF THE ALGORITHM . . . . . . . . . . . . . . . . . . . .

31

3.10 DECOMPOSITION ALONG CONCAVE SILHOUETTE EDGES . . . . . . . . . . . . . .

32

3.11 MODEL WITH SELF-INTERSECTING PROJECTED SILHOUETTE LOOP . . . . . . . . . .

33

3.12 DECOMPOSITION TO ELIMINATE SELF-INTERSECTIONS OF PROJECTED SILHOUETTE LOOP

34

3.13 SPLITTING SILHOUETTE LOOPS TO AVOID CYCLIC ORDERING . . . . . . . . . . . .

35

3.14 COMPACT DECOMPOSITION WITH PROCESS SEQUENCE

. . . . . . . . . . . . . .

36

4.1

WORKING PRINCIPLE OF MICROCASTING . . . . . . . . . . . . . . . . . . . . .

39

4.2

WORKING PRINCIPLE OF LASER DEPOSITION SYSTEM . . . . . . . . . . . . . . .

40

x

4.3

TYPES OF DEPOSITION PATHS . . . . . . . . . . . . . . . . . . . . . . . . . .

42

4.4

MAT OF A RECTANGLE

. . . . . . . . . . . . . . . . . . . . . . . . . . . .

43

4.5

MAT BASED DEPOSITION PATH . . . . . . . . . . . . . . . . . . . . . . . . .

44

4.6

RECTANGULAR HULL CONSTRUCTION . . . . . . . . . . . . . . . . . . . . . .

46

4.7

ZIGZAG PATH GENERATION . . . . . . . . . . . . . . . . . . . . . . . . . . .

47

4.8

TOWER DEPOSITION PATTERN . . . . . . . . . . . . . . . . . . . . . . . . . .

47

4.9

CONVEX DECOMPOSITION FOR DEPOSITION

. . . . . . . . . . . . . . . . . . .

48

4.10 CROSS HATCH DEPOSITION . . . . . . . . . . . . . . . . . . . . . . . . . . .

49

5.1

CNC CUTTING STAGES IN SDM . . . . . . . . . . . . . . . . . . . . . . . . .

51

5.2

PLANING OPERATION

. . . . . . . . . . . . . . . . . . . . . . . . . . . . .

52

5.3

VOLUME Vrc

. . . . . . . . . . . . . . . . . . . . . . . .

53

5.4

STEPS IN THE ROUGH CUT ALGORITHM

. . . . . . . . . . . . . . . . . . . . .

54

5.5

TYPES OF ROUGH CUT PATHS . . . . . . . . . . . . . . . . . . . . . . . . . .

55

5.6

DEGENERACIES IN CURVE OFFSET . . . . . . . . . . . . . . . . . . . . . . .

56

5.7

OFFSET COMPUTATION . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

57

5.8

OFFSET MODEL WITHOUT DEGENERACIES . . . . . . . . . . . . . . . . . . . .

58

6.1

TYPES OF CUTTER REGIONS . . . . . . . . . . . . . . . . . . . . . . . . . .

61

6.2

SURFACE SHRINKING FOR FLAT-END MILLED REGIONS . . . . . . . . . . . . . . .

64

6.3

INTERSECTION CURVES FOR 3-AXIS MILLED REGIONS . . . . . . . . . . . . . . .

65

6.4

TYPES OF GOUGING . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

67

7.1

CAD SYSTEM COMPARISON CHART . . . . . . . . . . . . . . . . . . . . . . .

77

8.1

CAD MODEL OF IMS-T2 . . . . . . . . . . . . . . . . . . . . . . . . . . . .

80

8.2

COMPACT DECOMPOSITION OF THE SUPPORT IN IMS-T2 . . . . . . . . . . . . . .

81

8.3

IMS-T2 MANUFACTURED WITH SDM

. . . . . . . . . . . . . . . . . . . . . .

82

8.4

INJECTION MOLDING TOOL . . . . . . . . . . . . . . . . . . . . . . . . . . .

83

8.5

CAD MODEL OF TILTED FRAMES . . . . . . . . . . . . . . . . . . . . . . . .

84

8.6

SILHOUETTE CURVES AND LOOPS . . . . . . . . . . . . . . . . . . . . . . . .

85

8.7

SPATIAL DECOMPOSITION OF TILTED FRAMES . . . . . . . . . . . . . . . . . . .

86

8.8

TILTED FRAMES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

87

TO BE ROUGH CUT

xi

8.9

. . . . . . . . . . . . . . . . . .

88

8.10 CAD MODEL OF SIMON GAME PIECE . . . . . . . . . . . . . . . . . . . . . . .

88

8.11 SDM-SIMON GAME . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

89

8.12 CRANK AND PISTON MECHANISM . . . . . . . . . . . . . . . . . . . . . . . .

90

VUMAN EMBEDDED ELECTRONIC STRUCTURE

A.1 COORDINATE SYSTEMS . . . . . . . . . . . . . . . . . . . . . . . . . . . . 100

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Chapter 1 Introduction 1.1

Problem Statement

In a global competitive environment that is intense and dynamic, the development of new products and processes increasingly is a focal point of competition. As an example, CAD/CAM systems are required that can quickly produce physical objects directly from CAD models. Rapid fabrication is useful for such manufacturing tasks as prototyping, low-volume parts production and for producing the custom tooling for high-volume production. A new class of manufacturing process, Solid freeform fabrication, addresses this challenge. Solid Freeform Fabrication (SFF) is a class of rapid manufacturing process that builds parts by incremental material deposition and fusion of thin 2-1/2 dimensional layers. Over this past decade, Solid freeform fabrication has taken the manufacturing industry to new heights. However, parts produced by SFF processes exhibit a stair-step surface texture due to the presence of 2-1/2 dimensional layers and exhibit limited material properties. These issues are addressed by a modified SFF process called Shape Deposition manufacturing (SDM).In SDM, layers are truly three dimensional in nature. In SDM, parts are built by incremental material deposition and material removal of these 3-D layers. Naturally a new manufacturing process such as SDM poses new challenges in process planning. This thesis focuses on the process planning issues in Shape Deposition Manufacturing. 1

CHAPTER 1. INTRODUCTION

2

The need for an automated and robust process planner is important in the case of SDM as it attempts to build fully functional parts directly from CAD models. The major issues in process planning for SDM involves the generation of 3-D layers and generation of deposition and CNC cutter paths for these 3-D layers. 3-D layers of varying thickness are generated from CAD models. The thickness of the layers are based on geometric and process constraints. Deposition paths are generated for depositing these layers. The deposited layer is then machined to the required shape through a series of CNC cutting operations. The CNC cutter paths are generated for roughing and finishing operations. The generation of CNC cutter paths has to be fully automatic as human intervention with so many layers would render the process impractical.

1.2

Solid Freeform Fabrication

Solid Freeform Fabrication [42], [70] is an emerging manufacturing technology that builds parts directly from CAD models using only material addition rather than the conventional material removal processes. SFF, which is also known as desktop manufacturing, is actually a subset to the rapid-prototyping area of net-shape manufacturing. In SFF, a three dimensional solid or surface model of CAD design is geometrically sectioned into planar layers of constant thickness (Figure 1.1). Each cross-sectional planar layer is then sent to a SFF machine. Each layer is created by incremental material build-up of the two-dimensional cross section to a uniform thickness. The overhanging regions of the part are supported either by a sacrificial support material, (Figure 1.1) or by predesigned supports like pillars and trusses that are built into the part model. The support structure is removed after the model building is completed. One of the main advantages of SFF is its ability to build complex parts from a CAD model in a very short time with very little human intervention. With SFF, the prototype of a complex part can be built in a short time, therefore designers and engineers can evaluate a design very quickly. This will help in substantially reducing the total time from concept to full-scale production. SFF is also used in making


3

Planar Cross-Section

3-D Geometry Decomposition

Sacrificial Support Material

Primary Material

Figure 1.1: THE WORKING PRINCIPLE OF SFF molds and dies with lower toolmaking time and cost. Due to its sequential, layered approach SFF can be used to build parts that would be impractical or impossible to build with traditional approaches. Some examples would be parts with internal channels or parts with mechanisms assembled during fabrication.

1.2.1

Review of SFF processes

Stereolithography (SLA) SLA [33] is the first commercially available SFF process. An elevator platform is submerged in a vat of liquid photo-polymeric resin and held near the surface. A low-power ultraviolet laser scans the surface of the liquid to partially cure the layer. After a layer is built, the elevator drops a user specified distance and a new coating of liquid resin covers the solidified layer and a new layer is scanned by the laser. When all layers are completed, the part is removed, cleaned and post-cured in a fluorescent oven with ultraviolet light to solidify any uncured resin. The part is finished by sanding and/or glass-bead blasting. For parts with overhanging features, support structures are needed. The support structure consists of vertical members extending from the platform to the part. The process planning effort in SLA is trivial. It consists of determination of layer cross-sections and generation of laser scan paths for the cross-section. A more challenging planning effort would be the


4

automatic design of support structures [29]. Fused deposition modeling (FDM) In an FDM process [32], a spool of thermoplastic filament feeds into a heated nozzle which traces an exact outline of each cross-section layer of the part. The movement of the nozzle is controlled by a computer. The material solidifies in 0.1s after exiting the nozzle. After one layer is finished, the nozzle moves up a programmed distance in z direction for building the next layer. Due to the short solidification time, FDM process does not need supports. But in some cases, a support may still be required to reduce part distortion. The process planning effort in FDM consists of generation of paths for nozzle motion. In complex parts, design of support structure needs to be handled. Laminated object manufacturing (LOM) The LOM process [19] produce parts from bonded paper, plastic, metal or composite sheet stock. In this process, a layer of sheet material is glued or welded to the previous layer, and then a laser beam follows the contour of the part cross-section to cut it to the required shape. The excess material of every sheet is either removed by vacuum suction or remains as next layer’s support. The process planning involves generation of contours to be followed by the laser. Solid ground curing Cubital’s Solider [39] process uses a photo-masking technique to solidify a whole layer of liquid photo-polymer at one time.

A mask is

generated by electrostatically charging a glass plate with a negative image of the layer’s cross-section. The mask is then positioned over a uniform layer of liquid photo-polymer and exposed under the ultraviolet light such that only the area shaded by the mask is left in liquid form. The liquid polymer is removed and is replaced with hot wax. After the wax has cooled, the layer is milled flat to the specified thickness. The mask plate is discharged and the cycle is repeated. When the part is constructed, the supporting wax is removed either by melting or by using a solvent. The process planning effort is mainly in the generation of mask.


5

Selective laser sintering(SLS) SLS [12] uses laser to sinter successive layers of powder instead of liquid. In the SLS process, a thin layer of heat-fusible powder is a spread over a surface by a counter-rotating roller. A laser traces the crosssection of the layer on the powder surface, sintering the portions exposed to the laser beam. The roller spreads another layer of powder over the sintered one and the process continues till the part is completed. The unsintered powder on every layer acts as support during the building process. Post processing of SLS parts involves the removal of binder. The process planning effort involves the generation of laser trajectories. With some materials, the product may suffer shrinkage and warpage due to sintering and cooling. In such cases, an interesting process planning problem would to be offset for shrinkage in the CAD model. Three-dimensional printing (3D Printing) 3D printing [53] is another powder based SFF technique. In this process, an inkjet sprays liquid binder onto a layer of powder tracing out the cross-sectional pattern. Another layer of powder is spread over the previous one and the process is repeated. After completion the part is subjected heat treatment to enhance the bonding of the glued powder and then the unbonded powder is removed. The unbonded powder of each layer serves as the support during the layering process. Generation of cross-sectional pattern for the inkjet is the main process planning issue. During the sintering process there might be significant shrinkage. Modification in the CAD model to account for this shrinkage will be an interesting process planning problem. Ballistic particle manufacturing (BPM) In BPM, a piezo-driven inkjet nozzle is used to shoot molten material droplets that cold-weld onto a previously deposited layer. The cross section of the layer is scanned by the nozzle. After a layer is formed, the base plate is lowered by a specified distance and a new layer is created over the previous layer and this is repeated till the part is completed. Support structures are needed to support overhanging features. The support material that is used is a water-soluble synthetic wax. The process planing effort is to generate deposition paths for the nozzle. In order to avoid excess material in any area, different deposition path patterns have to be explored.


6

Recursive mask and deposit(MD ∗ ) MD ∗ [68] is based on thermal spraying in which parts are manufactured by successively spraying cross-sectional layers. A disposable paper mask of the part cross-section is cut out with a laser. The mask is placed on the top layer of the growing part and the material is thermally sprayed through the mask by a robotically manipulated spray gun. Since the material being sprayed can be changed layer by layer or within a layer, multi-material parts can be manufactured by this process. Support is provided by a portion of mask in low melting material and by a sacrificial low melting support material for high melting materials. The process planning effort involves generation of laser beam trajectories to cut each cross-section.[45]

1.2.2

Limitations of SFF

While the SFF processes are very useful for rapidly creating prototypes, there are inherent limitations in these processes for creating high quality functional parts. The limitations could be classified under geometric and process and material categories. Geometric limitations In all SFF processes, layers consist of two-dimensional cross-sections that are built up to a uniform thickness. This will result in a stair-step surface texture (Figure 1.1). Also, many of the SFF process uses a faceted geometry as the input model. In a faceted representation, a higher tessellation resolution is needed for creating an accurate model. While a higher resolution works for simple models, it becomes almost impractical in the case of complex models with freeform surfaces. Process and Material limitations None of the SFF processes have the capability to produce parts with properties equivalent to those made with conventional manufacturing technologies. SFF parts have to be post-processed before they can be used. Most of the post-processing methods either modify the properties of the material or alter the shape of the part. For example, in 3D printing, liquid infiltration is done in order to produce dense parts and this might affect the resulting material properties. In SLS, parts might suffer shrinkage due to sintering and cooling. In theory, shrinkage can be compensated by modifying


7

the original CAD model, but it is very difficult to predict the actual shrinkage for any complex shape. Shrinkage might also cause the buildup of residual stresses. Residual stresses will also be caused due to temperature gradients between layers. These residual stresses might lead to distortions and delaminations. The poor surface quality could also be partially attributed to the material deposition process. During the material deposition process, the surface tension of the material prevents the generation of geometrically well-defined surfaces between layers . The current SFF processes are restricted to a limited set of materials. Processes like SLA, Solid ground curing and FDM are restricted to polymers. Processes like SLS and 3D printing use a wider range of materials but have shrinkage problems. Thus while offering the benefit of building complex parts directly from CAD models in a short time, SFF suffers from poor geometric and material tolerances. On the other hand, conventional methods using CNC machining can deliver high geometric and material quality, but are limited in part complexity. CNC machining is also expensive and requires human intervention for generating CNC cutter paths and for designing and selecting fixtures. Thus a process that combines the layered principle of SFF processes and the accuracy of CNC machining will seem to be a step in the right direction. Shape deposition manufacturing (SDM) is such a process that takes advantage of both material addition and material subtraction.

1.3

Present Work

This work addresses the process planning issues in SDM. Being a new manufacturing process, SDM poses new challenges in process planning. As a first effort, the process planning steps in SDM are identified. The major steps in process planning for SDM involves the generation of compacts

1

and generation of deposition and CNC cutter

paths for these compacts. An algorithm for the decomposition of any CAD model into compacts is described. This decomposition facilitates the manufacture of complex, 1

A compact is a manufacturable volume in SDM and will be described in Chapter 3.


8

multi-material objects in SDM. The concept of silhouette loops is introduced to help in this decomposition process. Silhouette edges are identified and are arranged in the form of silhouette loops and the decomposition requirements are expressed in terms of silhouette edges and loops. The decomposition algorithm also generates the process sequence for these compacts. Algorithms for generating deposition paths are described. Some of the factors that influences the derivation of deposition paths are identified. Algorithms for deriving spiral and zigzag deposition paths are described. Methods are also outlined to derive a few other deposition paths from these two types of paths. Algorithms for generating CNC cutter paths for compacts is described. A fully automated approach for CNC cutter path generation is described that takes advantage of the benefits such as absence of fixturing and tool accessibility problems, offered by the SDM process.

A new representation, manhattan solid, has been

proposed for generating efficient rough cutting algorithms. The generation of 2-D cutter paths is made robust by proposing a robust algorithm for offsetting 2-D crosssection. A new classification scheme based on the curvature information has been proposed for the surfaces of the model that helps in generation of fully automatic 3-D cutter paths. A great deal of effort was spent in identifying the ideal CAD system for the implementation of these algorithms. The process planner was implemented in two different CAD systems both of which partially met the requirements. The algorithms have been verified by building several complex test parts.

1.4

Thesis Outline

SDM is a modified solid freeform fabrication process that can manufacture arbitrarily complex shaped structures directly from CAD models in an automated environment. In addition, the SDM process allows the manufacture of multi-material and embedded structures that cannot be produced with the traditional manufacturing techniques. Chapter 2 gives an overview of the SDM process outlining the various processing steps needed to produce a part. Chapter 2 also outlines the process planning issues in SDM. In SDM, the CAD model is decomposed into 3-D layers of varying thickness based


9

upon both geometric and material criteria. The layers are further decomposed into compacts that have all their newly deposited surfaces to be non-undercut. Two approaches to this problem of spatial decomposition are explained in Chapter 3. Both the approaches rely on the generation of silhouette edges. The concept of silhouette edges and the process of generating them will also be explained in Chapter 3 Each compact is deposited to the near-net shape using material deposition techniques. Deposition paths are generated for the 2-D cross-section obtained by the XY projection of the compact. Chapter 4 describes the generation of deposition paths. Due to the nature of the deposition methods, the generation of deposition paths has to avoid revisiting the same position and should not leave any gaps. Chapter 4 also describes the various deposition methods used in SDM. SDM is different than other SFF processes in that it uses both material deposition and material removal processes to build a layer. The material removal process in SDM is done using CNC machining. Chapter 5 describes the generation of CNC cutter paths in SDM. CNC cutter path generation can be broadly separated into two categories, 2-D and 3-D cutter path generation. This chapter mainly deals with 2-D cutter path generation. 2-D cutting can be further classified into rough cutting and 2-D profile cutting, both of which require the offset of 2-D cross-section. Chapter 5 also describes the generation of offsets of 2-D models. Chapter 6 deals with the 3-D cutter path generation. Success has been eluding researchers in automating the generation of CNC cutter paths. It can be partially attributed to fixturing problems and tool accessibility problems. In the case of SDM, the absence of both these problems motivates us to find a method to successfully generate fully automatic 3-D CNC cutter paths. In Chapter 6, such a method is described. The surfaces of the model are subdivided and classified based on the cutting method. Cutter paths are then generated for each of these surface types. During the various process planning steps in SDM, the CAD model undergoes a series of geometric operations.

In order to withstand the complex geometric

operations, a powerful geometric engine should serve as a backbone for the process planner. Chapter 7 describes the requirements of a geometric engine for the process planner. It also describes the geometric modelers that were used for process planning


10

in SDM and some of the implementation difficulties in using those modelers. In Chapter 8 a variety of test parts that were built with the process planner are shown. The process planning problems in building some of those parts are described. Chapter 9 concludes the thesis by outlining the accomplishments of this work. Some of the process planning issues that are not addressed in this work are discussed. Some suggestions for improving some of the methods given in this work are outlined. Appendix A describes the inverse and direct kinematic transforms that are needed to convert the cutter paths into machine codes.

Chapter 2 Shape Deposition Manufacturing Solid Freeform Fabrication (SFF) has been widely investigated as a way to automatically fabricate parts directly from CAD models for applications in the area of rapid prototyping and short-run manufacturing. But it remains a goal to be able to directly build high performance metal shapes using SFF techniques. Fully dense metal parts that have accurate dimensions and good surface appearance are often required for such applications as custom tooling and production-ready prototypes. Shape Deposition Manufacturing (SDM) is a manufacturing technique that attempts to address the issue of directly creating fully functional metal shapes. In addition, SDM also has the potential to produce multi-material, functionally graded, embedded heterogeneous structures made of metal, plastic and ceramic materials.

2.1

The SDM Process

Shape Deposition Manufacturing [25],[43],[44] is a manufacturing process that creates functional metal parts by incremental material deposition and material removal. It combines the benefits of SFF (handling complex geometries), CNC milling (accurate and precise with good surface quality) and weld-based deposition (superior material properties). The steps involved in building parts with SDM is shown in Figure 2.1. In SDM, the CAD model is decomposed into simpler building block called compacts. The compacts are deposited as near-net shape using a deposition method 11

CHAPTER 2. SHAPE DEPOSITION MANUFACTURING

12

Figure 2.1: THE SDM PROCESS such as plasma or laser based deposition process. After deposition, each layer is accurately machined to net shape using CNC milling or EDM. Processes such as shot-peening are used to control the build-up of residual stresses. Sensors, electronic components, prebuilt mechanical parts or circuits can be embedded into each layer. After completing one layer, the next layer is deposited and the process is repeated till the part is completed. In SDM, support for overhanging features is provided by the sacrificial support material. Each layer is embedded in the support material. The CAD model of the support structure is obtained as the compliment of original CAD model. The support structure is built along with the original model and follows the SDM cycle shown in Figure 2.1. After the part is completed, the support material


13

is removed either by a melting or etching process. Multi-material and functionalgradient parts can be built by depositing different materials within each layer following the same cycle. The SDM setup consists several subprocessing stations for material deposition, material removal, cleaning and stress relieving. The parts are built on a pallet that is transported between different stations by a transfer robot. Each station has a pallet receiver mechanism that locates and clamps the pallet. Pallet transfer between individual stations is handled by a control program in the computer. The control program also downloads and executes the trajectories on the individual stations. A schematic of the setup is shown in Figure 2.2. Thermal deposition techniques

Figure 2.2: A SCHEMATIC OF THE SDM SETUP have been explored in SDM in order to produce high quality parts. While spraying techniques suffer from poor bonding properties, traditional welding based approaches suffer from penetration problems created by excessive heat input. In SDM, material is deposited by plasma or laser based droplet-deposition process that ensure good metallurgical bonding between layers without excessive heating of the substrate material.

Other deposition processes that are currently being explored include

selective casting of two-component or UV-curable resins, hot pressing of powders, sputtering and ceramic deposition. In SDM, material removal is done using a 5axis CNC milling machine. The CNC cutter paths generated by the process planner


14

are downloaded to the machine in the DNC mode. Other material removal stations that will be included in the future include EDM (electro discharge machining) and a 3-axis CNC milling machine for handling abrasive materials. The residual cutting fluids or the residue from the deposition process are removed in a washer that has the capability to spray a water-jet at different speeds. A shot peener is used to relieve stresses in the part. The shot peener uses a conventional pressurized media delivery system. Some of the current application areas of SDM are • Shape conformable embedded electro-mechanical structures • Manufacture of custom tools – Injection molds with cooling channels – Tools with multi-material inserts – Tools with embedded sensors • Functional prototype parts • Complex shaped parts made of hard-to-machine materials.

2.2

Process planning

In conventional CAD/CAM systems that rely on CNC machines to build parts, process planning plays a significant role. Process planning in such systems requires identification of machining features. Sarma and Wright [54] identifies two levels of planning for the conventional CAD/CAM systems. Macroplanning is a higher level planning that deals with access directions of features, process sequencing and selection of appropriate fixtures. Microplanning deals with tool path planning and selection of tools and process parameters. Although progress has been made towards automating these planning tasks, significant human intervention is still required which results in long lead times and expensive parts. Some of the difficulties in automating the conventional CAD/CAM processes are:


15

• Inaccessibility of some areas of the model by the cutting tool Figure 2.3a. This could be caused either due to insufficient tool length or due to inaccessible surfaces in the model. • Part-specific fixturing Figure 2.3b. In order to access undercut surfaces, special fixture or refixturing is needed. The design and selection of fixtures involves considerable human expertise and is difficult to automate.

Inaccessible by tool

Fixturing problems

Figure 2.3: DIFFICULTIES WITH CONVENTIONAL CAD/CAM PROCESSES • Generation of cutting tool trajectories for complex geometries. Geometric reasoning becomes a difficult task in the case of complex geometries. Problems like gouging and collisions becomes more difficult to handle in complex geometries. Multiple re-fixturing might be necessary to cut certain shapes without collisions. Verification tools are needed to ensure the correctness of the generated paths. On the other hand, one of the clear advantages with SFF processes is the ability to produce physical objects from CAD models in a completely automated fashion with very little process planning effort. SFF processes operate on planar geometries that makes them essentially independent of the part complexity. Support structures eliminate the need for custom fixturing and permit undercut features to be built up. The process planning effort in most of the SFF processes involves the generation of 2-D cross-sections and generation of scan paths for the 2-D cross-sections. Since it is possible to solve these issues in a robust and autonomous fashion, producing parts


16

using the SFF processes requires very little human intervention. Of course, issues such as shrinkage compensation and support structure determination would make the process planning effort in SFF processes more challenging. In SDM, there is a full 3-D shape control of all surfaces and it also uses material removal operations like CNC cutting. Both these make the process planning effort in SDM more complex than that of SFF processes. Figure 2.4 shows the process planning steps involved in SDM. In SDM, the CAD model is first decomposed into layers of varying thickness based upon both geometric and process criteria. Each layer is further subdivided into simpler building blocks called compacts that are of single material and which have all their newly deposited surfaces to be non-undercut surfaces.

The compacts are then sequenced for subsequent planning operations.

The compacts are deposited as near-net shapes using the deposition paths. The parameters for deposition paths, such as path spacing, deposition feedrate and height of deposit are dependent on the deposition method used and material being deposited. This information is obtained from the process database. The deposited compacts are machined to net shape using CNC cutting operations. The CNC cutter paths are transformed to machine coordinates and into the machine readable format. The CNC cutter paths are generated with different types of cutting tools with varying sizes. The feed-rate and the spindle speed are based on the cutter used and the material being cut. This information is derived from the tool database. Deposition paths and CNC cutter paths are then generated for the next compact and the path generation cycle is repeated till all the compacts are processed. One of the key challenges in process planning for SDM is to develop robust algorithms to automatically decompose any CAD solid model into a set of layers and compacts. This problem involves extensive geometric reasoning and is very difficult to be solved manually. Thus, it is essential that this is done in an automated fashion. With a host of interesting geometric issues, a robust solution to this problem will be a challenging task. The other major area in process planning for SDM is path planning. Path planning encompasses generation of deposition trajectories and cutting trajectories. Though there are some common issues in deposition and cutting path generation, there are some basic issues that separates these two problems. The


17

CAD Model

Adaptive layer Generation Compact Generation

Non-Monotonic Layer

Min/Max Layer Thickness

Process Database

Layer/Compact Sequence

Deposition Path Tool Database CNC Cutter Path

Machine Code

Figure 2.4: PROCESS PLANNING STEPS IN SDM


18

deposition path generation is highly influenced by the process whereas the cutting path generation is governed more by geometry than by the process. Trajectories generated for droplet-based deposition methods used in SDM control the integrity of the deposited material. It is very important to maintain accurate path spacing and torch angles to avoid gaps or overlaps in the deposit. A variety of trajectory patterns should be explored to overcome issues like unsymmetrical deposition properties, localized heating and thermal cycling. On the other hand, cutter path generation is mainly dictated by geometric complexities. As explained before, automation of CNC cutter path generation has not been possible. But in SDM, it is very essential that it is automated as human intervention with so many layers would cause considerable delays in the process. Also, with the original model decomposed into compacts, it is intuitively difficult to generate the CNC trajectories. At the same time, this process offers some benefits which helps towards this automation. The compacts won’t have any undercut features and since the compacts won’t be too high, all areas of the compact will be within the reach of the tool and there is no need to consider fixturing problems. Thus generation of CNC cutter paths in an automated fashion would be another major task of the process planning system.

2.3

Summary

This chapter described the SDM process and the process planning issues in SDM. SDM is a layered manufacturing process that employs material deposition and material removal processes for creating a part. Process planning is an important component in any manufacturing process. In conventional manufacturing processes that employ CNC machining, process planning involves selection and design of fixtures and generation of CNC cutter paths. This still needs significant human intervention resulting in long lead times and expensive parts. In SFF processes, process planning involves generation of 2-D cross-sections by slicing the CAD model and generation of scan paths for these 2-D cross-sections. This needs very little human intervention. Process planning in SDM has some similarities and differences with the above mentioned methods of process planning. In SDM, similar to SFF, the


19

CAD model has to be decomposed into simpler models but the difference is that these simpler models are 3-D models and are no longer 2-D cross-sections. Then similar to CNC process planning, cutter paths have to be generated for these 3-D models, but the difference is that the cutter path planning has to be fully automatic and is free of fixturing problems.

Chapter 3 Spatial Decomposition 3.1

Introduction

As mentioned before SFF parts are processed by decomposing 3-D CAD models into thin cross sectional layers which are used to plan the material deposition strategy for each layer. The physics of the material deposition process (e.g. surface tension) frequently prevents the generation of geometrically well defined surfaces between cross sections. Instead, surfaces with a stair step appearance may be created. In contrast, Shape Deposition Manufacturing (SDM) takes advantage of both material addition and subtraction. The SDM strategy is to first decompose a CAD model into simpler building blocks called compacts. A key challenge in SDM is to develop robust algorithms capable of automatically decomposing any 3-D model into a set of layers and compacts which can be fabricated by combined additive and subtractive process. To define the nature of the geometric problems involved, we describe the sequence of fabrication steps first. Each layer consists of a primary material and a sacrificial support material.

For example,

consider the object in Figure 3.1 which is decomposed into three planar layers. The layers comprising the primary material are classified as follows: • Class 1 has only non-undercut features • Class 2 has only undercut features 20

CHAPTER 3. SPATIAL DECOMPOSITION

21

• Class 3 is a combination of 1 and 2. Both Undercut Non-undercut

Class 1 Class 2 Class 3

Figure 3.1: SEQUENCE OF OPERATIONS Figure 3.1 shows the sequence of operations for these three class of layers. For class 1 the primary material is deposited first and then machined to net shape. Next, the sacrificial support material is deposited and planed together with the primary material. This sequence is reversed for class 2 objects. Class 3 geometries must be decomposed into compacts such that the strategies of class 1 and class 2 can be invoked recursively depending on the local geometry. As an example, a support compact is deposited and cut first followed by deposition and cutting of the primary material. Finally the rest of the support material can be deposited to complete the layer. This description serves to indicate some of the issues in shape decomposition for SDM processing. The following section aims at generalizing the definitions of geometric entities which will then lead into the development of the decomposition algorithm [52].


3.2

Overview

3.2.1

Definitions

22

ˆ v) The surfaces of the model are classified into three categories (Figure 3.2). If N(u, b

N N N N

Non-undercut

N

Undercut

Non-monotonic

Figure 3.2: TYPES OF SURFACES is the normal vector on any point (u, v) of the surface S and ˆb is the unit vector in the build-up direction, then ˆ (u, v) · ˆb < 0 for all (u, v) in the domain of S • S is an undercut surface if N ˆ v) · ˆb ≥ 0 for all (u, v) ∈ S • S is a non-undercut surface if N(u, • S is a non-monotonic surface if it has both undercut and non-undercut portions. A layer is a section of the model that is bound between two horizontal planes. A layer can consist of multiple materials and can have a variable thickness. In general, a layer cannot be processed in one SDM process cycle. A compact is the fundamental building block of the SDM process. A compact is composed of single material and has all its newly deposited surfaces to be nonundercut surfaces. A compact can be processed in one SDM process cycle. The next four definitions are illustrated in Figure 3.3. Silhouette edges are defined as those curves on the surface of the model along ˆ v) · ˆb = 0. Silhouette edges serves as the boundary between undercut and which N(u, non-undercut portions of the surface.


23

a b b

a

c

a - Convex surface silhouette edge b - Convex boundary silhouette edge

Silhouette loops

c - Concave boundary silhouette edge

Figure 3.3: SILHOUETTE EDGES AND LOOPS A convex silhouette edge is a silhouette edge where the surface across the edge is convex. Thus a convex silhouette edge has its adjacent undercut surface below its adjacent non-undercut surface. A concave silhouette edge is a silhouette edge where the surface across the edge is concave. Thus a concave silhouette edge has its adjacent undercut surface above its adjacent non-undercut surface. Silhouette loops are the loops formed by the connecting the silhouette edges into a closed contour. A silhouette loop can consist of both concave and convex silhouette edges. Build-up direction is the direction along which the part is built up. At present, parts in SDM are built along the z direction. Thus, without loss of generality, z direction (0,0,1) is assumed to be the built-up direction in the rest of this chapter.

3.2.2

Basic concepts

Some of the concepts in this section and the subsequent sections will be explained with the help of models of part and support shown in Figure 3.4. The main goal is to decompose the given CAD model into compacts that could be processed in a single step. We should also determine the sequence of compacts based on its geometry. Figure 3.5 and Figure 3.6 shows the spatial decomposition of the part and the support


CAD model of part

24

CAD model of support

Figure 3.4: PART AND ITS SUPPORT respectively. It will be shown later that this is not the only solution. The part model

P2

P3

P1

Spatial decompostion of part model

Figure 3.5: COMPACT DECOMPOSITION OF THE PART is decomposed into layers P1, P2, P3 and doesn’t need any subdivision. The layers S1,S2 of the support model do not need any subdivision, but layer S3 has to be subdivided into compacts S3 1 and S3 2. The process sequence for this set of layers and compacts will be P1-S1-S2-P2-S3 2-P3-S3 1. Silhouette edges are used as the starting point in the decomposition algorithm. There are two types of silhouette edges in a given model, surface silhouette edges and boundary silhouette edges. Surface silhouette edges are those that exist inside a surface and boundary silhouette edges are those that serve as the common boundary


25

S2 S1

S3

S3_1 S3_2

Spatial decomposition of support model

Figure 3.6: COMPACT DECOMPOSITION OF THE SUPPORT edge between two surfaces. The surface silhouette edges are present only in nonmonotonic surfaces and are used to subdivide the surface into monotonic surfaces. At the end of this subdivision, the model will consist only of boundary silhouette edges. These boundary silhouette edges are connected to form closed silhouette loops. Figure 3.3 shows the silhouette edges and loops in the example part. Partition surfaces are obtained as ruled surfaces by sweeping a certain set of silhouette edges along the z direction. These partition surfaces are used to decompose the model into layers and compacts. Since a compact can consist of both undercut and non-undercut surfaces, a compact with undercut surfaces can be processed only when all other compacts with which the current compact shares its entire undercut surface have been created. Each


26

compact is accumulated on the pre-built non-undercut surfaces of other compacts and provides new non-undercut surfaces for supporting other compacts to be processed later. Since silhouette loops represent the common boundary between undercut and non-undercut portions, they play a very important role in the generation of compacts. Any portion of the model with purely concave silhouette edges cannot be a compact because the non-undercut surface cannot be reached from top as there is an undercut surface hanging over a non-undercut surface. The exception to this is if the concave silhouette edge has its adjacent non-undercut surface as a vertical surface. A convex silhouette edge and a concave silhouette edge appear as a pair, because a convex silhouette edge for the part model is a concave silhouette edge for the support model and vice versa. For instance, a spherical surface of a positive ball has a convex silhouette circle while that of a negative ball has a concave silhouette circle.

3.2.3

Related work

The concepts of silhouette edges and loops are well known in the context of hidden line/surface removal algorithms. Appel[4] proposed a hidden line removal algorithm based on quantitative invisibility, which stands for the number of covering surfaces such that quantitative invisibility at visible points is equal to zero. He pointed out that quantitative invisibility changes when a point passes through a silhouette edge. Hornung[28] as well as Schweitzer and Cobb[55] indicated that connected silhouette edges form a closed loop. Walter[64] uses silhouette edges as a means for surface rendering. He generates silhouette edges as point sequences and uses them to compute sight indices that are then used to clarify the visibility of the surface. However, these studies were aimed at generating projected images rather than decomposition of CAD models. Silhouette edges were used just for eliminating hidden parts of lines or for determining the ends of scan lines. Researchers in the graphics area have also looked at the problem of generating surface silhouette edges. Schweitzer and Cobb[55] use a surface intersection method to compute silhouette edges on tensor product polynomial surfaces. In their approach, normal surface N , obtained by the surface representation of the normals at each point


27

on the surface S, is intersected with xy plane to obtain the silhouette edges. Their method was limited to bicubic patches and the algorithm has limitations when the normal surface is degenerate. Beusmans[6] outlines a method to generate silhouette edges of a model using its spherical image. The spherical mapping relates the points on the surface of a model with points on a unit sphere representing all possible surface normals. The algorithm makes use of the fact that the spherical image of a silhouette edge is confined to the great circle on the unit sphere. In this method, the extraction of silhouette edges is free of degeneracies and fairly straightforward subject to the generation of the spherical image of the object.

3.2.4

Requirements

The requirement for each compact is as follows: • A ray cast along the z-axis from the top should enter the compact through its non-undercut surface and exit through its undercut surface. • Any non-undercut surface of a compact cannot be covered by its own undercut surfaces. • The ray hits a non-undercut surface and an undercut surface at most once. These requirements can be expressed in terms of the silhouette edges and silhouette loops as below. Concave silhouette edges: There shouldn’t be any concave silhouette edge in a compact. In a model with concave silhouette edges, the non-undercut surface is covered by its own undercut surface. Here, the silhouette edge indicate a local self-overlap like in a bellow. Self-intersections of a projected silhouette loop: The xy projection of the silhouette loop shouldn’t have any self-intersections.

If the projection of a

silhouette loop has self-intersections, then there exists at least one ray that will hit a non-undercut surface and an undercut surface more than once. Here, there exists a global self-overlap like in a spiral shape.


28

Even if each compact fulfills the above two requirements, it might so happen that the compact cannot be processed due to a sequence conflict between the compacts. The compacts have to be ordered based on their relative z positions. The compact with a lower z value must be sequenced before the one with a higher z value. The z position of a compact is its minimum z value. All the compacts must be simply ordered in a sequence to be processed. However it is sometimes impossible to sort all compacts in a sequence based on the relative z positions. This could happen if there exist cyclic ordering relation as shown in Figure 3.7. Here A covers B, B covers C, and C covers A. This means A cannot be processed before B, B cannot be processed before C, and C cannot be processed before A. Therefore none of them can be processed in the given form. In terms of silhouette loops, this requirement can be stated as follows. Cyclic ordering among silhouette loops If the ordering relations between silhouette loops of compacts form a cycle, those compacts cannot be processed in a sequence.

A

B

A 0, p is grouped in the concave grid. • If κ1 (p) < 0, κ2 (p) < 0, p is grouped in the convex grid. • If κ1 (p) > 0, κ2 (p) < 0 or

p is grouped in the saddle grid

κ1 (p) < 0, κ2 (p) > 0 • If κ1 (p) = 0, or κ2 (p) = 0, p is grouped in the developable grid. The original surfaces are then trimmed to the sub-grids to form the trimmed surface patches each of which is completely convex, concave, saddle or developable. These trimmed surface patches are further categorized as: • Convex patches - Since convex patches could be machined with the flat-end mill cutter, they are categorized as flat-end milled regions.

CHAPTER 6. 3-D CUTTER PATH GENERATION

64

• Saddle patches - The parts of saddle patches for which one of the principal curvatures has a low positive value are categorized as flat-end milled regions and the rest is categorized as three axis milled regions. • Concave patches - Only those parts of concave patches where both the principal curvatures are low, are categorized as flat-end milled regions and the rest comes under three axis milled regions. • Developable patches - The developable patches could be machined using the side of the cutter if the cutter axis is aligned along the principal direction with zero curvature. Hence the developable patches are categorized as peripheral milled regions The cutter paths are then generated for the three regions.

Figure 6.2: SURFACE SHRINKING FOR FLAT-END MILLED REGIONS • Cutter path for flat-end milled regions : No surface offset operations are needed for flat-end milled regions[40]. In this, the operation involved in compensating for the tool radius is surface shrinking, in which the the curves bounding the surface are moved along the surface by a distance given by the radius of the tool (Figure 6.2). Cutter paths are generated by indexing the tool along the the shrunk surface with the orientation of the tool along the surface normal.


65

Isoparametric curves along with the surface normal information are used for this purpose. • Cutter path for peripheral-end milled regions : Cutter path generation for peripheral end milled regions requires the computation of offset surfaces at a distance equal to the radius of the cutter. Since the peripheral end milled regions are composed of developable or ruled surfaces, there won’t be any degeneracies that occur in surface offset operations. The cutter paths are generated by orienting the tool along the principal direction with zero curvature.

a) Surface to be 3-axis milled

b) Intersection curves

Figure 6.3: INTERSECTION CURVES FOR 3-AXIS MILLED REGIONS • Cutter path for three axis milled regions : Most of the literature for CNC cutter path generation [9],[30],[59] has been written for this category. In most of these cases ball-end mills are used. Here we consider two approaches. One is the use of adaptively extracted isocurves [16] to generate cutter paths. This method requires the computation of the offset surfaces. In a work by Tang et al. [59], an offset algorithm has been described that not only offsets surfaces but offsets boundary curves of the surfaces to generate tool paths that are smooth and have minimal un-cut area. But the offset surface may contain degeneracies like self-intersections [3] which are difficult to detect effectively. Hence, from a practical consideration, we have used intersection curves obtained by intersecting the region with parallel planes to generate the cutter paths (Figure 6.3). The intersection curves are offset for the radius of the tool in a manner similar to that described in the previous section and these offset curves are used to cutter trajectories with the cutter oriented along the z-direction.


6.2

66

Collision Free Paths

In the previous section, the cutter paths were generated without considering the cutter interference problem [38]. Cutter interference could be caused due to the interaction between different regions of the model and those between the model and machine components. The paths are generated to be executed in a 5-axis NC machine with two revolute joints and three prismatic joints. While the joint limits of the prismatic joints are of less importance (as the size of the parts are usually well within the limits), the joint limits of revolute joints have to be considered while generating the paths.

6.2.1

Collision types

The paths can have collision from the following sources. • Single surface gouging (SSG) : Gouging results when the tool overcuts the part surface (Figure 6.4 a). SSG is often encountered when the tool size is too large relative to the concave radius of curvature. • Multiple surface gouging (MSG) : This type of gouging occurs when the tool positioned in correct position results in an interference with the adjacent surface(s) (Figure 6.4 b). • Collision with Machine Structure (CMS) : This occurs when the machine components (tool head, coolant supply, etc.,) collide with the workpiece. • Revolute Joint Limits (RJL) : Though this is not an actual collision, the limits on the revolute joints can be modeled as artificial stops.

6.2.2

Collision Detection and Avoidance

Two objects are in collision if the distance between them is zero. Thus collision detection is related to distance computation between objects. The collision detection for the first two types of collision (SSG and MSG) will involve identifying collision


67

a) Single Surface Gouging

b) Multiple Surface Gouging

Figure 6.4: TYPES OF GOUGING between the tool and the part surface. SSG will be handled during cutter path generation in the case of flat-end milled and peripheral-end milled regions. In the case of three-axis milled regions we might have SSG since cutter paths were generated from iso-curves. Since the paths for different regions were generated independently without considering the interactions with neighboring regions, the cutter paths have to be checked for MSG and CMS. RJL will be an issue only in the case of flat-end milled and peripheral end-milled regions. It could be handled either at the cutter path generation stage or at this stage. In order to avoid a computational overhead at the cutter path generation stage, RJL is also handled at this stage. The joint limits are modeled as artificial stops and is captured under CMS. Since there are going to be a large number of points on the part surface along which the tool will travel, the number of collision checks will be very large. Thus an efficient algorithm has to be used for collision detection. The algorithm described by Quinlan [49] is adapted for this purpose. A hierarchical boundary representation is built for the part model, tool, machine components and the artificial stops. The bounding representation consists of an approximately balanced binary tree with the property that the union of all the leaf


68

spheres completely contains the surface of the object. Collision occurs when the distance between different objects is less than an epsilon value (which is based on the desired accuracy of detection). The bounding representation helps in narrowing down the pairs of surfaces for which distance has to be computed. After narrowing down to the pairs of surfaces, the distance between those surfaces have to be computed. Since a method to compute distances between any two surfaces is not known, the surfaces will described by convex polygons and the distance algorithms for convex objects will be used to compute the distance. One well known convex representation of a surface is the triangulated surface. For those points for which collision occurs, an alternate solution has to be proposed to avoid collision. In most cases the solution might be to go for ball end mill cut. But there are a couple of issues that makes this problem tricky. First, there will not be one-to-one correspondence between the different types of cutter regions. Next, there won’t be one-to-one correspondence between the polygonized surface and the actual surface. Hence as a first step, the solution is to generate the cutter paths for all types of cutter regions and test them for collision and drop those points at which collision occurs. If some regions of the model are still left un-cut, the next cutter size is chosen and the process repeated.

6.3

Summary

An algorithm has been proposed for fully automatic 3-D cutter path generation for a compact. Based on the curvature data, the surfaces of the model were grouped under four categories, concave, convex, saddle and developable surface patches. These patches were subsequently grouped into three types, flat-end milled, peripheral-end milled and three-axis milled cutter regions. Methods of cutter path generation were described for each of those regions. This chapter also described the way to avoid cutter interference problem that could be caused due to the interaction between different regions of the model and those between the model and machine components. A robotic collision detection algorithm has been modified and used for this purpose. Before being downloaded into the CNC machine, the cutter paths would have to be


69

transformed relative to the CNC machine coordinate system. Appendix A describes these kinematic transforms.

The algorithm presented in this chapter could be

enhanced by considering the problem of maintaining continuity in cutter paths across surface patches and the three types of cutter regions.

Chapter 7 Software Issues The CAD model undergoes a variety of geometric operations during different stages of process planning. In order to withstand the complex geometric operations, a powerful and robust geometric engine should serve as a backbone for the process planner. The geometric engine should also have the capability to create new models and accept different input formats. Some of the terms used in the context of geometric modeling are described in the next section.

7.1

Terminology

The following definitions have been culled from various geometric modeling and solid modeling texts [17],[27],[41],[46]. B-rep stands for Boundary representation. Here the object is represented in terms of its surface boundaries: vertices, edges and faces. It is the widely used representation of a solid model. Traditionally B-reps were restricted to planar, polygonal boundaries. In the past decade, there have been many efforts to incorporate parametric surfaces as boundaries in B-rep and these are also referred to as exact B-rep. CSG stands for constructive solid geometry. In CSG, simple primitives are combined by means of regularized Boolean set operators. An object is stored as a tree with operators at the internal nodes and primitives at the nodes. Transformations such as rotation and translation are also represented as nodes. 70

CHAPTER 7. SOFTWARE ISSUES

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NURBS stands for nonuniform rational B-splines. These are rational B-spline curves that are becoming the standard curve and surface descriptors in CAD. NURBS entities are defined by a set of control points and rational blending functions. Manifold topology. Most of the B-rep geometric modelers support only solids with two-manifold topology. Every point on a two-manifold topology has some arbitrarily small neighborhood around it that can be considered topologically the same (homeomorphic) as a disk in the plane. If there is any point on the boundary that does not satisfy the two-manifold condition, the object is classified as non-manifold.

7.2

CAD system requirements

Traditionally, surface modeling has been the widely used representation for CNC path planning. It is only in the past five years, solid models are being used for CNC path generation. In systems that use solid models, the solid modeling information is used to check collisions and the cutter paths are still generated on a surface-by-surface basis. Thus the solid needs to be represented as an exact B-rep in such systems. In SFF processes, linear tessellated geometry has been used to represented the solid. This kind of representation originally evolved for applications in rendering, but has become popular in SFF due to its ease of generation. In SDM, due to the nature of geometric operations and its ability to handle complex shapes, a more sophisticated geometric engine is needed. Some of the requirements of the geometric engine in SDM are: Availability in the form of an API API stands for Application Procedural Interface, wherein the geometric engine is provided in the form of libraries consisting of user-callable routines. The process planner for SDM is implemented using a high level programming language such as C or C++ by calling different geometric routines at different stages of the planner. An effective way to provide this interface is in the form of an API library. Ability to handle mixed-dimensional operations In SDM, the same compact is used for a variety of tasks such as deposition path generation, 2-D cutter path


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generation and 3-D cutter path generation. As part of the geometric querying process, both the two-dimensional and the three-dimensional representations of the solid are used. Thus the geometric engine should be able to accommodate entities of mixed dimensionality. Ability to handle non-manifold topology Though almost all physical artifacts are two-manifold objects, the domain of two-manifold topology does not have closure under set boolean operations. Thus non-manifold configurations can occur as a result of boolean operations involving manifold objects. In the case of SDM, non-manifold configurations could result during slicing in the compact decomposition process. Also, SDM has the capability to produce multi-material objects and it is very difficult to handle such objects with two-manifold topology. Ability to handle freeform (NURBS) surfaces As opposed to standard SFF processes, one of the main differences in geometry in SDM is its capability to reproduce freeform surfaces. Thus, in order to make take advantage of this, the geometric engine should be able to handle NURBS surfaces. Some of the key challenges in handling NURBS surfaces involves providing robust surfacesurface intersection routines and providing geometric queries on those surfaces. Graphical front-end It would be useful if the geometric engine has an user interface that will help in creating and editing solid models. The graphical front-end would also be helpful as a debugging tool. Neutral formats The models for SDM can come from different sources and the process planner should have the capability to handle these models. If the models were created using the same geometric engine as used by the process planner, then the process planner should be able to read in those models. But if the model was created using a different geometric engine, then it has to be converted into a neutral format and the geometric engine should have the ability to accept those neutral formats. Some of the standard neutral formats for geometric models are:


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STEP STEP stands for STandard for the Exchange of Product model data and it is an ISO standard that was developed to allow exchange of engineering product data. In STEP, the geometric information is captured by an application protocol called AP203. Some of commercial solid modelers have a STEP AP203 translator module and some of the remaining ones are developing a STEP AP203 translator. IGES IGES stands for Initial Graphics Exchange Specification and is the precursor to STEP. IGES permitted the exchange of product definition data by representing geometric and topological data in a neutral format. It was difficult to represent solid model information in an unambiguous manner using the IGES format. Most of the commercial CAD packages have the capability to output their results in the IGES format. STL It is the defacto standard among the SFF systems. In this format, the model is represented by a collection of triangular facets.

In order to

represent a solid model in this format, the faces of the model have to be tessellated. Though it is a very simple representation and could be generated by any CAD system, it is approximate and lacks in topological information. In addition to the capability of reading models in these neutral formats, the geometric engine should also be capable to output its model in these standard neutral formats. Geometric functionality In addition to providing the basic functions such as boolean operations, the geometric engine should be rich in its functionality. In the implementation of the process planner, there will often be situations where there will be a need to know geometric properties such as surface normals, surface curvatures, curve tangents, etc. Another useful functionality would be the sweep functionality which was needed as part of the compact decomposition algorithm.

Though it might be possible to implement geometric property

evaluations and sweep functionality as part of the process planner, it would be efficient if it is implemented within the geometric engine.


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Robustness Last but not the least, the geometric engine should be robust. The process planner is intended to be free of human intervention and if the underlying geometric engine fails often, it would be difficult to achieve that goal. The CAD model will undergo a variety of geometric operations within the process planner wherein it might encounter some degenerate geometric configurations. It would be best if the geometric engine handles such degenerate cases. If not, it should at least be able to identify them and report them as errors. Also, the geometric engine should be consistent in its results and should never return incorrect results. If the calling routine is unaware of an incorrect result being returned, it might lead to disastrous consequences.

7.3

CAD System Comparison

There weren’t many systems that met all the CAD requirements. One of requirements that is essential for the process planner is some sort of API functionality as it would have been infeasible to implement the process planner without API functionality. As far as we know, there were only five systems that had API functionality. These were: 1. NOODLES : NOODLES is a geometric modeling kernel developed at the Engineering Design Research Center of Carnegie Mellon University. NOODLES is based on non-manifold boundary representation and is available in the form of an API library. It is robust and handles mixed dimensional operations. One of the greatest drawbacks with NOODLES is that it cannot handle freeform surfaces. Thus all models created with NOODLES will have faceted geometry. Also, being a non-commercial system there is no provision to interchange models in neutral formats except for the STL format. NOODLES provides the basic primitives and boolean operations among those primitives to aid in model creation. It also permits geometric and topological queries on its geometric entities. An interface called DISH was developed at EDRC of Carnegie Mellon University to provide a graphical front-end for NOODLES.


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2. ACIS : ACIS is a geometric modeler from Spatial Technology Inc.. ACIS is the most popular geometric modeler available in the form of an API library. ACIS handles freeform geometry and permits geometric queries on its entities. Though it claims to handle non-manifold geometry, it is fundamentally a manifold modeler with limited non-manifold functionality. It is also not truly mixed-dimensional and it primarily deals with three-dimensional geometry with special functions to handle two-dimensional and mixed-dimensional operations. Though it doesn’t come with a powerful graphical interface, there are commercial solid modeling packages such as AutoCAD from AutoDesk Inc. that can be used as the graphical front-end for ACIS. ACIS doesn’t have provision to handle models in neutral formats, but there are quite a few commercial systems that can handle two-way translation of ACIS models into neutral formats such as IGES, STEP and STL. ACIS is not very robust and in our experience, it was failing or producing incorrect results in some situations. But the encouraging fact is that ACIS is continually under upgrade and development and hopefully in the future it will be a robust geometric modeler. 3. Pro/DEVELOP : Pro/DEVELOP is a toolkit that offers the ability to access geometric information created with Pro/ENGINEER of Parametric Technology Corporation. Pro/ENGINEER is one of the most popular CAD systems. It is known to be a robust CAD system. It is a parametric, feature-based modeling system with ability to handle freeform geometry. But, it was not a serious candidate in our case as Pro/DEVELOP has only a small fraction of the functionality provided by Pro/ENGINEER and also Pro/ENGINEER doesn’t have mixed-dimensional capability and is a manifold modeling system. 4. SHAPES : SHAPES is a geometric modeling library from XOX Corporation. SHAPES is a truly non-manifold boundary representation system and it can handle freeform surfaces. It is dimension independent and thus can handle mixed-dimensional operations. It is fairly robust. Some of its drawbacks are its lack of functionality, non-availability of powerful user interface and inability to interchange models in neutral formats. It offers only limited geometric queries


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on its entities and there aren’t any commercial systems that can translate models in neutral formats to SHAPES models. 5. Parasolid : Parasolid is a boundary-representation geometric modeler developed by EDS Unigraphics. Parasolid is supplied as an API library and supports freeform surfaces. It has a powerful user interface available as part of the Unigraphics CAD system. Unigraphics also has the facility to do a two-way translation of parasolid models into neutral formats. Parasolid offers geometric and topological enquiries on its entities. Though it offers some support for nonmanifold operations, parasolid is not fully non-manifold. It is not dimension independent, but it offers some support for mixed-dimensional operations. Though its robustness has not been fully tested, the initial indications are that it won’t be very robust due to its ambiguous handling of non-manifold and mixed-dimensional operations. These CAD systems were evaluated against the CAD system requirements. Figure 7.1 shows a chart indicating the performance of different CAD systems against those requirements. In the chart, the amount of filling of a CAD system/function box indicates the availability of that function in that CAD system.

7.4

Implementation issues

The first version of the process planner was implemented in NOODLES [58] in C language. NOODLES was selected as the initial system as it was available in-house and it could handle non-manifold topology [24] and it was available as an API library. Being the first prototype of the planner, it underwent several revisions and also helped us in refining our data structures. This planner failed in some degenerate geometric configurations which were caused by points on the model that were very close to each other. These problems were overcome by tweaking some of the parameters of the modeling system. But the biggest hurdles were the lack of support for freeform geometry and inability to handle models in neutral format. Some effort was spent to add freeform functionality in NOODLES, but since it was turning out to be a major


NOODLES

ACIS

77

Pro DEVELOP

SHAPES

ParaSolid

API Mixed Dimensionality Non-manifold Free-form Surfaces Graphical front-end Neutral formats Geometric Functionality Robustness

Figure 7.1: CAD SYSTEM COMPARISON CHART effort, it was dropped and the next version of the process planning system for SDM was implemented using ACIS [31] geometric modeler in C++ language. ACIS was selected as it claimed to have non-manifold and mixed-dimensional capability and it was available in the form of an API library and it was a very popular system. But as the implementation of process planner in ACIS progressed, we started facing quite a few robustness issues. Some of the ACIS functions were replaced by our own functions and this took care some of the problems. On the positive side, ACIS comes up with a new release every few months wherein they attempt to make it more robust. On the downside, the new releases are not downward compatible and thus it warrants


78

rewriting portions of the planner. Initially, without a powerful graphical interface model creation was very difficult in ACIS. This problem was overcome with the release of AutoCAD version 13. Currently, the process planner is being implemented in SHAPES and Parasolid.

Chapter 8 Applications Several parts were built in SDM using this process planner. The parts were varied in nature and all the aspects of the process planner were put to test. Most of the parts were built successfully using the process planner. In the case of some parts, the process planner had to be modified to overcome some errors. Most of these errors were due to the underlying geometric modeling kernel. Building these parts also helped in a better understanding of some of the finer aspects of the process which subsequentally helped in improving the process planner. The parts that were built using SDM could be broadly classified into three categories. • Geometrically complex parts • Next generation metal tooling • Non-conventional parts In the following sections, some example parts will be shown in each of the above categories highlighting the process planning aspects wherever necessary. I would like to thank my colleagues in SDM lab of CMU and RPL lab in Stanford for their effort in building these parts.

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CHAPTER 8. APPLICATIONS

8.1

80

Geometrically complex parts

These are parts with complex geometrical shapes that would require significant time and effort with the conventional methods. In the conventional manufacturing methods, these parts would be almost impossible to produce without human intervention. In SDM, with the availability of a process planner, these parts could be produced in a fairly automated fashion.

8.1.1

IMS-T2

Figure 8.1: CAD MODEL OF IMS-T2 IMS-T2 is one of the first test parts built using the SDM process. It was one of the test parts that was used in a world-wide assessment of rapid prototyping technologies [5]. At the time when this part was built, the process planner was in its early stages and was built on top of the NOODLES geometric modeling kernel [58]. The compacts were generated manually and the cutting paths were generated using the process planner. The model shown in Figure 8.1 was constructed as a CSG tree


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in NOODLES. Since NOODLES is a polygonal modeler all the freeform surfaces of the model were approximated by facets. The support model was decomposed into 8 compacts. The compacts C1−C7 shown in Figure 8.2 were generated by doing a rigid sweep of all the undercut surfaces of the model in the −Z direction. C8 (Figure 8.2) was obtained by subtracting the union of previous seven compacts with the part model from a block bigger in size than the bounding box of the model. These compacts along

C7

C6 C5 C2 C3

C4

C1 a) Compacts C1 - C7 C8

b) Wireframe rendering of compact 8

Figure 8.2: COMPACT DECOMPOSITION OF THE SUPPORT IN IMS-T2 with part model were sliced into 29 layers using horizontal planes to satisfy the process constraints. This resulted in a total of 79 compacts. The 2-D cutter paths for rough cutting and profiling were generated for the bottom cross-section of these compacts. Because of the polygonal representation of the compacts, there were some tiny facets for which 3D cutting strategies could not be generated. The presence of so many facets resulted in large CNC files. These factors prompted us to seriously consider a nonlinear geometric modeling kernel. After this part was completed, some effort was


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spent in adding the nonlinear functionality to NOODLES. Since this seemed to be a long-term effort, ACIS [31] was adopted as the geometric modeling kernel for the next version of the planner. Figure 8.3 shows the stainless steel IMS-T2 part produced with the SDM process. Copper was used as the support material and was etched out after the part was completed. The materials were deposited using microcasting. This part helped us to identify some of the process planning issues and also demonstrated the usefulness of the planner.

Figure 8.3: IMS-T2 MANUFACTURED WITH SDM

8.2

Next generation metal tooling

Next generation metal tooling are dies for injection molding with a strong steel exterior, conformable cooling channels, multi-material inserts such as copper and INV ART M and embedded sensors. Such tools have quite a few advantages. The steel exterior would provide a solid base for the die, cooling channels and copper inserts would help in heat distribution and avoid forming hot spots in the tool, materials with low coefficient of thermal expansion such as INV ART M would control distortion in geometry and the embedded sensors such as thermocouples would help to measure certain parameters during molding.


8.2.1

83

GM Injection molding Tool

The design for the tool was provided by GM as engineering drawings. The CAD model of the mold halves were created in the test harness provided by ACIS [31]. Internal U shaped cooling channels and models corresponding to copper inserts were also created in the model. All the concave silhouette loops were on horizontal planes and the model and support were sliced along these planes. Since all the compacts were 2.5D structures, the deposition paths and 2-D cutter paths were generated corresponding to the bottom cross-section of each compact. This part didn’t require any 3-D cutter paths. Figure 8.4 shows the injection molding tool made with the SDM process. The

Figure 8.4: INJECTION MOLDING TOOL part is made from 316L stainless steel. One half of the tool has four copper deposits. The part material was deposited using the laser system and microcasting was used to deposit the support material. Some of the small features that could not be cut with end-mills were machined with EDM.


8.3

84

Non-conventional parts

The most widely recognized advantage of layered manufacturing is the relative ease of fabricating complex geometric shapes. But a process such as SDM that builds parts by incremental material deposition and material removal has far-reaching potential. We could fabricate parts that are either impossible or almost impossible to manufacture with conventional manufacturing methods.

These parts are referred to as non-

conventional parts. The non-conventional parts could further be categorized as • Parts with interacting geometric features • Conformable, embedded electro-mechanical parts • Assembled mechanisms

8.3.1

Parts with interacting geometric features

Figure 8.5: CAD MODEL OF TILTED FRAMES These are parts with complex geometric interactions that makes them almost impossible to manufacture as a single piece with conventional methods. The parts in this category will make full use of the compact decomposition algorithm.


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Tilted frames Figure 8.5 shows the CAD model of a part that is very difficult, if not impossible to manufacture by conventional methods. The part was designed and subsequently built using SDM by Merz[43]. This model serves as a good test case for the compact decomposition algorithm. Figure 8.6 shows the silhouette edges and loops for this model.

Figure 8.6: SILHOUETTE CURVES AND LOOPS The model is then sliced into layers with horizontal planes passing through the lowest and the highest points of the concave silhouette edges (Figure 8.7a). Except for layer3, the decomposed models in all other layers do not violate any of the requirements to be satisfied by a compact. Layer3 is further decomposed as shown in Figure 8.7b such that all the compacts satisfy the three requirements. The support model is decomposed in a similar fashion and the compacts are sequenced for SDM processing. The deposition paths were generated corresponding to union of the top and bottom cross-sections for each compact. The zigzag deposition strategy was used. 2-D cutter paths were generated corresponding to the bottom cross-section of the compacts. For some of these cross-sections, there were self-intersections of the offset model which


86

Layer4

Layer3 Layer2

Layer1

b) Further decomposition of layer3

a) Decomposition using horizontal planes

Figure 8.7: SPATIAL DECOMPOSITION OF TILTED FRAMES were effectively handled by the planner. All the faces that had to be cut with a 3-D cutter were identified as peripheral milled regions and the corresponding cutter paths were generated. Figure 8.8 shows the tilted frames part produced using the SDM process. The part was made out of stainless steel and copper was used as the support material. Microcasting was used to deposit the materials. We faced some difficulties with the ACIS kernel when building this part. Some of the models produced after the compact decomposition were incorrect. This can be attributed to the non-uniform handling of non-manifold features in ACIS. Some slight changes to the model helped us to alleviate the problems.


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Figure 8.8: TILTED FRAMES

8.3.2

Conformable, Embedded Electro-mechanical parts

One other category of parts that are made possible by the SDM process are the embedded electronic parts [67]. These are parts in which the housing could be composed of different materials to provide strength, lightness and toughness. Inside the housing, electronic circuits that are pre-fabricated are embedded. The housing can be of conformable shapes. Such parts are compact, will be rugged in harsh environments and can made to have a very good aesthetic appeal. In the current planner, the pre-fabricated electronic circuits are inserted manually. VuMan VuMan [57] is a personalized wearable computer that can store maps for navigational aids or detailed assembly drawings for service or maintenance applications. VuMan was built in the AutoCADT M solid modeler. The AutoCAD T M model is saved in the ACIS format. Only the support model had to be decomposed into compacts. Both the model and the support were decomposed into three layers using horizontal planes to facilitate the insertion of the printed circuit boards (PCB). The model was made out of two-component polyurethane and was deposited manually and partially cured before machining. The bottom layer of the support and the top layer of the part involved 3-D cutting strategies. In this part, all three types of cutter regions were present. The conical portions were cut using the peripheral end mill strategy, some


88

of the cylindrical portions were cut with the flat end mill strategy and three axis mill strategy was used for some of the blended regions.

Figure 8.9: VUMAN EMBEDDED ELECTRONIC STRUCTURE Figure 8.9 shows the completed VuMan structure and cut-away view of VuMan CAD model.

As mentioned earlier, the part was built out of two-component

polyurethane mixture and wax was used as the support material. The PCBs were electrically interconnected using pin receptacles. Component parts which were not fully embedded were protected during deposition with plastic covers which were machined away during the final machining operation. Simon game

Figure 8.10: CAD MODEL OF SIMON GAME PIECE


89

Simon game is a popular 2-button hand-held game. This is another example of embedded electronic structure built with SDM. The CAD design of Simon part was first done in NOODLES as a CSG tree. The CSG tree primitives and operations were then replicated in the ACIS test harness to create the ACIS model. Figure 8.10 shows the CAD model of the simon game part. Figure 8.11 shows the simon game piece

Figure 8.11: SDM-SIMON GAME manufactured with SDM. It is made of two component polyurethane and wax was used as the support material. The wax was melted out at the end. Two Prefabricated PCBs were inserted manually at an intermediate stage of the process.

8.3.3

Assembled mechanisms

SDM was also used to produce simple mechanisms. It is possible to produce fully assembled functional mechanisms in an integrated fashion with the SDM process. This is mainly made possible by the presence of the sacrificial support structure that holds the moving parts of the assembly while the part is built. Once the support structure is removed the moving parts are free to move again. Figure 8.12 shows the photograph of a simple crank and piston mechanism made with SDM. The CAD model was built in the ACIS test harness. All the concave silhouette loops were on horizontal planes and the compacts were generated by slicing along these planes. The deposition paths and 2-D cutter paths were generated corresponding to the bottom cross-section of each compact. The part was made from stainless steel with copper


90

Figure 8.12: CRANK AND PISTON MECHANISM as the support material. Stainless steel was deposited using the laser station and microcasting was used to deposit the support material.

Chapter 9 Conclusions and Future work 9.1

Contributions

Identification of process planning issues The process planning requirements for a novel manufacturing process, SDM were identified. The three dimensional nature of the SDM process introduces some new challenges in process planning. There are some differences as well as similarities between the process planning issues in SDM and the process planning issues in existing manufacturing technologies. In conventional manufacturing processes like CNC machining, process planning deals with selection and design of fixtures and generation of CNC cutter paths. In SFF processes, process planning deals with slicing the model with a set of parallel planes and generation of scan paths for the 2-D cross-sections. In SDM process one of the main differences is that the model has to be decomposed into 3D layers and compacts. Also, special attention has to be paid to the generation of deposition paths in order to avoid thermal stresses. With the absence of fixturing and tool inaccessibility issues, CNC path generation could be viewed from a whole new angle. Thus a process plan has been outlined to manufacture the part directly from a CAD model. This will facilitate people from remote places to use our facility. With the tremendous growth of internet, such a capability will be of a great value. The approach presented here is thought to be relevant for a range of newly emerging SFF 91

CHAPTER 9. CONCLUSIONS AND FUTURE WORK

92

technologies. Also, the planning for fabrication of MEMS (Micro Electronic Mechanical Systems ) devices is expected to benefit from the ideas of this work. Compact decomposition An algorithm for the decomposition of any CAD model into layers and compacts was described. This decomposition method enables the manufacture of complex, multi-material objects with the help of SDM. Geometric model decomposition is accomplished through a sequence of geometric operations. Silhouette edges and silhouette loops are identified to help the decomposition of models into layers and compacts. Unlike techniques used in existing SFF methods which divide models into equally spaced slices, the present algorithm decomposes models into layers which are not necessarily planar and equally spaced. This has the advantage that the surface information of the original model is preserved and utilized for further process planning steps including CNC cutter path generation. In addition, processing methods permitting, relatively thick layers can be fabricated at once resulting in an increased building rate. Another key step of this algorithm is the determination of the process sequence. Solely based on geometric arguments a feasible sequence of material addition and removal processes is found. This sequence is not unique and the number of generated compacts is not necessarily minimal. The present algorithm focussed on the creation of robust solutions. Some of the ideas presented in this algorithm could also be used in other areas such as parting plane determination and convex decomposition of models. Also, the algorithm could be useful for some of the SFF processes that are entertaining the idea of variable layer thickness. A modification of this algorithm could be used for the determination of support structures in processes such as Stereolithography and FDM. In the existing manufacturing methods, the CAD model is approximated to suit the process planning needs, and it is nearly impossible to reconstruct the original CAD model. In the case of SFF, the CAD model is approximated by a faceted representation and in the case of CNC machining, the CAD model is


93

treated as a surface model. In SDM, the decomposition process doesn’t lose any geometric information from the CAD model and thus it is possible to reconstruct the original CAD model from the compacts. One of the main reasons for such an accurate representation is that the same compact is used for deriving deposition paths as well as CNC cutter paths and is also used in determining the process sequence. Deposition path generation Some of the factors that influence the derivation of deposition path were identified. In SDM, the deposition paths will have a direct influence on the quality of the final part. In particular, deposition paths for droplet based deposition methods can influence the accumulation of residual thermal stresses. Thus it is important to consider the geometric complexity of the part in deriving the deposition paths. Due to the evolving nature of the process, it is difficult to decide on a single deposition pattern for all cases. Methods were outlined to derive spiral and zigzag deposition paths. It was also shown that a variety of other deposition patterns could be derived from these two types of paths. As the process matures, a more intelligent choice of these paths will be possible. CNC cutter path generation Methods have been outlined to generate CNC cutter paths in a completely automated fashion for each compact.

Though

extensive research has been done in the area of CNC cutter path generation, success has been eluding the researchers in completely automating the process. Most of the existing work doesn’t consider the problem in its entirety which can be described as producing the final shape from the initial stock. Instead methods have been outlined to solve sub-problems such as surface machining, rough cutting, pocket milling, etc.. The reasons for a lack of automation and the lack of solution to the entire problem as a whole could be attributed to issues such as fixturing and the inaccessibility of tool to certain portions of the model. Also, the presence of complex undercut features will need multiple fixturing that makes it very difficult to automate the process. In SDM, with the decomposition of the model into compacts, there won’t be any tool accessibility


94

problems and due to the presence of support material, undercut features need not be machined. Also, SDM doesn’t need any complex fixturing operation. Thus, in this work a fully automated approach has been described for CNC cutter path generation. It should be noted that this automation is also an important need for SDM as human intervention with so many compacts would cause considerable delays. Also, it will be difficult for a CNC programmer to generate the paths as some of the original features would have been decomposed into non-intuitive features. The method described in this work offers a solution for the problem in its entirety, wherein a series of CNC cutting operations are used to arrive at the final shape of the part. A new method of decomposition, manhattan decomposition, has been proposed for generating efficient rough cutting algorithms. A robust algorithm has been proposed for generating the offset of 2-D profiles. This algorithm handles all the degeneracies that could result from the offset operation. An algorithm has been proposed for fully automatic 3-D cutter path generation of a solid model without undercut features. The surfaces of the model were grouped under three types of cutter regions based on the curvature information and the methods of cutter path generation for each of these regions were described. A robotic collision detection algorithm has been modified to generate collision free paths. The methods described for CNC cutter path generation are also applicable in areas outside SDM, if the model is free of undercut features. CAD system requirements The requirements to be met by a geometric modeling kernel for the process planner were identified. In contrast to SFF processes, SDM needs a more accurate representation of the model. Also, SDM’s ability to handle multi-material components warrants the need for a non-manifold geometric modeler. During the different stages of process planning, the 2-D and 3-D models are used alternatively. Thus the kernel should be able to support mixed dimensional operations. The planner was implemented under two different geometric modeling kernels and two other geometric modeling


95

kernels are being currently explored. Several parts were built using this process planner. It served as a very useful tool to automatically build several complex parts. It would have been impractical to build these parts without the aid of an automated process planner. In addition to corroborating the ideas presented in this work, the process planner also helped us in giving a better understanding of some process related issues and some planning related issues.

9.2

Future work

With an evolving process such as SDM, new functionalities needs to be added to the process planner as we gain a better understanding of the process. In that sense, this work could be considered as laying the ground work for a SDM process planning system. When using the process planner, the need for additional features was felt by its users. Some of these features have been implemented in the current system. In the following paragraphs, suggestions are given for further improving the process planner. Additional constraints in Compact decomposition The algorithm for compact decomposition presented in this work gives a solution purely based on geometric constraints. Future work in compact decomposition can address the issues of optimality through consideration of non geometric issues such as process economics and material quality. Some of the compacts generated with the current algorithm will have wedge shaped features. In order to process these wedge shaped compacts, cutting tools of infinitely small radius are needed and thus could be shaped only in an EDM machine. Thus, it would be useful if the compact decomposition algorithm could avoid generating wedge shaped compacts. One possible approach would be to sweep in the horizontal direction V = f (X, Y ), instead of the vertical direction in such regions. Of course the interaction of the swept volume with other compacts needs to be handled.


96

Silhouette edges and loops could be generated in the V direction to handle the interaction with other compacts. Due to finite radius of the tool, sharp corners in concave portions of the part will be rounded off by the tool. Such regions could be further decomposed along these sharp corners to generate compacts that doesn’t have any concave sharp corners. In this case, the edges forming the sharp corner will replace the silhouette edges of the current algorithm. The algorithm for compact decomposition doesn’t guarantee the minimum number of compacts. The infinite sweep algorithm generates a near minimal set of compacts, but it was found to be less suited to the process. In the future, if the optimal number of compacts becomes an issue, infinite sweep algorithm could be further explored. Correction based process planning In some cases, due to shrinkage and warpage, the final shape of the part produced by SDM varies in size and shape from the actual model. Shrinkage and warpage occurs due to the accumulation of internal residual stresses. In the case of ceramics and some thermoplastics, the part could shrink by as much as 50 %. In these circumstances, the original model could be modified to take care of these effects such that the part produced by SDM is closer to the original shape. This is in some sense similar to the modifications done to the mold in the casting process. In order to do this correction based planning, we need to have a much better understanding of the process characteristics and the influence of different process parameters on the final shape. The original model could be subjected to the process condition in a simulated environment and an FEM analysis could be done on the model to estimate the shrinkage and residual stresses. The original model would be modified to compensate for shrinkage and to reduce the residual stresses. The main challenges in such an effort would be • Effective modeling of the process conditions • Automatic interpretation of the results of FEM analysis


97

• Automatic modification of the original model based on the results of the analysis In order to effectively exchange data between the original model and the analysis model, an intermediate representation will be needed.

One such possible

representation would be the probabilistic model proposed by Yamaguchi, et. al. [69]. The probabilistic model can represent uncertain shapes with the use of a probability field. The probability field could be changed based on the results of the analysis which will seamlessly modify the original model. Selection of appropriate deposition paths could also be based on such a correction based scheme. In the case of droplet-based deposition process, the deposition paths will have a direct influence on the residual stresses of the part. Different deposition patterns could be characterized based on the resulting residual stresses in the part. Then based on the geometry of the part and the process conditions, an appropriate deposition pattern could be selected. Enhancements to the CNC cutting algorithm The algorithm for 3-D cutting didn’t consider the problem of maintaining continuity in cutter paths across surface patches. If we have C 2 continuity across surface patches, continuity in cutter paths could be maintained by considering multiple patches at the time of decomposing the model into three types of cutter regions. To ensure that we don’t have any un-cut material along the boundaries between different surface patches, the boundaries could be machined with a ball-end mill. The cusp height in 3-D cutting could be minimized by selecting the appropriate step-over distance (distance between two successive paths). Choi et. al., [10] have proposed a 2D constrained optimization problem to minimize the cusp height. In their formulation, cusp height is derived as a function of cutter orientation angles for a given step-over distance. Their formulation could be modified such that the cusp height is a function of the step-over distance for given cutter orientation angles. This function could then be optimized to give the minimum cusp height.


98

Incorporation of sacrificial walls In the case of materials with low viscosity that have a tendency to flow after deposition, the deposited material will have to be contained by building walls surrounding the part. Though the selection of the material to be used for such walls is still under investigation, the process planning effort could be directed in automating the building of such walls into the part. Methodologies for removing these walls should also be included as part of the process planner.

Appendix A Kinematic Transformations Chapters 5 and 6 described algorithms to generate CNC cutter paths for a compact. These paths were generated relative to the coordinate system attached to CAD model. These paths are ultimately executed in a 5-axis CNC milling machine. In SDM, two makes of CNC milling machines have been used : • FADAL VMC 6030 with a Tsudacoma TTNC-301 rotary/tilt table. • MAHO MH 600 C with rotary axes. The cutter paths are supplied to the CNC machine in the form of CNC machine code program, a listing of motion and control commands needed to execute the desired paths with the proper set of parameters. Before the cutter paths are expressed in terms of the machine code, the cutter paths will have to be transformed relative to the tool coordinate frame of the machine. This can be accomplished by modeling the CNC machine as a robotic manipulator and then use Denavit-Hartenberg (DH) [22] representation to describe the relationships between different parts of the machine. The D-H representation results in a 4X4 homogeneous transformation matrix representing one coordinate system with respect to another coordinate system. In the following section, these transformations are derived for the MAHO machine. The transformations for the FADAL machine could be derived in a similar fashion.

99

APPENDIX A. KINEMATIC TRANSFORMATIONS

A.1

100

Coordinate systems

In order to derive the kinematic equations, we need to establish different coordinate systems corresponding to the different moving parts of the CNC machine. Figure A.1 shows the placement of different coordinate systems for the MAHO CNC machine. d2 d3

d4

YA

A

ZA

Z

A O ZO XO

P

ZP

ZZ

Z

XP

XZ

B Y XB

B

ZB

X

Figure A.1: COORDINATE SYSTEMS O is the base coordinate system that is fixed in space and it is located at the top of the face plate. B is the coordinate system attached to the B-axis rotary table and d1 and d2 are the distances between the origins of O and B along the X and Z directions of O when B is in its starting position. A is the coordinate system attached to the A-axis rotary face plate and coincides with O in its starting position. Z is the tool coordinate system and it attached to the tip of the tool. d3 is the distance between O and Z along the Z direction of O when Z is in its starting position. d3 will be equal to the sum of the thicknesses of the air-collar, pallet receiver and base pallet.


101

P is the part coordinate system and it is located at the origin of the part model. d4 is a buffer height and will be equal to the distance between the top of the base pallet and part origin.

A.2

Kinematic equations

~ ) pairs, where P (x, y, z) gives The cutter paths are generated as a list of (P (x, y, z), V ~ gives the direction of a tool vector at the coordinates of the point on the part and V that point. These have to be expressed in terms of translational coordinates (X , Y, Z) and rotational coordinates A, B of the CNC machine. These coordinates are attached to the different coordinate systems as follows : X , Y and B motions are attached to B, A motion is attached to A and Z motion is attached to Z. By deriving the homogeneous transformation P TZ , relating the tool coordinate system Z to the part coordinate system P , we could derive relations for expressing X , Y, Z, A, B in terms of ~ . In the following expressions, i Tj is a homogeneous transformation that (x, y, z) and V specifies the location of the jth coordinate frame with respect to the ith coordinate frame. 

O

TB

   0 =   −sinB  

B

TA

cosB

0 cosA

   −sinA =   0 

0



O

TZ

0 sinB X + d1 1

0 cosB

d2

0

1

0

−sinA

0

−cosA

0

0

−1

0

0

1 0 0

   0 =   0 

Y

0

1 0 0 1

0 0 0

0

−d1

1

       

     −d2  

0



     Z + d3  

0



1

APPENDIX A. KINEMATIC TRANSFORMATIONS 

P

TA

1

   0 =   0 

0 P

0

0

0

−1

0

0

−1

0

0

102 

     −(d3 + d4 )  

0

1

TZ =

P

TA ∗A TZ

=

P

TA ∗A TO ∗O TZ

(A.1)

where A TO is the inverse of O TA which in turn is given by the product of O TB and B

TA . Substituting the expressions for the transformation matrices in Equation A.1

we get, 

P

TZ



cosAcosB −sinA −cosAsinB

P

TZ (1, 4)

cosA

−sinAsinB

P

0

cosB

P

TZ (2, 4)  

0

0

   sinAcosB =   sinB 

0

  

TZ (3, 4)   1

where, P

TZ (1, 4) = YsinA + [d1 − (Z − d2 + d3 )sinB − (X + d1 )cosB]cosA (A.2)

P

TZ (2, 4) = [d1 − (Z − d2 + d3 )sinB − (X + d1 )cosB]sinA − YcosA (A.3)

P

TZ (3, 4) = −(X + d1 )sinB + (Z − d2 + d3 )cosB + d2 − d3 − d4

(A.4)

~ is oriented along the Z-axis of the tool coordinate The given tool vector V system. Thus it will equivalent to the third column of the transformation matrix P

TZ . Equating the corresponding components we get, ~ [0] = −cosAsinB V

(A.5)

~ [1] = −sinAsinB V

(A.6)

~ [2] = cosB V

(A.7)


103

From the equations A.5, A.6 and A.7, we can obtain the expressions for A and B as follows: ~ [1], −V ~ [0]) A = arctan(−V

(A.8)

~ [0]cosA + V~ [1]sinA], −V ~ [2]) B = arctan(−[V

(A.9)

The tool coordinate system Z will be located at the given point P (x, y, z) of the part. Thus the coordinates of P should be substituted to the LHS of the equations A.2, A.3 and A.4 to obtain, x = YsinA + [d1 − (Z − d2 + d3 )sinB − (X + d1 )cosB]cosA

(A.10)

y = [d1 − (Z − d2 + d3 )sinB − (X + d1 )cosB]sinA − YcosA

(A.11)

z = −(X + d1 )sinB + (Z − d2 + d3 )cosB + d2 − d3 − d4

(A.12)

From the equations A.10, A.11 and A.12, we obtain the expressions for X , Y and Z as follows: X = −[z − (d2 − d3 − d4 )]sinB − [xcosA + ysinA − d1 ]cosB − d1

(A.13)

Y = xsinA − ycosA

(A.14)

Z = −[xcosA + ysinA − d1 ]sinB − [z − (d2 − d3 − d4 )]cosB + d2 − d3(A.15) The equations A.8, A.9, A.13, A.14 and A.15 gives the expressions for CNC ~ ). machine coordinates A, B, X , Y, Z in terms of the cutter path pairs (P (x, y, z), V

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