Automatic disassembly navigation for accurate virtual ...

Assembly Automation Automatic disassembly navigation for accurate virtual assembly path planning Wanbin Pan Yigang Wang Peng Du

Article information: To cite this document: Wanbin Pan Yigang Wang Peng Du , (2014),"Automatic disassembly navigation for accurate virtual assembly path planning", Assembly Automation, Vol. 34 Iss 3 pp. 244 - 254 Permanent link to this document: http://dx.doi.org/10.1108/AA-01-2014-008

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Users who downloaded this article also downloaded: Germanico Gonzalez-Badillo, Hugo Medellin-Castillo, Theodore Lim, James Ritchie, Samir Garbaya, (2014),"The development of a physics and constraint-based haptic virtual assembly system", Assembly Automation, Vol. 34 Iss 1 pp. 41-55 http:// dx.doi.org/10.1108/AA-03-2013-023 Hong Xiao, Yuan Li, Jian-Feng Yu, Hui Cheng, (2014),"Dynamic assembly simplification for virtual assembly process of complex product", Assembly Automation, Vol. 34 Iss 1 pp. 1-15 http://dx.doi.org/10.1108/AA-12-2012-093 Germanico Gonzalez-Badillo, Hugo I. Medellin-Castillo, Theodore Lim, James M. Ritchie, Raymond C.W. Sung, Samir Garbaya, (2014),"A new methodology to evaluate the performance of physics simulation engines in haptic virtual assembly", Assembly Automation, Vol. 34 Iss 2 pp. 128-140 http://dx.doi.org/10.1108/AA-05-2013-046

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Automatic disassembly navigation for accurate virtual assembly path planning Wanbin Pan, Yigang Wang and Peng Du


School of Media and Design, Hangzhou Dianzi University, Hangzhou, China Abstract Purpose – The purpose of this paper is to develop an automatic disassembly navigation approach for human interactions in the virtual environment to achieve accurate and effective virtual assembly path planning (VAPP). Design/methodology/approach – First, to avoid the error-prone human interactions, a constraint-based disassembly method is presented. Second, to automatically provide the next operable part(s), a disassembly navigation mechanism is adopted. Finally, the accurate assembly path planning can be obtained effectively and automatically by inversing the ordered accurate disassembly paths, which are obtained interactively in the virtual environment aided with the disassembly navigation matrix. Findings – The applications present that our approach can effectively avoid the error-prone interactive results and generate accurate and effective VAPP. Research limitations/implications – There are several works that could be conducted to make our approach more general in the future: to further study the basic disassembly direction deducing rules to make the process of determining disassembly direction totally automatic, to consider the hierarchy of the parts in virtual reality system and to consider the space for assembly/disassembly tools or operators. Originality/value – The approach has the following characteristics: a new approach to avoid the error-prone human interactions for accurate assembly path planning obtaining, a new constraint deducing method for determining the disassembly semantics automatically or semi-automatically is put forward and a new method for automatically identifying operable parts in VAPP is set forward. Keywords Assembly, Virtual reality, Disassembly, Assembly path planning, Automatic disassembly navigation Paper type Research paper

1. Introduction

exploratory stage (Seth et al., 2011; Yang et al., 2013), and the state-of-the-art works on VAP mainly focus on virtual assembly path/sequence planning (VAPP) to achieve a successful VAP, as VAPP determines the geometric feasibility of an assembly planning (Su, 2007; Su and Lai, 2010; Yu and Wang, 2013). To obtain an effective and a realistic virtual assembly path planning in geometric feasibility, many works on VAPP have endeavored to implement precise object manipulation methods for assembly interactions (Leu et al., 2013; Peng et al., 2008; Rashid et al., 2012), as humans have difficulty in performing precise positioning tasks in the virtual environment. However, the state-of-the-art approaches on VAPP, mainly adopting assembly method (assembling a product from a pile of scattered parts), still have many drawbacks, such as inaccurate positioning part guides (Chryssolouris et al., 2000; Gomes and Zachmann, 1999) and error-prone interactive results (Peng et al., 2008; Yang et al., 2007; Zhu, 2012). One of the fundamental problems for these approaches is that the semantic information (such as constraints and parts’ relations) for an accurate VAPP is insufficient (Leu et al., 2013) and/or usually has been inappropriately used in the virtual environments (Zhu et al., 2010). To realize precise object manipulations for assembly and disassembly activities, in this paper, a novel automatic

It is well known that assembly is a critical step for product development and a time-consuming process in manufacturing. According to the research of Pan (2005), the traditional assembly usually costs 50 per cent of the production developing time while nearly taking up 20 per cent of the total manufacturing time. Thus, how to make a feasible and an efficient assembly planning is always of significance in assembly research (Leu et al., 2013; Rashid et al., 2012). According to the above sense, virtual assembly planning (VAP) provides a new idea to interactively make an assembly planning and verify it in the virtual environment before manufacturing the real products; thus, it has been widely used in product development (Gao et al., 2013; Yang et al., 2013; Zhu, 2012; Zhu et al., 2010) and gradually replaces the computer-aided assembly planning (CAPP) (Leu et al., 2013). Furthermore, it is well known that a successful VAP can reduce the time and the cost of the assembly process, and increase production efficiency. Generally speaking, the research of VAP is still at an

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Assembly Automation 34/3 (2014) 244 –254 © Emerald Group Publishing Limited [ISSN 0144-5154] [DOI 10.1108/AA-01-2014-008]

The authors are very grateful to the financial support by the Defense Industrial Technology Development Program of China.

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Automatic disassembly navigation

Assembly Automation

Wanbin Pan, Yigang Wang and Peng Du

Volume 34 · Number 3 · 2014 · 244 –254

disassembly navigation approach for accurate VAPP, mainly focusing on the parametric computer-aided design (CAD) models, is presented with a view to overcome the above mentioned problems for an accurate VAPP. Our approach consists of the following parts: ● we propose a disassembly navigation matrix for each product by deducing its disassembly semantics; ● we import the input product model into our virtual reality (VR) system while maintaining its parts’ global positions and orientations; ● we interactively disassemble each part from the model according to its disassembly navigation matrix; and ● an accurate VAPP (motion) can be conveniently obtained by inversing the above disassembly process.

Du (2008) present an approach for automatic assembly sequence planning by using an integrated framework of assembly relational model and assembly process model. Zeng et al. (2013) present a multi-agent evolutionary algorithm for assembly sequence planning to improve individuals’ intelligence and decrease blind searching. Disassembly-based CAPP This type of CAPP approach aims to obtain the optimal assembly sequence or path by disassembling an assembly into parts (Kim et al., 2007). Zha et al. (1998) present an approach to generate all feasible assembly sequences of the product by reasoning and decomposing the feasible subassemblies, and representing them by the assembly Petri net modeling. Huang et al. (2002) present an approach to generate all of the possible disassembly sequences and directions for components in a tree diagram by using a Boolean operation or an arithmetic operator with the depth-first search method. Kongar and Gupta (2006) present a genetic algorithm for disassembly sequencing of the end-of-life of products. González et al. (2006) present a scatter search metaheuristic aiming to deal with the optimum disassembly sequence problem for the case of complex products with sequence-dependent disassembly costs. Tseng et al. (2011) present a green assembly sequence planning model with a closed-loop assembly and disassembly sequence planning using a particle swarm optimization method. Su et al. (Su, 2007; Su and Lai, 2010) reason assembly precedence and optimal sequence in a CAD system using the angle interval (as disassembly constraints) and the minimal constraint assembly state. Based on a CAD environment, Yu and Wang (2013) present a method for discriminating geometric feasibility in assembly planning based on the two interference matrixes (extender interference matrix and turning interference matrix). However, the existing CAPP approaches commonly have several limitations, such as: ● selecting an optimal assembly planning is difficult and time-consuming; and ● the embedded semantic information is insufficient. Furthermore, most of them mainly focus on sequence planning but neglect the path planning, which determines the geometric feasibility of an assembly planning.

The remaining paper is organized as follows. In Section 2, we give a brief review of related works. In Section 3, an overview of our approach is provided. In Section 4, a detailed process of determining disassembly navigation information for an input CAD assembly is given. In Section 5, we present our approach for VAPP based on the disassembly navigation matrix and a collision detection method. Section 6 introduces the implementation details of the prototype system and illustrates some experiments and comparisons. In Section 7, we conclude the paper and present further works.

2. Related works Although the research of VAP is still at an exploratory stage, there are many relevant works on assembly planning (focusing on sequence and/or path planning). The works we survey here are those most closely related to mechanical engineering domain. The CAPP has the ability to automate assembly planning to reduce labor intensity and simplify the planning process. Generally speaking, CAPP approaches can be roughly divided into two categories: assembly-based CAPP and disassembly-based CAPP. Assembly-based CAPP This type of CAPP approach aims to obtain the optimal assembly sequence or path by assembling the parts into the final product. Sinanoglu and Börklü (2005) present an assembly sequence planning system with the input of each assembly’s connection graph and use a neural network approach to determine the optimum assembly sequence. Lai and Huang (2004) present a systematic approach for automatic assembly sequence planning generation. The approach aims to propose a unified and integrated mathematical representation that allows an optimal assembly sequence be generated for various different production conditions and environments. Çiçek and Gülesin (2007) present an approach to recognize the CAD models through their face adjacency relations and attributes (represented in a square matrix FORM) and to automatically assemble the recognized parts in a CAD environment. Zhao and Li (2009) present a formalized reasoning method for assembly sequence generation by using a polychromatic sets matrix to describe the relations between the part-match (mapping to parts’ relations) and freedom (indication the assembly constraints). Zhou and

These limitations have led CAPP into the realm of VAP. Generally speaking, the works on VAP mainly focus on VAPP currently. The state-of-the-art approaches on VAPP fall broadly into the following categories. CAPP combination The general idea of this type of VAP approaches (Fan et al., 2004; Che, 2010; Christiand and Yoon, 2007) is that virtual environment is used to verify the given disassembly or assembly sequences or paths, which are generated using some efficient algorithms adopted in CAPP. Fan et al. (2004) introduce an integrated assembly object model to represent different kinds of assembly data and knowledge and support virtual assembly, to realize automation and intelligence of product disassembly process in a virtual environment. Liu et al. (2012) present a max–min ant system-based methodology for product disassembly sequence planning, which is transformed into the problem of searching optimal 245



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path on a feasibility graph. The main drawbacks of these approaches are that the feasible disassembly or assembly sequence or path reasoning is time-consuming, and operator’s randomicity during assembly or disassembly process is not taken into consideration (Zhu et al., 2010).

The interference-related path is the focus of the works on semantics-based VAPP (also as the focus of this work) and directly determines the effectiveness and the accuracy of a VAPP in geometric feasibility (Leu et al., 2013; Zhu, 2012). The input of our approach is a parametric CAD product, which is a parametric solid model and is composed of more than one part. Regarding the drawbacks for obtaining the interference-related paths in current VAPP works (i.e. inaccurate positioning part guides, error-prone interaction results, etc.) and the feasible paths generated by disassembly are more reasonable and understandable, in this work, we resolve it using a semantics-based navigation disassembly method based on the assumption that the given product can always be disassembled. Figure 1 shows the systematic overview of the approach which consists of the following parts: ● by deducing the model’s assembly constraints, the disassembly navigation matrix for the given CAD model is determined automatically or semi-automatically; ● with the aid of a continuous collision detection method in the virtual environment, parts are interactively disassembled from the model one by one according to the disassembly navigation matrix. Meanwhile, each disassembly path will be recorded, such as the disassembly path (from red line to black curve) shown in Figure 1; and ● inversing the above disassembly paths, an accurate VAPP can be conveniently obtained, such as the assembly path (from black curve to red line) shown in Figure 1.

Direct manipulation This type of VAP works for the investigation and simulation of products mainly relies on collision detection and threedimensional (3D) equipment integration. Gomes and Zachmann (1999) present several interaction paradigms and functionality which a VR system must be implemented in order to be suitable for that area of application. Chryssolouris et al. (2000) present a virtual assembly work cell, which can be used as a planning tool for assembly processes based on VR techniques. However, the works on direct manipulation in the virtual environment are weak at accurately guiding users’ interactions. Semantics-based path planning This kind of VAPP approaches integrates semantic (non-geometric) data into the assembly and disassembly actions in the virtual environment. Furthermore, the key semantic information widely used in currently VAPP works is the assembly constraint (Leu et al., 2013). Peng et al. (2008) present a constraint-based motion navigation approach to ensure that the manipulation of a fixture component does not violate the existing constraints. Yang et al. (2007) present the algorithms of constraint recognition, constraint confirmation and motion navigation based on DOF analysis in a virtual environment. Zhu (2012) and Zhu et al. (2010) present an assembly semantic modeling approach for interactive assembly and process generation. Yang et al. (2013) present a product assembly model to support the assembly operation actions obtained through virtual assembly simulation. However, in these approaches, all the predefined semantics (constraints) need recognizing in virtual assembling process (which may be recognized or confirmed falsely as the operation process is not convenient enough).

In view that the third part of our approach is simple, we just describe parts 1 and 2 in detail below.

4. Determination of disassembly navigation matrix Many existing works (Yu and Wang, 2013; Zhu, 2012) show that assembling or disassembling a product with accurate navigations can avoid the error-prone human interactions. Thus, we propose a disassembly navigation matrix (Figure 2(c)) to supplement human interactions for accurate disassembly path generation. Here, each disassembly direction in a disassembly navigation matrix (Figure 2(c)) for a part (in row) represents the part’s disassembly freedom relative to other part (in column). Different from the interference matrix method (Yu and Wang, 2013), in this paper, the disassembly direction is not confined to the axial direction of each part’s local coordinate or global coordinate. Furthermore, as the traditional methods for deducing degree of freedom (deriving DOFs from the mates (constraints)) (Chen et al., 2012; Turner et al., 1992; Yang et al., 2007) are used to describe the remaining permissible rigid-body motions of a part after assembling, they are not suitable here for deducing disassembly freedoms for each part. Thus, in this work, we determine the disassembly direction for one part relative to other one in the following two steps: 1 According to the mate type between two mated geometric elements respectively belonging to two parts, we

3. Approach overview Generally speaking, the virtual assembly path for each part is composed of two paths: 1 interference-free path (black path in Figure 1); and 2 interference-related path (red path in Figure 1). A part’s disassembly or assembly path is represented by the motion path of the part’s geometric center. Interference-related path An interference-related path for a part is the motion path for separating/linking the part from/with other one in their joints’ interfaces, where the collisions are unavoidable. For example, in Figure 1, manipulating the part A along the red path, which is the only effective path to disassemble or assemble the two parts, is collision unavoidable. Thus, the red path is called an interference-related path for parts A and B. Otherwise, the motion path is called an interference-free path, such as the black path. 246


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Figure 1 Overview of our approach (the product is composed of two parts: A and B; the vector Vi is the disassembly direction for separating B from A according to the disassembly navigation matrix (described in Section 4); motion path of a part’s geometric center represents the part’s disassembly or assembly path; the red motion path (red line) represents the interference-related path while the black motion path (black curve) represents the interference-free path and the two paths compose the final disassembly/assembly path) CAD Environment

Virtual Environment

Vi A

Constraints

Vi

B

deduction

Data exporting

Process inverse

Vi

A B A Φ -Vi B Vi Φ Disassembly navigation matrix


Disassembly & Process recording

Assembly path

Figure 2 Illustration of the process to deduce disassembly navigation matrix (FA1 and FA2 represent two faces in part A; FB1, FB2, FB3 and FB4 represent four faces in part B; FC1 and FC2 represent two faces in part C; each row item in (b) represents that each mate (constraint) between two faces corresponds to a basic disassembly direction for the two parts, respectively, containing the two faces; each matrix value in ⬍Pi, Pj⬎ of (c) represents the final deduced disassembly direction that separates the Pi part (in the Pi row) from the Pj part (in the Pj column); all of the directions are obtained from the clamp model’s global coordinate) FB3

FB1 FA2

FB2 o

90

V2

FA1 A

FB4

B

FC1 B

V1 A

D1

C

FC2

Mate Mated type elements Mate mapping Concentric FA1-FB1 Coincident FA2-FB2 Coincident FB4-FC1 …… FC2-FB3 Distance

(a)

Basic disassembly Deducing direction disassembly V1 / -V1 direction V1 i V2

A

B

C

A

Φ

V1

Φ

B

-V1

Φ

-V1

C

Φ

V1

Φ

V1

(b)

(c)

Notes: (a) Clamp model; (b) basic disassembly directions; (c) clamp’s disassembly navigation matrix V(v1, v2, v3) that the direction component of any force vector ⌫(⌫1, ⌫2, ⌫3) imposing on A in V must ⱖ 0 for separating A from B on these two mated geometric elements (in other words, v1⌫1 ⫹ v2⌫2 ⫹ v3⌫3 ⱖ 0). For example, in Figure 2(a), two mated faces FA2 and FB2 belong to parts A and B, respectively. A basic disassembly direction for separating A from B is V1, as V1 determines the direction for separating A from B on the two mated faces (Figure 2(b)): 2 According to the above definition, the final disassembly direction V(X, Y, Z) for separating A from B is deduced

determine a basic disassembly direction for the two parts on these two mated geometric elements as shown in Table I. The common mates between two faces (cylinders, planes) can be automatically mapped to a basic disassembly direction(s). In other cases, we use an assistant tool to map each mate to a basic disassembly direction. Basic disassembly direction The basic disassembly direction for separating part A from part B, on one pair of their mated geometric elements, is a unit vector

Table I Mapping between typical mates and basic disassembly directions (geometric element X belongs to part A while geometric element Y belongs to part B) Mate type

Two mated geometric elements

Basic disassembly direction

Comments

Concentric Tangent

cylinder X-cylinder Y cylinder X-cylinder Y plane X-cylinder Y

V1 and ⫺V1: V1 is axial direction of X

Translating A(B) along V1/⫺V1

V1: normal of X

plane X-plane Y any type X-any type Y

V1: normal of Y V1: human interaction

Translating Translating Translating Translating

Coincident/distance Other mate

247

A along ⫺V1; B along V1 A along V1; B along ⫺V1


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5. Path planning aided by automatic disassembly navigation

by solving the following non-linear optimization problem: N

Max P ⫽

N

After determining the disassembly navigation matrix for a given product, we carry out assembly path planning in our VR system built on OpenSceneGraph (OpenSceneGraph). To be a common method, we use mesh to represent each part after exporting the part from a CAD system to our VR system, as exporting the parametric information of a product from a CAD system into a VR system is still a critical issue (Leu et al., 2013). Furthermore, we use an assistant tool to export all the parts to our VR system according to the product’s global coordinate. Thus, although the parametric information in the product is lost and the geometric representation for each part becomes mesh, the disassembly direction for each pair of the exported parts is still effective, as the relative positions and relative orientations among all the parts in the virtual environment are the same as those in the CAD system. As a result, we can lead to an accurately part disassembling in our virtual environment. Furthermore, instead of searching separable parts in the whole model human-dependently, each separable part is automatically identified with the aid of disassembly navigation matrix. The whole process of our path planning approach is shown in Figure 3. Here, a part will be identified as the first separable part in each disassembly step (Figure 4) if it satisfies one of the following cases: ● the part only has one disassembly direction in the product; and ● the part has more than one disassembly directions while all the disassembly directions are equal.

N

兺v X ⫹ 兺v Y ⫹ 兺v z i1

i⫽1

i2

i3

i⫽1

i⫽1

S.T. v11X ⫹ v12Y ⫹ v13Z ⱖ 0 v21X ⫹ v22Y ⫹ v23Z ⱖ 0 vN1X ⫹ vN2Y ⫹ vN3Z ⱖ 0 X2 ⫹ Y2 ⫹ Z2 ⫽ 1


Here, we assume V1(v11, v12, v13), V2(v21, v22, v23), [. . .] [. . .] and VN(vN1, vN2, vN3) are the N (ⱖ2) basic disassembly directions between parts A and B (separating A from B), respectively, mapping to N mates between A and B. We use Mathematica (Wolfram Mathematica) to solve the non-linear optimization problem. The result of the optimization problem represents the most effective direction for separating A from B. Besides, we use a “disassembly navigation matrix” (Figure 2(c)) to represent all of the final disassembly directions between each pair of the parts in a given product. For example, vector V1 is the basic disassembly direction for separating part A from B on the two mated faces FA2 and FB2, and the other basic disassembly direction for separating part A from B on the two mated faces FA1 and FB2 is V1 (as using ⫺V1 as the basic disassembly direction, the optimization problem has no solution), the final disassembly direction for separating part A from B is equal toV1. Besides, if there is no mate between two parts, there is no disassembly direction between them as well and we use ⌽ to represent that, such as the disassembly direction between part A and C is ⌽.

For example, in step 1 of Figure 4(a), disassembling part A from the whole model, we shall separate it from parts B and F according to the disassembly navigation matrix. Because the

Figure 3 The process of path planning with the aid of disassembly navigation matrix Product composed of mesh parts & corresponding disassembly navigation matrix Identifying the first separable part from the matrix

No

Existing a separable part Yes Notifying users and waiting for manipulation

No

User confirmation

Separated parts & the disassembly path group

Yes 1. Restricting user’s manipulation to get the interference-related disassembly path before separating the part from other one(s); 2. Using human interaction aided with a collision detection method to get the interference-free disassembly path after separating the part from other one(s); 3. Appending the above disassembly paths to the disassembly path group based on their recording times; 4. Modifying the matrix.

248

1. Inversing the path order in the disassembly path group; 2. Inversing each disassembly path.

One feasible assembly path planning


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Figure 4 Illustration of disassembling a product aided by a disassembly navigation matrix (each mark ➀ represents the first identified separable part and its corresponding disassembly path in each step; the assembly sequence of 1, 2, 3, 4, 5 and 6 is the final accurate virtual assembly path planning) D B

C

E

G

A

F


V1

A B C 4 D ƻ E F G

A B C D E F G

A Φ Φ Φ Φ Φ Φ Φ

B Φ Φ Φ Φ Φ Φ Φ

C Φ Φ Φ Φ Φ Φ Φ



D Φ Φ Φ Φ Φ Φ Φ

(g)


E Φ Φ Φ Φ Φ Φ Φ

1 A ƻ B C D E F G

D Φ Φ Φ Φ V1 V1 V1 (d)

F Φ Φ Φ Φ Φ Φ Φ

A B Φ V1 -V1 Φ Φ Φ Φ Φ Φ V1 -V1 V1 Φ V1

E Φ Φ Φ -V1 Φ Φ V1

G Φ Φ Φ Φ Φ Φ Φ

F Φ Φ Φ -V1 Φ Φ -V1

C D Φ Φ Φ Φ Φ V1 -V1 Φ Φ V1 -V1 V1 Φ V1 (a) G Φ Φ Φ -V1 -V1 V1 Φ

E F G Φ V1 Φ -V1 -V1 -V1 Φ V1 Φ -V1 -V1 -V1 Φ Φ -V1 Φ Φ V1 V1 -V1 Φ


A 2 B ƻ C D E F G

B Φ Φ Φ Φ V1 V1 V1

C Φ Φ Φ -V1 Φ -V1 Φ

D Φ Φ V1 Φ V1 V1 V1

E Φ -V1 Φ -V1 Φ Φ V1

F Φ -V1 V1 -V1 Φ Φ -V1

G Φ -V1 Φ -V1 -V1 V1 Φ

A B 3 C ƻ D E F G



C Φ Φ Φ -V1 Φ -V1 Φ

(b)

A B C D 5 E ƻ F G



C D Φ Φ Φ Φ Φ Φ Φ Φ Φ Φ Φ Φ Φ Φ (e)

F Φ Φ Φ Φ Φ Φ -V1

E Φ Φ Φ -V1 Φ Φ V1

F Φ Φ V1 -V1 Φ Φ -V1

G Φ Φ Φ Φ -V1 V1 Φ

A B C D E 6 F ƻ G




D Φ Φ Φ Φ Φ Φ Φ (f) 3 ƶ

E F Φ Φ Φ Φ Φ Φ Φ Φ Φ Φ Φ Φ Φ -V1

G Φ Φ Φ Φ Φ V1 Φ

V1

3 ƻ

2 ƻ

4 ƶ 2 ƶ

6 ƻ

1 ƶ

5 ƶ 1 ƻ

(h)

G Φ Φ Φ -V1 -V1 V1 Φ

(c)

V1

4 ƻ

5 ƻ

E Φ Φ Φ Φ Φ Φ V1

D Φ Φ V1 Φ V1 V1 V1

6 ƶ

(i)

Notes: (a) Step 1: A is the 1st separable part; (b) step 2: B is the 1st separable part; (c) step 3: C is the 1st separable part; (d) step 4: D is the 1st separable part; (e) step 5: E is the 1st separable part; (f) step 6: F is the 1st separable part; (g) final disassembly navigation matrix; (h) the recorded disassembly paths; (i) an accurate assembly path planning two directions (in the same row of A) are the same, respectively, for separating A from B and separating A from F, part A is identified and provided to the user as the first separable part in this step. According to the process shown in Figure 3, after getting the user’s confirmation, the interference-related disassembly path for A is obtained by an interactive translation in the restricted direction V1 (shown in Figure 4(h)). Then, each disassembly direction in the disassembly navigation matrix referring to part A should be set to ⌽ (shown in red in Figure 4(b)), as A has been separated (disassembled) from the whole model. Besides, each interference-related disassembly path (such as each red line in Figure 4(h)) for a part is visualized as a directed straight line segment (as human interaction is restricted before separating the part from other one(s) in this work) along the direction of the part’s movement. Each interference-free path is obtained interactively in our VR system aided with the efficient continuous collision detection method VolCCD (Tang et al., 2011), which is a culling algorithm that includes a continuous separating axis

test to conservatively check whether two meshes (volume mesh parts and triangle mesh parts) overlap during a given time interval. Furthermore, the adopting method can efficiently compute the first time of contact in our interaction process, while the collision result is more accurate than the method used in Zhu et al.’s (2010) work (using collision method to get the assembly path). Besides, each interference-free disassembly path (such as each black line in Figure 4(h)) for a part in this work is visualized as a directed free-form curve segment (after separating the part from other one(s), human interaction is not constrained, except for the collision avoidance in this work) along the direction of the part’s movement. In addition, each part in our VR system has been associated with a motion recorder AnimationPath (OpenSceneGraph), which can simultaneously and sequentially record the motion path (disassembly path composed of interference-related disassembly path and interference-free disassembly path) of the part in its whole disassembling process. Thus, inversing the above sequential 249



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record (inversing the disassembly path), we can get the part’s assembly path. Here, according to the above sense, each disassembly/assembly path is definitely accurate and feasible. After all the disassembly paths for all the input mesh parts having been recorded and stored in a disassembly path group, an accurate disassembly path planning for the input product is obtained. Then, inversing the path order in the disassembly path group and each disassembly path, an accurate virtual assembly path planning is obtained. For example, as shown in Figure 4(h), the ordered disassembly paths ①, ②, ③, ④, ⑤ and ⑥ are recorded for disassembling parts A, B, C, D, E and F, respectively. Its corresponding virtual assembly path planning is composed of the order 1 , ƶ 2 , ƶ 3 , ƶ 4 , ƶ 5 and ƶ 6 as shown in virtual assembly paths ƶ Figure 4(i).

approaches, as we focus on the interference-related path planning. We adopt one additional complex model Backhoe (shown in Figure 5, Apendix Figure 1 and Appendix Figure 2; designed and provided by Branko Stokuca) to demonstrate the effectiveness of our approach.

6.1 Comparison Compared with the state-of-the-art approaches on semantics-based path planning, our approach has several advantages. Here, we conduct the comparisons (Table II) between the work of Zhu et al. (2010) (a representative work on semantics-based path planning) and our approach according to the following items: ● what is the input of CAD-based VAPP prototype; ● what is the semantic type; ● what about the semantics definition means; ● whether the input of virtual environment is separated (scattered) parts (whether the parts (meshes) keep their relative orientations and positions as they were in CAD environment); ● what about the semantics navigation means; ● whether the approach has the ability of identifying the next operable part(s) automatically; ● whether the approach is low 3D equipment requirement; ● whether the approach needs elaborate and complex interaction; and ● what about the obtaining means for path planning.

6. Implementation and comparison The proposed automatic disassembly navigation approach for accurate VAPP has been implemented in our DNAfAVAPP prototype (CAD-based VAPP prototype) as shown in Figure 5. The assistant tools for exporting models and for interactively mapping each mate to a basic disassembly direction are developed by using Microsoft Visual C# 2008 and built as plug-ins of SolidWorks (2012). Furthermore, although we use VolCCD to obtain interference-free paths in real time, our approach is relatively independent on continuous collision detection Figure 5 The user interface of our DNAfAVAPP prototype

Table II Comparisons between the approach of Zhu et al. (2010) and our approach

Input Semantic type Semantics definition means Separated (scattered) parts for VR Semantics navigation means Identifying the next operable part(s) automatically Low 3D equipment requirement Need elaborate and complex interaction Obtaining means for path planning

Zhu et al. (2010)

Our approach

One parametric product Assembly semantics Interactive definition Yes Interactively recognizing and confirming No No Yes Obtaining after assembling

One parametric product Disassembly semantics Automatic or semi-automatic deduction No Automatically constraining interaction Yes Yes No Inversing the obtained disassembly path

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7. Conclusion and future works

Chryssolouris, G., Mavrikios, D., Fragos, D. and Karabatsou, V. (2000), “A virtual reality-based experimentation environment for the verification of human-related factors in assembly processes”, Robotics and Computer-Integrated Manufacturing, Vol. 16 No. 4, pp. 267-276. Çiçek, A. and Gülesin, M. (2007), “A part recognition based computer aided assembly system”, Computers in Industry, Vol. 58 Nos 8/9, pp. 733-746. Fan, J., Ye, Y. and Cai, J.-M. (2004), “Multi-level intelligent assembly sequence planning algorithm supporting virtual assembly”, IEEE International Conference on Systems, Man and Cybernetics, Hague, pp. 3494-3499. Gao, W., Shao, X. and Liu, H. (2013), “Virtual assembly planning and assembly-oriented quantitative evaluation of product assemblability”, The International Journal of Advanced Manufacturing Technology, DOI: 10.1007/ s00170-013-5514-8 Gomes, A. and Zachmann, G. (1999), “Virtual reality as a tool for verification of assembly and maintenance processes”, Computers and Graphics, Vol. 23 No. 3, pp. 389-403. González, B. and Adenso-Díaz, B. (2006), “A scatter search approach to the optimum disassembly sequence problem”, Computers and Operations Research, Vol. 33 No. 6, pp. 1776-1793. Huang, Y.M. and Huang, C.-T. (2002), “Disassembly matrix for disassembly processes of products”, International Journal of Production Research, Vol. 40 No. 2, pp. 255-273. Kim, H.-J., Lee, D.-H. and Xirouchakis, P. (2007), “Disassembly scheduling: literature review and future research directions”, International Journal of Production Research, Vol. 45 Nos 18/19, pp. 4465-4484. Kongar, E. and Gupta, S.M. (2006), “Disassembly sequencing using genetic algorithm”, The International Journal of Advanced Manufacturing Technology, Vol. 30 Nos 5/6, pp. 497-506. Lai, H.-Y. and Huang, C.-T. (2004), “A systematic approach for automatic assembly sequence plan generation”, The International Journal of Advanced Manufacturing Technology, Vol. 24 Nos 9/10, pp. 752-763. Leu, M.C., ElMaraghy, H. A., Nee, A.Y.C., Ong, S.K., Lanzetta, M., Putz, M., Zhu, W. and Bernard, A. (2013), “CAD model based virtual assembly simulation, planning and training”, CIRP Annals-Manufacturing Technology, Vol. 62 No. 2, pp. 799-822. Liu, X., Peng, G., Liu, X. and Hou, Y. (2012), “Disassembly sequence planning approach for product virtual maintenance based on improved max-min ant system”, The International Journal of Advanced Manufacturing Technology, Vol. 59 Nos 5/8, pp. 829-839. OpenSceneGraph 3.1.0 (2012), an open source, available at: www.openscenegraph.org (accessed 9 May 2013). Pan, C. (2005), Integrating CAD Files and Automatic Assembly Sequence Planning, IA State University Press. Peng, G., He, X., Yu, H., Hou, X. and Alipour, K. (2008), “Precise manipulation approach to facilitate interactive modular fixture assembly design in a virtual environment”, Assembly Automation, Vol. 28 No. 3, pp. 216-224. Rashid, M.F.F., Hutabarat, W. and Tiwari, A. (2012), “A review on assembly sequence planning and assembly line balancing optimisation using soft computing approaches”,

Although the VAPP is essential and important for VAP, there are few works that guarantee to obtain an accurate and effective VAPP (in geometric feasibility). In this paper, we propose an automatic disassembly navigation approach for accurate VAPP. The approach has the following contributions and characteristics: ● the approach can obtain an accurate assembly path planning effectively and automatically by inversing the ordered accurate disassembly paths, which is obtained interactively in the virtual environment aided with the accurate disassembly constraints (deduced in CAD environment) to avoid the error-prone human interactions; ● a new constraint deducing method for determining the disassembly semantics automatically or semi-automatically is put forward; and ● a new method for automatically identifying operable parts in VAPP is set forward based on the proposed disassembly navigation matrix. It is important to note that while our approach also creates an assembly sequence in the process of making an accurate VAPP, we do not claim that it is an optimal assembly sequence. To find an optimal assembly sequence after obtaining all disassembly paths is one of our future works. Considering that the accurate VAPP is a well-recognized challenging problem, we choose to solve the problem step by step. There are several works that could be conducted to make our approach more general in the future: ● to further study the basic disassembly direction deducing rules to make the process of determining disassembly direction totally automatic; ● to consider the hierarchy of the parts in VR system, as each product usually is assembled hierarchically; and ● to consider the space for assembly/disassembly tools or operators and so on. Although we use matrix to navigate disassembly operations, it would be very interesting to further study the relevance between the assembly task and some kind of the inverse of the matrix.

Note 1. We claim that all of the Figures in our paper (Automatic disassembly navigation for accurate virtual assembly path planning AA-01-2014-008.R1) are designed and rendered by ourselves. Thus, there is no issue with copyright infringement about using them in this paper.

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Appendix A

C and E, C and E have no interference after separating A from the whole model. Similarly, parts C and I have no interference after separating part B from the whole model, as B is a bolt that links C and I. Thus, after separating both A and B from the whole model (such as the cases in Figure A2 and Figure A2(b)), the disassembly path of C is actually its interference-free disassembly path ③ as shown in Figure A2.

Figure A1 shows illustration of virtual assembly path planning for a partial digger model (the model are composed of 29 parts; the colored paths (29 paths: ①, ②, etc.) compose the recorded disassembly paths in disassembly stage; the colored paths (29 paths: , , etc.) compose the final assembly path planning in assembly stage). Here, because part A as a bolt that links part


Figure A1 Illustration of VAPP for a partial digger model (the model is composed of 29 parts; the colored paths (29 paths: ➀, ➁, etc.) composes the recorded disassembly paths in disassembly stage; the colored paths (29 paths: , , etc.) compose the final assembly path planning in assembly stage)

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Figure A2 The process of identifying separable parts and generating disassembly sequence for the digger model (Figure 1) with the aid of its disassembly navigation matrix H Φ Φ Φ Φ Φ Φ Φ Φ -V1

I Φ V1 Φ V1 Φ Φ V1 V1 Φ

A 2 B ƻ C D E F G H I

A Φ Φ Φ Φ Φ Φ Φ Φ Φ

B Φ Φ -V1 Φ Φ Φ Φ Φ -V1

C Φ V1 Φ Φ Φ Φ Φ Φ Φ

D E Φ Φ Φ Φ Φ Φ Φ Φ Φ Φ -V1 -V2 Φ Φ Φ Φ -V1 Φ

……


B Φ Φ Φ Φ Φ Φ Φ Φ Φ

C Φ Φ Φ Φ Φ Φ Φ Φ Φ


……

F Φ Φ Φ V1 V2 Φ Φ Φ Φ

G Φ Φ Φ Φ Φ Φ Φ Φ -V1

H Φ Φ Φ Φ Φ Φ Φ Φ -V1

I Φ Φ Φ V1 Φ Φ V1 V1 Φ

A B C D 5 E ƻ F G H I




D Φ Φ Φ Φ Φ Φ Φ Φ Φ




E Φ Φ Φ Φ Φ Φ Φ Φ Φ

……

(g)

I Φ V1 Φ V1 Φ Φ V1 V1 Φ

A B 3 C ƻ D E F G H I





……

F Φ Φ Φ Φ Φ Φ Φ Φ Φ



I Φ Φ Φ Φ Φ Φ V1 V1 Φ

A B C D E F G 8 H ƻ I






……




I Φ Φ Φ V1 Φ Φ V1 V1 Φ






G Φ Φ Φ Φ Φ Φ Φ Φ Φ

H Φ Φ Φ Φ Φ Φ Φ Φ Φ

I Φ Φ Φ Φ Φ Φ Φ Φ Φ

(c) F Φ Φ Φ Φ V2 Φ Φ Φ Φ




A B C D E 6 F ƻ G H I






……

(e)

……


E Φ Φ Φ Φ Φ -V2 Φ Φ Φ

……

(d)

A B C D E F 7 G ƻ H I


……

A B C 4 D ƻ E F G H I


(b)

……


(a)


……


……

……


(f) F Φ Φ Φ Φ Φ Φ Φ Φ Φ

G Φ Φ Φ Φ Φ Φ Φ Φ Φ


(h)

…… ……

I Φ Φ Φ Φ Φ Φ Φ V1 Φ

A B C D E F G H 9 I ƻ






……

……

D E Φ V1 Φ Φ Φ Φ Φ Φ Φ Φ -V1 -V2 Φ Φ Φ Φ -V1 Φ

……

C V1 V1 Φ Φ Φ Φ Φ Φ Φ

……

A B Φ Φ Φ Φ -V1 -V1 Φ Φ -V1 Φ Φ Φ Φ Φ Φ Φ Φ -V1

……

1 A ƻ B C D E F G H I

(i)

Notes: (a) Step 1: A is the 1st separable part; (b) step 2: B is the 1st separable part; (c) step 3: C is the 1st separable part; (d) step 4: D is the 1st separable part; (e) step 5: E is the 1st separable part; (f) step 6: F is the 1st separable part; (g) step 7: G is the 1st separable part; (h) step 8: H is the 1st separable part; (i) step 9: I is the 1st separable part

Corresponding author Yigang Wang can be contacted at: yigang.wang@hdu. edu.cn

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