Proposal for Tool-based Method of Product Cost ...

Journal of Engineering Design, Vol. 19/2, pp.159 – 17, 2008

Proposal for Tool-based Method of Product Cost Estimation during Conceptual Design M. MAUCHAND†, A. SIADAT‡, A. BERNARD*, N. PERRY The undertaken project aims at offering a support for the manufacturing cost estimation of products in the conceptual design phase. This need for dedicated tools for designer emerges from the lack of means to determinate the best technical solution that permits to save costs and to reach safe quality. The main objective of this tool is to assist the designer in the process of manufacturing cost calculation of a product that is defined by little and inaccurate information in the preliminary design. This paper presents a procedure to develop such a tool. Keywords: Preliminary design, decision-making system, cost estimation, expert knowledge, and ontology. 1 Introduction The aim of this project is to provide a support for the manufacturing cost estimation of products in the conceptual design phase. This article presents the specification needs of such a tool in order to achieve a relevant cost estimation. In order to perform a manufacturing cost estimation, it is necessary to classify the costs models that could be used to estimate the product cost. For instance, it could be an equation or a logical rule. This constitutes a part of our expert knowledge. The other part resides in the manufacturing expert rules. This knowledge is essential to determine the activities and the factors that generate cost. The first problem resides in the fact that the product description that can be done in preliminary phase is poor in information. This report brings us to think about the criticity of the different product parameters on its final cost. The first part explains the designer activity so as to understand the development framework. Then, a literature review is done in order to show that few works were made to respond to such a problem for more detailed product designs. After this review, the proposed procedure to develop an expert knowledge tool for cost estimation is explained. 2 Design activity in mechanical industries Product design cycle starts with the requirement phase (specifications list at which the product must respond) and is followed by the preliminary or conceptual design phase. This phase is based on first a solution concepts research step and followed by an embodiment design step where the product structure is defined. During this last phase, the designer is in charge of the selection of the material type, the realization of a drawing with approximate dimensions and the consideration of technological possibility (manufacturing process) (Pahl and Beitz, 1996). For our work, we wish to set up a method that facilitates the designer work in order to make a manufacturing product cost estimation of the design concepts. By making choices on product characteristics, the designer †

IRCCyN, IVGI, Ecole Centrale de Nantes – France LGIPM, CER ENSAM de Metz – France * Corresponding author: Email: [email protected]. ‡

M. Mauchand et al. induces constraints relatively to manufacturing process and resources that can be used for the product manufacturing. According to known characteristics on the product concept, such as the material, the shape, the structure and the tolerances, primary manufacturing processes are chosen such as casting, forging and machining. In order to support the automatic process of the input data, it is necessary to define formalism for each kind of characteristic parameterized by the user. For example, the material choice realized beforehand, the material is a part of the product characteristics that we will enter in our tool so as to determinate the capable processes. If we choose to define the material by the ISO norm, the tool must be able to transcript this data to determine a set of processes. Information must be understandable and manageable by the interpretation system. This is one of the main point on which we work at the present time. 3 Literature review on knowledge-based systems aiming to perform manufacturing cost estimation by selection of technological process ER and DIAS propose a method to perform a choice between few processes in a same domain of manufacturing (casting) (Er and Dias, 2000). A sequence is developed to make this choice and different parameters are successively defined: Material, casting alloy, Geometrical complexity: this module is structure by a set of questions asked to the designer to evaluate the complexity of the part based on his experience, Precision of the casting process: tolerance and surface quality wished, Production volume. Comparative costs of the different manufacturing processes are calculated in function of the product characteristics previously defined. These characteristics are defined as pertinent (relevant) characteristics relatively to the problem of casting process selection. The developed system allows performing « what if » analyses. Indeed, the input characteristics can be modified constantly. The capable process set is determinate for each level (relatively to each parameter). An assessment is made in order to know the processes that check the constraints on the parameters. After, on these processes, a choice is made relatively to the manufacturing cost that they generate on the manufactured part. The product characteristics are formalized by the product model that allows capitalizing the whole of the product data. This model is progressively enriched during the design activity. They present the steps involved in expert system development methodology (Figure 1). Regarding cost factors, they consider: tooling costs processing costs production quantity They assume that rough cost estimation using casting weight and shape complexity may be quite sufficient for comparative costing of various casting process at the design phase. Their knowledge acquisition includes 14 casting processes. They furnish rule that evaluate if a process is suitable according to geometric features. The geometric features are: internal hole; shape of hole; minimum hole size; minimum section thickness; maximum section thickness; casting weight; maximum length; number of parting planes required.

Proposal for Tool-based Method of Product Cost Estimation during Conceptual Design

Problem Identification

Analysis of Problem & Knowledge Acquisition

System Specification & Development Tool Option

Knowledge Base Construction

Prototype System System Refinement

Test & Validation

Implementation

Figure 1. Steps involved in expert system development methodology. (Er and Dias, 2000)

For the cost comparison, they use “cost weights” rules associated with various ranges of production quantity for each casting process using “sand casting” as the reference process. They don’t make a cost estimation of the different casting process. They only use rules of comparison. A rule-based expert system has been proposed for casting process selection to assist casting product designers in making correct process choice decisions for a given design situation. FENG and ZHANG associate the Conceptual Design and the Conceptual Process Planning in order to conduct a manufacturing cost estimation of the product during the conceptual design phase. “The Conceptual Process Planning (CPP) is an activity of preliminary manufacturability assessment of conceptual design in the early product design stage. It aims at determining manufacturing processes, selecting resources and equipment, and estimating manufacturing costs roughly. Conceptual process planning supports product design to optimize product form, configuration, and material selection and to minimize the manufacturing cost.” (Feng and Zhang, 1999). See Figure 2. The process of manufacturing process selection is performing by step. Firstly, the possible manufacturing processes are determinate according to the product material. Secondly, the possible manufacturing processes are determinate according to the quality of the product. Thirdly, the possible manufacturing processes are determinate according to the product shape. Fourthly, the possible manufacturing processes are determinate according to the tolerances imposed on the product dimensions. And finally, the manufacturing processes that respond to all these constraints are proposed to the designer and cost estimation is performed. This insures a traceability of the impact of the product characteristics.

M. Mauchand et al. Conceptual Process Planning

Conceptual Design

Requirement

Form/Structure & property

Functional Design Function

Process •Fabrication •Assembly •Inspection

Behavioral Specification Behavior Embodiment Design Form/Structure Detailed Design •Geometry •Topology •Tolerances •Dimensions •Surface Conditions •Materials

Estimated Time & Cost

Process Selection

Resource Selection

Equipment/Skill Time & Cost Estimation Time & Cost Detailed Process Planning •Operation sequences •Process parameters •Setup/Fixture •Accurate time& cost •Manufacturing resource

Figure 2. Interactions between Conceptual Design and Conceptual Process Planning (Feng and Song, 2000)

In (Feng and Zhang, 1999), FENG and ZHANG describe the shape features of the product and then associate them to one or more processes (operation). Such a method can be used in the preliminary phase of product design due to lack of information to specify the features that compose the product. The cost estimation method is based on resources consumption. A process consumes material, capital, labor and overhead. According to ESAWI and ASHBY (Esawi and Ashby, 2003), process selection has three steps: Screening: identification of the process subset that can give a chosen material to the desired shape with the desired detail, precision and finish, see Figure 3. Ranking: Choice, from among these, the ones that will do so at the lowest cost (Figure 3). Supporting information: Investigation of the most promising process in depth, exploring considerations such as availability, in-house experience, safety and environmental issues. The cost estimation method used for guiding the process selection is a resource-based cost estimation. Also, they develop resource-based cost models to estimate the relative manufacturing cost of a product. In order to perform this estimation, the designer must inform: design parameters used for process selection: material class, shape class, mass, section thickness, tolerance, roughness, complexity (can be seen as a manufacturing parameter), primary process necessity, discrete process necessity; manufacturing parameters used in the cost models: overhead rate, batch size, capital write-off time, and load factor. They illustrate their method with case studies on a nozzle, a jug kettle, a manifold jacket (Esawi and Ashby, 2003), an elevator control quadrant (Esawi and Ashby, 2000) and a connecting rod (Esawi and Ashby, 1998). SHEHAB and ABDALLA present an intelligent knowledge-based system that accomplishes an environment to assist inexperienced users to estimate the manufacturing cost modeling of a product at the conceptual design stage of the product life cycle (Shehab and Abdalla, 2001). They underline that it is essential to devise a representation scheme for part design that allows the computer to capture and manipulate the design

Proposal for Tool-based Method of Product Cost Estimation during Conceptual Design information to make evaluation decisions. Because of the variety of manufacturing process, there is no formal definition of a feature.

Figure 3. The screening stage and the ranking stage (Esawi and Ashby, 2000)

For them, one feature is realized at least by one process (operation), they estimated the process time and then calculate the process cost knowing the unit time cost by process. The cost structure used to estimate manufacturing cost is decomposed in material cost, tooling cost (mould) and processing cost (Figure 4). So, the required resources generate the cost of the product.

Figure 4. The cost structure of the molding component. (Shehab and Abdalla, 2002)

M. Mauchand et al. CHEN and LIU present how they identify cost factors for injection molding product, a cost model extract from results of process characterization (Chen and Liu, 1999). The cost model depicts the relationships between cost factors and product development activities and with product geometry. This product modeling is based on features dedicated to injection molding. In (Tang et al. 2001), TANG et al. introduce the notion of complexity to qualify stamping parts to perform a manufacturing cost estimation. Among this review of the literature, the learning that we can retain is that cost drivers can be refined along the design process. In preliminary design, only few product parameters can qualify the product and so provide factors for cost estimation. Fewer in the design, the cost estimation can be refined by decomposition of the global parameters. 4 The proposed method for cost estimation tool development 4.1 Decision support system requirements The decision support system that we aim to develop must follow a list of requirements: take relevant decisions regarding process selection during the design phase; imply the user in all steps of the methodology to validate its proposals; give indicators for take considered decisions; provide appropriate cost structure of the final cost; use generic cost models based on resource consumption; use a product model to support and manage information required for the process selection and the cost estimation; use a process model to support and manage information required for the process selection relatively to product data and production data and for the cost estimation of the manufacturing cost of the product; be quick and easy to use; perform quick process based on expert rules. The following steps define the method suggested to obtain such a tool: definition of available information on the product and the manufacturing processes; determination of the necessary (relevant) data; structuring the data mentioned above with a formalism which allows the data-processing treatment; implementation of expert knowledge. We assume that what induces the product cost in manufacturing firm is the resource consumption. Also, we hope to qualify this resource consumption by the description of the product concept in preliminary design phase. So, we try to define a mean to determinate manufacturing processes that can be used to produce the studied solution concept. 4.2 Define the available information on the product and the manufacturing process all along the design phase In the preliminary design phase, little information on the product is available. The available information on the product and the manufacturing process all along the design phase must be formalized to support the input data of the application method. A product is defined by such parameters as: Its material, when we chose a material type we chose a set of physical and mechanical characteristics, Its weight, size,

Proposal for Tool-based Method of Product Cost Estimation during Conceptual Design Geometrical parameters: dimensions, tolerances, The time – life cycle parameters, The production volume… How can we qualified and classified a product concept in order to define all the necessary parameters used to perform a cost estimation? Moreover, the definition of design variables is function of the technical solutions. A solution could be described by its shapes and dimensions. This description can’t directly guide the estimation process. That’s why we think that such a description can permit to determinate the manufacturing processes that could be use to make the product. After that, other characteristics of the product must be declared to perform a parametric estimation of the manufacturing product cost. An example can be extracted from (Verlinden et al., 2005). It is relative to cost estimation for bidding in sheet metal organization. They need to develop a fast and accurate cost estimation model without having information on the process plan. They extract entities or parameters that are furnished by the customer on CAD-file of the parts. But, they need to determinate what type of sheet metal cutting process they can use. In fact, this permits to define the parameters that are relevant for the cost estimation. For instance, if they choose the laser cutting, the pertinent parameters are thickness and material type, inner and outer contour, number of sharp corners and number of cut-outs whereas if they choose the punching process, the pertinent parameters are always thickness and material type but also the number and classes of cut-outs, and that’s all. They proved that the pertinent parameters depend on the process type and its cost modelling. 4.3 Data formalization and structuring In order to perform the estimation process, we structure the data mentioned above with formalism that allows the treatment of these one. We proceed to the structuring of the product and manufacturing data in three steps. First step: the Product Model The product modelling is based on the solution concept description, which is an approximate description of the technology, working principles and form of the product. So a solution concept is a concise description of how the product will satisfy the customer needs. A concept is usually expressed as a sketch or a rough 3D model often accompanied by a brief textual description. Also the model must give us the mean to describe the attributes of the drawing and the characteristics underlined by the textual description. In the first step, a product model must be developed so as to support the data implementation that is necessary to perform the estimation. Our aim is to use a product model that allows supporting different kind of data (qualitative, quantitative…) with coherence between them. The structuring of the required concepts is essential to maintain coherence. All the terms must be defined in order to avoid ambiguity. The literature is rich in works on product modelling in design phase. The FBS-PPRE model (Figure 5) is a product model that can be the support of our modelling of the studied product. The product can be modelled at all the different phases of its life cycle. For our study, the model must be enriched to support cost estimation. This product model permits to simultaneously integrate product model and process model. The object can be the solution concept. Second step: the activity model and the process model In the second step, we develop a process model so as to support the expert knowledge that is used to identify the manufacturing process that could be performed to produce the article. We need to define the conceptual manufacturing process of the studied product. We need to generate a database relative to manufacturing process and to product specifications. We can’t use manufacturing features to identify the necessary operations. So, the level of information not allows us to describe the product concept by the mean of feature. We have to elaborate entities that help us to create a link between the product specifications and the manufacturing process.

M. Mauchand et al. Connection between the models In the last step, we connect the two models by the relations that exist between them and we transcript this model into an ontology that represents the studied domain supported by OWL (Web Ontology Language). See Figure 6 for an illustration of the relation between the concepts. Operational function

Technical function Feature

Function Solution pattern *

1

1

*

Object

Next

0..1

*

Ass-Obj 1 link

0..1

1 *

*

1..*

*

Structure

0..1 1

Assembly 1 * *

Str-Obj link

1

0..1

1..*

satisfies

Expected behavior

*

*

Input/Output

Performance Indicator

Behavior

0..1 +Product/Resource/External effect

*

Representation

1

Real behavior

Input state

0..2

State

0..1

Shutter release

0..1

Status

*

Behavior law

Output state

Figure 5. UML class diagram of the FBS-PPRE product model. (Labrousse, 2004)

Figure 6. Example of the concepts relative to the product and the process modelling in Protégé software.

Proposal for Tool-based Method of Product Cost Estimation during Conceptual Design 4.4 Formalization - Expert knowledge modelling The aim is to perform a manufacturing cost estimation. Also, it is necessary to classify the costs models that could be used to estimate the product cost. For instance, it could be an equation or a logical rule. This constitutes a part of our expert knowledge. The other part resides in the manufacturing expert rules. This knowledge is essential to determine the activities and the factors that generate cost. Cost models types Analogical cost estimations can be use. TALBI proposes an application to the determination of the product cost in the preliminary design (Talbi, 2001). He has an historical base of data on past product fabrication and can classify it in order to build a decision system for bidding. We have a lack of data so this cannot be applied. A case based reasoning system for cost estimation in design is presented in (Rehman and Guenov, 1998). For early cost estimation, Parametric cost models were also developed in all manufacturing fields such as in sheet metal (Verlinden et al. 2005), in hot forging (Berlioz et al. 1999)… For a more complete apprehension of the cost estimation, a detailed literature review on costing and cost management can be found in (Geiger and Dilts, 1996). FENG and ZHANG perform a quantitative cost estimation based on resources consumption (Feng and Zhang, 1999). The estimated cost per part is expressed by C = Cm + Cc + Cl + Cnp , where Cm , cost of materials, Cc , N N' cost of capital, Cl , cost of labour per unit time, Cnp , cost of overhead (non-production cost), N number of work piece to be manufactured, N’ number of work piece manufactured per unit time. In (Feng and Song, 2000), they use advanced cost models and more detailed modelling of product and process manufacturing. The concept of “Entité Coût” (cost entity) developed by H’MIDA (H’Mida et al. 2006) is based on the same postulate as Activity Based Costing (Berliner and Brimson, 1988), activities consume resources that induce costs. The industrial context is restricted to machining manufacturing. Moreover, the product is defined by its manufacturing features. The main point is that they determine one cost driver per activity. So the variation of the activity resources must be homogenous with the cost driver for all case studies. Previous researches on ontology and expert knowledge system have been performed in the LGIPM for manufacturing cost estimation based on manufacturing features, and more precisely on machining features. These researches prove that a costing system based on “Entité Coût”, ontology and expert system can be developed and used to estimate the cost of a product in embodiment design. Our problem cannot be solving by the same modelling of the product so this method cannot be applied to preliminary design where the manufacturing features of the product are not already defined. Moreover the historical cost data must be consequent to determinate with accuracy cost drivers for each activity that can be required for product fabrication. Manufacturing expert knowledge modelling All the first part described above constitutes the structuring of the data needed for the estimation. The ontology permits to integrate in the same tool the product model and the manufacturing expert knowledge so as to perform cost estimation. Indeed, the expert rules that are the basis of the expert knowledge must be formalized in such a manner that the information relative to the concepts contained in the ontology constitutes the objects on which the expert system makes the computation treatment. An expert system is a software that can make decisions based on “If… Then… Else…” rules. It is composed of three components: Factual data base: collects all the data required. This factual data base is the product taxonomy. Rule base: collects all reasoning rules that will guide choices and decisions making. Inference tool: it is the expert system brain. It uses the rule base and the factual data base to make the final decisions.

M. Mauchand et al.

Then the user will have to specify the product model while the knowledge captured in the taxonomy is traduced in the rule base. The expert system will collect the information entered by the user, apply the expert rules and then will estimate the product cost. The structure of the program develop in (Houin, 2005) to perform the process selection is illustrated in Figure 7.

Figure 7. CLIPS Program structure. (Houin, 2005)

To implement the system, we chose to use the “C Language Integrated Production System” (CLIPS see CLIPS website). This system was created by the NASA. The NASA released the first version of CLIPS in

Proposal for Tool-based Method of Product Cost Estimation during Conceptual Design

1986. The CLIPS tool provides a complete environment for the construction of rule and/or object based expert systems. For each branch of the structure, the program follows the same scheme: a data is entered by the user in the general list of processes, some are selected as compatible with the entered data all selected processes are gathered in a new processes list. Then we end with four different processes list. Then we compare them and create a fifth list gathering the processes that are compatible with all the criteria. Here is an example of a selection rule translated in CLIPS. (defrule material_aluminium (declare(salience 100)) ?o (make-instance slow_cold of PROCESS_MATERIAL (name slow_cold)) (make-instance slow_hot of PROCESS_MATERIAL (name slow_hot)) (make-instance by_gravity of PROCESS_MATERIAL (name by_gravity)) This CLIPS instruction is the transcription of the following rule : IF the class « ALUMINUM ALLOY » contains an element (which means that the used material is an aluminium alloy), THEN create objects « slow_cold », « slow_hot », « by_gravity » in the list “PROCESS_MATERIAL”. This means that this list will contain all the processes that can be applied to aluminium alloys. So by entering all these rules in the expert system, we will be able to select what are the compatible processes. Afterwards the user will be asked for the one he wants to use and we will then know the process and will be able to evaluate the cost. 4.5 Software procedure

The software procedure and the awaited behaviour of the software must be defined, the steps that the user must follow in order to evaluate his product and the simultaneous steps that the software must automatically process (Figure 8). Product Description

User data

Product DB

Product Model

Manufacturing Processes DB

Manufacturing Process Model

Process 1

Manufacturing process selection Processes characterization

Processes cost estimate Process selection

User choice and relative data

Manufacturing Product cost

Process 2

Figure 8. Application structure and procedure.

Decision support system

Capable manufacturing processes

M. Mauchand et al.

During this process, the user is guided in his cost estimation procedure, but his point of view is taken into account all along. The user must make choice with respect to the software propositions. The result that could be expected by the user is a report on which all his decisions are mentioned and a cost structure is presented. The Figure 9 materializes the selection of the manufacturing process according to qualitative parameters of a solution concept implement in an ontology and knowledge base acquisition in OWL. For the considered solution concept parameterized according to Material, Rugosity_Depth and Volume, the racer indicates that the acceptable process is machining_01.

Figure 9. Manufacturing process selection – Classification of concepts in Protégé.

5 Conclusion and perspectives

In order to help designer in their preliminary choice concerning solution concepts, it is crucial to evaluate the different concepts according to manufacturing and cost criteria. A detailed literature review on the former researches and developments underlines the lack of method for cost estimation during the preliminary phase. They are more interested in manufacturing features-based costing. This paper explains what the requirements to set up a tool that supports this evaluation are. The future step of our work is to apply this method and implement it in a software tool. References

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Proposal for Tool-based Method of Product Cost Estimation during Conceptual Design

S. Feng, Y. Zhang, 1999, Conceptual Process Planning: A Definition and Functional Decomposition, Manufacturing Science and Engineering, Vol. 10 in the Proceedings of the International Mechanical Engineering Congress and Exposition, pp. 97-106. S. Feng, E. Song, 2000, Information Modelling on Conceptual Process Planning Integrated with Conceptual Design, Paper Number DETC00/DFM - 14009, the 5th Design For Manufacturing Conference in the 2000 ASME Design Engineering Technical Conferences. A.M.K. Esawi, M.F. Ashby, 2003, Cost estimates to guide pre-selection of processes, Materials & Design, Volume 24, Issue 8, December 2003, Pages 605-616. A.M.K. Esawi, M.F. Ashby, 2000, The Development And Use Of Software Tool For Selecting Manufacturing Processes At The Early Stages Of Design, Journal of Integrated Design & Process Science, Volume 4 , Issue 2, pp. 27 – 43, April 2000. A.M.K. Esawi, M.F. Ashby, 1998, Cost-based Ranking for Manufacturing Process Selection, in Integrated Design and Manufacturing in Mechanical Engineering ‘98, Proceedings of the 2nd IDMME Conference held in Compiègne, France, 27-29 May, 1998, Jean-Louis Batoz, Patrick Chedmail, Gérard Cognet and Clément Fortin (editors), Kluwer Academic Publishers. E. Shehab, H. Abdalla, 2001, Manufacturing cost modelling for concurrent product development, International Journal of Robotics and Integrated Manufacturing Technology, Elsevier Publishers, Vol. 17, No. 4, pp 341-353. E. Shehab, H. Abdalla, 2002, An intelligent knowledge-based system for product cost modelling, International Journal of Advanced Manufacturing Technology, Springer-Verlag Publishers, Vol. 19, pp. 49-65. Y.-M. Chen, J.-J. Liu, 1999, Cost-effective design for injection molding, Robotics and Computer-Integrated Manufacturing, Vol. 15, pp. 1-21. D.-B. Tang, L. Zheng, Z.-Z. Li, 2001, An intelligent feature-based design for stamping system, International Journal of Advanced Manufacturing Technology, Vol. 18, pp. 193-200. B. Verlinden, P. Collin, J.R. Duflou, 2005, Cost estimation for sheet metal parts: a case study, 3rd International Conference on Manufacturing Research (ICMR 2005), Cranfield University. M. Labrousse, 2004, Proposition d’un modèle conceptuel unifié pour la gestion dynamique des connaissances d’entreprise, Thèse en Génie Mécanique, ECN. A. Talbi, 2001, Apport d’une méthode de classification de données et d’un outil d’aide à la décision dans l’estimation du prix de revient”, 3e Conférence Francophone de MOdélisation et SIMulation, Conception, Analyse et Gestion des Systèmes Industriels, MOSIM’01 – du 25 au 27 avril 2001 - Troyes (France) S. Rehman, M. D. Guenov, 1998, A methodology for modelling manufacturing costs at conceptual design, Computers and Industrial Engineering, Vol. 38, Part 3/4, pp. 623-626, ISSN 0360-8352.

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M. Berlioz, P. Marin, S. Tichkiewitch, 1999, A fast and reliable cost-estimation tool for hot-forged parts, Integrated Design and Manufacturing in Mechanical Engineering '98, Kluwer Academic Publishers, Ed. Batoz, Chedmail, Cognet, Fortin, pp. 595-602. T.S. Geiger, D.M. Dilts, 1996, Automated design-to-cost: integrating costing into the design decision, Computer-Aided Design, 28(6/7): 423–438. F. H’mida, P. Martin, F. Vernadat, 2006, Cost estimation in mechanical production: The Cost Entity approach applied to integrated product engineering, International Journal of Production Economics, Article in Press. C. Berliner, J.A. Brimson, 1988, Cost Management for Today's Advanced Manufacturing - The CAM-I Conceptual Design, Harvard Business School, Boston. X. Houin, 2005, Estimation des coûts et Conceptual Process Planning, PFE Report - LGIPM de Metz, France. http://www.ghg.net/clips/CLIPS.html