An integrated information system for product design

Int. J. Product Lifecycle Management, Vol. 1, No. 3, 2006

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An integrated information system for product design assistance based on artificial intelligence and collaborative tools Jérémy Legardeur,* Christophe Merlo and Xavier Fischer Laboratory for Engineering of Industrial Processes and Services, Superior Institute of Advanced Industrial Technologies ESTIA, Technopole Izarbel, Bidart 64210, France E-mail: [email protected] E-mail: [email protected] E-mail: [email protected] *Corresponding author Abstract: Most of the time, the innovative product concept identification is based on strategic and complex processes. Design actors’ individual initiatives and development of new ideas emerge from conflicting contexts combining the technical, economical and social aspects. In this paper, we propose a new approach that aims at assisting design product from the early phases of the design process to the embodiment design phase. We suggest a combination of Product Lifecycle Management (PLM) system and specific developed tools (Meta-modelling techniques, Numeric-CSP solver and ‘Innovation Development and Diffusion’ (ID2) system) to enhance cultural heterogeneity encountered within the team project and to take advantage of this aspect to foster design innovation and product quality. Keywords: product design support system; Product Life Management; Knowledge Management; Constraint Satisfaction Problem (CSP) solver; Artificial Intelligence- (AI-) based meta-modelling techniques. Reference to this paper should be made as follows: Legardeur, J., Merlo, C. and Fischer, X. (2006) ‘An integrated information system for product design assistance based on artificial intelligence and collaborative tools’, Int. J. Product Lifecycle Management, Vol. 1, No. 3, pp.211–229. Biographical notes: Dr. Jérémy Legardeur is a Lecturer in the Laboratory of Industrial Processes and Services Engineering (LIPSI) at the Superior Institute of Advanced Industrial Technologies (ESTIA). He graduated as a Mechanical Engineer from the Montpellier University in 1997 and received his PhD from the Institut National Polytechnique de Grenoble (INPG) in 2001. His research interest is focused on the problematic of methods and tools to foster innovation in early design phases. His work is based on both an observation/participation of industrial design situations and the development of the new computer tools to foster interaction and coordination between the actors in integrated design and concurrent engineering. He is the chairman of the publicity committee of the international conference ‘Virtual Concept’ (www.virtualconcept.estia.fr), mainly focused on the use of virtual reality and artificial intelligence tools in the product design process. Dr. Christophe Merlo is a Lecturer in the Laboratory of Industrial Processes and Services Engineering (LIPSI) at the Superior Institute of Advanced Industrial Technologies (ESTIA). After nine years working as a consulting Copyright © 2006 Inderscience Enterprises Ltd.

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J. Legardeur, C. Merlo and X. Fischer engineer involved in CAD/CAM and PDM projects, he joined the research team of ESTIA in 1999 and received a PhD from the University of Bordeaux in 2003. His PhD dissertation dealt with the modelling of engineering design coordination knowledge and the development of the related computer-aided environment using multiagent concepts. His research focuses on collaborative design, Product Lifecycle Management and human factors in Design Coordination. Dr. Xavier Fischer is a Lecturer in the Laboratory of Industrial Processes and Services Engineering (LIPSI) at the Superior Institute of Advanced Industrial Technologies (ESTIA). He graduated as a Mechanical Engineer and he joined the research team of ESTIA in 1999 and received a PhD from the Ecole Nationale des Arts et Métiers (ENSAM), University of Bordeaux in 2000. His research interests are focused on the use of artificial intelligence and virtual reality tools based on Constraint Satisfaction Problem (CSP) techniques. He is the chairman of the international conference ‘Virtual Concept’ (www.virtualconcept.estia.fr) mainly focused on the use of virtual reality and artificial intelligence tools in the product design process.

1

Introduction

Products result from a complex design process that involves knowledge across the entire firm. In fact, a product is the faithful representation of the company’s cultural richness. The development process must achieve technical, economical, social and corporate objectives. Thus, it is important for companies to manage knowledge and information in a manner that: accounts for cultural diversity (Filson and Lewis, 2000); combines heterogeneous opinions; facilitates the quick identification of consensus and allows the reuse of knowledge. To improve Knowledge Management and to support decision-making in a design process, we propose to combine several techniques that are linked through a Product Lifecycle Management (PLM) system. Meta-modelling techniques and both the new tools (Innovation Development and Diffusion (ID2) and Constraint Explorer (CE)) are proposed to support preliminary design phases. The synergy between them is possible through a specific methodology that aims to improve the collaboration and interactions between the design actors. The main goal of our methodology is to foster the information sharing and knowledge management during the development of innovative ideas and identification of embodiment design solutions. Each tool is under the control of a PLM system that promotes their use and that automates the proposed methodology. The PLM system fosters collaboration between the design actors and finally ensures a high-quality level of final product. The implementation of the PLM system structures design data generated during the early design phases. We configure the PLM environment to structure links between the documents in such a way that the design actors can share and retrieve adequate information at each phase of the design process. This integration facilitates the sharing of information and the reuse of a document according to its state and maturity. We define validation and diffusion workflows and technical forums so that the PLM environment fosters collaboration between the actors of different skills and expertise.

An integrated information system for product design assistance

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This section describes the main objectives of our research and the common design process is given in detail. Section 2 presents the tool ID2 that supports the development of new ideas in the very early design phases. Then, in Section 3, we provide a new methodology that aims at improving engineering during the embodiment design phase. Finally Section 4 shows how a PLM system may be used to manage the information and the new proposed support tools.

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ID2: a tool for the preparatory phase

Classical design process is commonly presented as a sequential (Pahl and Beitz, 1984) and iterative approach (Blessing, 1994; March, 1984). The design process (Figure 1) includes several steps that imply the use of different knowledge, information, cultures and support tools. During a routine design phase, several operations remain stable permitting designers to use technical, economical and organisational points of reference. In such situations, designers can easily determine the essential steps of the considered product development: the designers to be involved in the network are quickly identified during the first step of the investigation; required knowledge for the design of the product is generally known and characterised by minor changes and finally the methods and tools are well known. Figure 1

Design process based on RGAERO 00040 (Cavaillès, 1991 and SAE, 2004)

However, it is now a well-established fact that innovative design process of a manufactured product is complex and takes place within conflicting contexts combining technical, economical and social aspects (Buccarelli, 1988). In a context of innovation the design process does not follow a predefined pattern: stakeholders’ actions cannot be

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always identified before they happen. Moreover, the network of actors is very unstable with, notably, the progressive arrival of new agents bringing the new assessment criteria with them at different stages in the project. As they progressively define their own issues and shared objectives, individual work periods become collective ones. The content of the corresponding tasks is not known before they are carried out but is structured during the action, at the same time as the project itself. The final result of this process is not an accumulation of all individual actions, but relies on a complex combination of the discourse and the adjustment of various and heterogeneous skills and the negotiation of compromises between different points of view. Thus, there is an uncertainty for the designers to find the best way to define the product but also to identify the right network of people to involve. In the previous work (Legardeur et al., 2003), we defined this first phase of the process as the preparatory phase of the design process. This first step consists of determining new ideas and without following a predefined way. This step concerns all firms’ actors and is often the starting point for innovation. We propose in the following section a new tool to support team interactions during the early design phase. This tool provides the first input data of the design process that is given in detail in Figure 1.

2.1 Background research concerning ID2 Our previous works (Legardeur et al., 2001) put forward the importance and the difficulties of the early design development phases, those that mostly remain informal. The work carried out during these phases widely determines the emergence and the success of an innovative project. Before launching a new project, an important work is carried out to convince the different participants that the new idea is reliable for the given application. At this stage, this work is often developed at the specific actor’s instigation. This actor we named as the ‘driver’ or the ‘pilot’ of the new ideas, plays a key role in selecting and proposing the potential applications, enabling the connections between various actors to build credible propositions in terms of cost and quality. If a proper work is carried out, the argumentation developed at this stage should lead to the definition of proper specifications (technical and economical), providing the input for an official predevelopment phase. This point led to the development of ID², a software tool (Legardeur et al., 2003) based on the web technologies. We present this tool and its last evolution in the following section.

2.2 Using ID² during early informal design phases The heart of a project on ID² is based on the Concepts and Criteria Table (CCT). This table displays a summary of all the exchanged information concerning the project. For example, a CCT is presented in Figure 2. The existing solution in the first column is compared with the innovative proposals in the following columns. The different concepts of solution are compared against a number of evolving design criteria (rows). This table allows a synthesis of the first exchanged information concerning the emergence of the new project. The main idea of this tool is to organise the capitalisation of the non-structured information, especially during the informal early design phase.

An integrated information system for product design assistance Figure 2

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Concepts criteria table in ID²

In ID², the pilot of the project can invite a number of ‘network actors’ with different expertise to help provide the data to validate the innovative proposal, so that the different points of view and areas of expertise can be compared. The idea is to provide a shared support tool enabling each actor to specify and explain his/her assessment criteria for the solutions. Thus, the structure of the table is dynamic and each actor can put forward new criteria (and thus new lines) as the project progresses. The criteria and information are therefore open to public viewing and discussion throughout the network. The table is structured so that the different boxes can be gradually filled in. The most recent information is displayed in each box of the table, whereas the previous information given by the different participants is stored in a tree structure. Each piece of information provided can include a value and a description. The information can be modified and both history of each piece of information and evolution of the CCT are accessible. The concepts/criteria table provides a multiview support, where each actor can react, comment on and request explanations with regard to any aspect of the project. The tool thus provides an instrumental support to guide interactions among the different specialists via five annotation modes: links, alarms, questions, comments and information requests. The links allow actors to link two dependent pieces of information, whose dependency is not obvious and is worth being underlined. The warnings indicate an actor’s remark about a specific point. The questions show the need to look for information about a specific point and thus also help to mark the degree of uncertainty surrounding the solution. The comments are used to add any further point of view on specific information. The information requests allow actors to express their interest in a specific point of the project.

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The tool is structured to encourage actors to formulate and explain their own criteria thus facilitating discussion within the network. Each new actor adds his/her vision of the solution, which may be positive, neutral or negative, resulting in a certain number of assessment criteria. In this situation, we think that CCT and annotations functions can help to structure design activities and collective cognitive processes. They are used to clarify and compare opposing or convergent points of view, thereby creating a meaning that can be understood by everyone. Moreover, we also propose an ‘Event table’ (see Figure 2) dedicated to exchange among the stakeholders the different key points and decisions related to the project. The main interest of this tool is to propose two tables (CCT and events tables) that present complementary aspects: the development of new ideas and the project context. Context information structuring is of no use, if it is not oriented towards the knowledge creation and the improvement of the actors’ competencies. Our proposition includes a search engine and functionalities to assist in the reuse of information available in ID². With a ‘knowledge asset’ page, we aim to structure and choose the information necessary to provide the greatest support for learning and reuse and present it in the most accessible way. Consequently, each project now includes a ‘knowledge asset’ page, refer to Figure 3, in which the coordinating actor can record the key elements and knowledge mobilised or gained from the project. Figure 3

Knowledge asset page in ID²


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Our study leads us to select the capitalisation of the different elements generated automatically from the data of the CCT such as the actors involved, the design criteria used, the proposed concepts and a calendar of the project evolution. The other capitalised elements (project summary, the general context of the project, principal results and current state of the project, the key decisions made, obstacles and problems encountered) are requiring some ‘human review’ by the coordinating actor of the project. The element of ‘human review’ guarantees the pertinence and validity of the information recorded, yet the fairly formalised process ensures that it is not significant extra work. The sole fact of having reflected on the outcome of an action is useful, and if any useful lessons can be recorded to minimise the future duplication and maximise sharing then it is especially worthwhile. We cannot formalise and capitalise all the knowledge that is mobilised throughout the design process. Because of time and resource, only a small amount of explicit knowledge can be stored in a searchable database for reuse. Moreover, the tacit knowledge (Nonaka and Takeuchi, 1995), which is highly contextual and linked to the actors involved, cannot be easily formalised. This being the case one must therefore provide other methods to foster tacit knowledge sharing and enhance the learning process. In this sense, meetings and informal discussions between the actors can represent highly productive occasions for the knowledge exchange. Furthermore, to concur with the idea developed in Davies (2000), we consider that invisible and tacit networks exist within the companies that are specific to each person and that connect people. Such networks are built according to ‘weak ties’ that are established among the designers during their professional or even extra-professional life. Industrial organisations are places where tacit agreements among the people develop and are linked to several parameters such as: collective success on a project, attendance at high schools, similar interests, former colleagues, neighbours and so on. In practical terms, these ‘weak ties’ enable somebody to get information and answers or to gather skills to accomplish their own activities by involving people from their informal network, even if they do not belong to the formal project group. As others past works such as McArthur and Bruza (2003) are based on mining semantic associations from e-mail communications. We think that actors networking can be natured by the new functionality of the CSCW system. It is therefore beneficial to promote this type of interaction by the implementation of a ‘Who Knows What?’ function within ID². This functionality enables the research expert in a company by a number of search criteria: research field, participation in previous projects and problems encountered. Furthermore, we propose to promote the interactions between actors and the creation of ‘weak ties’ through a personalised profile of each actor (see Figure 4). Accordingly, each actor owns a page upon which they can optionally provide some information regarding their professional activities (some keywords describing their activities, their position, their expertise both general and concerning ID2 projects, their links to internet resources) and equally, personal information such as their interests (hobbies, passions, etc.). Whereas a few methods and tools dedicated to this problem are available in the literature, ID² is here proposed to support the early design phase. Thus, the ID² tool does not aim to offer help in looking for new ideas but encourages innovation by distributing information about the solution and putting it to the test.

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Figure 4

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Example of an actor’s profile in ID²

A methodology for embodiment design phase

3.1 Embodiment design decision making The embodiment design stage consists of defining components for the product, regarding every design’s rules that have been to be simultaneously satisfied to obtain the most suitable product. It takes into account, for example, the innovative ideas that have emerged from the very first phase of process, the specifications that exhaustively define the main objectives of the design project, concepts of the product that have been sorted out from conceptual design phase, expected product behaviour, quality and performance aims, industrial constraints and design process actors’ know-how that is intended to enhance the final result. To follow rapidly such a huge set of rules appears to be impossible. Even if the information and knowledge would be well managed, it would be difficult to identify the best consensus for design choices. As a matter of fact, rules are commonly in conflict and it is useful and shorter to choose one point of view, for example, to provide a car that is both resistant and low-cost is difficult, as the cost increases with the resistance; often it is the low cost sight that is preferred. For solving such a difficulty, we suggest the use of Constraint Satisfaction Problem (CSP) solvers.


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A few significant literature works have demonstrated the interest of the CSP techniques use in design (Lottaz, 2000; Serrano, 1987; Thorton, 1993). A ConstraintBased Representation (CBR) (Fischer et al., 2004) of a design problem is made of a set of variables and a set of domains of values. The set of variables are used to (Vernat et al., 2004) define the product configuration. The Design Variables; translate the properties, and another set of variables are used to define the state or the quality of design choices the Criteria Variables, and add useful information to the model that is not essential but are commonly used in a few engineering approaches. These variables are named Intermediate Variables. The set of domains of values defines for each variable the available values; these domains may be discrete or continuous. The set of laws links variables of the design problem and takes different forms (Gelle, 1998). Despite of the number of works related to studies in Constraint-Based Problem Solving (CBPS), the literature does not provide specific methodologies aiming to assist the engineers in problem modelling and solving with the CSP solvers matching design process restrictions. In the following sections, we propose a methodology that would enable firms to quickly determine the best consensus from well-suited Constraint-Based Modelling Techniques involving the handling of combined AI techniques.

3.2 Model reduction techniques for CBR The designer’s habits and experiences can be modelled by relations having various forms. Our approach consists in developing a design problem model, built from the required knowledge and information for solving it, with a specific type of relations named ‘constraints’. Constraints are discrete or continuous relations that, in our process, come from the translation of professional rules and knowledge. A constraint may be equality or inequality Equation (1). This type of constraint is named ‘continuous constraint’: it links variables taking values in continuous domains (real or intervals of real set: IR). These constraints only represent connectionist knowledge: from learning and several experiences, engineers approximate and explain a particular behaviour by developing extended statements. This kind of approximation links variables by accurately describing the products or processes. Every real value taken by a variable of a continuous constraint directly implies the emergence of real values for other variables: the linear or non-linear relationships making the continuous constraints allow the process to restrain the domain of consistent values.

 f ( x1 ,… , x p ) ℜ 0 f : IR → IR  ℜ ∈ {=, ≤, ≥}

(1)

The previous constraints, called in our design approach, calculus constraints, can derive from: differential equations that traduce mass, momentum or energy balance equations inside the product or a process being studied and bases of consistent combination of values extracted from different experiences. To translate the previous laws in continuous constraints, we suggest the employment of Model Reduction Techniques (MRT) allowing engineers to obtain reduced equations having the ability to exactly represent the knowledge. The suited MRT mixes Genetic Algorithms and Neural Networks. The Neural Networks are used for their aptitude to model behaviours with the parsimonious equalities from the set of reference cases being bases of established combination of values. To ensure a well-structured network, we use

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genetic algorithms that manage the choice of fundamental parameters of the approximation (type of approximation functions and the number of functions). On the other hand, the discrete constraints often appear in the translation of knowledge or information deriving from the industrial practices: this kind of modelling involves conditional formalism, commonly named as rules in AI. They lead to the implementation of reasoning or a response related to a specific statement Equation (2). For instance, the manufacturing costs calculus, the use of specific professional lists of components, the handling of particular information based on the industrial history, etc. are often applied in specific conditions. Discrete constraints match the way design actors express their own procedural knowledge being heuristic and extracted from their own experience. IF (Conditional Statement) Then (Implemented Conclusion)

(2)

Our approach has also led us to the studies of knowledge mixing connectionist knowledge and heuristic information mainly involving the handling of variables only being able to have a limited number of values. This modelling implies ‘mixed constraints’. In such a situation, the modelling process implies the creation of equations integrating both the variables taking values within discrete and continuous domains. The handling of such models allows an engineer to manipulate the classical equalities of the physics or engineering by imposing some group of values. The mixed and discrete constraints mainly traduce the design and expertise laws. In particular, they manage the quality of the solution by relaxing the field of consistent solutions. As a matter of fact, the mixed and discrete constraints accept the fuzzy values or interval of real as solutions. In such an approach, the discrete and mixed constraints become a function of acceptability of possible solutions and lead to a consistent range of values and not only to a single real value by involving (Fischer, 2000; Fischer et al., 2002) fuzzy models: we use the fuzzy inferences to obtain constraints that model preferences or enable designers to value the quality level of design choices and rulebased representation integrating both equalities and catalogues (enumerated/linguistic values); it enables designers to naturally express know-how. The discrete and continuous constraints wholly represent the knowledge required for solving a design problem. To solve it, we use a specific tool named CE, developed through the CO2 project led by the Dassault Aviation company.

3.3 CE: a tool to sort out embodiment design solutions From the constraint-based model that has been made with meta-modelling techniques, we propose to identify design solutions. A specific tool, named CE, employs CSP techniques to sort out the combination of values that satisfy every constraint. Such a process appears to be rapid, high-performance and relevant in design. CE integrates these three functionalities. Firstly, it has a specific interface that enables the engineer to verify the syntactic consistency of the model. Secondly, it permits the use of a very high-performance process that aims at reducing the domain of values only to values that would be able to become solutions; this process phase is named the filtering phase. Finally, it leads to design the solutions that are consistent combinations of design values (Figure 5), as shown in the graph (Figure 6) that defines links between the variables (the constraint graph).


CE: model solution interface

Figure 6

CE: constraint graph

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3.4 A methodology to support embodiment design solution in design process CE and MRT are the bases of assistance to decision making in embodiment design. Our methodology proposes to limit the iteration in the design process, as found solutions respect every rule that would be able to take into account a solution: the constraint-based

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model integrates those rules. But such an approach implies links with all sources of knowledge that may be required for design problem solving. The presented methodology enables engineers to hasten and to foster the identification of dimensioned embodiment design solutions. The identified design solutions are then shared with the process actors, who can see a representation of their know-how. In Section 2, a tool was presented for supporting the preparatory design phase. Then, we have introduced a methodology and tools dedicated to product dimensioning. To coordinate the design process and human activities (Baumberger et al., 2003), tools and related information must be integrated and managed through a coherent environment. As PLM systems are dedicated to product data management, the next section introduces how they can be implemented to structure such shared information and to coordinate such design activities.

4

PLM: a link between design support tools

4.1 PLM system specifications PLM systems are dedicated to the product data structuring and their evolution management during the whole design process (CIMdata, 2001; Liu and Xu, 2001). Actual PLM systems integrate the project management functionalities (Saaksvuori and Immoen, 2004) including scheduling, task management and planning, which Coates et al. (2000) consider as the most important issues for an operational design coordination. They also offer groupware-like functionalities (Eynard et al., 2002; Johansen, 1988) for collaboration between the actors such as technical forums or generic viewers. As the main information system for product development, PLM systems must be the integration framework for handling unstructured information based on ID² and managing actors’ knowledge through the CE tool from preparatory phase to embodiment design phase. The objective is to define a new product development environment to manage the multidisciplinary experts involved in the design project (Conroy and Soltan, 1997). Its specifications are established in four steps: •

Firstly, the new design process is analysed to formalise the main steps of the design project and human activities from the preparatory design phase to the embodiment phase using the IDEFØ diagrams.

•

Secondly, previous activity diagrams are used to identify, then characterise the main documents and product data managed during the design process.

•

Thirdly, for each kind of documents/product data are formalised the corresponding life cycles and workflows.

•

Finally, users and roles are defined and previous results implemented into a PLM system.

The implementation has been achieved with Windchill (PTC, 2002) PLM system and its functionalities seem to correspond to the required specifications.


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4.2 Structuring integrated product data Product information is structured through two kinds of objects: documents and parts. A document or part can be defined by a file via meta-data links and can refer to other attached files. All the different documents generated by the actors involved in the design process are managed. To formalise actors’ knowledge and to integrate the use of ID2 and CE tools, it is necessary to identify the generic documents, then the optional ones and finally the links between these different tools. The generic documents are linked to the main design phases shown in Figure 1: ‘specifications’ document for requirements; ‘product concept’ document for the conceptual design and ‘expert know-how models’, ‘CE model’ and ‘CE solutions’ for the embodiment design. The ‘CE model’ document stores the input file for the CE tool and ‘CE solutions’ is the resulting document that describes the calculated solutions. The ‘Expert know-how models’ documents are generated by each specialist, for example, designer and ‘design model’, mechanical engineer and ‘mechanical model’, quality expert and ‘quality model…’, to formalise their specific rules. They are integrated by the CE expert, who defines the complete model into ‘CE model’. According to the design process, these documents are structured hierarchically as shown in Figure 7: ‘specifications’ are used to establish ‘product concept’, which is used to characterise ‘CE solutions’ as well as ‘CE model’. This logical structure corresponds to the CE tool product data and allows each actor retrieving documents previously generated by using the structural links. Figure 7

Global document structure

Each document of this structure can be referenced by complementary documents generated by actors to manage their traceability. For example, in Figure 8 ‘CE fittering solutions’, ‘CE log 1’ or ‘cases database’ can be checked in as files generated when the complete ‘CE model’ is used by the CE tool to obtain ‘CE solutions’. In this way all the product data defined with the CE tool is integrated through the PLM system and shared between actors.

224 Figure 8

J. Legardeur, C. Merlo and X. Fischer Data correlated to ‘CE solutions’

The product data and other documents are also centralised and shared using the PLM system. A folder view is then used to manage them according to the main design phases (Figure 9). This view improves the way actors can find the product information in a ‘usual’ way. Figure 9

Collaborative folder structure

The actors also need to retrieve the information about the early phases of the design project such as the history of the decisions criteria, the initial context of the project or the design alternatives (Karsenty, 1996). As ID2 is an internet-based tool, the documents and specific information can be associated to documents as an URL reference (Figure 9) to avoid duplication. The document structure and the folder structure are stored as a predefined ‘product model’ to be reused for each new product development process.


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4.3 Automating product data evolution The proposed document structure allows actors to manage the traceability of all files during the design process. Specific lifecycles and workflows are defined to synchronise their evolution from creation to obsolescence and to manage users’ access according to their maturity level. For example, the lifecycle of a ‘expert know-how’ document such as the ‘design model’ (Figure 9) is composed of three states: ‘In work’ when the designer generates it, ‘Under Review’ when the product manager and the CE expert validate it and ‘Released’ when the document is validated. The corresponding workflow is described in Figure 10. The ‘submit’ activity is assigned to the designer to start the validation sequence. At the ‘validate’ activity, the product manager can ask the designer to modify (‘rework’) the document or to validate it. This validation is only a technical validation of this specific model. Figure 10

Flexible workflow for know-how models

The strong expertise required when applying the meta-modelling techniques and defining valid models for the CE tool requires a second validation by the CE expert, which is not necessarily an expert of the domain of the evaluated model. Its evaluation may be followed by non-predefined activities, for example, asking a new expert to formalise more knowledge into the model to obtain a coherent model. The management of the product development processes requires a great flexibility in the activities (Weber et al., 2002) and traditional workflows with predefined activities do not bring this flexibility. Therefore, ‘Ad hoc’ activities are introduced into a predefined workflow. This activity allows the assigned user to define a new sequence of activities that will be dynamically integrated into the running process as a subprocess. Then, an ‘Ad hoc’ activity is assigned to the CE expert, which has to evaluate the consistency of the formalised rules. The CE expert is then able to ask the designer for the improvements or to involve other technical experts for several expertise activities. Such a workflow brings more flexibility to the design process and fosters the coordination of actors when realising their tasks or when collaborating. Figure 11 represents the ‘Ad hoc expertise’ activity when the CE expert is defining a new activity named ‘Evaluate Mech. & Design models’. As long as the CE expert does not terminate his ‘ad hoc expertise’, he can define the new activities, including ad hoc activities assigned to him or to other actors. Such a workflow introduces flexibility into a document-oriented process.

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Figure 11

CE expert view of ‘Ad hoc expertise’ activity and dynamic activity definition

4.4 Coordinating project activities Workflows and life cycles allow the coordination of actors’ tasks. As they are associated to documents, a global synchronisation is needed to manage the coordination of actors at the project level. The project component is dedicated to the management of documents through a project point of view. The design process is defined using the project activities grouped by phases and milestones, which validate intermediate steps or design process ending phases. Deliverables are defined and associated with each milestone. These deliverables correspond to the documents identified in the document structure (Figure 12). This allows actors to know when they have to start their activities and generate the expected documents and the related workflows. The project managers can fit this schedule whenever required by the design context. With an internet-based PLM system, the collaboration between actors is improved by using technical discussion forums and by subscribing to document evolution notifications. For example, the CE expert can subscribe to each ‘expert know-how’ document to engage its own evaluations before its ‘ad hoc expertise’ becomes active in the document workflow. As for the document structure, a ‘project model’ integrating the schedule, the documents structures, life cycles and workflows can be stored, to be reused for the new design projects. This configuration of a PLM system allows the characterising of a collaborative environment that improves the coordination of the new proposed design process (Figure 13): at the document level, at the actor’s activity level and at the project level. The proposed tools and techniques were developed within the industrial projects. However, their integration through a PLM system must be tested on several projects to evaluate the real improvements of such a collaborative design environment.


Predefined schedule of the design process

Figure 13

Integrated coordination of design process

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Conclusions

In this paper, a new and global approach is proposed to manage shared knowledge between actors from the very early design phases to the embodiment design phase. The aim of this approach is to integrate information structuring and management and to formalise a methodology that fosters the innovation in design. First, ID2 has been developed to improve the creative interactions and collaborations in design teams from the very early phase of the design process until the conceptual design stage. When the product concepts are fixed, the designers can determine embodiment design choices with new dedicated techniques: a CSP solver named CE and meta-modelling techniques. An implementation of a PLM environment is also proposed to coordinate the whole design process and to manage the information and documents generated during the design phases including those generated by the ID2 and CE tools. The proposed approach and tools improve the knowledge sharing and information management from the first idea of a new product concept to the detailed solution.

References Baumberger, C., Pulm, U. and Lindemann, U. (2003) ‘Co-ordination and controlling of distributed product development processes’, Proceedings of the 13th International Conference on Engineering Design – ICED 2003, Stockholm, Sweden, 19–21 August. Blessing, L.T.M. (1994) ‘A process-based approach to computer-supported engineering design’, PhD Thesis, University of Twente, Enschede, The Netherlands. Buccarelli, L.L. (1988) ‘An ethnographic perspective on engineering design’, Design Studies, Vol. 9, No. 3, pp.159–168. Cavaillès, R. (1991) Méthodes de Management de Programmes, In Technea-DGA. CIMdata (2001) Collaborative Product Definition Management (cPDM): An Overview, CIMdata Inc, Available at: http://www.cimdata.com/cPDm_request.htm, Ann Arbor. Coates, G., Whitfield, R.I., Duffy, A.H.B. and Hills, B. (2000) ‘Co-ordination approaches and systems. Part II: an operational perspective’, Research in Engineering Design, Vol. 12, pp.73–89. Conroy, G. and Soltan, H. (1997) ‘ConSERV, a methodology for managing multi-disciplinary engineering design projects’, International Journal of Project Management, Vol. 15, No. 2, pp.121–132. Davies, N. (2000) ‘Knowledge Management’, BT Technology Journal, Vol. 18, No. 1, pp.62–63. Eynard, B., Merlo, C. and Carrat, B. (2002) ‘Aeronautics product development and certification workflow based on process modeling’, Proceedings of the Eighth International Conference on Concurrent Enterprising (ICE), Rome, Italy, 17–19 June. Filson, A. and Lewis, A. (2000) ‘Cultural issues in implementing changes to new product development process in a small to medium sized enterprise (SME)’, Journal of Engineering Design, Vol. 11, No. 2, pp.149–157. Fischer, X. (2000) ‘Stratégie de conduite du calcul pour l’aide à la décision en conception mécanique intégrée, application aux appareils à pression’, PhD Thesis, ENSAM, France. Fischer, X., Merlo, C., Legardeur, J. and Zimmer, L. (2004) ‘Knowledge Management and support environment in early phases of design process’, DETC ASME 2004, Salt Lake City. Fischer, X., Nadeau, J.P., Sébastian, P. and Joyot, P. (2002) ‘Qualitative constraints in integrated design’, Integrated Design and Manufacturing in Mechanical Engineering, Kluwer Academic Publisher.


229

Gelle, E. (1998) ‘On the generation of locally consistent solution spaces in mixed dynamic constraint problems’, PhD, Ecole Polytechnique Fédérale de Lausanne, Switzerland. Johansen, R. (1988) Groupware: Computer Support for Business Teams, The Free Press. Karsenty, L. (1996) ‘An empirical evaluation of design rationale documents’, Proceedings of the ACM Conference on Human Factors in Computing Systems (CHI’96), Vancouver, ACM Press, 14–18 April. Legardeur, J., Boujut, J.F. and Tiger, H. (2001) ‘An interface tool for driving innovation during preparatory phases: application in the design of composite parts’, International Conference in Engineering Design ICED, Glasgow, August. Legardeur, J., Boujut, J.F. and Tiger, H. (2003) ‘ID²: a new tool to foster innovation during the early phases of design projects’, Concurrent Engineering: Research and Applications, Vol. 11, No. 3, ISSN 1063 293X, pp.235–244. Liu, D.T. and Xu, X.W. (2001) ‘A review of web-based product data management systems’, Computers in Industry, Vol. 44, pp.251–262. Lottaz, C. (2000) ‘Collaborative design using solution spaces’, PhD, EPFL, Lausanne, Switzerland. March, L. (1984) ‘The logic of design’, in N. Cross (Ed). Development in Design Methodology, John Wiley & Sons. McArthur, R. and Bruza, P. (2003) ‘Discovery of implicit and explicit connections between people using email utterance’, Proceedings of the Eighth European Conference of ComputerSupported Cooperative Work, Helsinki, September. Nonaka, I. and Takeuchi, H. (1995) The Knowledge-Creating Company, USA: Oxford University Press Inc. Pahl, G. and Beitz, W. (1984) Engineering Design, London: Design Council. PTC (2002) Windchill Business Administrator’s Guide, Release 6.2, Needham, USA: PTC Global Services. Saaksvuori, A. and Immoen, A. (2004) Product Lifecycle Management, Berlin: Springer-Verlag. SAE International (2004) AS9100: Quality Management Systems – Aerospace – Requirements. Serrano, D. (1987) ‘Constraint management in conceptual design’, PhD of Massachusetts Institute of Technology. Thorton, A.C. (1993) ‘Constraint specification and satisfaction in embodiment design’, PhD Thesis, Cambridge University, UK. Vernat, Y., Fischer, X., Nadeau, J.P. and Sébastian, P. (2004) ‘Strategy for model formalization in preliminary design’, SCI 2004, Orlando. Weber, C., Werner, H. and Deubel, T. (2002) ‘A different view on PDM and its future potentials’, Proceedings of the Seventh International Design Conference DESIGN 2002, Dubrovnik, Croatia, pp.101–112.