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Knowledge Brokering for Assisting the Generation of Automotive Product Design
Knowledge Brokering for Assisting the Generation of Automotive Product Design K.K.B. Hon*(l), J. Zeiner" *Department of Engineering, University of Liverpool, Liverpool, UK "Robert Bosch GmbH, Stuttgart, Germany
Abstract The aim of this paper is to present a pragmatic model for the systematic transfer of ideas and knowledge at the early stage of product design in a company environment. In using the model, the basic premise is not to build a new product 'from scratch' but to reuse existing ideas and knowledge from other objects and products developed previously. This new approach is called Knowledge Brokering (KB). The developed KB model consists of four sequential steps, which cover the collection and clustering of explicit design knowledge, the systematic learning process, retention and transfer of tacit design knowledge. The premises for using the KB model and case study results from the automotive industry on the advantages and limitations of the new approach are also described. Keywords: Product, Knowledge, Design
1 INTRODUCTION New products are vital to the success and prosperity of any modern company. Facing new technologies, shorter product life cycles, increasing global competition and dynamic market needs, companies must focus on product innovation and reducing product development time and cost. One major contribution to a successful product design is to develop the product by a Simultaneous Engineering (SE) team [ I ] . As the primary target for all companies in new product development is the same, i.e., to get from the start of the development process to having a product in the marketplace in the most efficient and effective manner, the value of an SE team with a shared vision for achieving the product objectives is well recognised. The input of knowledge and expertise of members from different technical and business disciplines at the early stage is crucial [2]. However, generating a product design requires more knowledge than any single individual or any single group possesses, because the knowledge relevant to a problem is distributed among many different stakeholders [3]. Consequently, the challenge is on how to acquire knowledge or how to find a person who has the requisite knowledge for generating a specific product design feature. Nevertheless, before knowledge is needed, ideas are necessary for generating the concept of the design. VDI guideline 2221-1 states that the finding of Design Solutions (ideas) is the crucial step within the whole design process [4]. Further, Frankenberger states that many companies develop complex products in various series independently, even though between the product lines of those companies the sub-problems to be solved are comparable to a certain extent. It is often noted that a new design contains results of working steps which are similar to the results of the same steps in former design projects. For example, the set of Design Solutions considered to solve a sub-problem can be derived from an earlier project [5]. But the larger a company becomes, the harder it is for anyone to know what other designers is doing and which Design Solutions exist already [6].
The aspects depicted were observed in the case study company which is a major company in the automotive industry. In that company, contact persons for exchanging information and experience from other business units or other departments are not readily known. product concepts are generated without appropriate access to Design Solutions which were integrated in former or other product designs. Another contribution to a successful product design is to develop the product by using Working Methods (WM) such as Target Costing, Quality Function Deployment or Design for Manufacture and Assembly in order to increase effectiveness and efficiency [7]. While more and more products are developed with Working Methods within a company, for many products the steps for their execution continue to start at the beginning even though these methods were already applied to earlier or similar products. Consequently, the challenge is to find those products to which WMs were already applied in order to reuse knowledge generated in previous product development. Research focus In essence, this paper is concerned with the early phases of Product Development (PD). The aim of this research is to develop a pragmatic model for the systematic transfer of ideas and knowledge for product designs within a company. In using this new model, the basic premise is not the building of a new product 'from scratch' but the reuse of existing ideas and knowledge from other objects for products already developed.
2 MODELS WITHIN THE EARLY STAGES OF PD The early phases of PD considered in this paper are divided into three models: Market Model, Function Model and Design Model as shown in Figure 1 [8]. Various quantitative and qualitative activities undertaken during the early stages of Product Development can be assigned to these three models. The Market Model is the first one that needs to be established. Important aspects which need to be taken into
account in setting up a Market Model for the product are customer/user demands, expected sales, company internal requirements and allowable marketing costs. Furthermore, the target functionality of the product and also the functionality of competing products have to be considered. Such information is then used as a basis for assessing the competition and for generating engineering requirements and specifications.
:+
Market Model
(0
P
objects can be prototypes, models, product examples or other kind of physical representations. They can be products from the same or different business units of the company, competitors' products and products from suppliers. The Background Information (BI) is linked to the object and contains explicit knowledge drawn from design and production departments, e.g., the Product Functions, specifications of the functions, descriptions of the object, drawings of the object, product cost allocations and Working Methods applied. This information is stored in a KB Database. Figure 2 shows the first tab of the BI on a throttle device which will be described in the next section
Background Information E w
W
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2005
2007
Background Information1
Year
Function Model
Background Information2
Integratiin d a k 20.09.02
Object Name:
illuminate obJeai
DB-
I
Background Information3
No:
16
I
I
*wdims
Object- Id.:
7
Throttle device
-
Product Functionk
I
Design Models
I
(2nd level) adjus~a,r flow
. represent electrical interface
Remark I Description of the function/$: To change the rotation angle of the throttle plate Flange to customer part
Specificatiods of the functbnls: Rotation angel:
7 -93"
MLK connector
Figure 2: Screen from the KB Database
Figure 1: Models within early Product Development. Based on these insights the next step is the generation of the Function Model (FM). This model is the logical arrangement of the Product Functions. The term Product Function (PF) is used according to the definition of Pahl and Beitz, i.e., the general and intended correlation between input and output with the objective to fulfil a task [9]. However, in this paper, PFs only represent the tangible technological product functionality of the product. To obtain Design Models is the core process within Product Development. An important activity is to discover Design Solutions for realising the required Product Functions and to combine them for conceptual designs. Further downstream processes such as detailed CAD modelling are outside the scope of this paper. 3
PREMISES FOR THE KNOWLEDGE BROKERING MODEL In this research, the term Knowledge Brokering (KB) is used for the process whereby Product Design Knowledge (PDK) from a product or object is reused for the generation of another product design within a company. Knowledge Brokering aims to enhance the exploitation of knowledge from existing product designs in order to share and reuse it for other products that have to be developed. The main focus group of KB is staff members in the product design departments. The concept of knowledge is based on the hierarchy of data, information and finally knowledge. In this context, data is the raw material which can be diagrams, facts or text. When data is organised and structured in a useful way, it becomes information. When information is read and interpreted by an individual, it becomes knowledge [9]. In other words, information is concerned with 'what' whereas knowledge addresses the question 'why'. Product Design Knowledge consists of a tangible object and Background Information on the object. The tangible
However, not all PDK can be easily articulated or transferred in explicit forms because it is personal and context-specific. Such type of knowledge is tacit knowledge which is individual-based, context related, analogous, practice related knowledge. Tacit knowledge can be exchanged effectively in person-to-person situation. The object of Knowledge Brokering is therefore not to codify tacit knowledge into explicit knowledge but to provide contact details as part of BI for the user of the KB model. Other forms of design knowledge management systems were also proposed by Ha, et al [lo].
3.1 The KB Data- and KB Objectbase A premise for using the Knowledge Brokering model is the KB Base which consists of a KB Database filled with background information of objects, plus a KB Objectbase filled with physical representations of these objects. The KB Base helps to spread requisite information and objects within the organisation. A Design Solution (DS) contains a representation of how a PF is realised constructively. In other words, one or more DS are implemented in an object. If all functions of the product are considered, the DS is the whole object. If one function or a subfunction is considered, the DS is merely a sub-assembly or one part of the object. A Design Solution is a possibility for solving one or more Product Functions. On the other hand, one PF can be achieved by several different Design Solutions. An electrical throttle device for a car engine is depicted in Figure 3 as an example of an object from the KB Objectbase. The Design Solution which fulfils the function 'to connect parts', i.e., to connect the plastic cover with the aluminium housing, is marked. The more information in the KB Base, the greater is the chance that the appropriate PDK for a query will be retrieved. It is obvious that if the reasoning mechanism is complete and correct, then the usefulness of Design Solutions and the linked Background Information depend principally on the quality and coverage of its two data bases.
Figure 3: Example of an object where an integrated Design Solution (DS) is marked. 3.2 Criteria for clustering relevant Product Design Knowledge Ideas from one domain might solve the problems of another, but only if connections between existing ideas (Design Solutions which are integrated in objects in the KB Base) and new design problems can be made across the boundaries between them as shown in Figure 4. Hargadon points out that if such connections are made, existing ideas often appear new and creative when they change form, combining with other ideas, to meet the needs of different stakeholders. These new combinations are essentially new concepts or objects because they are built from existing but previously unconnected ideas [ I I ] . Therefore, the challenge is to identify relevant PDK which is useful for generating the product design. -Common aspects -.Fonnections
................. ....
--
depends on the individual to describe and characterise the functions. For example, the battery of a flashlight fulfils the Product Function 'provide energy' but it can also be formulated as 'provide electricity'. So the same function can be described by using different words thereby complicating information search and retrieval. This difficulty can be eliminated by the introduction of Standard Product Functions. A Standard Product Function (SPF) is formulated in terms of a verb and a noun [4, 91. The words are selected from a pool of verbs and nouns for formulating Product Functions. Figure 5 shows a partial example of the words chosen for automotive products. The pools of words for describing SPF will grow and evolve naturally in accordance with the change of technology in information, energy and materials flow.
verbs
?
I
I
I
n
Figure 5: Partially filled pool of verbs an nouns for formulating Standard Product Functions (SPFs)
4 THEKBMODEL The Knowledge Brokering model as visualised in Figure 6 was generated through an iterative process inspired by three different sources. These sources were: a) observations made while attending different design activities in an automotive company, b) discovery of the fact that similar Design Solutions are realised in different products within different business units of one company and c) application of different WMs on various products.
Figure 4: Overview of the connections between existing PDK and 'searched' PDK. Before relevant PDK for generating a product design can be found, the DSs, integrated in objects and the BI on them have to be clustered according to their common properties so they can be addressed. The aim of clustering is to arrange knowledge into a form that makes it more easily accessible to those who need it. It makes knowledge as organised, explicit, portable, and easy to understand as possible. The importance of systematisation of design knowledge for supporting reuse and sharing knowledge was also recognised by Yoshikawa [12]. The approach adopted in this investigation is to cluster the captured DSs according to their Product Functions. As a result, the above-mentioned connection between existing idea and the new design problem is made. Another reason for using PFs for clustering the objects is that Product Functions are also used in many Working Methods. Consequently, designers and SE team members are familiar with using Product Functions and understand the same vocabulary. However, the vocabulary used for the formulation of PFs is neither well defined nor standardised. This means that it
4.1 Step 1: Generate the Function Model The first step in the KB procedure is to generate the Function Model (FM) for that product which is being developed by using SPFs. The FM is a proven procedure that assists product developers to design their product at an abstract level, and through this, to develop a sensible product structure without restricting the search space to specific solutions. In this case, the FM is hierarchical and it consists of two levels. 4.2 Step 2: Find and exhibit relevant objects The Function Model of the product is the basis for a directed search of Design Solutions already collected and realised in captured objects in the KB Base. This step is assisted by a software program where the input is the SPF descripter. The outputs for each SPF are tangible objects for exhibition and Background Information on DSs. This outcome of this step is an environment of clustered DSs and potential ideas to stimulate the development process. 4.3 Step 3: Experience the objects The SE team and those directly concerned with the new product design have full access to the exhibits. The object is to inspire them with Design Solutions, which are implemented in exhibits. They can examine, touch, feel and experience the tangible objects. The individuals can use all of their sensory organs for evaluation and
understanding, and by doing so could lead to a recognition point for re-using existing Design Solutions. Designers and SE team members have to identify the potential value of a Design Solution in order to adapt it to their disparate products, but they must be familiar enough with the DS to generate analogies appropriate for their current design needs. A good understanding is the basis for finding possible analogies between the Design Solutions realised in the captured objects and the sought Design Solution for generating their new product design. When using analogies, the main point is not the exactness of transformation but the resulting inspiration gained. The already realised Design Solutions can become the starting point of the problem solving process. It is obvious that the more diverse the exhibited objects, the higher the possibility to get an 'unconventional' idea through one of them. Another advantage of this approach is that individuals not merely discuss possible 'theoretical' ideas. They can also discuss physical, tangible representations of DSs, which have already been approved and realised in other objects. As observed by Probst, new ideas and new knowledge can take effect only if they are at least somewhat compatible with the old ones. The less familiar a new idea, the more likely for it to be rejected because of greater uncertainty and risk [13]. 1. Generate the 2. Find and exhibit Function Model relevant objects
B '7
F
Implement
ideas I Design Solutions
i
I
Object Name:
Function:
KB procedure
\ 4. Learn from
'9,I
3. Experien the o b j d
c
Figure 6: Overview of the Knowledge Brokering procedure. 4.4 Step 4: Learn from the objects An individual can gather information through the Background Information assigned to each object to obtain the explicit knowledge of the Design Solution/s. As another approach, an individual can also get information through enquiring the contact persods, such as designers and production engineers. The tacit knowledge of the 'knower' is already integrated in the design of the object. By studying the DSs of the objects, the individual will gain the knowledge on how a Product Function can be met- 'know how'. Through the contact person, the individual can enquire about 'why' it is realised in such a way- 'know why'. Consequently, parts of tacit knowledge can be extracted, shared and reused. 5 INDUSTRIAL CASE STUDY The developed KB approach was tested in case studies in the automotive division of an international company. The KB model as well as the premises for using KB were largely accepted and confirmed. 104 persons were involved in the KB project and 24 of them took active part in evaluating KB by testing it on 60 objects. From the industrial tests, it is concluded that the main benefits of the KB approach are its enabling agent effects for enhancing product innovation, increasing product
quality and reducing product costs and development time. The estimated savings in development costs ranged from 5 to 20% and the reduction in time to market varied from 1 to 3 months depending on product complexity. The main limitations can be summarised as: a) the maximum benefit of Knowledge Brokering can best be harvested in large companies and b) PDK integrated in the KB Base must be adapted to the design problem by human creativity. Finally, a number of issues have to be noted in the implementation of the Knowledge Brokering approach: a) both technical and financial resources are required for maintenance and updating of the KB Base, b) the contents of the KB Base have to be adapted to each individual company and c) confidentiality issues have to be addressed. 6 CONCLUSIONS This paper presents a new hybrid knowledge-based and human-centred model aimed at finding and re-using existing explicit and tacit product design knowledge systematically. Knowledge Brokering links the disciplines of Knowledge Management, Product Design and Working Methods for the early stages of Product Development through a sequential four-step model. This model covers the analysis, collection and clustering of explicit design knowledge, the systematic learning process, retention and transfer of tacit design knowledge. Industrial scale testing in the automotive industry has demonstrated the viability of knowledge brokering for new product development in terms of both time and cost reduction.
7 ACKNOWLEDGMENT The authors would like to acknowledge the financial support and technical assistance from Robert Bosch GmbH for this research investigation. 8 REFERENCES [ I ] Bullinger, H.-J., Warschat, J., 1996, Concurrent Simultaneous Engineering Systems- The Way to Successful Product Development, Springer Verlag. [2] Baylis, C., 1994, Simultaneous Engineering, World Class Design to Manufacture, 1/1:17-20. [3] Fischer, G., 2001, The Software Technology of the 21st Century, Proc. SFST2001, China, 1-8. [4] VDI guideline 2222-1, 1997, Methodisches Entwickeln von Losungsprinzipien, Beuth Verlag. [5] Frankenberger, E., 2001, Computer Supported Systematic Design and Knowledge-Management in the Early Design Phase, Proc. ICED, Glasgow. [6] Hargadon, A,, Sutton, R.I., 2000, Building an Innovation Factory, Harvard Business Manager, 22/6: 46-54. [7] Lindemann, U., 2002, Efficiency and Effectiveness of Working Methods, Proc. 8th International Symposium on QFD, Germany, 13-22. [8] Hon, K.K.B., Zeiner, J., 2002, The Function Model: Basis for Guiding The Collaborative Design Process in The Early Stages, Proc. 1st Int. Conf. Digital Enterprise Technology, Durham, UK. [9] Pahl, G., Beitz, W., 1997, Konstruktionslehre Methoden und Anwendung, Springer Verlag. [ l o ] Ha, S., Pahng, G., Chang, M., Park, S., Rho, H.M., 1999, Managing Design Knowledge: Active Document System, ClRP Annals, 48/1: 89-92. [ I l l Hargadon, A,, 1998, Knowledge Brokers: A Field Study of Organisational Learning and Innovation, Proc. Academy of Management Conference. [I21 Yoshikawa, H., 1993, Systematization of Design Knowledge, ClRP Annals, 42/1: 131-134. [I31 Probst, G. J. B., 1998, Practical Knowledge: A Model That Works, Arthur D. Little Prism, no 2, 17-29.
Abstract The aim of this paper is to present a pragmatic model for the systematic transfer of ideas and knowledge at the early stage of product design in a company environment. In using the model, the basic premise is not to build a new product 'from scratch' but to reuse existing ideas and knowledge from other objects and products developed previously. This new approach is called Knowledge Brokering (KB). The developed KB model consists of four sequential steps, which cover the collection and clustering of explicit design knowledge, the systematic learning process, retention and transfer of tacit design knowledge. The premises for using the KB model and case study results from the automotive industry on the advantages and limitations of the new approach are also described. Keywords: Product, Knowledge, Design
1 INTRODUCTION New products are vital to the success and prosperity of any modern company. Facing new technologies, shorter product life cycles, increasing global competition and dynamic market needs, companies must focus on product innovation and reducing product development time and cost. One major contribution to a successful product design is to develop the product by a Simultaneous Engineering (SE) team [ I ] . As the primary target for all companies in new product development is the same, i.e., to get from the start of the development process to having a product in the marketplace in the most efficient and effective manner, the value of an SE team with a shared vision for achieving the product objectives is well recognised. The input of knowledge and expertise of members from different technical and business disciplines at the early stage is crucial [2]. However, generating a product design requires more knowledge than any single individual or any single group possesses, because the knowledge relevant to a problem is distributed among many different stakeholders [3]. Consequently, the challenge is on how to acquire knowledge or how to find a person who has the requisite knowledge for generating a specific product design feature. Nevertheless, before knowledge is needed, ideas are necessary for generating the concept of the design. VDI guideline 2221-1 states that the finding of Design Solutions (ideas) is the crucial step within the whole design process [4]. Further, Frankenberger states that many companies develop complex products in various series independently, even though between the product lines of those companies the sub-problems to be solved are comparable to a certain extent. It is often noted that a new design contains results of working steps which are similar to the results of the same steps in former design projects. For example, the set of Design Solutions considered to solve a sub-problem can be derived from an earlier project [5]. But the larger a company becomes, the harder it is for anyone to know what other designers is doing and which Design Solutions exist already [6].
The aspects depicted were observed in the case study company which is a major company in the automotive industry. In that company, contact persons for exchanging information and experience from other business units or other departments are not readily known. product concepts are generated without appropriate access to Design Solutions which were integrated in former or other product designs. Another contribution to a successful product design is to develop the product by using Working Methods (WM) such as Target Costing, Quality Function Deployment or Design for Manufacture and Assembly in order to increase effectiveness and efficiency [7]. While more and more products are developed with Working Methods within a company, for many products the steps for their execution continue to start at the beginning even though these methods were already applied to earlier or similar products. Consequently, the challenge is to find those products to which WMs were already applied in order to reuse knowledge generated in previous product development. Research focus In essence, this paper is concerned with the early phases of Product Development (PD). The aim of this research is to develop a pragmatic model for the systematic transfer of ideas and knowledge for product designs within a company. In using this new model, the basic premise is not the building of a new product 'from scratch' but the reuse of existing ideas and knowledge from other objects for products already developed.
2 MODELS WITHIN THE EARLY STAGES OF PD The early phases of PD considered in this paper are divided into three models: Market Model, Function Model and Design Model as shown in Figure 1 [8]. Various quantitative and qualitative activities undertaken during the early stages of Product Development can be assigned to these three models. The Market Model is the first one that needs to be established. Important aspects which need to be taken into
account in setting up a Market Model for the product are customer/user demands, expected sales, company internal requirements and allowable marketing costs. Furthermore, the target functionality of the product and also the functionality of competing products have to be considered. Such information is then used as a basis for assessing the competition and for generating engineering requirements and specifications.
:+
Market Model
(0
P
objects can be prototypes, models, product examples or other kind of physical representations. They can be products from the same or different business units of the company, competitors' products and products from suppliers. The Background Information (BI) is linked to the object and contains explicit knowledge drawn from design and production departments, e.g., the Product Functions, specifications of the functions, descriptions of the object, drawings of the object, product cost allocations and Working Methods applied. This information is stored in a KB Database. Figure 2 shows the first tab of the BI on a throttle device which will be described in the next section
Background Information E w
W
2003
2005
2007
Background Information1
Year
Function Model
Background Information2
Integratiin d a k 20.09.02
Object Name:
illuminate obJeai
DB-
I
Background Information3
No:
16
I
I
*wdims
Object- Id.:
7
Throttle device
-
Product Functionk
I
Design Models
I
(2nd level) adjus~a,r flow
. represent electrical interface
Remark I Description of the function/$: To change the rotation angle of the throttle plate Flange to customer part
Specificatiods of the functbnls: Rotation angel:
7 -93"
MLK connector
Figure 2: Screen from the KB Database
Figure 1: Models within early Product Development. Based on these insights the next step is the generation of the Function Model (FM). This model is the logical arrangement of the Product Functions. The term Product Function (PF) is used according to the definition of Pahl and Beitz, i.e., the general and intended correlation between input and output with the objective to fulfil a task [9]. However, in this paper, PFs only represent the tangible technological product functionality of the product. To obtain Design Models is the core process within Product Development. An important activity is to discover Design Solutions for realising the required Product Functions and to combine them for conceptual designs. Further downstream processes such as detailed CAD modelling are outside the scope of this paper. 3
PREMISES FOR THE KNOWLEDGE BROKERING MODEL In this research, the term Knowledge Brokering (KB) is used for the process whereby Product Design Knowledge (PDK) from a product or object is reused for the generation of another product design within a company. Knowledge Brokering aims to enhance the exploitation of knowledge from existing product designs in order to share and reuse it for other products that have to be developed. The main focus group of KB is staff members in the product design departments. The concept of knowledge is based on the hierarchy of data, information and finally knowledge. In this context, data is the raw material which can be diagrams, facts or text. When data is organised and structured in a useful way, it becomes information. When information is read and interpreted by an individual, it becomes knowledge [9]. In other words, information is concerned with 'what' whereas knowledge addresses the question 'why'. Product Design Knowledge consists of a tangible object and Background Information on the object. The tangible
However, not all PDK can be easily articulated or transferred in explicit forms because it is personal and context-specific. Such type of knowledge is tacit knowledge which is individual-based, context related, analogous, practice related knowledge. Tacit knowledge can be exchanged effectively in person-to-person situation. The object of Knowledge Brokering is therefore not to codify tacit knowledge into explicit knowledge but to provide contact details as part of BI for the user of the KB model. Other forms of design knowledge management systems were also proposed by Ha, et al [lo].
3.1 The KB Data- and KB Objectbase A premise for using the Knowledge Brokering model is the KB Base which consists of a KB Database filled with background information of objects, plus a KB Objectbase filled with physical representations of these objects. The KB Base helps to spread requisite information and objects within the organisation. A Design Solution (DS) contains a representation of how a PF is realised constructively. In other words, one or more DS are implemented in an object. If all functions of the product are considered, the DS is the whole object. If one function or a subfunction is considered, the DS is merely a sub-assembly or one part of the object. A Design Solution is a possibility for solving one or more Product Functions. On the other hand, one PF can be achieved by several different Design Solutions. An electrical throttle device for a car engine is depicted in Figure 3 as an example of an object from the KB Objectbase. The Design Solution which fulfils the function 'to connect parts', i.e., to connect the plastic cover with the aluminium housing, is marked. The more information in the KB Base, the greater is the chance that the appropriate PDK for a query will be retrieved. It is obvious that if the reasoning mechanism is complete and correct, then the usefulness of Design Solutions and the linked Background Information depend principally on the quality and coverage of its two data bases.
Figure 3: Example of an object where an integrated Design Solution (DS) is marked. 3.2 Criteria for clustering relevant Product Design Knowledge Ideas from one domain might solve the problems of another, but only if connections between existing ideas (Design Solutions which are integrated in objects in the KB Base) and new design problems can be made across the boundaries between them as shown in Figure 4. Hargadon points out that if such connections are made, existing ideas often appear new and creative when they change form, combining with other ideas, to meet the needs of different stakeholders. These new combinations are essentially new concepts or objects because they are built from existing but previously unconnected ideas [ I I ] . Therefore, the challenge is to identify relevant PDK which is useful for generating the product design. -Common aspects -.Fonnections
................. ....
--
depends on the individual to describe and characterise the functions. For example, the battery of a flashlight fulfils the Product Function 'provide energy' but it can also be formulated as 'provide electricity'. So the same function can be described by using different words thereby complicating information search and retrieval. This difficulty can be eliminated by the introduction of Standard Product Functions. A Standard Product Function (SPF) is formulated in terms of a verb and a noun [4, 91. The words are selected from a pool of verbs and nouns for formulating Product Functions. Figure 5 shows a partial example of the words chosen for automotive products. The pools of words for describing SPF will grow and evolve naturally in accordance with the change of technology in information, energy and materials flow.
verbs
?
I
I
I
n
Figure 5: Partially filled pool of verbs an nouns for formulating Standard Product Functions (SPFs)
4 THEKBMODEL The Knowledge Brokering model as visualised in Figure 6 was generated through an iterative process inspired by three different sources. These sources were: a) observations made while attending different design activities in an automotive company, b) discovery of the fact that similar Design Solutions are realised in different products within different business units of one company and c) application of different WMs on various products.
Figure 4: Overview of the connections between existing PDK and 'searched' PDK. Before relevant PDK for generating a product design can be found, the DSs, integrated in objects and the BI on them have to be clustered according to their common properties so they can be addressed. The aim of clustering is to arrange knowledge into a form that makes it more easily accessible to those who need it. It makes knowledge as organised, explicit, portable, and easy to understand as possible. The importance of systematisation of design knowledge for supporting reuse and sharing knowledge was also recognised by Yoshikawa [12]. The approach adopted in this investigation is to cluster the captured DSs according to their Product Functions. As a result, the above-mentioned connection between existing idea and the new design problem is made. Another reason for using PFs for clustering the objects is that Product Functions are also used in many Working Methods. Consequently, designers and SE team members are familiar with using Product Functions and understand the same vocabulary. However, the vocabulary used for the formulation of PFs is neither well defined nor standardised. This means that it
4.1 Step 1: Generate the Function Model The first step in the KB procedure is to generate the Function Model (FM) for that product which is being developed by using SPFs. The FM is a proven procedure that assists product developers to design their product at an abstract level, and through this, to develop a sensible product structure without restricting the search space to specific solutions. In this case, the FM is hierarchical and it consists of two levels. 4.2 Step 2: Find and exhibit relevant objects The Function Model of the product is the basis for a directed search of Design Solutions already collected and realised in captured objects in the KB Base. This step is assisted by a software program where the input is the SPF descripter. The outputs for each SPF are tangible objects for exhibition and Background Information on DSs. This outcome of this step is an environment of clustered DSs and potential ideas to stimulate the development process. 4.3 Step 3: Experience the objects The SE team and those directly concerned with the new product design have full access to the exhibits. The object is to inspire them with Design Solutions, which are implemented in exhibits. They can examine, touch, feel and experience the tangible objects. The individuals can use all of their sensory organs for evaluation and
understanding, and by doing so could lead to a recognition point for re-using existing Design Solutions. Designers and SE team members have to identify the potential value of a Design Solution in order to adapt it to their disparate products, but they must be familiar enough with the DS to generate analogies appropriate for their current design needs. A good understanding is the basis for finding possible analogies between the Design Solutions realised in the captured objects and the sought Design Solution for generating their new product design. When using analogies, the main point is not the exactness of transformation but the resulting inspiration gained. The already realised Design Solutions can become the starting point of the problem solving process. It is obvious that the more diverse the exhibited objects, the higher the possibility to get an 'unconventional' idea through one of them. Another advantage of this approach is that individuals not merely discuss possible 'theoretical' ideas. They can also discuss physical, tangible representations of DSs, which have already been approved and realised in other objects. As observed by Probst, new ideas and new knowledge can take effect only if they are at least somewhat compatible with the old ones. The less familiar a new idea, the more likely for it to be rejected because of greater uncertainty and risk [13]. 1. Generate the 2. Find and exhibit Function Model relevant objects
B '7
F
Implement
ideas I Design Solutions
i
I
Object Name:
Function:
KB procedure
\ 4. Learn from
'9,I
3. Experien the o b j d
c
Figure 6: Overview of the Knowledge Brokering procedure. 4.4 Step 4: Learn from the objects An individual can gather information through the Background Information assigned to each object to obtain the explicit knowledge of the Design Solution/s. As another approach, an individual can also get information through enquiring the contact persods, such as designers and production engineers. The tacit knowledge of the 'knower' is already integrated in the design of the object. By studying the DSs of the objects, the individual will gain the knowledge on how a Product Function can be met- 'know how'. Through the contact person, the individual can enquire about 'why' it is realised in such a way- 'know why'. Consequently, parts of tacit knowledge can be extracted, shared and reused. 5 INDUSTRIAL CASE STUDY The developed KB approach was tested in case studies in the automotive division of an international company. The KB model as well as the premises for using KB were largely accepted and confirmed. 104 persons were involved in the KB project and 24 of them took active part in evaluating KB by testing it on 60 objects. From the industrial tests, it is concluded that the main benefits of the KB approach are its enabling agent effects for enhancing product innovation, increasing product
quality and reducing product costs and development time. The estimated savings in development costs ranged from 5 to 20% and the reduction in time to market varied from 1 to 3 months depending on product complexity. The main limitations can be summarised as: a) the maximum benefit of Knowledge Brokering can best be harvested in large companies and b) PDK integrated in the KB Base must be adapted to the design problem by human creativity. Finally, a number of issues have to be noted in the implementation of the Knowledge Brokering approach: a) both technical and financial resources are required for maintenance and updating of the KB Base, b) the contents of the KB Base have to be adapted to each individual company and c) confidentiality issues have to be addressed. 6 CONCLUSIONS This paper presents a new hybrid knowledge-based and human-centred model aimed at finding and re-using existing explicit and tacit product design knowledge systematically. Knowledge Brokering links the disciplines of Knowledge Management, Product Design and Working Methods for the early stages of Product Development through a sequential four-step model. This model covers the analysis, collection and clustering of explicit design knowledge, the systematic learning process, retention and transfer of tacit design knowledge. Industrial scale testing in the automotive industry has demonstrated the viability of knowledge brokering for new product development in terms of both time and cost reduction.
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