Product Knowledge Management:Role of the
Hyman Duan, Quentin Xie, Yunmei Hong, Leonid Batchilo, Alp Lin
 IWINTALL, Inc.
 
 
Abstract
 
With the acceptance of Knowledge Management by industries and the mass application of PDM/PLM systems in enterprises in recent years, the issue of Product Knowledge Management (PKM) has drawn remarkable attention. However, current PDM/PLM systems are not able to support knowledge management activities in product lifecycle; and the existing knowledge management theory, such as SECI (Socialization-Externalization-Combination-Internalization) model, also has limitations when applied to R&D process. 
 
In this paper, we analyze the difficulties and drawbacks of applying SECI model in product lifecycle. We propose using both TRIZ and ontology to overcome the difficulties. We present a systematic inventive problem solving workflow using TRIZ and ontology-based search scheme, analyze how they interact with product knowledge creation, representation, organization and reuse. Finally we draw the conclusion that SECI model can be enhanced with synthesis of TRIZ and ontology in R&D process. 
 
Keywords: Product Knowledge Management, TRIZ, Ontology  
 
Ikujiro Nonaka and Hirotaka Takeuchi [1] propose a SECI model of the knowledge creating process to understand the dynamic nature of knowledge creation, and to manage such a process effectively. They distinguished between two types of knowledge – explicit and tacit. As shown in Figure 1, Nonaka and Takeuchi claim that the four conversion processes involving these two types of knowledge constitute the essence of knowledge creation: 
 
² From tacit to tacit (i.e., socialization),
 
² From tacit to explicit (i.e., externalization),
 
² From explicit to tacit (i.e., internalization), and
 
² From explicit to explicit (i.e., combination).
 
The creation of knowledge is a continuous process of dynamic interactions between tacit and explicit knowledge. Only by tapping into tacit knowledge can new and improved explicit knowledge be created. In turn, better explicit knowledge is essential for stimulating the development of new, higher level, tacit knowledge. The four modes of knowledge conversion interact in the spiral of knowledge creation. The spiral becomes larger in scale as it moves up through organizational levels, and can trigger new spirals of knowledge creation. 
 
 Figure 1. The SECI cycle of knowledge creation [1] 
 
SECI model recognizes the dynamic nature of knowledge and knowledge creation and provides a framework for management of the relevant processes. But it has some disadvantages. It is based on a study of Japanese organizations, which heavily rely on tacit knowledge. So SECI model do not pay more attention to the sharing of explicit knowledge.
 
We think that SECI model is more about an idea of knowledge management than about an operable tool, especially for product knowledge.
 
The knowledge of an organization comprises three types of knowledge, including customer knowledge, product knowledge and management knowledge. They decide, support and implement the enterprise strategy respectively. The main focus of customer and management knowledge is to locate knowledge from both within and beyond an organization, leverage, store and distribute that knowledge in an efficient way. All of these are major components of traditional knowledge management. Product knowledge is quite unique from its abstract nature and high intellect involved, which makes it hard to represent. How to create and utilize new knowledge based on existing ones becomes the main focus, which remains a dark area in traditional knowledge management system.
 
With the acceptance of Knowledge Management by industries and the mass application of PDM/PLM systems in enterprises in recent years, the issue of Product Knowledge Management (PKM) has drawn remarkable attention. PKM emphasize the conscious analysis, optimization and organization of production information in PDM system in order to reuse them in new product development and then transfer them into product knowledge and enterprise intellectual assets. The core idea of PKM is to generate knowledge from information and to guide innovation with the knowledge. PKM is high level application of PDM and PLM. However, current PDM/PLM systems are not able to provide fully support to product knowledge management activities in product lifecycle.
 
Research [2] indicates that, in a typical organization, only 4% of organizational knowledge is available in a structured and reusable format and the rest is either unstructured or resides in peoples minds. The structured knowledge, although small in volume, has high value for companies because it can be accessed easily, mined and used for decision making. Generating structured knowledge, through transformation from tacit form into explicit form, is one of the critical steps of product knowledge management.
 
The remainder of this paper is structured as follows: Section 2 reviews the knowledge creation role of TRIZ in R&D process; Section 3 discusses the product knowledge organization powered by ontology and presents the benefits of using TRIZ and ontology in problem solving process. In section 4, we propose using both TRIZ and ontology to overcome the above difficulties of product knowledge management. We analyze how they interact with product knowledge creation, representation, organization and reuse. Finally in section 5, we draw the conclusion that SECI model can be enhanced with synthesis of TRIZ and ontology in R&D process.
 
Knowledge is the essence of innovation and competitive advantage in R&D process, and thus knowledge creates the ‘platforms’ on which a company can expand into new product markets, enabling it to maintain or enhance its competitive advantages [2]. Therefore Effective tools and processes for knowledge creation and management are becoming a critical issue. TRIZ is recognized as the most effective methods and tools for engineering problem solving and innovative concept generation, and also is being aware of its value on knowledge creation. 
  Figure 2. TRIZ concepts and tools
  
TRIZ (Figure 2) was designed for problem solving and provides a logical way of thinking for development of the technical systems through overcoming contradiction and towards the increase of ideality with utilizing resources.
 
    Figure 3. TRIZ problem solving process
 
The TRIZ standard problem solving process is illustrated in Figure 3. From Specific Probl