Yuh-Jen Chen

Structured methodology for supplier selection and evaluation in a supply chain

Supply chain management (SCM) is one of the most important competitive strategies used by modern enterprises. The main aim of supply chain management is to integrate various suppliers to satisfy market demand. Meanwhile, supplier selection and evaluation plays an important role in establishing an effective supply chain. Traditional supplier selection and evaluation methods focus on the requirements of single enterprises, and fail to consider the entire supply chain. Therefore, this study proposes a structured methodology for supplier selection and evaluation based on the supply chain integration architecture. In developing the methodology for supplier selection and evaluation in a supply chain, enterprise competitive strategy is first identified using strengths weaknesses opportunities threats (SWOT) analysis. Based on the competitive strategy, the criteria and indicators of supplier selection are chosen to establish the supplier selection framework. Subsequently, potential suppliers are screened through data envelopment analysis (DEA). Technique for order preference by similarity to ideal solution (TOPSIS), a multi-attribute decision-making (MADA) method is adapted to rank potential suppliers. Finally, the Taiwanese textile industry is used to illustrate the application and feasibility of the proposed methodology. This study facilitates the improvement of collaborator relationships and the management of potential suppliers to help increase product development capability and quality, reduce product lifecycle time and cost, and thus increase product marketability.

Development of a method for ontology-based empirical knowledge representation and reasoning

In the knowledge economy era of the 21st century [14,17], the competitive advantage of enterprises has shifted from visible equipment, capital and labor in the past to invisible knowledge nowadays. Knowledge can be distinguished into tacit knowledge and explicit knowledge. Meanwhile, tacit knowledge largely encompasses empirical knowledge difficult to be documented and generally hidden inside of personal mental models. The inability to transfer tacit knowledge to organizational knowledge would cause it to disappear after knowledge workers leaving their post, ultimately losing important intellectual assets for enterprises. Therefore, enterprises attempting to create higher knowledge value are highly concerned with how to transfer personal empirical knowledge inside of an enterprise into an organizational explicit knowledge by using a systematic method to manage and share such valuable empirical knowledge effectively. This study develops a method of ontology-based empirical knowledge representation and reasoning, which adopts OWL (Web Ontology Language) to represent empirical knowledge in a structural way in order to help knowledge requesters clearly understand empirical knowledge. An ontology reasoning method is subsequently adopted to deduce empirical knowledge in order to share and reuse relevant empirical knowledge effectively. Specifically, this study involves the following tasks: (i) analyze characteristics for empirical knowledge, (ii) design an ontology-based multi-layer empirical knowledge representation model, (iii) design an ontology-based empirical knowledge concept schema, (iv) establish an OWL-based empirical knowledge ontology, (v) design reasoning rules for ontology-based empirical knowledge, (vi) develop a reasoning algorithm for ontology-based empirical knowledge, and (vii) implement an ontology-based empirical knowledge reasoning mechanism. Results of this study facilitate the tacit knowledge storage, management and sharing to provide knowledge requesters with accurate and comprehensive empirical knowledge for problem solving and decision support.

Enabling collaborative product design through distributed engineering knowledge management

Collaborative product design (CPD) is a knowledge-intensive process that encompasses conceptual design, detailed design, engineering analysis, assembly design, process design, and performance evaluation. Each task involves various areas of knowledge and experience. However, successful collaborative product design depends on the ability to effectively manage and share engineering knowledge and experience throughout the entire development process. Consequently, the realization of distributed engineering knowledge management, which not only supports collaborative product design but also accumulates and utilizes corporate memory situated at various locations, has become one of the key tasks managed by industries. This paper presents a distributed engineering knowledge management approach for the practice of collaborative product design. In developing the proposed approach, a CPD-based engineering knowledge management methodology is first proposed under the concepts of knowledge management and collaboration. This methodology includes a knowledge management-oriented engineering management work model, a distributed engineering knowledge management framework, and rules and methods for managing engineering knowledge. The CPD-based engineering knowledge management system framework is designed, on the basis of this proposed methodology. Finally, a CPD-based engineering knowledge management system is developed using unified modeling language (UML) modeling techniques.

Development of a mechanism for ontology-based product lifecycle knowledge integration

Compared with relying on the efforts of various enterprises collaborating on product lifecycle activities, such as coordination, communication and control, the ability to effectively share product information and knowledge is more important. Therefore, how to best integrate such heterogeneous product knowledge distributed among various cooperating enterprises has become an extremely important knowledge management subjects associated with collaborative product lifecycle. This study develops a novel mechanism for integrating ontology-based product lifecycle knowledge to effectively integrate the heterogeneous product knowledge distributed among different enterprises during a products lifecycle, thereby facilitating sharing of this product knowledge. This study: (i) designed an integration and sharing process for collaborative product lifecycle knowledge, (ii) developed techniques associated with integration of ontology-based product lifecycle knowledge, and (iii) implemented an integration and sharing mechanism for ontology-based product lifecycle knowledge. In developing techniques associated with integration of ontology-based product lifecycle knowledge, which involves establishing a product lifecycle ontology, designing local ontology schema, designing an integration algorithm for ontology-based product lifecycle knowledge, and designing a searching method for ontology-based product lifecycle knowledge.

On technology for functional requirement-based reference design retrieval in engineering knowledge management

Engineering design is a knowledge-intensive process, and includes conceptual design, detailed design, engineering analysis, assembly design, process design, and performance evaluation. Each of these tasks involves various aspects of technical knowledge and experience. Whether this technical knowledge and experience can be effectively shared is key to increasing product development capability and quality, and also to reducing the duration and cost of the development cycle. Consequently, providing engineering designers various query methods for retrieving engineering knowledge is one of the most important tasks in engineering knowledge management. The study develops a technology for functional requirement-based reference design retrieval as a decision support mechanism, which can assist engineering designers to retrieve relevant design and associated knowledge for reference in conducting functional requirements of a product. This study involves the following tasks: (i) designing a functional requirement-based reference design retrieval process, (ii) developing techniques related to the technology for functional requirement-based reference design retrieval, and (iii) implementing a functional requirement-based reference design retrieval mechanism. The retrieval process includes the steps of functional requirement-based query, case searching and matching, and case ranking. The technology involves (i) a structured query model for functional requirements, (ii) an index structures for historical design cases, (iii) functional requirement-based case searching and matching mechanisms, (iv) a functional requirement-based case ranking mechanism, and (v) a case-based representation of designed entities. Finally, the experimental example with indexing and retrieving similar designed entities is conducted to demonstrate the proposed techniques worked efficiently.

Knowledge Refinement for Engineering Knowledge Management

Engineering design is a knowledge-intensive process, including conceptual design, detailed design, engineering analysis, assembly design, process design, and performance evaluation. Each of these tasks involves various aspects of knowledge and experience. They are the most valuable sources for capitalizing enterprise knowledge and know-how on building enterprise memory, which may become part of enterprise assets. Therefore, capturing and representing product design information, design intents, and underlining design knowledge for later reuse is the basis of and one of the key tasks in engineering knowledge management. This study develops an approach for engineering knowledge refinement to facilitate engineering knowledge management. This approach is basically a refinement process that includes the steps of knowledge capture, knowledge representation and storage, and knowledge compilation. This study involves the development of a semantic graph for describing product-related information, design intent and know-how, a tag-based scheme for representing various types of captured product information and engineering knowledge, a case-based representation for a designed entity, and the design of a knowledge compilation model and algorithm. The objective of this study can be achieved by performing the following tasks: (i) developing an engineering knowledge management framework, (ii) establishing an engineering knowledge refinement process, (iii) developing levels of knowledge representation schemes, and(iv) implementing engineering knowledge refinement mechanisms.

Development of an Ontology-based Expert Recommendation System for Product Empirical Knowledge Consultation

Product lifecycle, a knowledge-intensive process, consists mainly of market analysis, product design and process development, product manufacturing, product distribution, product in use, post-sale service, and product recycling. Performing and achieving each activity or its supply chain activities require product empirical knowledge at different levels to resolve product-related problems or make certain decisions. However, effective consultation and sharing of tacit product empirical knowledge would greatly enhance product market competitiveness. Therefore, effectively and correctly sharing product empirical knowledge from domain experts in different organizations require developing an expert recommendation system for product empirical knowledge consultation, which is priority concern for product knowledge management. This study develops an expert recommendation system for product empirical knowledge consultation by using ontology to matchmaking of the required consultative experts quickly and correctly for the product empirical knowledge requester, thus sharing required product empirical knowledge by interpersonal communication to resolve product-related problems efficiently. The tasks involved in this study include: (i) designing an expert recommendation process for product empirical knowledge consultation, (ii) developing an expert recommendation method for product empirical knowledge consultation, and (iii) implementing an expert recommendation mechanism for product empirical knowledge consultation.

Ontology-based empirical knowledge verification for professional virtual community

A professional virtual community provides an interactive platform for enterprise experts to create and share their empirical knowledge cooperatively, and the platform contains a tremendous amount of hidden empirical knowledge that knowledge experts have preserved in the discussion process. Therefore, enterprise knowledge management highly prioritises how to verify the empirical knowledge effectively before archiving it into enterprise knowledge repository for reuse. This work develops a novel scheme of ontology-based empirical knowledge verification for professional virtual community to assist domain experts in a professional virtual community to verify the logics of empirical knowledge, thus ensuring the quality of empirical knowledge and providing accurate knowledge decision support for knowledge workers. In particular, this work has the following objectives: propose an empirical knowledge verification model for a professional virtual community, design an ontology-based empirical knowledge verification process, develop techniques related to the ontology-based empirical knowledge verification and implement an ontology-based empirical knowledge verification mechanism with an illustrative example of securities trading. Results of this study facilitate efforts within the professional virtual community to verify empirical knowledge in order to provide knowledge workers with logic-correct empirical knowledge for decision support.

Development of a Distributed Product Knowledge Service System

Conventional business models focus on providing end products and services regardless of product- or service-related knowledge. Such models are unable to meet customer requirements in a knowledge economy. Therefore, to effectively capture, accumulate, store and apply knowledge to provide product knowledge service to customers is central to enterprise success. This study has the following three objectives: (i) to propose a novel product knowledge service model based on the product lifecycle and its supply chain, (ii) to design a system framework for product knowledge service, and (iii) to implement the proposed system. The product knowledge service model can be seen as a product knowledge supplier chain developed based on the integration of product lifecycle and its supply chain. Based on the knowledge management cycle, software agent technology and service-oriented architecture (SOA), the agent-based knowledge service-oriented system framework is designed to reflect the distributed, flexible and hierarchical characteristics of the product knowledge service model. Finally, the proposed agent-based knowledge service-oriented system framework is developed and implemented using Unified Modeling Language (UML) and Java programming language with the Java Agent Development Framework (JADE).

Demand-driven knowledge acquisition method for enhancing domain ontology integrity

Knowledge, as the most important resource for the knowledge economy in the 21st century, is fundamental to enterprise competitive strength. Therefore, how to effectively integrate internal and external knowledge and provide correct knowledge to the right users in a timely fashion have become key success factors in business operation. This study attempts to develop a demand-driven knowledge acquisition method to enhance the integrity of domain ontology. Based on the demand of the user request, the developed method can dynamically discover the insufficient knowledge concepts in the domain ontology, acquire such knowledge concepts from knowledge documents available on the Internet, and integrate the acquired knowledge concepts into the domain ontology to make it more correct and complete, thus enhancing its reuse value. This objective can be achieved by performing the following tasks: (i) design of a demand-driven knowledge acquisition process to enhance domain ontology integrity, (ii) development of techniques related to demand-driven knowledge acquisition to enhance domain ontology integrity, and (iii) implementation of a demand-driven knowledge acquisition mechanism to enhance domain ontology integrity. Developing techniques associated with demand-driven knowledge acquisition involves demand preprocessing, knowledge retrieval and searching, ontology construction, and ontology integration.