Knowledge kanban system for virtual research and development

Chia Jou Lin, F. Frank Chen, Yuh Min Chen

Research output: Contribution to journalArticlepeer-review

14 Citations (Scopus)

Abstract

Virtual research and development (R&D) is inevitable to reduce the product life cycle. Enterprises tend to rely on their foreign partners for supporting technology and knowledge acquisition to conduct and improve firms' product development with low R&D risk. R&D is a highly creative and knowledge-intensive activity, Therefore, efficient knowledge flow, which transmits the right knowledge to the right people at the right time, is key to improving efficiency of the R&D process. Kanban supports visual production control using the card of providing information to regulate the flow of inventory and materials. To enhance the knowledge flow efficiency in the virtual R&D process, this study proposes a knowledge kanban system utilizing the philosophy of kanban management and knowledge engineering techniques. Employees can quickly, easily, and exactly determine what knowledge they need to learn, create, share, and maintain by the knowledge kanban system. This system assists employees to do the right thing, to reduce the cycle time of R&D processes, and to enhance the reuse of knowledge, to create new knowledge. To achieve this objective, this study first proposes a knowledge flow model in virtual R&D based on the analysis result of knowledge in virtual enterprises (VEs), and then designs the knowledge kanban model according to the knowledge flow model in virtual R&D and proposes the knowledge kanban functional framework based on the knowledge kanban model. Finally, this study develops the related technologies to implement the knowledge kanban system. The knowledge kanban system is an effective tool to facilitate knowledge creation, storage, transmission and sharing for R&D engineers to develop knowledge in problem solving and product development, to improve enterprise competitiveness.

Original languageEnglish
Pages (from-to)119-134
Number of pages16
JournalRobotics and Computer-Integrated Manufacturing
Volume29
Issue number3
DOIs
Publication statusPublished - 2013

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering
  • Software
  • Mathematics(all)
  • Computer Science Applications
  • Industrial and Manufacturing Engineering

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