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A Knowledge-Based System for Sharing and Reusing Tacit Knowledge in Robotic Manufacturing

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  • Lei Wang

    (Kyoto University, Japan)

  • Yajie Tian

    (Kyoto University, Japan)

  • Tetsuo Sawaragi

    (Kyoto University, Japan)

  • Yukio Horiguchi

    (Kyoto University, Japan)

Abstract

A critical problem in robotic manufacturing is that the task of teaching robotics is rather time-consuming. This has become a serious problem in the present age of cost reduction. Collaboration with a company in the field has revealed that the root cause of this problem is that there is not a common knowledge base in this domain, which can serve as shared and reused knowledge. In robotic manufacturing, the skills and experiences of skilled workers are a form of tacit knowledge that is difficult to be acquired and transferred to other workers and robots. This paper proposes a knowledge-based system for sharing and reusing tacit knowledge in the robotic assembly domain. In this system, a modified EBL (Explanation-based Learning) method is proposed to generalize tacit knowledge from specific robotic programs made by skilled workers. A newly operational criterion is proposed for the generalized tacit knowledge, which demands that it should be expressed understandably by human workers and be reusable by robots to generate programs automatically.

Suggested Citation

  • Lei Wang & Yajie Tian & Tetsuo Sawaragi & Yukio Horiguchi, 2010. "A Knowledge-Based System for Sharing and Reusing Tacit Knowledge in Robotic Manufacturing," International Journal of Knowledge and Systems Science (IJKSS), IGI Global, vol. 1(4), pages 61-78, October.
    • Handle: RePEc:igg:jkss00:v:1:y:2010:i:4:p:61-78
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