Despite the recent efforts towards the introduction of advanced digital and automation technologies in the industry, most of the manufacturing processes are still governed and optimized by human expertise. This fundamental contribution is often in the form of explicit and implicit (or tacit) human knowledge, which is extremely difficult to document, structure and transfer to other people. In this scenario, manufacturing companies run the risk of losing this intrinsic asset, held by their personnel, worsening in turn the quality and efficiency of their products and processes. To cope with this knowledge loss problem, a novel approach to knowledge formalization is presented that lays the foundations for the realization of a digital platform equipped with interfacing capabilities as well as AI-based knowledge representation and reasoning tools. The paper focuses on evaluating the current scenario, generalizing the problem in the manufacturing context, identifying the main actors who will interact with the platform and proposing a possible procedure for knowledge formalization.

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A Novel Knowledge Formalization Framework to Support Decision-Making in Manufacturing Processes

  • Chiara Cimino,
  • Mattia Torta,
  • Paolo Albertelli,
  • Michele Monno

摘要

Despite the recent efforts towards the introduction of advanced digital and automation technologies in the industry, most of the manufacturing processes are still governed and optimized by human expertise. This fundamental contribution is often in the form of explicit and implicit (or tacit) human knowledge, which is extremely difficult to document, structure and transfer to other people. In this scenario, manufacturing companies run the risk of losing this intrinsic asset, held by their personnel, worsening in turn the quality and efficiency of their products and processes. To cope with this knowledge loss problem, a novel approach to knowledge formalization is presented that lays the foundations for the realization of a digital platform equipped with interfacing capabilities as well as AI-based knowledge representation and reasoning tools. The paper focuses on evaluating the current scenario, generalizing the problem in the manufacturing context, identifying the main actors who will interact with the platform and proposing a possible procedure for knowledge formalization.