A framework and prototype system in support of workflow collaboration and knowledge mining for manufacturing value chains. Issue 1 (9th January 2023)

• Record Type: Journal Article
• Authors: Qin, Bo; Peng, Peng; Zhang, Jian; Wang, Hongwei; Ma, Ke
• Is Part Of: IET collaborative intelligent manufacturing. Volume 5:Issue 1(2023)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2023-01-09
• Subjects: computer supported cooperative work -- knowledge graph -- knowledge mining -- manufacturing value chains; Production management -- Periodicals; Production engineering -- Periodicals; Production management; Production engineering; Electronic journals; Periodicals; 658.5
• DOI: 10.1049/cim2.12073
• Languages: English
• ISSNs: 2516-8398

Abstract

Abstract: In the field of industrial design and manufacture, computer‐supported collaborative work (CSCW) systems have been widely deployed for better teamwork. However, the traditional CSCW systems have a main drawback in effectively processing and utilising knowledge across different industrial workflows. To bridge this gap, we propose a framework for collaboration between members across the manufacturing value chains to increase efficiency and reduce duplication in team cooperation. The framework contains three parts, namely workflow, knowledge mining, and services. Specifically, the workflow part provides a collaborative environment for multiple users. The knowledge mining part, as the core of the framework, extracts in‐context knowledge from workflows. The part of services can interact with users with different users in each workflow, including information recommendation they need in the future or information retrieval they want to know from other workflows. Furthermore, we develop a prototype system for supporting multiple value chains collaboration to verify the effectiveness and efficiency of the framework. Abstract : This paper aims to deal with the gap in effectively processing and utilising knowledge across different industrial workflows through a proposed knowledge mining‐based collaborative framework. A prototype system is constructed to verify the effectiveness and efficiency of the framework.