A framework and prototype system in support of workflow collaboration and knowledge mining for manufacturing value chains

IF 2.5 Q2 ENGINEERING, INDUSTRIAL IET Collaborative Intelligent Manufacturing Pub Date : 2023-01-09 DOI:10.1049/cim2.12073
Bo Qin, Peng Peng, Jian Zhang, Hongwei Wang, Ke Ma
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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.

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一种支持制造价值链工作流协作和知识挖掘的框架和原型系统
在工业设计和制造领域,计算机支持的协同工作(CSCW)系统已被广泛应用于更好的团队合作。然而,传统的CSCW系统在有效地处理和利用不同工业工作流程的知识方面存在一个主要缺点。为了弥合这一差距,我们提出了一个制造价值链成员之间合作的框架,以提高效率并减少团队合作中的重复。该框架包括工作流、知识挖掘和服务三个部分。具体来说,工作流部分为多个用户提供了一个协作环境。知识挖掘部分作为框架的核心,从工作流中提取上下文知识。服务部分可以与每个工作流中不同用户的用户进行交互,包括他们将来需要的信息推荐或他们想要从其他工作流中了解的信息检索。此外,我们开发了一个支持多价值链协作的原型系统,以验证该框架的有效性和效率。
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来源期刊
IET Collaborative Intelligent Manufacturing
IET Collaborative Intelligent Manufacturing Engineering-Industrial and Manufacturing Engineering
CiteScore
9.10
自引率
2.40%
发文量
25
审稿时长
20 weeks
期刊介绍: IET Collaborative Intelligent Manufacturing is a Gold Open Access journal that focuses on the development of efficient and adaptive production and distribution systems. It aims to meet the ever-changing market demands by publishing original research on methodologies and techniques for the application of intelligence, data science, and emerging information and communication technologies in various aspects of manufacturing, such as design, modeling, simulation, planning, and optimization of products, processes, production, and assembly. The journal is indexed in COMPENDEX (Elsevier), Directory of Open Access Journals (DOAJ), Emerging Sources Citation Index (Clarivate Analytics), INSPEC (IET), SCOPUS (Elsevier) and Web of Science (Clarivate Analytics).
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