交互式制造系统分析:迈向基于绩效的评估方法

IF 2.5 Q2 ENGINEERING, INDUSTRIAL IET Collaborative Intelligent Manufacturing Pub Date : 2022-09-14 DOI:10.1049/cim2.12063
Jose Antonio Mulet alberola, Irene Fassi
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引用次数: 0

摘要

当前的制造系统被迫在可持续因素下满足最动态的市场需求。然而,不仅技术改革将解决这一挑战,而且为了充分满足社会需要,在高度相互作用的系统中分析人的作用仍然是决定性的,并遵循社会可持续的办法。为了从两个agent的性能角度充分提取最大价值,需要仔细分析、捕获和提升agent在工作环境中的主要附加价值。环境塑造了特定的操作或任务,从而根据个人需求驱动最终结果。此外,仍然缺乏一种可能有助于对这些基于性能的交互进行适当评估的方法。贡献的重点是在整体观点下定义一种新的以人为中心的方法,以分析基于性能的交互,并定义适当的指标和度量,以帮助评估制造领域中的人类系统交互。该方法应用于一个案例研究,以指导从业人员使用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

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Analysis of interactive manufacturing systems: Towards a performance-based assessment methodology

Current manufacturing systems are forced to meet the most dynamic market demands under sustainable factors. However, not only technical transformations will address the challenge but, to fully cover social needs, the analysis of the human role in highly interactive systems is still decisive, following a socially sustainable approach. To fully extract the most from both agents under a performance point of view, the main added value of agents in the work environment needs to be carefully analysed, captured, and boosted. The context shapes a specific operation or task, which consequently drives the final outcome according to individual necessities. Furthermore, a methodology that potentially helps a proper assessment of these performance-based interactions is still missing. The contribution focusses on the definition of a novel human-centric methodology under a holistic point of view to analyse performance-based interactions and to define appropriate indices and metrics that helps assessing the human-system interactions in the manufacturing domain. The methodology is applied in a case study to guide practitioners with its use.

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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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