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Evaluation of smart manufacturing performance using a grey theory-based approach: a case study
Grey Systems: Theory and Application ( IF 2.9 ) Pub Date : 2021-07-16 , DOI: 10.1108/gs-04-2021-0049
Anilkumar Malaga 1 , S. Vinodh 1
Affiliation  

Purpose

The purpose of the article is to report a study on evaluation of smart manufacturing (SM) performance using a grey theory-based approach.

Design/methodology/approach

In total, 30 criteria and 79 attributes for SM performance have been developed. A grey theory-based approach has been used for SM performance evaluation. The grey index has been calculated, and weaker areas have been derived. Performance level of SM has been evaluated using the Euclidean distance approach.

Findings

The SM performance index is found to be (3.036, 12.296). The ideal grey performance importance index (GPII) is obtained as (3.025, 4.875). The level of visibility and traceability, vertical integration, lead time and configuration data espionage and control ability are strong performing attributes. Integration abilities of services and manufacturing systems, ability of self-control, worker and raw material productivity, collaboration among buyers and suppliers and dynamic scheduling are identified as weaker areas, and suggestions for improvement have been derived. SM performance level has been identified as “Good.”

Research limitations/implications

Additional performance measures could be included as a part of evaluation. Practitioners can overcome weaker areas in the early phase. Management achieves confidence and practitioners attain success in implementation of SM in industry through the developed SM performance indexing system.

Originality/value

Identification of SM performance measures and analysis of SM performance is the original contribution of the authors. The developed approach assists practitioners and managers to focus more on specific areas for performance improvement.



中文翻译:

使用基于灰色理论的方法评估智能制造绩效:案例研究

目的

本文的目的是报告一项使用基于灰色理论的方法评估智能制造 (SM) 性能的研究。

设计/方法/方法

总共制定了 30 个标准和 79 个属性来衡量 SM 绩效。基于灰色理论的方法已用于 SM 性能评估。计算了灰度指数,推导出了较弱的区域。SM 的性能水平已经使用欧几里德距离方法进行了评估。

发现

发现 SM 性能指数为 (3.036, 12.296)。理想的灰色性能重要性指数(GPII)为(3.025,4.875)。可见性和可追溯性水平、垂直整合、交货时间和配置数据间谍和控制能力是强大的执行属性。服务和制造系统的集成能力、自我控制能力、工人和原材料的生产力、采购商和供应商之间的协作和动态调度被确定为薄弱环节,并提出了改进建议。SM 性能水平已被确定为“良好”。

研究限制/影响

作为评估的一部分,可以包括额外的绩效指标。练习者可以在早期克服薄弱环节。通过开发的 SM 绩效指标体系,管理层获得信心,从业者在行业实施 SM 方面取得成功。

原创性/价值

识别 SM 性能指标和分析 SM 性能是作者的原创性贡献。开发的方法可帮助从业者和管理人员更多地关注绩效改进的特定领域。

更新日期:2021-07-16
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