Gadekar Rimalini, Sarkar Bijan, Gadekar Ashish
Mechanical Engineering Department, Government Polytechnic, Gondia, Maharashtra India.
Production Engineering Department, Jadavpur University Kolkata, Kolkata, West Bengal India.
Ann Oper Res. 2022;318(1):189-249. doi: 10.1007/s10479-022-04828-8. Epub 2022 Jul 26.
Global corporate giants are keen to adopt Industry 4.0 (I4.0) owing to its continuous, impactful, and evident benefits. However, implementing I4.0 remains a significant challenge for many organizations, mainly due to the absence of a systematic and comprehensive framework. The risk assessment study is key to the flawless execution of any project is a proven fact. This paper aims to develop a KPIs-based sustainable integrated model to assess and evaluate risks associated with the I4.0 implementation. This research paper has developed the I4.0 risks evaluation model through fifteen expert interventions and an extensive systematic literature review. This research, based on sixteen KPIs evaluates six risks impacting the organization's decision to adopt I4.0. Initially, the Fuzzy Decision-Making Trial and Evaluation Laboratory method is used to map the causal relationship among the KPIs. Further, the additive ratio assessment with interval triangular fuzzy numbers method is used to rank the risks. The study revealed that information technology infrastructure and prediction capabilities are the most crucial prominence and receiver KPIs. Simultaneously, technological and social risks are found to be highly significant in the I4.0 implementation decision-making process. The developed model meticulously supports the manufacturer's, policymaker, and researchers' viewpoint toward I4.0 implementation in the present and post COVID-19 pandemic phases in manufacturing companies. The comprehensive yet simple model developed in this study contributes to the larger ambit of new knowledge and extant literature. The integrated model is exceptionally based on the most prominent risks and a wider range of KPIs that are further analyzed by aptly fitting two fuzzy MCDM techniques, which makes the study special as it perfectly takes care of the uncertainties and vagueness in the decision-making process. Hence, this study is pioneering and unique in context to I4.0 risks prioritization aiming to accelerate I4.0 adoption.
全球企业巨头热衷于采用工业4.0（I4.0），因为它具有持续、显著且明显的优势。然而，对许多组织来说，实施I4.0仍然是一项重大挑战，主要原因是缺乏系统全面的框架。风险评估研究是任何项目完美执行的关键，这是一个已被证实的事实。本文旨在开发一个基于关键绩效指标的可持续集成模型，以评估与I4.0实施相关的风险。本研究论文通过十五次专家干预和广泛的系统文献综述，开发了I4.0风险评估模型。本研究基于十六个关键绩效指标，评估影响组织采用I4.0决策的六种风险。最初，使用模糊决策试验与评价实验室方法来绘制关键绩效指标之间的因果关系。此外，采用区间三角模糊数的加法比率评估方法对风险进行排序。研究表明，信息技术基础设施和预测能力是最关键的突出和接收关键绩效指标。同时，在I4.0实施决策过程中，技术和社会风险被发现具有高度重要性。所开发的模型精心支持制造商、政策制定者和研究人员在当前以及新冠疫情后制造业公司I4.0实施阶段的观点。本研究中开发的这个全面而简单的模型为新知识和现有文献的更广泛范围做出了贡献。该集成模型特别基于最突出的风险和更广泛的关键绩效指标范围，通过恰当地拟合两种模糊多准则决策技术对其进行进一步分析，这使得该研究具有特殊性，因为它完美地处理了决策过程中的不确定性和模糊性。因此，本研究在I4.0风险优先级排序方面具有开创性和独特性，旨在加速I4.0的采用。
