Introduction:: The transformation happening globally, though referred by different names and nomenclatures, the overall objective to inspire digitalization and smart practices by reducing human intervention and enhancing machines intelligent to take on the global manufacturing and production to another level of excellence is a proven fact now. However, earlier research has been found, lacking in the strategic approach to evaluate and analyze the I4.0 adoption related risks for its implementation. This ultimately deprived organizations of multitude of the benefits of I4.0 adoption. Objective:: This research proposes a systematic methodology for understanding and evaluating the most evident risks in the context of I4.0 implementation. Method:: The research is mainly based on the inputs from experts/consultants along with robust literature review and researcher’s experience in the area of risks handling. The MCDM methods used for investigation and assessment are Fuzzy AHP and Fuzzy TOPSIS. The outcomes of the study are further validated through sensitivity analysis and real world scenario. Results:: Technical and Information Technology (IT) risks are found to be on the top of the priority list, which needs urgent attention while embarking on I4.0 adoption in the industry and the most important criteria, which needed urgent attention was, Information Security. The paper has also developed the ‘Industry 4.0 Risks Iceberg model’ and systematicaly categoried the challenges into 5 dimensions for easy assessment and analysis. Discussion:: The transformation happening globally, though referred by different names and nomenclatures, the overall objective to inspire digitalization and smart practices by reducing human intervention and enhancing machines intelligent to take on the global manufacturing and production to another level of excellence is a proven fact now. However, earlier research has been found, lacking in the strategic approach to evaluate and analyze the I4.0 adoption related risks for its implementation. This ultimately deprived organizations of multitude of the benefits of I4.0 adoption. Conclusions:: This systematic and holistic study of the I4.0 associated risks can be used to find the most critical and crucial risks based on which the strategies and policies may be modified to harness the best of I4.0. This will not only ensure the returns on investment but also will build the trust in the system. The research would be very beneficial to managers, academicians, researchers and technocrats who would be involved in I4.0 implementation.
Industry 4.0 (I4.0) adoption is becoming predominant in manufacturing industries due to its limitless opportunities. Even though companies are interested in adopting digitalization, several perceived barriers stymied them. However, in the interest of its smooth adoption, these perceived barriers must be addressed urgently. This research aims to analyze the broader spectrum of possible barriers that impede the implementation of I4.0 and converge them into the most prominent inhibitors, further assessing these inhibitors to develop contextual relationships among them. A comprehensive literature review and an empirical research-based survey considering a large sample size are used to address the study’s research objectives. Industry and academia experts’ inputs are considered to derive the I4.0 implementation barrier’s current prominence. The interrelationship among extracted twelve significant inhibitors through principle component analysis (PCA) is modeled using interpretive structural modeling (ISM) to manifest each inhibitor’s direct and indirect effect. Fuzzy matriced’ impacts croise’s multiplication applique’e a’ un classement (MICMAC) analysis is further considered to classify these inhibitors into drivers and dependents. The study depicts inadequate organizational strategies, uncertainty about financial decision making, limited employee readiness, inconsistent legal and government policies, Insufficient IT and automation infrastructure as the most prominent driver inhibitors of the I4.0 adoption. An integrated novel PCA-ISM Fuzzy MICMAC model developed in this research paper is unique and used for the first time to establish the hierarchical relationship among I4.0 implementation inhibitors considering the post-COVID-19 scenario. This study offers practical insights and outcomes that will help researchers, decision-makers, and practitioners in unlocking the potential of I4.0 by dealing with its inhibitors efficaciously.
This research is focused on the identification, assessment, analysis, and evaluation of the impact of the most prominent out of many roadblocks impeding the implementation of Lean-Green and I4.0 practices in manufacturing industries. The research methodology is underpinned by an extensive literature review with expert interventions to make it comprehensive and far-reaching. Further, this exploratory research to address the broad objectives is based on a large sample size, which is validated statistically and empirically for its aptness. A combination of widely used statistical methods is used to converge, assess, analyze, and evaluate the impact of each roadblock individually and in the group on I4.0 implementation in industry. The study prominently depicts lack of organizational leadership, unclear waste management practices, and missing environment-friendly practices as the most prominent roadblocks hindering the progression of Lean-Green and I4.0 adoption. The novel PCA-ISM Fuzzy MICMAC integrated model developed in this research makes this article unique.
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