John Reyes1,2, Josefa Mula1 and Manuel Díaz-Madroñero1
1Universitat Politècnica de València, Research Centre on Production Management and Engineering (CIGIP), Alcoy, Spain
2Universidad Técnica de Ambato, Ambato, Ecuador
jreyvas@doctor.upv.es; fmula@cigip.upv.es; fcodiama@cigip.upv.es; johnpreyes@uta.edu.ec
1. Introduction
In today’s world, industrial SCs face formidable challenges to efficiently establish tools that lower costs and are competitive in a digitalized environment. Supply chain management (SCM) has been used for planning and controlling physical and information flows, internal and external logistics activities, and processes with other companies, and also for addressing the relationship developed and the processes shared with both customers and suppliers [1]. In this context, a number of approaches like lean manufacturing (LM) and, more recently, Industry 4.0 (I4.0), have been developed to help manufacturers to fulfill these objectives [2]. To date, very few authors have studied the I4.0 technologies that most favor the implementation of LM tools to improve organizational performance, especially with disruption risks like pandemics or other unexpected crises [3–5]. This paper aims to determine the relations between I4.0 technologies and LM practices to provide a lean supply chain management 4.0 (LSCM 4.0) framework. This analysis also provides theoretical arguments that can help researchers and practitioners to develop resilient SCs in situations with disruptive risks because they may affect performance.
2. Review Methodology
The systematic literature review strategy proposed by Denyer [6] was applied in this study. It is a specific methodology that locates existing studies, selects and evaluates contributions, analyzes and synthesizes data, and reports evidence to reach conclusions on the questions posed to fulfill the research objective. This paper reviewed articles about SCM and LM, combined with I4.0 to develop a flexible and resilient organization. First, research questions were defined: what is the current LSCM knowledge state?; which I4.0 technologies provide the most support for the implementation of LM tools?. The Scopus and Web of Science (WoS) databases were chosen for the review.
3. Conclusions
A general LSCM 4.0 construct is proposed, based on identified theoretical evidence. The use of lean tools supports the change in the organizational culture toward a flexible resilient organization. I4.0 technologies, such as IoT, cloud computing, artificial intelligence (AI) and simulation, are fundamental for the digital transformation of supply chains (SCs) and well support the implementation of LM tools like Kanban and Just-in-time. This article highlights the influence of key I4.0 technologies on an SC’s planning. In this context, technological innovation allows SCs to continue with a constant process of continuous improvement because AI and blockchain applied with enterprise social networks are being implemented for better real-time visibility, predictive outage analyses, cost reduction and customer satisfaction. The findings of this study contribute to the relevant existing literature to identify particular aspects of how SCs’ digitization positively enhances the adoption of Kanban, just in time (JIT), value stream mapping (VSM), total productive maintenance (TPM) and the 5S lean operations practices. The present findings offer a valuable theoretical contribution to identify ways to integrate I4.0 technologies. SC survival issues were not studied in-depth, but are recognized as crucial issues after the spread of the COVID-19 pandemic [4]. For SC users and researchers, the results contribute a decision-making approach in a digitization context and, at the same time, to reduce ten waste types, even when facing possible disruptions. Finally, the quantitative validation of the LSCM 4.0 conceptual proposal is a future research line.
Acknowledgements. This research leading to these results received funding from the: European Union H2020 Program under grant agreement No 958205 “Industrial Data Services for Quality Control in Smart Manufacturing (i4Q)”; Spanish Ministry of Science, Innovation and Universities under grant agreement RTI2018-101344-B-I00 “Optimisation of zero-defects production technologies enabling supply chains 4.0 (CADS4.0)”; and PhD grant from Technical of Ambato University.
References
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