Lean manufacturing and Internet of Things - a synergetic or antagonist relationship?

Anosike, Anthony, Alafropatis, Konstantinos, Garza-Reyes, Jose Arturo, Kumar, Anil, Luthra, Sunil and Rocha-Lona, Luis (2021) Lean manufacturing and Internet of Things - a synergetic or antagonist relationship? Computers in Industry. ISSN 0166-3615 (In Press)

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Abstract / Description

This paper explores the relationship between five LM methods (JIT, TPM, Autonomation, VSM and Kaizen) and three IoT technologies (RFID, WSN and Middleware) and the implications that arise from their combination. Four hypotheses and four complimentary research questions were formulated and tested. 136 responses were obtained through a questionnaire survey and analysed using descriptive statistics, 2-Sample proportion, Kruskal-Wallis, ANOVA and Pairwise comparison tests. The findings indicate that IoT can significantly improve the operational performance of manufacturing organisations. The findings advocate that all LM methods, apart from Kaizen, benefit from improved effectiveness by combining them with IoT. The results suggest that this can be attributed to the general perception about IoT, which despite the support and benefits it provides to people, is seen to be reducing human involvement whereas Kaizen is seen to be more people-focused. Improvements in information flow, decision-making and productivity were also found to be the most important motivations and benefits of combining LM methods with IoT. The findings of this research can be used by LM organisations that wish to embark into the new digitalised manufacturing era and businesses seeking to improve their performance through the combination of traditional efficiency-based methods and I4.0 technologies.

Item Type: Article
Uncontrolled Keywords: lean manufacturing; Internet of Things; Industry 4.0.
Subjects: 600 Technology > 650 Management & auxiliary services
Department: School of Social Sciences and Professions
Depositing User: Anil Kumar
Date Deposited: 07 Apr 2021 10:27
Last Modified: 20 Jul 2021 09:39
URI: http://repository.londonmet.ac.uk/id/eprint/6509

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