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Assessing the uptake of Industry 4.0 technologies: barriers to their adoption and impact on quality management aspects

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Date
2023-03-14
Author
Laskurain Iturbe, Iker
Arana Landín, Germán
Landeta Manzano, Beñat
Jiménez Redal, Rubén
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  Estadisticas en RECOLECTA
(LA Referencia)

International Journal of Quality & Reliability Management 40(10) : 2420-2442 (2023)
URI
http://hdl.handle.net/10810/65150
Abstract
Purpose Industry 4.0 technologies have the potential to improve the quality management performance of industrial companies. The paper analyses the influence of Industry 4.0 technologies on quality management aspects, but also the barriers that slow down the deployment of each Industry 4.0 technology and limit each impact. Design/methodology/approach The impact of Industry 4.0 technologies on quality management aspects (QMAs) is a heterogeneous and multidimensional phenomenon dependent on the current context, a holistic multiple case study has been applied. Twenty-six case studies were carried out on eight Industry 4.0 technologies, with a minimum of two cases per technology. These cases were selected from the 168 projects presented in the four editions of the BIND 4.0 program, winner of the 14th edition of the European Enterprise Promotion Awards. The cases were selected based on a preliminary survey of 124 project managers. Subsequently, individual case and cross-case analyses for each technology were carried out. Finally, these results were confirmed by interviews with a minimum of two customers per Industry 4.0. Findings Results show that the adoption of Industry 4.0 technologies positively affects QMAs. Specifically, the influences received by “process control” and “customer satisfaction” from all the Industry 4.0 technologies studied are medium to high. In addition, barriers from the “economic and legal” and “workers” categories exert greater influence than the barriers pertaining to “organization”, “lack of training and information” and “technology”. Research limitations/implications The main limitation is the generalizability of the findings of qualitative studies (ergo the case study). In this sense, statistical generalizability, characteristic of a random sample, is not intended in this paper. Therefore, the use of multiple case studies has been chosen to reinforce analytical generalizations with corroborated evidence (literal replication). Practical implications Managers interested in adopting Industry 4.0 technologies Ts should plan the implementation process to minimize the impact of these barriers and optimize the results for each stakeholder. In this sense, the barriers that concern the workers should be managed. It is the responsibility of managers to inform and explain how data will be handled, and how privacy concerns will be addressed. Social implications It is essential to explain and convince workers about the need for a renewal of tasks. New types of jobs (i.e. the use of robots) will involve training for workers to enable their integration alongside the new technologies. Originality/value This paper addresses two under-researched areas that are essential when defining strategies in the industrial business context. Firstly, the paper analyses the influence of each I40 T on each QMA. Secondly, it analyses the barriers to adopt that slow down the rollout of each I40 T and limits each impact.
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