There is limited scientific and grey literature studying the phenomenon of how the current job profiles are being affected by Industry 4.0 technologies at the operational level. This paper aims to answer the following question: how can the evolution of Workforce 4.0 job profiles be analyzed from a job-task perspective concerning the adoption of smart and digital technologies in manufacturing companies? To this end, it presents a task classification framework addressing three task classification dimensions, namely: (i) routine/nonroutine tasks, (ii) physical/cognitive tasks, and (iii) individual/social tasks, and a job-task analysis method to analyze the evolution of job profiles due to smart or digital technology adoption at the task level. Both artifacts were created using a state-of-the-art review to ground their conceptualization in the most recent knowledge available on work design and job-task analysis methods and were later evaluated and refined using an action-research approach to increase their applicability and usefulness for academic researchers and practitioners. The applicability of the proposed framework and method was demonstrated in an industrial case study discussing the theoretical and managerial contributions of these two artifacts for the development of Workforce 4.0 job profiles. It was concluded that the proposed framework and method are valuable artifacts that contribute to the limited universe of tools available in the literature to first analyze how operators' tasks and roles change concerning the adoption of new Industry 4.0 technologies and then identify the requirements of new skills and competencies for the evolving and emerging job profiles on the shop floor.

(2023). Task Classification Framework and Job-Task Analysis Method for Understanding the Impact of Smart and Digital Technologies on the Operators 4.0 Job Profiles [journal article - articolo]. In SUSTAINABILITY. Retrieved from https://hdl.handle.net/10446/262309

Task Classification Framework and Job-Task Analysis Method for Understanding the Impact of Smart and Digital Technologies on the Operators 4.0 Job Profiles

Cimini, C.;Pinto, R.;Cavalieri, S.
2023-01-01

Abstract

There is limited scientific and grey literature studying the phenomenon of how the current job profiles are being affected by Industry 4.0 technologies at the operational level. This paper aims to answer the following question: how can the evolution of Workforce 4.0 job profiles be analyzed from a job-task perspective concerning the adoption of smart and digital technologies in manufacturing companies? To this end, it presents a task classification framework addressing three task classification dimensions, namely: (i) routine/nonroutine tasks, (ii) physical/cognitive tasks, and (iii) individual/social tasks, and a job-task analysis method to analyze the evolution of job profiles due to smart or digital technology adoption at the task level. Both artifacts were created using a state-of-the-art review to ground their conceptualization in the most recent knowledge available on work design and job-task analysis methods and were later evaluated and refined using an action-research approach to increase their applicability and usefulness for academic researchers and practitioners. The applicability of the proposed framework and method was demonstrated in an industrial case study discussing the theoretical and managerial contributions of these two artifacts for the development of Workforce 4.0 job profiles. It was concluded that the proposed framework and method are valuable artifacts that contribute to the limited universe of tools available in the literature to first analyze how operators' tasks and roles change concerning the adoption of new Industry 4.0 technologies and then identify the requirements of new skills and competencies for the evolving and emerging job profiles on the shop floor.
articolo
2023
Cimini, Chiara; Romero, D.; Pinto, Roberto; Cavalieri, Sergio
(2023). Task Classification Framework and Job-Task Analysis Method for Understanding the Impact of Smart and Digital Technologies on the Operators 4.0 Job Profiles [journal article - articolo]. In SUSTAINABILITY. Retrieved from https://hdl.handle.net/10446/262309
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