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Towards industry 5.0: A multi-objective job rotation model for an inclusive workforce

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  • Battini, Daria
  • Berti, Nicola
  • Finco, Serena
  • Zennaro, Ilenia
  • Das, Ajay

Abstract

The new Industry 5.0 paradigm complements the well-known Industry 4.0 approach by specifically driving research and innovation to facilitate the transition to sustainable, human-centric and resilient industry. In the manufacturing context, workers' diversity in terms of experience, productivity and physical capacity represents a significant challenge for companies, especially those characterized by high staff turnover and manual processes with high workload and poor ergonomics. In seeking to address such challenges, this research adopts a human-centric perspective to define new flexible job arrangements by developing a new multi-objective job rotation scheduling model. The proposed model is unique in that it aims to achieve multiple job assignment objectives by simultaneously considering different socio-technical factors: workers' experience, physical capacity and limitations, postural ergonomic risks, noise and vibration exposure, and workers' boredom. The model's implementation in real environments can be supported by new sensor-based technologies that collect data on workers' efficiency, ergonomic scores and task performance and enable workers to participate in measuring perceived fatigue and boredom. The primary goal of our model is to find the most appropriate assignment of job and individual-flexible rest-break plan for each worker. The authors test the model application in an industrial setting. Useful managerial insights emerge and prescriptive recommendations are provided.

Suggested Citation

  • Battini, Daria & Berti, Nicola & Finco, Serena & Zennaro, Ilenia & Das, Ajay, 2022. "Towards industry 5.0: A multi-objective job rotation model for an inclusive workforce," International Journal of Production Economics, Elsevier, vol. 250(C).
    • Handle: RePEc:eee:proeco:v:250:y:2022:i:c:s092552732200202x
    DOI: 10.1016/j.ijpe.2022.108619
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    References listed on IDEAS

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    Cited by:

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    2. Severino, Gonzalo & Rivera, José & Parot, Roberto & Otaegui, Ernesto & Fuentes, Andrés & Reszka, Pedro, 2024. "Workforce and task optimization to guarantee oxygen bottling under a COVID-19 pandemic scenario: A Chilean case study," International Journal of Production Economics, Elsevier, vol. 271(C).
    3. Mukherjee, Abheek Anjan & Raj, Alok & Aggarwal, Shikha, 2023. "Identification of barriers and their mitigation strategies for industry 5.0 implementation in emerging economies," International Journal of Production Economics, Elsevier, vol. 257(C).
    4. Aldrighetti, Riccardo & Battini, Daria & Ivanov, Dmitry, 2023. "Efficient resilience portfolio design in the supply chain with consideration of preparedness and recovery investments," Omega, Elsevier, vol. 117(C).
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    6. Ranasinghe, Thilini & Senanayake, Chanaka D. & Grosse, Eric H., 2024. "Effects of stochastic and heterogeneous worker learning on the performance of a two-workstation production system," International Journal of Production Economics, Elsevier, vol. 267(C).

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