Considering workers' features in manufacturing systems: a new job-rotation scheduling model. Issue 2 (2020)

• Record Type: Journal Article
• Authors: Finco, Serena; Zennaro, Ilenia; Battini, Daria; Persona, Alessandro
• Is Part Of: IFAC-PapersOnLine. Volume 53:Issue 2(2020)
• Page Start: 10621
• Page End: 10626
• Publication Date: 2020
• Subjects: Ageing workforce -- costs -- job rotation -- human skills -- mathematical model; Automatic control -- Periodicals; 629.805
• DOI: 10.1016/j.ifacol.2020.12.2819
• Languages: English
• ISSNs: 2405-8963

Abstract

Abstract: The European manufacturing industry is entering a new era in which working populations are ageing. The E.U. had set itself strategy objectives to increase the labour market participation of older workers. However, practical limits arise, and a complete re-thinking of operation management strategies and manufacturing systems design and management is needed. As underlined in several works, older workers have not the same physical capacity as the younger ones. Consequently, they are more subjected to develop work-related musculoskeletal disorders despite younger colleagues. On the other hand, they might present higher skill levels in doing some specific tasks due to their considerable experience. Thus, they can be employed in teaching or training younger or unskilled workers. Starting from these initial considerations, in this paper, we develop a new age-oriented job rotation scheduling model. Both physical capacity and experience level aspects are included in the mathematical model aiming to maximize daily productivity. We quantify physical fatigue by using the energy expenditure rate and the maximum acceptable energy expenditure. Then, the rest allowance concept is evaluated according to the workers' age and the shift work duration. Variable execution times of each job according to the workers' experience level and mandatory training activities for unskilled workers are also taken into consideration. Finally, a numerical case derived by a real application is proposed to validate the model and demonstrate benefits we can achieve by applying it.