Human learning is nowadays taken into account in several research fields, including the assembly line balancing problem. Despite the plethora of contributions and different approaches to solving the problem, the autonomous learning phenomenon, that is to say, the time-dependent or position-dependent reduction of assembly task times due to repetition, should also be explored using stochastic models which, to the best of our knowledge, have been disregarded. In this paper, a well-established cost-based stochastic balancing heuristic has been coupled with a time-dependent learning curve in order to investigate the role of learning in the rebalancing of assembly lines with repetitive tasks. Finally, a real case study has been conducted with the aim of demonstrating the applicability of our proposal.

Stochastic assembly line balancing with learning effects / Lolli, Francesco; Balugani, Elia; Gamberini, Rita; Rimini, Bianca. - 50:1(2017), pp. 5706-5711. ((Intervento presentato al convegno 20th World Congress of the International-Federation-of-Automatic-Control (IFAC) tenutosi a Toulouse, France nel 09-14 July 2017 [10.1016/j.ifacol.2017.08.1122].

Stochastic assembly line balancing with learning effects

Lolli Francesco;Balugani Elia;Gamberini Rita;Rimini Bianca
2017

Abstract

Human learning is nowadays taken into account in several research fields, including the assembly line balancing problem. Despite the plethora of contributions and different approaches to solving the problem, the autonomous learning phenomenon, that is to say, the time-dependent or position-dependent reduction of assembly task times due to repetition, should also be explored using stochastic models which, to the best of our knowledge, have been disregarded. In this paper, a well-established cost-based stochastic balancing heuristic has been coupled with a time-dependent learning curve in order to investigate the role of learning in the rebalancing of assembly lines with repetitive tasks. Finally, a real case study has been conducted with the aim of demonstrating the applicability of our proposal.
20th World Congress of the International-Federation-of-Automatic-Control (IFAC)
Toulouse, France
09-14 July 2017
50
5706
5711
Lolli, Francesco; Balugani, Elia; Gamberini, Rita; Rimini, Bianca
Stochastic assembly line balancing with learning effects / Lolli, Francesco; Balugani, Elia; Gamberini, Rita; Rimini, Bianca. - 50:1(2017), pp. 5706-5711. ((Intervento presentato al convegno 20th World Congress of the International-Federation-of-Automatic-Control (IFAC) tenutosi a Toulouse, France nel 09-14 July 2017 [10.1016/j.ifacol.2017.08.1122].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11380/1152712
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