Fashion is one of the world’s most important industries, driving a significant part of the global economy representing, if it were a country, the seventh-largest GDP in the world in terms of market size. Focusing on the footwear industry, assembly line balancing and sequencing represents one of the more significant challenges fashion companies have to face. This paper presents the results of a simulation-optimization framework implementation in such industry, highlighting the benefits of the use of simulation together with a finite capacity scheduling optimization model. The developed simulation-optimization framework includes the conduction of a scenario analysis that compares production KPIs (in terms of average advance, delay and resource saturation) related to different scenarios that include or not one or more type of stochastic events (i.e. rush orders and/or delays in the expected critical components delivery date).

Balancing assembly line in the footwear industry using simulation: A case study / Fani V.; Bindi B.; Bandinelli R.. - STAMPA. - 34:(2020), pp. 56-64. (Intervento presentato al convegno 34th International ECMS Conference on Modelling and Simulation, ECMS 2020 tenutosi a deu nel 2020).

Balancing assembly line in the footwear industry using simulation: A case study

Fani V.;Bindi B.;Bandinelli R.
2020

Abstract

Fashion is one of the world’s most important industries, driving a significant part of the global economy representing, if it were a country, the seventh-largest GDP in the world in terms of market size. Focusing on the footwear industry, assembly line balancing and sequencing represents one of the more significant challenges fashion companies have to face. This paper presents the results of a simulation-optimization framework implementation in such industry, highlighting the benefits of the use of simulation together with a finite capacity scheduling optimization model. The developed simulation-optimization framework includes the conduction of a scenario analysis that compares production KPIs (in terms of average advance, delay and resource saturation) related to different scenarios that include or not one or more type of stochastic events (i.e. rush orders and/or delays in the expected critical components delivery date).
2020
Proceedings - European Council for Modelling and Simulation, ECMS
34th International ECMS Conference on Modelling and Simulation, ECMS 2020
deu
2020
Goal 9: Industry, Innovation, and Infrastructure
Fani V.; Bindi B.; Bandinelli R.
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Utilizza questo identificatore per citare o creare un link a questa risorsa: https://hdl.handle.net/2158/1215570
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