The fashion industry is characterized by a fragmented production environment. The sector requires organizations to demonstrate a high degree of flexibility so they can respond to customer needs. Consequently, mixed-model lines are relevant, in which multiple models are produced by alternating production between different batches without any set-up. Optimizing the sequencing of mixed-model assembly lines is crucial to ensuring their flexibility and efficiency. A sequencing problem involves the determination of the best sequence in which products should be introduced into production in order to meet the planned demand and achieve the objectives. Due to the operational level of decision-making for sequencing problems, they have a short-term planning horizon, as they involve considerations for plant floor activities and daily production results. Optimization tools often require high computational power to find the absolute optimum. The purpose of this research is to present a flexible solution to the sequencing problem. A case study has been conducted based on first-hand observations of a company that manufactures bags as part of a luxury group. In this case, it is the preparation department that requires the most attention, like a mixed-model line. There were two stages to the implementation of the proposed case study model. The first phase involved the implementation of an Excel spreadsheet to define an optimized sequence using the evolutionary algorithm solver to optimize the department's mixed-model line. As part of the second phase, the simulation model was implemented and validated using real-life data. Consequently, the proposed sequencing model was validated, and the current situation was compared with the TO - BE scenario. Based on the results obtained from the implemented optimization tool, the sequence proposed by the tool improves the department's performance compared to the current situation in terms of productivity (+7,9%) and utilization (+5,7%).
Optimization for mixed model assembly lines: a case study in the fashion industry
Fani V.;
2023-01-01
Abstract
The fashion industry is characterized by a fragmented production environment. The sector requires organizations to demonstrate a high degree of flexibility so they can respond to customer needs. Consequently, mixed-model lines are relevant, in which multiple models are produced by alternating production between different batches without any set-up. Optimizing the sequencing of mixed-model assembly lines is crucial to ensuring their flexibility and efficiency. A sequencing problem involves the determination of the best sequence in which products should be introduced into production in order to meet the planned demand and achieve the objectives. Due to the operational level of decision-making for sequencing problems, they have a short-term planning horizon, as they involve considerations for plant floor activities and daily production results. Optimization tools often require high computational power to find the absolute optimum. The purpose of this research is to present a flexible solution to the sequencing problem. A case study has been conducted based on first-hand observations of a company that manufactures bags as part of a luxury group. In this case, it is the preparation department that requires the most attention, like a mixed-model line. There were two stages to the implementation of the proposed case study model. The first phase involved the implementation of an Excel spreadsheet to define an optimized sequence using the evolutionary algorithm solver to optimize the department's mixed-model line. As part of the second phase, the simulation model was implemented and validated using real-life data. Consequently, the proposed sequencing model was validated, and the current situation was compared with the TO - BE scenario. Based on the results obtained from the implemented optimization tool, the sequence proposed by the tool improves the department's performance compared to the current situation in terms of productivity (+7,9%) and utilization (+5,7%).I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
