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Using dynamic programming and unsupervised learning to optimize material flow in assembly line  supermarket: A case study of Volvo Powertrain at Skövde
Högskolan i Skövde, Institutionen för informationsteknologi.
2019 (Engelska)Självständigt arbete på avancerad nivå (masterexamen), 20 poäng / 30 hpStudentuppsats (Examensarbete)
Abstract [en]

Replenishment is an important process in automotive industries. It is the process by which parts required at assembly lines are stored and organized in assembly lines supermarket. Over many years replenishment have been done with the aim of positively impacting the varying demand frequency of articles in multi flows mixed-model assembly lines (MMALs) operating in just-in-time (JIT) fashion. However, a series of successive replenishment actions have negative impacts on the number of reallocation movements of parts within volume flows of supermarkets especially within a context of multi-flows supermarkets (MFSs). The cost of movements of parts within the supermarket has not been taken into consideration in previous replenishment methods. This is a significant problem since both un-optimized reallocation movements, and articles misplacement resolutions lead to production halts which cost assembly plants valuable time and money. Therefore, this research study proposes a replenishment method that optimizes flow of material within multi-flow assembly lines supermarkets and hence reduces the cost due to reallocation movement of multi-flow assembly lines supermarkets. The proposed method has been evaluated in the context of Volvo automobile engine assembly plant in Skövde. The proposed replenishment method has been evaluated by conducting an experiment using real-world data for the assembly plant in context. Performance metrics such as accuracy, F1-score, precision, sensitivity, and specificity were used to demonstrate the utility and validity of the proposed method. The evaluation results showed that the proposed method for optimizing material flow in supermarkets performed better than the existing method. In addition to utility, the proposed method provides contribution to knowledge by providing means for the industry to adopt replenishment method that takes into consideration the cost of reallocation movements of the parts within the supermarket. 

Ort, förlag, år, upplaga, sidor
2019. , s. 66
Nyckelord [en]
Replenishment, Supermarkets, Optimization, Design science research, Multi-flows, Assembly lines, MMALs
Nationell ämneskategori
Systemvetenskap, informationssystem och informatik Datavetenskap (datalogi)
Identifikatorer
URN: urn:nbn:se:his:diva-17597OAI: oai:DiVA.org:his-17597DiVA, id: diva2:1346364
Externt samarbete
Volvo Powertrain Skövde
Ämne / kurs
Informationsteknologi
Utbildningsprogram
Data Science - masterprogram
Handledare
Examinatorer
Tillgänglig från: 2019-08-29 Skapad: 2019-08-27 Senast uppdaterad: 2019-08-29Bibliografiskt granskad

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Institutionen för informationsteknologi
Systemvetenskap, informationssystem och informatikDatavetenskap (datalogi)

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