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Decision Support for new Process Design via Discrete-event Simulation
University of Skövde, School of Engineering Science.
University of Skövde, School of Engineering Science.
2019 (English)Independent thesis Basic level (degree of Bachelor), 20 credits / 30 HE creditsStudent thesis
Abstract [en]

As a result of the technical breakthrough of modern age, manufacturing organisations are put through immense pressure to continually improve their internal processes with the purpose of economic growth in order to stay competitive in the global market. Thus, making trial and error obsolete in the real world systems, in relation to calculated decision making. This thesis aims to facilitate the decision making basis for the partner companies’ future production design by measuring its expected productivity with the purpose to further strengthen the collaboration with the customer, by the use of discrete-event simulation.AB Furhoffs Rostfria is a family-owned company with its base in Skövde that manufactures and pro-cesses stainless steel products and specialises in three central departments, plumbing, kitchen, and subcontracting products. This thesis focus is within the production of heat shields in the department of subcontracting products as they are projecting an annual increase of 20%.The project was initialised with a pre-study phase that includes the theoretical framework, covering all main subjects to be presented along with analysing relevant literature studies for valuable insight into previous studies within the same field. Following a method and execution phase was carried out coher-ently with creating a simulation model and data collection. Different scenarios in the simulation model have been presented to the partner company along with wastes that have been observed within the production flow during Gemba.The different scenarios in the simulation model included, for instance, the production of both bigger and smaller batch sizes for each variant to analyse how that factor correlates with the product lead time and to also find out what the most optimal batch sizes would be for the respective variant in order to build full pallets. The future state production was evaluated and the results reduced the mean lead time by roughly 59% compared to the current state production.

Place, publisher, year, edition, pages
2019. , p. 54
National Category
Production Engineering, Human Work Science and Ergonomics
Identifiers
URN: urn:nbn:se:his:diva-18422OAI: oai:DiVA.org:his-18422DiVA, id: diva2:1427925
External cooperation
AB Furhoffs Rostfria
Subject / course
Automation Engineering
Educational program
Manufacturing Engineer
Supervisors
Examiners
Available from: 2020-05-04 Created: 2020-05-04 Last updated: 2020-05-04Bibliographically approved

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School of Engineering Science
Production Engineering, Human Work Science and Ergonomics

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16171819202122 22 of 22
CiteExportLink to record
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  • apa
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Output format
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