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Batch sizing and scheduling on a volatile production line through the usage of linear optimisation

Mini Dissertation (B Eng. (Industrial and Systems Engineering))--University of Pretoria, 2018.

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Main Author: Hugo, Jeanne-Marie
Format: Thesis
Language:English
English
Published: University of Pretoria. Faculty of Engineering, Built Environment and Information Technology. Dept. of Industrial and Systems Engineering 2019
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access_status_str Open Access
author Hugo, Jeanne-Marie
author_browse Hugo, Jeanne-Marie
author_facet Hugo, Jeanne-Marie
author_sort Hugo, Jeanne-Marie
collection Thesis
dc_rights_str_mv © 2018 University of Pretoria. All rights reserved. The copyright in this work vests in the University of Pretoria. No part of this work may be reproduced or transmitted in any form or by any means, without the prior written permission of the University of Pretoria.
description Mini Dissertation (B Eng. (Industrial and Systems Engineering))--University of Pretoria, 2018.
format Thesis
id oai:repository.up.ac.za:2263/68342
institution University of Pretoria (South Africa)
language English
English
last_indexed 2026-06-10T12:37:40.523Z
license_str Other — see source repository
provenance_str_mv Harvested via OAI-PMH from UPSpace — University of Pretoria Institutional Repository
publishDate 2019
publishDateRange 2019
publishDateSort 2019
publisher University of Pretoria. Faculty of Engineering, Built Environment and Information Technology. Dept. of Industrial and Systems Engineering
publisherStr University of Pretoria. Faculty of Engineering, Built Environment and Information Technology. Dept. of Industrial and Systems Engineering
record_format dspace
source_str UPSpace — University of Pretoria Institutional Repository
spelling oai:repository.up.ac.za:2263/68342 Batch sizing and scheduling on a volatile production line through the usage of linear optimisation Hugo, Jeanne-Marie Mini-dissertations (Industrial and Systems Engineering) Mini Dissertation (B Eng. (Industrial and Systems Engineering))--University of Pretoria, 2018. This report examines and determines the optimisation solution to a complex batch sizing problem. A mix of low- and high-volume production causes complexity in batch sizing and scheduling at Mecalc Manufacturing. Prototyping and a volatile demand forecast only adds to the intricacy. After in-depth analyses of the production problem, it is determined that the main restriction of the optimal solution is parameter control. Various Industrial Engineering techniques that relate to batch sizing and operations research are studied in the report. With the control and determination of the production variables being the most crucial factor, the literature study is summarised into three main models. The first model that is considered, is an economic manufacturing quantity (EMQ) with random breakdowns (Lin & Kroll 2007). Stochastic programming is then studied, from which the next two models originate – The recourse model with a multi-stage problem and the probabilistically constrained model. These two are very similar in results, working with production and variable scenarios. After comprehensive comparisons between the models researched, it is decided to formulate both stochastic-type models. The reason for this is the unpredictability of Mecalc’s production parameters and data. Both models are programmed on Python giving results that are not satisfactory for Mecalc’s unique production process. The multi-stage model is chosen as the base for the solution model and adjustments are made accordingly. The final solution formulation is clearly laid out with all its elements, explanations, and interpretations. Variables are analysed, and complexities are determined. The data frames that function as the input, are explained with some of the variables’ simulations. Validation of the solution and the sensitivity analysis thereof is evaluated nearing the end of the report. Some analyses of which resulted in determining the parameters in which the model works and doesn’t work. Variables such as inventory quantities, maximum batch sizes, and reliability factors are assessed. Finally the report is concluded with the proposed implementation with some recommendations for Mecalc. 2019-01-31T13:03:26Z 2019-01-31T13:03:26Z 2018 2018 Mini Dissertation http://hdl.handle.net/2263/68342 en en © 2018 University of Pretoria. All rights reserved. The copyright in this work vests in the University of Pretoria. No part of this work may be reproduced or transmitted in any form or by any means, without the prior written permission of the University of Pretoria. PDF application/pdf University of Pretoria. Faculty of Engineering, Built Environment and Information Technology. Dept. of Industrial and Systems Engineering
spellingShingle Mini-dissertations (Industrial and Systems Engineering)
Hugo, Jeanne-Marie
Batch sizing and scheduling on a volatile production line through the usage of linear optimisation
title Batch sizing and scheduling on a volatile production line through the usage of linear optimisation
title_full Batch sizing and scheduling on a volatile production line through the usage of linear optimisation
title_fullStr Batch sizing and scheduling on a volatile production line through the usage of linear optimisation
title_full_unstemmed Batch sizing and scheduling on a volatile production line through the usage of linear optimisation
title_short Batch sizing and scheduling on a volatile production line through the usage of linear optimisation
title_sort batch sizing and scheduling on a volatile production line through the usage of linear optimisation
topic Mini-dissertations (Industrial and Systems Engineering)
url http://hdl.handle.net/2263/68342
work_keys_str_mv AT hugojeannemarie batchsizingandschedulingonavolatileproductionlinethroughtheusageoflinearoptimisation