Optimal production, scheduling, lot-sizing and power generation for a soft drink factory in absence of a power grid
Optimal production, scheduling, lot-sizing and power generation for a soft drink factory in absence of a power grid
Lot-sizing and scheduling has become an important aspect of manufacturing businesses nowadays. The effective and efficient management of scheduling and planning has the potential of reducing production cost which leads to increase in quality of products, which brings about competitive advantage. Lot-sizing and scheduling is a critical success factor especially in developing countries that lack technological infrastructure and resources available in developed countries. Due to the peculiar nature of the issue in Nigeria, the unit commitment problem (UCP) has to added to production planning to include energy considerations.
Inspired by the complexity and the challenges faced by the soft drink industry in Nigeria. The aim of this thesis is to develop mathematical models for production planning that minimises production and backorder cost, evaluate the models under various demand profiles and determine the power needs of the factory under various demand profiles. Secondly, the thesis examines the operational and performance of diesel generators in preparation for model development, develops models that help determine minimum investment and running costs of diesel generators which falls under the unit commitment problem.
The contributions of this thesis brings about development on a academic front by developing mathematical models that combine production planning and unit commitment with real world implications.
A case study of a Nigerian soft drink producing company provides motivation and provides practical importance for the contribution of this thesis in the real world.
University of Southampton
Baba, Abubakar Yusuf
2ff23347-e77f-4857-a498-269c420b73ee
May 2019
Baba, Abubakar Yusuf
2ff23347-e77f-4857-a498-269c420b73ee
Beullens, Patrick
893ad2e2-0617-47d6-910b-3d5f81964a9c
Baba, Abubakar Yusuf
(2019)
Optimal production, scheduling, lot-sizing and power generation for a soft drink factory in absence of a power grid.
University of Southampton, Doctoral Thesis, 180pp.
Record type:
Thesis
(Doctoral)
Abstract
Lot-sizing and scheduling has become an important aspect of manufacturing businesses nowadays. The effective and efficient management of scheduling and planning has the potential of reducing production cost which leads to increase in quality of products, which brings about competitive advantage. Lot-sizing and scheduling is a critical success factor especially in developing countries that lack technological infrastructure and resources available in developed countries. Due to the peculiar nature of the issue in Nigeria, the unit commitment problem (UCP) has to added to production planning to include energy considerations.
Inspired by the complexity and the challenges faced by the soft drink industry in Nigeria. The aim of this thesis is to develop mathematical models for production planning that minimises production and backorder cost, evaluate the models under various demand profiles and determine the power needs of the factory under various demand profiles. Secondly, the thesis examines the operational and performance of diesel generators in preparation for model development, develops models that help determine minimum investment and running costs of diesel generators which falls under the unit commitment problem.
The contributions of this thesis brings about development on a academic front by developing mathematical models that combine production planning and unit commitment with real world implications.
A case study of a Nigerian soft drink producing company provides motivation and provides practical importance for the contribution of this thesis in the real world.
Text
Final_Thesis
- Version of Record
More information
Published date: May 2019
Identifiers
Local EPrints ID: 433185
URI: http://eprints.soton.ac.uk/id/eprint/433185
PURE UUID: 98a67d46-b78a-4e12-a473-be0ba174674d
Catalogue record
Date deposited: 09 Aug 2019 16:30
Last modified: 16 Mar 2024 03:59
Export record
Contributors
Author:
Abubakar Yusuf Baba
Download statistics
Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.
View more statistics