Operational and maintenance planning of production and utility systems in process industries.
| dc.contributor.advisor | Hanak, Dawid P. | |
| dc.contributor.advisor | Leeke, Gary | |
| dc.contributor.author | Zulkafli, Nur Izyan BT. | |
| dc.date.accessioned | 2024-02-21T12:36:19Z | |
| dc.date.available | 2024-02-21T12:36:19Z | |
| dc.date.issued | 2019-01 | |
| dc.description.abstract | Major process industries have installed onsite the utility systems that can generate several types of utilities for meeting the utility requirements of the main production systems. A traditional sequential approach is typically used for the planning of production and utility systems. However, this approach provides suboptimal solutions because the interconnected production and utility systems are not optimised simultaneously. In this research, a general optimisation framework for the simultaneous operational and maintenance planning of utility and production systems is presented with the main purpose of reducing the energy needs and resources utilisation of the overall system. A number of industrial-inspired case studies solved show that the solutions of the proposed integrated approach provides better solutions than the solutions obtained by the sequential approach. The results reported a reduction in total costs from 5% to 32%. The reduction in total costs demonstrate that the proposed integrated approach can result in efficient operation of utility systems by avoiding unnecessary purchases of utility resources and improved utilisation of energy and material resources. In addition, the proposed integrated optimisation-based model was further improved with the presence of process uncertainty in order to address dynamic production environment in process industries. However, integrated planning problems of production and utility systems results to large mixed integer programming (MIP) model that is difficult to solve to optimality and computationally expensive. With this regards, three-stage MIP-based decomposition strategy is proposed. The computational experiments showed that the solutions of the proposed MIP-based decomposition strategy can achieve optimal or near-optimal solutions at further reduced computational time by an average magnitude of 4. Overall, the proposed optimisation framework could be used to integrate production and utility systems for effective planning management in the realistic industrial scenarios. | en_UK |
| dc.description.coursename | PhD in Energy and Power | en_UK |
| dc.identifier.uri | https://dspace.lib.cranfield.ac.uk/handle/1826/20844 | |
| dc.language.iso | en | en_UK |
| dc.publisher | Cranfield University | en_UK |
| dc.publisher.department | SWEE | en_UK |
| dc.rights | © Cranfield University, 2019. All rights reserved. No part of this publication may be reproduced without the written permission of the copyright holder. | en_UK |
| dc.subject | Cleaning | en_UK |
| dc.subject | scheduling | en_UK |
| dc.subject | production | en_UK |
| dc.subject | optimisation | en_UK |
| dc.subject | energy supply chain | en_UK |
| dc.subject | simultaneous | en_UK |
| dc.title | Operational and maintenance planning of production and utility systems in process industries. | en_UK |
| dc.type | Thesis or dissertation | en_UK |
| dc.type.qualificationlevel | Doctoral | en_UK |
| dc.type.qualificationname | PhD | en_UK |