MODELING INFRASTRUCTURE MAINTENANCE SERVICE CONTRACTS WITH APPLICATIONS TO OIL REFINERIES
Restricted (Penn State Only)
- Author:
- Alsanousi, Mowffq
- Graduate Program:
- Industrial Engineering
- Degree:
- Master of Science
- Document Type:
- Master Thesis
- Date of Defense:
- March 17, 2023
- Committee Members:
- Steven Landry, Program Head/Chair
Vittaldas V Prabhu, Thesis Advisor/Co-Advisor
Paul Griffin, Committee Member - Keywords:
- maintenance
shutdowns
refineries
deterministic
integer programming
optimize
procurement - Abstract:
- Infrastructure maintenance reduces equipment failure and unscheduled downtime, extends the useful life and effectiveness of equipment, promotes worker safety, and keeps expenses in check. There is significant interest in applying maintenance methods to oil refineries to reveal the state of infrastructural properties. Total shutdowns at refineries are essential periodic activities that must be implemented on an ongoing basis to carry out necessary maintenance operations. Any delays could have several negative financial and economic consequences, including reduced cash flow, lost sales, unhappy consumers, and the inability to remain competitive in the market. A key element in these activities is preparing short-term maintenance contracts that are submitted to the contracting administration, which then awards them to contractors. These contractors then provide the required services and complete the necessary tasks during the shutdown period. This work develops a deterministic integer programming model to optimize the procurement of maintenance service contracts during a total refinery shutdown based on the concept of clustering. Essential factors related to the required effort and the lack of conflict between contracts are considered. The suggested model will help refinery management overcome the problem of awarding essential contracts to the same contractor to avoid the risk of failure due to any issues related to the contractor. It will also help in monitoring the quality and progress of the work more efficiently because the number of contractors will be reduced.