Date of Award

Spring 2012

Document Type

Thesis

Degree Name

Master of Science (MS)

Department

Mechanical & Aerospace Engineering

Program/Concentration

Mechanical Engineering

Committee Director

Han P. Bao

Committee Member

Sebastian Bawab

Committee Member

Alok K. Verma

Call Number for Print

Special Collections; LD4331.E56 K368 2012

Abstract

Ships are maintained at regular intervals in a scheduled manner. But there may be unexpected problems which necessitate immediate or as-soon-as-possible attention. These kinds of problem are handled through some type of Unplanned Maintenance Scheduling (UMS).

In a recent paper, Bao, Mittal and Dean I presented a method for planning and scheduling maintenance jobs using lean maintenance principles. In this method, the priority levels of the jobs are initially identified through a Maintenance Priority Evaluation Matrix (MPEM), then conflicts between the jobs because of personnel, tooling and spatial uses are taken into account concurrently to force a re-prioritization of the sequence of the jobs. The job scheduling process has been facilitated by a C++ program for determining the schedule of each job by an iteration process involving a number of novel ideas. While this method is innovative, it suffers from a number of weaknesses which makes it less useful for practical applications. One of the major weaknesses has to do with the way it handles a set number of jobs in one single planning session. Any new jobs which turn up during this planning phase cannot be incorporated in the initial plan and, therefore, have to wait until all jobs in this initial plan have been executed.

This thesis presents a dynamic scheduling method that can overcome the problem mentioned above. Furthermore, it introduces an easy way to add new jobs via an Excel spreadsheet as well preparing the output data for insertion into any popular planning and scheduling software tool such as MS Project™. The use of MS Project enhances significantly the usefulness of the algorithm initially developed by Bao et al and prepares the application of this algorithm to real-life scheduling problems of unplanned maintenance work.

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DOI

10.25777/5gtx-7g94

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