OPERATION READINESS LEVEL (ORL) ASSESSMENT USING MULTI CRITERIA DECISION MAKING (MCDM) METHODS

Open Access
- Author:
- Kocaman, Veysel
- Graduate Program:
- Industrial Engineering
- Degree:
- Master of Science
- Document Type:
- Master Thesis
- Date of Defense:
- None
- Committee Members:
- Dr Soundar Kumara, Thesis Advisor/Co-Advisor
Soundar Rajan Tirupatikumara, Thesis Advisor/Co-Advisor - Keywords:
- ORL
MCDM
AHP
LINMAP
DEA
Lp Metrics
Borda Count
Readiness
Ranking
Scaling
Normalization - Abstract:
- Achieving and maintaining the highest operation readiness level (ORL) is the back bone of strong and effective armed forces which is the main component of national security. Operations Research (OR) methods, invented and enhanced by military itself, play a key role in evaluation and determination of ORL in order to ensure the impartial and robust assessment. This study is aimed to be one of the most practical models in readiness forecasting mainly depending upon multi criteria decision making (MCDM) which considers the decision makers (DMs) into account. The primary focus of this study is to establish a suitable and feasible assessment methodology based on MCDM methods in order to derive Operational Readiness Level (ORL) through Material Readiness Level (MRL). In this study, one of the most prevalent mechanisms is researched and tried to be optimized. In this kind of mechanism, every single warship periodically (e.g. once a week) applies a routine complete check on the reliability and the operability of her material systems and assigns a credit score in a given range for each main system and a subsystem according to the relevant technical documents. After summing up the credits to get an overall score for each main system, she sends a routine report to her immediate headquarters periodically in a given format unless otherwise stated. However, problems, such as a failure in value estimation of a subsystem or biased evaluation, may occur due to the simplicity of the procedure and arbitrary rating methods. Various MCDM methods in literature are used in this study in order to find the most feasible ones for our case. For scaling and normalizing the sample generated data, Linear Normalization and Ideal Values methods are utilized, whereas AHP, Borda Count, LINMAP, DEA and Lp Metrics are implemented for weighting each subsystem through questionnaires and ranking the war ships. After analyzing the results and evaluating the methods one by one for our case, it is observed that LINMAP and DEA methods are nonviable for our case while AHP, Borda Count and Lp Metrics are quite practical and produced more consistent results. At the end, it is concluded that the most suitable combination would be Borda Count via Ideal Values considering the practicality and consistency of the methodologies mentioned.