# Determination of Benefits of the Application of CMMS Database Improvement Proposals
## 1 Introduction
The quality of databases and their impact have been studied by many authors [21; 22; 23; 24], but only for the land industry. This research topic is very limited or non-existent in the maritime industry. The first discovery at the beginning of the research was that a large number of ship databases have very poor data and numerous problems. At this point, the team faced a major problem, a major challenge to solve. Although it was clear that the databases were in poor condition, their conclusion was based only on subjective opinion and personal experience. There was no tool or method in the industry to evaluate CMMS databases, measure their quality, identify areas for improvement, and determine the steps needed to improve database quality. To solve the problem, the team's first task was to develop a universal tool to assess the quality of the CMMS database. The main method used to create the new tool was DQA (Data Quality Assessment), shown in Figure 1, which is based on the idea designed by [PERSON] et al. [25]. DQA is a methodology developed to provide the general principles for the definition of data quality metrics [26] and the method; according to the authors of the cited text ([PERSON] et al. and [PERSON] et al.) [27], the main characteristic of the methodology is that it is tailor-made, created specifically for each task. The solution where \"one size fits all\" in different circumstances cannot be a solution [26]. There are many examples of the DQA methodology in practice and the use of the methodology for different aspects and different types of research [28; 29]. The research team encountered an interesting problem in studying databases to determine how the database improvement proposal program works. In examining 17 vessels from two companies, seven similar improvement requests were found on three vessels, each claiming that there were no manufacturer's maintenance schedules on board and requesting that the company provide them. The number of improvement requests for this type of deficiency is relatively low, mainly due to the fact that both companies only purchase new vessels. This type of issue often occurs when a company buys a used vessel and the previous crew takes all the operating manuals with them, along with the maintenance logs, data, etc., so the new crew starts from scratch, often without the manufacturer's operating manuals. These seven deficiencies were identified during the CMMS system implementation phase and then reported to the company, which worked to correct them. Five of these deficiencies were successfully corrected, while two were not. The reason for the failure to correct this issue was not identified, although the company's SMS was reviewed to determine whether it contained instructions or recommendations for correcting this deficiency. Consequently, in five out of seven cases, the maintenance plan and spare parts were added to the CMMS by copying the data from the manual received, while in two cases, the items were still missing. Reviewing various articles and books, the research team found that no one has yet answered the question of how to create the equipment maintenance plan without using the manufacturer's manual. From the above, it can be concluded that a significant improvement in database quality (read: maintenance and safety) can be achieved if these two database problems are solved. These tasks are the focus of the research team, and this paper presents the potential  
Figure 1: DQA in practice, based on [25]. benefits of these two solutions. The design and methods used to create the Evaluation Methodology for the Ship PMS are described in Section 2, while the methods used to solve the second problem are explained in Section 3. The results and discussions are presented in Section 4, followed by the Conclusion, which summarizes the overall benefits of applying these proposals and highlights the importance of the research.