## 2 Literature Review
[13] expressed the importance of reducing machine failures to have an uninterrupted operation and emphasized the poor efficiency of the conventional preventive maintenance method, which sometimes causes unnecessary costs because it does not consider the current state of the equipment. In this study, the researchers developed a dynamic preventive maintenance model based on the reliability of the current of the equipment rather than the conventional fixed maintenance. In addition, they proved in a case study that the proposed model can reduce the unavailability of the equipment and increase the efficiency of its operation throughout its useful life. [PERSON] and [PERSON] [14] considered the decision-making process in maintenance strategy for water distribution systems. The probability of having a functional network system upon demand was calculated based on the current level of components reliability based on which maintenance need could be prioritized in low reliability areas. They also took into account the severity of impact on the entire system from the failure of every component. In addition, a report was published by Stiftelsen for industriell og teknisk forskning (SINTEF) along with the cooperation of multiple global organizations in the oil and gas industry [15]. It mainly provides an estimation with regards to the reliability data for selected equipment normally used in control systems within the oil and gas industry. The reliability data can support organizations to analyze reliability levels in line with the international standards IEC 61508 and IEC 61511. Generally,the study took the reliability approach to investigate the root causes of failures in equipment and to analyze the effect level in terms of failure on demand and critical safety failures. The biggest documented and published project by oil and gas exploration and production organization evaluated, assessed, recorded, and analyzed failures of a huge number of piping components and mechanical machines used in these industries over a defined period of time. The project considered both the operational and calendar time in the assessment of the failure rates that took place in the normal operating lifecycle rather than the infant mortality or burn-in phase. The main purpose of this project is to provide the stated industry with a comprehensive reliable data to ensure cost-effective and safe process improvement. To minimize the effect of variation in the collected failure data, we considered a 90% uncertainty interval for the lower and upper limits. Additionally, the failure modes of each component are categorized based on their severity; allowing the readers to understand the likelihood of a critical failure in each of these components [16]. The previous two studies, SINTEF and Offshore Reliability Data (OREDA), are the best documented sources of oil and gas equipment reliability data due to their practical nature, which came from the collaboration of a number of large operation organizations in that field. The data are also reliable because of the wide range of involvement within the operation organizations and outside of these organizations. Some of the components in the oil and gas transportation systems are highly reliable, which makes it extremely hard to estimate a failure rate for them. These two studies fill this gap by applying long periods of tests to these particular components. Furthermore, a study has been conducted by [PERSON] et al. [17] to improve the long-term preventive maintenance decisions using a reliability prediction approach. A case study of water pipelines was developed to collect real failure data of two main segments: exposed pipelines and buried pipelines. The case study was developed on the basis that each one of the two pipeline segments had its own failure distribution, which helps one come up with an overall system reliability. In addition, the study investigates the improvement of the preventive maintenance on the system reliability to develop a cost-effective system maintenance strategy.