## 1 Introduction
[14] indicated a means for the integration of RAMS and risk analysis as a guide in maintenance policies for the recurrence of failures and maintenance costs to be reduced. It is believed that RAM is one of the most crucial fields for profitability improvement [15]. Furthermore, RAM will be instrumental in an increased environmental performance and safety, a vital element in maintenance of function, by contributing real and up to date database which concerns the genuine condition of the system. The RAM analysis in any industrial system is different because of various factors, e.g., the operating conditions of the system, the training level of the employees (operators, technicians, and managers), from the existing maintenance policy, etc. As a result, the system is particular and requires special know-how to solve it. This study may, therefore, be a valuable tool for product manufacturers wishing to develop their design and operation production lines. [PERSON] et al. [16] explained the possibility and prerequisites to execute RAM simulation in industrial practice, through developing, implementing, and employing a RAM simulation model for the GE Plastics Lexan factory in Bergen op Zoom, Netherlands. [PERSON] and [PERSON] [17] highlighted the role of RAM features to enhance the performance of engineering plans. [PERSON] et al. [18] submitted a general framework for reliability analysis not only for non-repairable but also repairable components, which is characterized by stationary or non-stationary failure times, and deemed censored data. A case study involving a light commercial vehicle manufacturing system is extended for framework validation purposes. Failure time modeling was noted by [PERSON] et al. [19] for transmission belt failures at a pulp producing factory by examining external factors and multiple failure modes. A complete methodology of reliability analysis by examining stated factors has been presented. Operational reliability and evaluation-based maintenance planning for an automotive manufacturing system werestudied by [PERSON] et al. [20]. [PERSON] and [PERSON] [21] purposed a new approach for reliability analysis of a steam boiler system by expert judgment method. [PERSON] et al. [22] defined reliability in relation to technical means of transport and to illustrate an original solution leading to the determination of the expected fitness time of the available vehicle fleet, using the example of a selected military unit.Zeng et al. [23] studied reliability analysis by considering common cause failure. Historical reliability data (failure and repair data) are the primary inputs for a dependable design and efficient maintenance program [24]. The accumulation of failure and repair data is vital for the analysis of the reliability and availability of the system to acquire unfailing and precise results [25; 26]. In addition, historical and or benchmarking data, pertained to failure systems and repair patterns, are challenging to procure and they are often enough unreliable due to varied practical restrictions [27]. However, in view of the uncommon event of components, human oversight, and economic restraints, it is challenging to acquire large quantity of data from any specific factory for a lengthy period of time. Furthermore, companies are focused on the manufacturing procedure instead of the collection of failure database. In addition, various companies are withdrawn to issue their data owing to the competition [28]. Consequently, it is rather challenging to accumulate precise and reliable failure data. The insufficient amount of quantitative data is one of the critical concerns driving researchers to implement qualitative methods for reliability analysis [29]. The application of reliability engineering to oil and gas pipeline systems was investigated by [PERSON] et al.