**1. Introduction**

Through extensive research, we found that nearly half of all major accidents and economic losses were caused by failure of the equipments that are inherently high risk in the petrochemical industry. While most equipment failures were attributed to the current maintenance decision method in the petrochemical industry that was backward and unscientific. Moreover, the conventional maintenance methods could not guide the maintenance personnel to carry out timely maintenance for reliability and safety of the mechanical equipment. As we all known, some maintenance decision models and maintenance methods are widely applied in different industries, such as aerospace, electricity generation, and transportation. But there were no effective decision-making methods or scientific theoretical models to satisfy the special mechanical equipment in the petrochemical industry. So that there are some negative outcomes, including surplus repair, insufficient repair, unreasonable repair intervals, higher maintenance costs, and so on, which were

brought about in their maintenance work [1]. At present, based on the different attention focuses in each industry and the different model and method choices in the maintenance and management process, many research results are related to the maintenance decision method. Bertolini and Bevilacqua [2] proposed a new maintenance decision method to adopt a modified FEMCA analysis and a type of Monte Carlo simulation (MCS) approach based on different important levels of the power plant equipment. Bertolini and Bevilacqua presented a new maintenance decision technique to determine the better maintenance strategies for the critical centrifugal pumps in an oil refinery [3]. A maintenance decision method of a multi-criteria classification of equipment was proposed by Gómez de León Hijes and Cartagena by the analytic hierarchy process (AHP), and oil pipeline projects were effectively evaluated by Dey with a multiple attribute decision-making technique [4, 5]. Chang et al. applied a new maintenance decision model to estimate the production availability in offshore installations [6]. In the study above, some mathematical models, including AHP and MCS, are often used for making maintenance decisions. However, through research and investigation, very few applications of both AHP and MCS exist for making maintenance decisions of the mechanical equipment based on their different risk levels. Moreover, there are some differences between the mechanical equipment in the petrochemical industry and the ones in other industries, such as types and distribution of the failure, the methods and costs of the maintenance, and requirements for reliability and safety, due to the factors of harsh construction environments, complicated working conditions, and extremely high safety requirements in the production process [7].

Thus, these existing maintenance decision models and the maintenance strategies applied to the equipment in other industries are not directly suitable for the mechanical equipment in the petrochemical industry [8]. Therefore, it is necessary to study the maintenance decision method belonging to the mechanical equipment in the petrochemical production process by focusing on the features of its high risks and hazards [9]. A new framework is put forward for making maintenance decisions based on the different risk levels of the mechanical equipment. Finally, through the framework of maintenance decision making, a more reasonable and more effective maintenance strategy can be devised for the mechanical equipment to guarantee the reliability and security of the production operation.

the degree of influence of each factor is more effectively quantified. Therefore, by experts, professional maintenance personnel and field operators through the review pointed out that the risk level of influencing factors according to the situation divided into 3–5 levels, using a 10-point system for scoring. The scoring standards for the 10 influencing factors related to the risk level of mechanical equipment are

**Index Serial number Factors of affecting risk Level** Reliability factor 1 Personnel safety (PS)

Economic factor 5 Production loss (PL)

Monitorability factor 7 Inspectability (IN) Maintainability factor 8 Downtime (DT)

Other factor 10 Service length (SL)

**Serial number Casualty Grading** No impact at all 0 Minor injury 1–3 Seriously injured 4–7 One death 8–9 Mass casualties 10

2 Environment and health (EH) 3 System functions (SF) 4 Failure frequency (FF)

6 Maintenance costs (MC)

9 Maintenance difficulties (MD)

For petroleum and petrochemical companies, ensuring production safety is the

most important issue. Amongthe petroleum and petrochemical companies' mechanical equipment, some object failures will cause casualties to the platform personnel. The PS indicator is divided into five levels, and the scoring standards are

Whether object failures have an impact on the environment and health is receiving much more attention from enterprises, which will cause social public opinion and bring disaster to enterprises. Therefore, considering the degree of the impact of object failures on the environment, the determination of the EH-scoring standard is mainly based on the country and the enterprise environmental safety system and requirements. The EH index is divided into five levels, and the scoring

as follows [11].

*Scoring criteria of PS.*

**Table 1.**

**Table 2.**

*2.1.1 Influence of failure on personnel safety (PS)*

*Influencing factors of risk level about the mechanical equipment.*

*Maintenance Decision Method Based on Risk Level DOI: http://dx.doi.org/10.5772/intechopen.91913*

*2.1.2 Influence of failure on environment and health (EH)*

formulated as shown in **Table 2**.

standards are shown in **Table 3**.

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The remainder of this chapter is organized as follows. In Section 2, the influence factors of the risk level of the mechanical equipment are defined, and their scoring criteria are formulated. In Section 3, an evaluation model for the risk level of the mechanical equipment is established using AHP, and then, the MCS approach is applied to reduce the subjective influences in the scoring process. Then, three MDMETs for the mechanical equipment are obtained based on their categories of different risk levels in Section 4. Finally, Section 5 provides some discussion and conclusions.
