For continuous operating units such as petrochemical plants, the production loss due to downtime is high, and the economic profitability is conditioned by the implementation of suitable maintenance policy that could increase the availability and reduce the operating costs. In this paper, a preventive maintenance plan approach is proposed for a multi-component series system subjected to random failures, where the cost rate is minimized under general lifetime distribution. The expected total cost is given by corrective and preventive costs, which are related to the components, and by the common costs related to the whole system, especially the production loss during system shutdown. When the system is down, either correctively or preventively, the opportunity to replace preventively non-failed components is considered. A solution procedure based on Monte Carlo simulations with informative search method is proposed and applied to the optimisation of the component replacement for the hydrogen compressor in an oil refinery.
For continuous operating units, the production loss is often very large when unexpected shutdown occurs. Their economic profitability implies the implementation of suitable maintenance policy which could increase the availability and reduce the operating costs. To underline the consequences of unavailability, it can be mentioned that production losses in chemical plants can range from $5000 to $100,000 per hour (Tan & Kramer, 1997). For refineries, the total production losses soar to millions of dollars (Nahara, 1993). In addition, the safety requirements enforce to decrease the failure probability, on a very low level in order to avoid disastrous consequences.
The preventive maintenance (PM) is often carried out to prevent or to slow down the deterioration processes. PM is a scheduled downtime, usually periodical, in which a well-defined set of tasks (e.g., inspection, replacement, cleaning, lubrication, adjustment and alignment) are performed. In oil refining facilities, the problems associated with part replacement are more concerned than other routine maintenance activities such as cleaning and lubricating, from the PM scheduling point of view. This is because the direct costs due to part failure and replacement are usually very high, and the impact of different replacement intervals on the overall maintenance cost is often very sensitive and significant, in addition to the safety requirements.
In a series system, the one-by-one preventive replacements of components improve the global system reliability on the account of its availability, which would be largely penalized, because of frequent shutdowns for component replacements. For multi-component systems, an optimal maintenance policy must take into account the interactions between the various components of the system. These interactions are of three types (Thomas, 1986): economic dependence, structural dependence and stochastic dependence. We are mainly concerned by the economic dependence reflecting the influence of component operation/maintenance costs on the overall system costs; in this case, saving in costs or downtime can be achieved when several components are jointly maintained.
The objective of this paper is to develop a preventive/corrective/opportunistic maintenance plan for a multi-component system subjected to high production losses and economic dependence. In the next section, we review the relevant literature, particularly that dealing with multi-component systems. In Section 3, we provide the cost formulation and the maintenance models in several cases; an algorithm allowing for combined preventive/corrective/opportunistic replacement of the system components is also presented. In Section 4, the proposed approach is illustrated by a simple example with two components, allowing to explain the formulation interest and to verify the convergence of the solution procedure. An industrial application is provided in Section 5, where the results show the effectiveness of the proposed approach for practical systems.
The proposed maintenance plan is based on opportunistic multi-grouping replacement optimisation for multi-component systems. As in continuous operating units such as chemical plants, the production losses are very high. Therefore, the maintenance optimisation has the potential for substantially reducing the operating costs and for increasing corporate profit by increasing availability and production. The proposed approach is based on the analysis of individual components, according to the well-known age-based model. The optimisation algorithm allows rearranging the optimal individual replacement times in such a way that all component times become multiple of the smallest one to allow for joint replacements. In this way, the times obtained by the multi-grouping approach do not give individual optimality conditions, but satisfies the optimal cost regarding the whole system.
The proposed algorithm is a numerical procedure, where the life cycles are simulated and the optimal solution is numerically searched. The large number of random simulations by Monte Carlo method, which is very useful in solving nonlinear and complex optimisation problems, ensures the stability of the estimates and guarantees the solution convergence to the optimal one. As all significant combinations are considered, the optimal solution cannot be missed. The most important facts revealed in this study are: (1) the effectiveness of the opportunistic policy in cost saving for multi-component systems and the capacity of the Monte Carlo simulations in solving these complex problems, and (2) the evident grouping configuration, which is sometimes adopted by maintenance managers, is not necessary cost-effective; therefore, an optimisation procedure must be considered.
It is well known that in process units such as oil refineries and chemical plants, the production loss is proportional to the downtime and the costs induced are very high. It seems to be more suitable to relax the assumption of the instantaneous maintenance actions to highlight the effect of this variable on the grouping configuration; this topic is currently under consideration.
