A knowledge based hierarchical reliability allocation (HIRAL) approach for shipboard systems

Reliability has become a greater concern in shipboard systems due to increasing amount of technology level, system complexity, and multiple design demands. Enhancement of the shipboard system’s reliability ensures safe and continuous operation onboard a ship. To enhance the reliability of the shipboard system, it is essential to identify each individual component’s reliability. Within this scope, the onerous task of reliability allocation analysis enhances the reliability of shipboard systems through the optimization of component-based designs, construction, and operations. This study proposes a hybrid reliability allocation methodology based on a hierarchical structure with the integration of an analytic hierarchy process (AHP), data envelopment analysis (DEA), and feasibility of objectives (FOO) methods. The proposed methodology provides reliability allocation analyses for systems with any number of components. The study also examines the usefulness of the adaptation of AHP-DEA into reliability allocation analysis. To demonstrate the applicability of the proposed methodology, a case study on the steering gear system is presented.

A Time-Variant Reliability Analysis Method Based on the Stochastic Process Discretization under Random and Interval Variables

In practical engineering, it is a cost-consuming problem to consider the time-variant reliability of both random variables and interval variables, which usually requires a lot of calculation. Therefore, a time-variant reliability analysis approach with hybrid uncertain variables is proposed in this paper. In the design period, the stochastic process is discretized into random variables. Simultaneously, the original random variables and the discrete random variables are converted into independent normal variables, and the interval variables are changed into standard variables. Then it is transformed into a hybrid reliability problem of static series system. At different times, the limited state functions are linearized at the most probable point (MPP) and at the most unfavorable point (MUP). The transformed static system reliability problem with hybrid uncertain variables can be solved effectively by introducing random variables. To solve the double-loop nested optimization in the hybrid reliability calculation, an effective iterative method is proposed. Two numerical examples and an engineering example demonstrate the validity of the present approach.

A hybrid reliability-centered maintenance approach for mining transportation machines: a real case in Esfahan

PurposeThe purpose of this study is to propose a hybrid reliability-centered maintenance (RCM) approach for mining transportation machines of a limestone complex, a real case in Esfahan, Iran.Design/methodology/approachCriteria for selecting critical machines were collected within literature and selected by decision-makers (DCs), and critical machines have been identified using the preference ranking organization method for enrichment of evaluations (PROMETHEE). Also, multi-criteria decision-making (MCDM) methods were used in addition to failure mode, effects and criticality analysis (FMECA) for selecting and prioritizing high-risk failures as well as optimizing the RCM performance. More specifically, the criteria of severity, detectability and frequency of occurrence were selected for risk assessment based on the previous studies, and were weighted using the analytic hierarchy process (AHP) method. Also, the technique for order of preference by similarity to ideal solution (TOPSIS) has been applied to prioritize failures' risk. Finally, the critical failures were inserted in the RCM decision-making worksheet and the required actions were determined for them.FindingsAccording to the obtained values from PROMEHTEE method, the machine with code 739-7 was selected as the first priority and the most critical equipment. Further, based on results of TOPSIS method, the failure mode of “Lubrication hole clogging in crankpin bearing due poor quality oil,” “Deformation of main bearing due to overwork” and “The piston ring hotness due to unusual increase in the temperature of cylinder” have the highest risks among failure modes, respectively.Originality/valueRCM has been deployed in various studies. However, in the current study, a hybrid MCDM-FMECA has been proposed to cope with high-risk failures. Besides, transportation machineries are one of the most critical equipment in the mining industry. Due to noticeable costs of this equipment, effective and continuous usage of this fleet requires the implementation of proper maintenance strategy. To the best of our knowledge, there is no research which has used RCM for transportation systems in the mining sector, and therefore, the innovation of this research is employment of the proposed hybrid approach for transportation machineries in the mining industry.