In this paper, the maintenance optimization problem of multi-component system is considered. It is assumed that the exact cause of system failure might be masked. That is, the exact cause of failure is unknown, and we only know that it belongs to a set called mask set. Both opportunistic perfect preventive maintenance (OPPM) and perfect corrective maintenance are considered. Threshold of OPPM and inter-inspection interval are considered as decision parameters which are optimized using long-run cost rate criteria. The applicability of the proposed maintenance policy is investigated using an illustrative example.
Background: Educational quality assessments are those activities you undertake to demonstrate the accuracy and precision of your monitoring. A good strategy for increasing educational services quality can be achieved by considering the result of SERVQUAL (Gap Analysis) model. Objectives: Quality measurement of educational services that are offered at the Military University of Medical Science is evaluated based on the SERVQUAL model in this study. Methods: This study is a descriptive-analytic study. In this study, the dimensions of the quality of service provided by the SERVQUAL (Gap Analysis) model have been investigated in Five dimensions including tangible, responsiveness, empathy, reliability, and assurance. Data set of this sectional analytical descriptive study coordinates 317 students and 102 professors' observations in the mentioned university. Stratified sampling method, according to the number of students and professors in each faculty (five faculties) and SERVQUAL questionnaire, were used. Descriptive statistics and statistical inferences were done by SPSS23 software. Results: Based on the findings, a negative gap was observed in all dimensions of the model. Empathy dimension (-2.215) had the maximum gap value, while the responsiveness dimension (-2.109) had the minimum gap value based on the student's viewpoint. Moreover, based on the professor's viewpoint maximum gap was related to physical dimension (-1.866) and the minimum gap was related to the responsiveness dimension (-1.292). Unlike professors, students who are studying in different faculties have not same idea regard to services quality. The quality gap can be sufficiently predicted by using the logistic regression model with assuming age as a predictor variable. Professor's viewpoint is not affected by their age and gender. Conclusions: Based on the results, student's and professors' expectations are greater than their perceptions. Empathy and physical dimensions are the priority of the model as they have a positive relationship with the quality.
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