International Journal of Industrial Engineering & Production Research

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CCC-r control chart is a monitoring technique for high yield processes. It is based on the analysis of the number of inspected items until observing a specific number of defective items.  One of the assumptions in implementing CCC-r chart that has a significant effect on the design of the control chart is that the inspection is perfect. However, in reality, due to the multiple reasons, the inspection is exposed to errors. In this paper, we study the economic-statistical design of CCC-r charts when the inspection is imperfect. Minimization of the average cost per produced item is considered as the objective function. The economic objective function, modified consumer risk, and modified producer risk are simultaneously considered, and then the optimal value of r parameter is selected.

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The subjects of reliability acceptance sampling plans and failure-censored life tests have usually been investigated from the viewpoint of statistical properties; indeed, few researchers have shed light on the economic aspects of these issues. In this research, a constrained mathematical model is developed to optimally design a reliability sampling plan under failure censoring life testing. Minimizing the expected total cost (ETC) involved in the sampling and life testing is considered as the objective function of the model. Ensuring the producer’s and the consumer’s risks is taken into consideration as the constraint of the model. To minimize the ETC, the model optimally determines three decision variables including the total number of the items put to the life test, the number of the failed items to terminate the test, and a criterion to make decisions about the acceptance or rejection of the lot. Examples are provided and analyses are conducted to gain some insight regarding the model performance. 

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Condition-based maintenance (CBM) is a well-known maintenance cost minimization strategy in which maintenance activities are performed based on the actual state of the system being maintained. The act of combining maintenance activities for different components is called opportunistic maintenance or maintenance clustering, which is known to be cost-effective, especially for multi-component systems with economic dependency. Every operating system is subject to gradual degradation which ultimately leads to system failure. Since each level of degradation can be represented by a state, every system can be modeled as a multi-state structure. The state of a system can be estimated through condition monitoring, albeit with uncertainty. The majority of studies in the field of maintenance planning are focused on preventive perfect maintenance operations such as replacement. But in practice, most of the maintenance operations are imperfect because of time, technology, and resource limitations. In this paper, we present a CBM clustering model that factors in uncertainty in alerting and lifetime distribution and considers the possibility of using the imperfect maintenance approach. This model is developed for a system with three levels of warning (Signal, Alert, Alarm), which combines inspections and condition monitoring to avoid unnecessary inspections and thereby achieve better cost-efficiency. Our analysis and results provide a general view of when and how to cluster maintenance activities to minimize maintenance costs and maximize system availability. Numerical investigations performed with MATLAB show that clustering CBM activities can result in as much as 80% cost saving compared to No clustering.