Journal of Quality Engineering and Management

Abstract Applying preventive maintenance strategies in control chart design, which is one of the main tools in statistical process quality control, not only increases the reliability of the system and reduces its wear and tear, but also reduces the cost of chart design. However, the cost of quality in the classical approach to control chart design, derived from the Crossby football gate philosophy, depends only on whether the quality characteristic is within or outside the control limits. In contrast, using the loss function approach in in-production monitoring activities such as control charts, where quality cost based on Taguchi's concept of social loss quality depends on the amount of quality characteristic deviation from the target value, is a more comprehensive assessment of the process and therefore decisions. It is better guided in planning and management. This paper presents an integrated model of Taguchi loss function, preventive maintenance strategies including incomplete maintenance and early replacement, and economic control diagram design in which the shock model or process failure mechanism has an incremental failure rate. In addition, due to the fact that the data obtained from the measurements related to the output of the production process may not follow the normal distribution or the assumptions of the central limit theorem may not be true for them, it is necessary to study the integrated model in these situations. Normal distribution is necessary. To illustrate the issue, numerical examples based on non-uniform sampling design and Weibull shock model are provided. The adjustment parameters obtained from the integrated model (sample size, sampling intervals, coefficient width of control limits, early replacement time, and cost level and incomplete maintenance time) in addition to significant differences in normal and abnormal conditions, show that with increasing preventive maintenance level, The average design cost will be reduced in both normal and abnormal modes.

Abstract Control chart is one of the basic tools of statistical quality control and monitoring during production of production and service processes. The cost of quality in the classical approach to control chart design depends on whether the quality characteristic is inside or outside the control range. Since the integration of the loss function approach into in-production monitoring activities such as control charts, which is derived from Taguchi's concept of social quality loss, in which the cost of quality depends on the amount of deviation of the quality characteristic from the target value, is a more comprehensive evaluation process. It is better guided in the management strategy. This paper combines the Taguchi loss function and the economic design of the X نمودار control chart. In addition, since the output data of the process may not follow the normal distribution or the assumptions of the central limit theorem may not be true of it, it is necessary to study the integrated model in these situations, in addition to the normal distribution mode. In this regard, the economic design parameters of the integrated model will be compared in the presence of normal and abnormal data, in which, due to the extent of incremental failure rate in production systems, from non-uniform sampling design for sample inspection and Weibull shock model for failure mechanism. The process is used.