Morvarid Derakhshan Andisheh Journal of Quality Engineering and Management 3134-0849 6 3 2016 10 22 A generalized integrated model of incomplete maintenance strategies, early replacement and Taguchi loss function in the economic design of X ̅ control diagram for declining processes A generalized integrated model of incomplete maintenance strategies, early replacement and Taguchi loss function in the economic design of X ̅ control diagram for declining processes 158 167 66164 FA Mohammad Bamenimoghadam Professor, Allameh Tabatabai University, Department of Statistics, Tehran, Iran Mojtaba Aghajanpour Faculty of Mathematics and Statistics, Allameh Tabatabai University, Tehran, Iran Journal Article 2018 07 20 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. 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. https://www.pqprc.ir/article_66164_05a22bc5d471ce277a5e9b234081d475.pdf