Integrated Production, Maintenance, and Quality Strategy for Production Systems subject to Several Assignable Causes of Process Variation

In this work, we propose a new framework that employed combined and continuous quality monitoring techniques involving statistical process control in conjunction with the AFNOR principles. To jointly optimize maintenance policy according to planned production and inventory decisions that satisfy a randomly failing production system's customer service and quality requirements. We formulate our problem as a stochastic program that considers the interaction between the process reliability state and product quality. To determine the optimal number of imperfect maintenance be planned periodically before, during, and after the process variation. The optimization of maintenance strategy consists to minimize the costs related to preventive imperfect, corrective (minimal repairs) in several cases of different possible scenarios. Sequential optimization techniques are used to find the optimal production and delivery quantities from one period to another. Then we used the output of the first optimization as a constraint to the second optimization model using a PYTHON software. The decision algorithm determined the combination of the optimal decision parameters to achieve the model objectives. The proposed approach is found useful for minimization of the total production cost in consideration of all possible process statuses due to multiple causes.