Tool replacement policy for one-sided processes with low fraction defective

In most manufacturing industries, tool replacement policy is essential for minimizing the fraction defective and the manufacturing cost. Tool wear is caused by the action of sliding chips in the shear zone, and the friction generated between the tool flank and workpiece. This wear, apparently, is a dominant and irremovable component of variability in many machining processes, which is a systematic assignable cause. As the tool wear occurs in the machining processes, the fraction of defectives would gradually become significant. When the fraction defective reaches a certain level, the tool must be replaced. Therefore, detecting suitable time for tool replacement operation becomes essential. In this paper, we present an analytical approach for unilateral processes based on the one-sided process capability index CPU (or CPL) to find the appropriate time for tool replacement. Accurate process capability must be calculated, particularly, when the data contain assignable cause variation. By calculating the index CPU (or CPL) in a dynamical environment, we propose estimators of CPU (or CPL) and obtain exact form of the sampling distribution in the presence of systematic assignable cause. The proposed procedure is then applied to a real manufacturing process involving tool wear problem, to demonstrate the applicability of the proposed approach.