Optimum process targeting with error and error-free sampling inspection plan

This thesis focuses on a class of targeting problem. The targeting problem is concerned with the selection of the optimal target mean for a production process. The literature in the area of process targeting focused more on targeting problem with the assumption that inspection is error-free. However, the inspection is error prone. Inspector commits type I and type II errors. These errors are expected to have tremendous impact on the optimal process target. In this thesis, three mathematical models are developed under acceptance sampling with and without error. The first model developed considers the effect of error in the sampling inspection plan on the optimal set point or mean of a filling operation. Sensitivity analysis is conducted to the above developed model to see the effect of error on the solution. The second model developed for the case of three-class targeting problem with quality sampling plan. The third model is the generalized model in which three-class targeting model is considered with inspection error in sampling inspection plan. Sensitivity analysis on errors and cost parameters are performed. Results show that type I and type II errors have tremendous impact on the optimal process parameters. The process mean is forced higher at higher values of type I error thus, reducing the expected profit and the process mean tends to decrease with the increase in the level of type II error. The thesis is concluded by suggesting a number of recommendations for future research.