Decisions, about product acceptance or rejection, based on technical measurement report in ultra-precise and high-tech manufacturing environment is highly challenging as product reaches nal stage after high value-added processes. Moreover, the role of technical personnel in decision making process for inventory models with focus on group-technology manufacturing setup has been considered relatively less. Most of the literature assumes that decisions are perfect and error free. However, in reality, human errors exist in making such decisions based on measurement reports. This paper incorporates human errors into the decision making process focusing on group-technology inventory model, where high value-added machining processes are involved. Therefore, a mathematical model is developed for the optimal lot size considering human errors in the decision making process and the imperfect production process with focus on work-inprocess inventory. Lot size is optimized based on average cost minimization by incorporating human error Type I and human error Type II. Numerical examples are used to illustrate and compare the proposed model with the previously developed models for group-technology high-tech manufacturing setups. The proposed model is considered more flexible as it incorporates imperfection in process with human errors in decision making process.