Human errors incorporation in work-in-process group manufacturing system

Abstract

KEYWORDSHuman error Type I; Human error Type II; Group-technology; Optimal lot size.Abstract. 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 exible as it incorporates imperfection in process with human errors in decision making process.

Production models of multiple products using a single machine under quality screening and reworking policies

“…Another extension of the model would involve including the sampling inspection plans (Khan et al, 2011b;Rezaei, 2016). As human resources are involving in the inspection process, and in fact, it is impossible to eliminate them from the manufacturing process, future studies can consider human errors during the inspection process (Kang et al, 2017). Moreover, another extension to study the property of inspection can be done by evaluating the performance of inspections (Kang et al, 2018).…”

Optimal Production Inventory Decision with Learning and Fatigue Behavioral Effect in Labor Intensive Manufacturing

“…Other authors have also considered human errors and customer satisfaction in the production inventory decision. Kang et al [33] incorporated human errors into the decision making process focusing on group technology inventory model. Cheng et al [34] assumed that the inspection process was carried out by the vendor and the defective items were disposed in multiple batches.…”