Author/Authors :
Kang Chang-Wook نويسنده PhD in Statistics from University of Minnesota , Ullah Misbah نويسنده Assistant Professor in Industrial Engineering Department, , Sarkar Biswajit نويسنده currently an Assistant Professor
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.