A study on operator allocation aiming at the skill improvement for cell production system

Abstract

The cell manufacturing system of a labor concentration type is still in the important position of the manufacturing industry at this stage. Since an operator's skill is greatly related to productivity in labor concentration type cell productions, the operator's effective training is important. On the other hand, when operators learn and acquire the multi-skill tasks, the level of difficulty in their mastery depends on the contents of target operations, so a sufficient plan for training is required. In this study, the main objective is the rapid improvement of operator's skill. Therefore, after classifying operator's skills about all the operation tasks, we try to optimize the task allocation in training mode, and evaluate its validity quantitatively.

A study on operator allocation and scheduling method considering demand fluctuations in cell manufacturing systems

“…Here, capacity for work is expressed according to the task by "skill index" adapting a skill map [7]. When a job standard time of task k in the product j is STjk and practical operation time of the operator i is set to ETjki, the value of skill index sjki is calculated by equation (1).…”

Effect of Instructions on Parts' Positions during an Assembly Task on Efficiency and Workload

“…Workspace configuration, task scheduling, and workers' education are investigated for a few workers in cell production. To schedule on-the-job training, Haraguchi et al [3] introduced a skill index and demonstrated that labor allocation based on this index efficiently improved the skill level of labors in computer simulations. Tanimizu et al [4] proposed two types of learning or familiarization, namely operational familiarization and knowledge familiarization, and demonstrated that the acquisition of knowledge during tasks shortens the assembly time effectively.…”