Holonic Goal-Driven Scheduling Model for Manufacturing Networks

This study is about the generation of prospective job schedules by manufacturing networks prior to selection of the best manufacturing network for the job. The primary objectives of the manufacturing network selection process were to find networks with the best job lead time (determined by the scheduling process), then those with the best job quality, and finally those with the best job cost. In this paper, forward scheduling of jobs was combined with the popular priority rules namely FCFS, SPT, DDATE and SLACK, and compared with instances when resource slack time reduction algorithm was used. A Computer-Aided-Software-Engineering tool was created to provide the infrastructure that inputted relevant scenarios to the scheduling algorithms and outputted the results in terms of the indicators of lead time, quality, cost and resource slack time. The tool is an implementation of the distributed and holonic manufacturing model and was used to develop the decision making algorithms. These algorithms are presented in this paper. Results show improvements in terms of aforementioned indicators. In the case of SPT priority rule, resource slack time improvements were encouraging.