Schedule coordination of parallel machines in large manufacturing systems
Date Issued
2014
Date
2014
Author(s)
Lin, Yue-Lan
Abstract
Assigning jobs to parallel machines is a classic problem in manufacturing and computer science. In many manufacturing environments, machines availability and job orders might change dynamically. The aim of reactive scheduling is mainly to revise a previous schedule. Reactive scheduling requires fast methods and knowledge rules in response to unexpected events. This research presents some analytical rules on the dominance relationships on job mixings under Poisson job arrival and a method for estimating machine workload when there are alternative machines. It is found that uneven mixings of job types are better than even mixings in reducing setup time. An iterative procedure is shown to converge in workload balancing and the resultant makespan. Workload can be estimated with accuracy without running time-consuming optimization programs. Applications are demonstrated with numerical examples. Large factories that manufacture high mixes of complex products are usually composed of a number of workstations and the manufacturing control function is divided between a factory and a workstation level. While the management of individual workstations tends to focus on efficient machine utilization, the top-level factory management is usually concerned with job flow control. Integration of operation decisions between the two organization levels can recover productivity loss stemming from disparate objectives. This research also presents a method for aligning the job batching decision for serial-batch machines that require machine setup to serve stochastic arrivals of multiple job types. The effect of batching on flow time is first analyzed and closed-form formulas for the probability of setup are derived for a time-based batching policy. The misalignment in batching decisions at the two organization levels is next illustrated. Finally, a state-based performance measure is designed for decision integration. Numerical simulation and regression are used to test the proposed method. The main contribution of this paper is on developing a distributed vertical alignment method which compliments the approaches of horizontal coordinated scheduling and vertical functional decomposition in architecture design of distributed manufacturing control.
Subjects
Job-machine assignment
Reactive planning
Setup reduction
Meta rules
Load balancing,
Distributed manufacturing control,
Serial-batch production
Type
thesis
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