Situation dependent decision selector for production control in testing and rework cell

This paper presents a production control approach for the testing and rework cell in a dynamic and stochastic computer integrated manufacturing (CIM) system. The proposed situation dependent decision selector (SDDS) observes the status of the system and jobs at every decision point, and makes its three different decisions on dispatching, pre-emption, and dispatching within pre-emption in real time. This paper also develops a new feature selection algorithm for the SDDS. Experimental results show that the SDDS is better than other static control rules and another dynamic control approach with respect to the number of tardy jobs.     

Application of Petri Nets and a Genetic Algorithm to Multi-Mode Multi-Resource Constrained Project Scheduling

Multi-mode and multi-resource constrained scheduling of a project is a complex task. This paper addresses the use of a Petri net as a modelling and scheduling tool in this context. The benefits of Petri nets in project scheduling are discussed. We propose extensions to Petri nets to suit scheduling of activities in a decision CPM. We also propose the use of a P-matrix for token movements in Petri nets. A genetic algorithm is used to find a better solution. Petri-net-aided software including genetic-algorithm-based search and heuristics is described to deal with a multi-mode, multi-constrained scheduling problem with pre-emption of activities.     

Corrective maintenance through dynamic work allocation and pre-emption: case study and application

This case study develops an innovative management and scheduling system for corrective maintenance of machines in a manufacturing facility. The study also involves a comparative evaluation of the proposed and the existing systems under a spectrum of operating conditions. A comprehensive simulation is used to evaluate system performances under a variety of settings which include reliability, service level, and cost consequences. The analysis is based on a full factorial experimental design. In summary, the developed self-regulating management system which involves dynamic work allocation and pre-emption is shown to yield higher machine availability and higher mechanic utilisation even with fewer mechanics. The study also finds that the new system is more streamlined, agile, and robust although it is subject to more-constrained machine reliability and mechanic service time environments. Further, a major reduction of current manpower can still achieve at least 95% machine availability, illustrating the cost effectiveness and efficacy of the developed system. This rule-based corrective maintenance system can be operated in uncertain environments on a real-time basis without additional reformatting costs and provides a competitive measure to deal with managerial issues such as low retention rate for skilled mechanics, highly uneven training levels and pay scales. The financial consequences and gains in strategic advantage with respect to the facility's operational structure are promising after implementation. Moreover, the system developed in this case study represents a meaningful starting point for a more vigorous theoretical research on the bucket brigade system to different functions in industrial and operations management.     

Dynamic production control with dispatching within pre-emption

This paper deals with a production control problem for the testing and rework cell in a dynamic and stochastic computer integrated manufacturing (CIM) system. This research first defines dispatching within pre-emption for an extended form of pre-emption. A dynamic controller called competitive decision selector (CDS) is then modified and extended as CDSplus to handle three different production control decisions; dispatching, pre-emption, and dispatching within pre-emption. It observes the status of the system and jobs at every decision point, and makes its three different decisions in real time. The CDSplus dynamic control shows better performance than static control rules with respect to the number of tardy jobs.     

Optimal maintenance headcount allocation: an application of Chebyshev Goal Programming

In a semiconductor wafer fabrication facility (as well as virtually any type of factory), the allocation of maintenance technicians to tool sets (or clusters of tools) plays a crucial role in the determination of tool set availability. Tool availability, in turn, determines factory capacity and serves to drive factory performance in terms of outs, inventory, cycle time and WIP velocity. With tools now composing 70% or more of the cost of current (i.e. 300?mm wafer) multi-billion dollar facilities, even seemingly slight increases in tool set availability can translate into savings on the order of millions or hundreds of millions of dollars. In this paper, an approach for deriving the allocation of maintenance technicians for this problem by means of Chebyshev Goal Programming is described and illustrated.     

Architecture of a dynamic production controller in CIM enterprise environments

This paper deals with a production control problem for the testing and rework cell in a dynamic and stochastic computer integrated manufacturing (CIM) system. A dynamic controller is designed to handle three different production control decisions; dispatching, pre-emption, and dispatching within pre-emption. The model of this system also helps users deal with a large number of input features in real situations. This paper describes a technical architecture of dynamic production control and design issues of a dynamic production controller. It explains the overall development processes of the system and functional diagrams in order to give readers a design guideline for the dynamic production controller.