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Scheduling of a semiconductor wafer fabrication system (SWFS) is complicated due to its re-entrant product flow, high uncertainties in operations, and rapidly changing products and technologies; thus dispatching rules have been widely used for real-time scheduling because they can provide a very quick and pretty good solution. However, deciding how to select appropriate rules is very difficult and seldom tackled. This paper describes an approach into the evaluation and optimization of dispatching rules by integrating the simulation and response surface methodology (RSM). In order to implement the proposed approach, a dynamic bottleneck dispatching (DBD) policy is designed, in which bottlenecks are detected in a timely way and adaptive dispatching decisions are made according to the real-time conditions. In addition, two case studies are carried out to demonstrate the approach. One case compares DBD to regular rules, such as CR + FIFO, EDD, SRPT, SPT, SPNB and Justice, a bottleneck dispatching method. Simulation results show that the DBD policy is superior to the other six methods. In another case study, the parameters of DBD are optimized by RSM and desirability function, and the result proves that the optimized DBD method can get even better performance. [ABSTRACT FROM AUTHOR]

In recent years, as an emerging concept in industry, agile manufacturing has attracted considerable attention, combining virtual manufacturing cells to construct new manufacturing systems to respond to the changing market needs, especially in nonlinear processes. In this paper, a multi-stage cell formation methodology, which can help select appropriate resources and form the VCs, is presented. First, appropriate resources for completing production tasks are selected by a LP model considering the available capacity and the costs. In order to form VC in a logical mode, parts having alternative product process routings as multi-functional machines are analyzed by a resource element approach. Furthermore, some routing-based heuristic rules are introduced to optimize the candidate VCs in the form of resource elements. Finally a case study is used to illustrate the detailed formation methodology. [ABSTRACT FROM AUTHOR]

With the development of computer technology, the anticipated extensive use of virtual production systems (VPSs) in the future has encouraged its intensive research recently. However, a limited amount of research has been made on its efficient control. In this paper, a hybrid supervisory control approach based on autonomy and coordination is proposed for VPSs to enhance the efficiency of control. Its three primary advantages are: (1) application of supervisory control theory, which can efficiently obtain the desired property through closed-loop feedback; (2) use of hybrid control structure combining hierarchical and distributed ones, which can avoid the exponential explosion of state space due to synthesis of models; and (3) utilization of autonomous and coordination mechanisms, which can keep the balance of local quick response and global optimization. A case study is used to illustrate how to implement the proposed approach, and is finally analyzed and simulated by an integrated tool named UPPAAL. [ABSTRACT FROM AUTHOR]

In this paper, an infrastructure for adaptive production control in an agile manufacturing environment is proposed. With this infrastructure, Virtual Production Systems (VPSs), each of which takes care of the production of a specific customer ordered product, can be dynamically and flexibly constructed. This can be achieved logically by product workflow and physically by the resources in one or more manufacturing systems, e.g. job shops. To respond to changes and disturbances to a VPS, architecture for the adaptive controller of a VPS is designed based on adaptive control principles and Temporised Object-Oriented Petri Nets with Changeable Structure (OPNs-CS) modelling. A case study is used in this paper to illustrate how adaptive production control of VPS functions can be conducted to cope with changes and disturbances to the production system. [ABSTRACT FROM AUTHOR]