Penalty Function-Based Two-Level Hybrid Shop Floor Control System

Abstract

Although several hybrid shop floor control architectures have been proposed in the literature, varying degrees of autonomy of subordinate controllers and their effects on supervisory level performance have not been studied. In this paper, we present a new hybrid control architecture with two levels, where the autonomy of subordinate agents changes adaptively. The penalty function in the architecture represents the degree of negative impact on performance that will result from changing the original schedule. When a disturbance occurs, the disturbance agent invokes rescheduling at the appropriate level depending on the threshold disturbance level. The subordinate agents execute tasks based on the schedule from the supervisory agent in the absence of disturbances; or else revise the original schedule optimally with regard to the supervisory level performance (via penalty function) and the disturbance before executing the tasks. We present math programming formulations, quantitative metrics to indicate the disturbance level and the levels of autonomy. The proposed architecture is illustrated using a job shop problem and is then tested with various other problems. Note to Practitioners-In a hybrid shop floor control system, the objective of global system performance conflicts with the objective of a timely response to local disturbances. For a given disturbance, there is a need to compare the cost (e.g., computation time) associated with supervisory level rescheduling against the potential improvement in system performance that this rescheduling can provide. If the cost of rescheduling is higher, rescheduling at the subordinate level will be appropriate. Otherwise, rescheduling at the supervisory level will be appropriate. In this paper, manufacturing scheduling problems of various complexities are used to discuss the tradeoff between the objectives listed above. We then use these problems to show how to find an appropriate threshold value to trigger subordinate or supervisory level rescheduling. Limited classes of performance metrics are considered. Work is currently being carried out to extend the approach to broader performance metrics. It is believed that our results can be applied to other systems for which hierarchical structures are commonly used. Examples of such systems exist in the transportation, health-care, and defense sectors