A semantic-level component-based scheduling method for customized manufacturing

Abstract

• Information model obtains the job shop state through semantic reasoning. • Computation model generates the optimal schedules for guiding the control of manufacturing resources. • The integration of information model and computation model reduces the search of the solution space. To meet the increasingly complex needs of customers, scheduling faces challenges of the high uncertainty of product arrival in customized manufacturing (CM). This paper proposes a semantic-level component-based scheduling method to solve the uncertainty via the integration of the information model and the computation model. In our proposal, we first construct a component-based framework to illustrate the composition and execution mechanism of a component. Then we present a semantic-enriched information model to obtain the state of the shop floor through automatic semantic reasoning. Additionally, we build a computation model to abstract the stochastic scheduling process of CM. Finally, we design an iteration algorithm to solve the computation model through the interaction between the information model and computation model. In experiments, we show that for random arrivals of products, our proposal can ensure the timeliness of the learning and decision-making, and the task assignment performance is the best compared with the other two methods.