Deadlock-free scheduling of knowledgeable manufacturing cell with multiple machines and products

Abstract

Under the stochastic production environment of uncertain job arrival, processing times and product demands, the deadlock-free scheduling is studied for a kind of knowledgeable manufacturing cell with multiple machines and products. First, the expected cost objective function is established based on continuous Markov chain with a discount factor, and a stochastic dynamic programming model is obtained by the virtual self-transfer method. Then, the properties of optimal objective function are analyzed and proved, and a heuristics approximate dynamic programming algorithm is proposed, which can effectively overcome the curse of dimensionality problem in the process of solving the dynamic programming model. With the above settled as premises, the deadlock-free scheduling strategy for knowledgeable manufacturing cell is proposed to control the processing rate and avoid system deadlock simultaneously. Finally, a case study is conducted to demonstrate and validate the effectiveness of the deadlock-free scheduling approach.