Research On Robust Scheduling Of Manufacturing Enterprises Under MTO Mode

Facing the limited production resources and the fierce competition of the market, the manufacturing enterprises under MTO mode need to consider the market strategy and production management in a unified manner from the internal and external environments. And to deliver the personalized products in contracted time and quantity, the logistics storage, production manufacturing system and business management of the manufacturing enterprises should be highly integrated. However, the unpredictable situation of the market and complex manufacturing system would lead to the emergence of all kinds of disturbance factors in the practical production process. Therefore, in order to deal with those disturbance factors effectively, keep the stability of the manufacturing system and improve production benefit of manufacturing enterprises, the reasonable disturbance detection method and the robust scheduling model should be established. As a kind of the robust scheduling, rescheduling is able to eliminate the negative influence of the disturbance. Thus, the rescheduling has received widespread attention from engineering circles and academic circles.Firstly, this paper describes the common disturbance factors in manufacturing shop and classifies these factors based on the influence degree of the manufacturing system. Then the fuzzy neural network algorithm which is combined fuzzy mathematics and probabilistic neural networks is established to assess the influence degree of the disturbance factors for manufacturing system. After that, aiming at deficiency of the hybrid rescheduling strategy, an improved hybrid rescheduling strategy based on the evaluation result is put forward to select the appropriate processing way, and the deficiency is solved by introducing minimum interval constraint.Secondly, aiming at rebuilding the scheduling scheme in production process under uncertain environment, an adaptive rescheduling model of the flexible job shop as the is established. And then, an extended dual-layer chromosomes coding genetic algorithm which is combined depicting job sequence and machine assignment is put forward to solve the rescheduling model.Finally, an adaptive rescheduling procedure of the manufacturing system by combining the intelligent optimization algorithm and manual scheduling is proposed to ensure the continuity and proportionality in manufacturing process.