Simulation Research Of Scheduling Strategy For A Mould Workshop Based On Plant Simulation

Mould production is typical production mode of small-batch, varieties and MTO where exists a great uncertainty, such as work hour of job, time of machine failure and repair and order arrival time, etc.. Moreover, one of the core competitiveness of the mold companies is delivery cycle and service. Therefore the scheduling problem in mold production is a challenge and an important issue. The scheduling of mould flexible flow shop studied in the paper belongs to the most difficult constraint combinatorial optimization problem and a typical NP-hard problem, which is hard to find an optimal solution by an effective algorithm.The analysis method by a mathematical model tend to have certain limitations, on the one hand, the mathematical model is highly complex and difficult to get the optimal solution, on the other hand the mathematical model is difficult to fully reflect actual production characteristics in the mold manufacturing system. Another way to study the mold production scheduling problem using computer simulation technique is a better way in some respects.Responding to the uncertainty in mould manufacturing, the new when-to-reschedule policy was proposed to determine suitable timing of rescheduling. The paper built a when-to-rescheduling process by calculating cumulative task delay. And the3stages flexible flow shop model was developed with Plant Simulation. At last, the example based on actual production history data in a tire mould company, was given to verify the validity of the proposed policy. The main contents of the paper included:Firstly, a model of the flexible flow shop of tire mould was built, which determined the boundary of simulation system and related assumptions. With quantitative analysis of historical production data,a discrete probability model of the job working hours was established, that is data base of the Plant Simulation platform.Secondly, a when-to-reacting policy was proposed based on the concept of a control limit policy and rolling schedules. Under the proposed policy, rescheduling was carried out based on a cumulative delay which can be a measure to determine suitable timing of rescheduling. Thirdly, the3stages flexible flow shop model was developed with Plant Simulation to implement the policy proposed. The paper described in detail the modeling process.At last, some computational experiments demonstrated the effectiveness of the proposed policy by simulation platform. It was also demonstrated that the proposed policy could outperform typical rescheduling policies.The work was financially supported by the National Natural Science Foundation, China (No.50875051).