Research On Optimizatiom Model Of Job-shop Scheduling Problem Based On Advanced Planning And Scheduling

In today’s era, the rapid development of information technology, intensified global competition, rapidly changing market environment, make the manufacturing industry’s operating environment be increasingly complex, the specific performances is a sundry, personalized customer demand, significantly shortene product life and cycleand delivery, et cetera. Accordingly, the mode of production is undergoing tremendous changing, traditional mass production is gradually changing to the direction of to the sundry, small quantities mode or even a large number of customers customized mode. Due to the change in the mode of manufacturing, frequent changes or corrections of the factory production plan, production planning and control system is facing unprecedented challenges. Formulating the production and operation plan with traditional human experience has been far from being able to meet the needs of production. The implementation effect of ERP in many companies is not satisfactory. APS’s appearance overcomes the shortcomings of the ERP system, such as the using of the static approach does not match the dynamic problems. Aiming at the shortcomings of the ERP planning module, APS uses mathematical algorithms, simulation technology, TOC and a series of advanced technology to formulate jobs scheduling plan based on the limited capacity. APS is a strong complement to the ERP planning module.In the APS, the scheduling logic and algorithm is the core, but also difficult. This article conducts an in-depth study on this. On the basis of the in-depth study of TOC, this article will use the job shop scheduling module’s scheduling logic of APS to establish a conceptual model of job shop scheduling based on the bottleneck process according to the characteristics of small or medium-sized manufacturing enterprise production management. Try to increase the utilization of the bottleneck resource in job shop and the effective output of the manufacturing system through the creation and application of the concept model. The model contains the bottleneck identification technology, mathematical model based on the bottleneck resources, model solution using genetic algorithm. Optimize the scheduling for the the bottleneck resources and bottlenecks process of job shop, making the bottleneck resource production tasks time shortest. To develop a job shop scheduling solution suitable for small and medium-sized manufacturing enterprises whose production process is multi-variety, small batch and having more complex. Investigate the application of the job shop optimal scheduling model combining a typical example of bearing parts manufacturing plant, and finally output scheduling results with a Gantt chart, confirmed the feasibility and effectiveness of the model and algorithm.