This technology aims to develop a smart scheduling system for the flexible job shop environment of the back-end assembly section of surface mount technology (SMT) production line. In contrast to the past, which the way to dispatch the jobs was mainly decided by the foremen’s working experience, our technology makes a good use of the advantages of the algorithms to effectively search for the best solution, and generates excellent scheduling results follow a meticulous dispatching logic. We concerned all of production restriction, including machine, jig, and workforce, which make the problem be much complicated. We propose several techniques to improve time efficiency and validity of scheduling results. In terms of results, the system has been proven to be a practical and powerful tool and is helpful for doing resource scheduling and capacity planning. Moreover, the development process is valuable in digital transformation and enhance the smart manufacturing capabilities.

1. Propose a hybrid genetic algorithm combining quantum annealing (QA) and genetic algorithm (GA) encoded with auxiliary capacity planning strategy. This tech takes about one third of the time of the general genetic algorithm to evolve to the same excellent solution.
2. Develop advanced chromosome generation methods that are more adaptable to environmental factors instead of completely random generation. This tech makes the initial value of genetic algorithm be much better, and improve the evolutionary efficiency.
3. Propose three adjustment methods for re-optimizing the scheduling results. We adopt the one of the methods, reduce the idle situation of machines and manpower, to improve the scheduling result. In 100 testing results, 81% is better, 18% not change, and only 1% is worsening.

Instead of foremen experience, we developed an intelligent scheduling system for scheduling and dispatching in job shop production environment, which based on the combination of heuristic algorithm and dispatching logic.
We demonstrate scheduling result by table and Gantt chart with three kinds of view: job, workforce and machine. These are useful for production management to do a long-term planning, as well as, for on-site staff to follow and participate in production. These are helpful for doing resource scheduling and capacity planning.
The system has been actually verified on the production line and proven that which is a practical tool. Moreover, the development process is valuable in digital transformation and enhance the smart manufacturing capabilities.