Task scheduling based on genetic algorithm for robotic system in 5G manufacturing industry - Anwar Apandi, Nur Ilyana; Wan, Wing Sheng; Muhammad, N. A. (Penerbit Universiti, UTeM, 2022)
With the development of 5G technology, the robotic system has been bought into industrials. Even manufacturers plan the task flow by using project management. An error may occur and make the tasks overlap because they use the traditional scheduling method. It may waste much time between the tasks, and robots will get into standby mode to wait for the next tasks if the scheduling is failed. An algorithm with flexible scheduling is needed to arrange the tasks accordingly with the shortest total completion time. Genetic Algorithm (GA) is applied to task scheduling, and it provides a better solution from previous results or arrangements due to iteration. In this study, an analysis involves multi robots to complete various industrial operations, consisting of multi-tasks. To save time during processing and costs in production, GA may help it have the optimal value about total complete time to avoid any wastage. In short, the manufacturer will have higher productivity and better performance among the robots when applied a suitable Task Scheduling in the industry or workplace.