Recent Information Technology Trend of Using Machine Learning in Manufacturing Scheduling
Abstract: Production Scheduling is the process of arranging, controlling and optimizing work and workloads in a production process or manufacturing process. Scheduling is used to allocate plant and machinery resources, plan human resources, plan production processes and purchase materials. It is a key tool for manufacturing and engineering, where it can have a major impact on the productivity of a process. Scheduling jobs in a manufacturing system is by implementing Job release rules. Performance of the Job release rules depends on the state of the system in at each moment and an ideal rule that caters to all states in the system doesn’t exist. To improve performance of scheduling plan that caters to dynamic demands, a scheduling approach that uses machine learning can be used. Machine learning algorithms by analyzing the historical demand, forecast and performance of the system (including simulation runs) can decide which is the most appropriate dispatching rule at each moment in time.
Keywords: Dynamic Scheduling, Production scheduling, Machine Learning
How to Cite?: Dhanesh Thatikonda, "Recent Information Technology Trend of Using Machine Learning in Manufacturing Scheduling", Volume 9 Issue 7, July 2020, International Journal of Science and Research (IJSR), Pages: 861-863, https://www.ijsr.net/getabstract.php?paperid=SR20712050357, DOI: https://dx.doi.org/10.21275/SR20712050357