The scheduling of manufacturing equipment is critical in production facilities. Research on production scheduling has traditionally focused on component throughput and cycle time. However, the increase of electricity price in the United States following the market deregulation in 1990s has led to efforts to reduce energy cost via manufacturing scheduling. This paper explores the possibility of reducing electricity cost of a manufacturing facility subject to real time electricity pricing by dynamically changing operation schedules, while maintaining a pre-determined production throughput. A time series model is developed to forecast the hourly electricity price and time-indexed integer programming is used to determine the manufacturing schedule. The electricity price forecast is updated every hour based on the price history, and manufacturing schedule is updated according to the updated price forecast. A hypothetical flow line with 3 processes operating 16 hours per day is used as a case study. The line has a limited public buffer between processes and all machines in the shop have three operational states. With a throughput of 60 parts per day, the results suggest that it is possible to reduce the cost by 3.6% using an hourly forecast compared with a schedule based on a day-ahead price forecast.
- Manufacturing Engineering Division
Dynamic Manufacturing Scheduling Under Real-Time Electricity Pricing Based on MILP and ARIMA
- Views Icon Views
- Share Icon Share
- Search Site
Zhai, Y, Wang, H, Zhao, F, & Sutherland, JW. "Dynamic Manufacturing Scheduling Under Real-Time Electricity Pricing Based on MILP and ARIMA." Proceedings of the ASME 2017 12th International Manufacturing Science and Engineering Conference collocated with the JSME/ASME 2017 6th International Conference on Materials and Processing. Volume 4: Bio and Sustainable Manufacturing. Los Angeles, California, USA. June 4–8, 2017. V004T05A030. ASME. https://doi.org/10.1115/MSEC2017-2930
Download citation file: