The Need

Energy use is a major concern for many industrial and manufacturing companies. Given the cost of energy and the increasing importance green energy policies, it is critical that manufacturers understand how their energy usage can be performed in a way that minimizes cost and environmental impact.

The Technology

The Ohio State University researchers Dr. Nicholas G. Hall and Dr. Marc E. Posner have developed a novel polynomial time algorithm to solve this optimization problem. By using inputs such as energy cost forecasting data and information about the manufacturing or other industrial process (e.g., the speed of the machine when it performs a task, how much energy it consumes at discrete speeds performing a task, how long machine tasks take, etc.), the algorithm can schedule machine tasks in a way that minimizes energy cost. Other relevant considerations such as minimizing CO2 emissions, are also possible. The algorithm thus allows a company to closely plan and monitor their energy usage and cost.

Commercial Applications

• Manufacturing: Efficient scheduling of machine tasks to minimize energy costs.
• Industrial Processes: Optimal use of machinery in various industrial processes to reduce energy consumption.
• Energy Management: Effective planning and monitoring of energy usage across different sectors.

Benefits/Advantages

• Cost Savings: Significant financial savings due to efficient energy usage.
• Environmental Impact: Potential reduction in CO2 emissions contributing to environmentally friendly practices.
• Optimization: Robust evaluation techniques allow for precise and efficient planning tools to schedule cost-conscious energy usage.
• Adaptability: The technology can be adapted to various industrial processes and manufacturing settings.