An optimization-based control strategy for energy efficiency of discrete manufacturing systems

Area of Science:

• Industrial Engineering
• Control Systems Engineering
• Energy Management

Background:

• Manufacturing systems face significant energy consumption and peak power demands.
• Optimizing peripheral device operation is crucial for energy efficiency in industrial processes.

Purpose of the Study:

• To develop and validate an optimization-based controller for selective switching of peripheral devices.
• To reduce global energy consumption and peak power loads in manufacturing test benches.
• To improve energy efficiency and minimize energy costs in periodic systems.

Main Methods:

• Energy consumption models for test-bench devices were developed using data and subspace identification.
• A receding horizon control strategy was designed incorporating these models and operating constraints.
• The proposed strategy was validated through emulation on a test bench.

Main Results:

• The optimization-based controller demonstrated reductions in energy consumption by approximately 7%.
• The strategy effectively minimized energy costs related to nominal power purchases.
• Productivity was maintained while achieving significant energy savings.

Conclusions:

• The proposed optimization-based controller offers a viable solution for reducing energy consumption in manufacturing systems.
• Intelligent control of peripheral devices can lead to substantial energy efficiency improvements.
• This approach provides a practical method for minimizing operational energy costs in industrial settings.