Production energy optimization using low dynamic programming, a decision support tool for sustainable manufacturing

• A model predictive controller platform is used for energy management.
• A linear programming approach is used for industrial energy optimization.
• Cost-based and Energy-efficiency optimization metrics are evaluated.

The presented study investigates the application of a Model Predictive Controller, equipped with linear-programming based optimizer, with application to energy management in production environments. The study focuses on an automotive OEM assembly plant that consumes fossil fuel (natural and landfill gas) in addition to electricity drawn from the grid. This manuscript details the optimization structure under two different cost functions; specifically, cost-savings and energy efficiency. The predicted results are in agreement with the current plant consumption and demonstrate the conflicting nature of the two cost models proposed; thusly, highlighting the importance of objective decision making tools, driven by specific performance criteria, in managing the energy and the overall sustainability of production environments. Additionally, the study discusses the role of the co-generation process efficiency on the overall plant energy consumption.