Development and evaluation of risk treatment paths within energy-oriented production planning and control

Abstract

Production planning and control pursues high delivery reliability and short delivery time of the production system at the lowest possible costs. Especially in energy-intensive industries, energy cost account for a significant amount of manufacturing costs. The consideration of variable electricity market prices using energy-flexibility measures facilitates reduced costs by adapting the load profile of production to an electricity price forecast. However, it also increases the production planning and control system’s complexity by additional input variables and possible risks due to the influence of flexibility measures on the production system. In the case of unexpected events, such as failure of machines or faulty materials, it is difficult to adapt the complex production system to the new situation quickly. There is a risk of high additional costs by various causes, such as delays in deadlines or load peaks. Therefore, this paper presents an approach for developing and evaluating risk treatment paths, which include possible combinations of risks and measures for the mitigation of risk effects. The advantage of these paths compared to a situational reaction is that all effects and possible further interactions can be considered and thus overall cost-efficient solutions can be found. The approach is based on the determination of interactions through interpretive structural modelling and the calculation of conditional probabilities using Bayesian Networks. The approach was implemented in MATLAB® and applied using real order and energy data from a foundry. The results show that the presented approach enables structured and data-based comparison of risk treatment paths.