Risk Treatment for Energy‐Oriented Production Plans through the Selection, Classification, and Integration of Suitable Measures

With rising electricity prices, industries are trying to exploit opportunities to reduce electricity costs. Adapting to fluctuating energy prices offers the possibility to save electricity costs without reducing the performance of the production system. Production planning and control play key roles in the implementation of the adjustments. By taking into account the price forecasts for the electricity markets in addition to machine utilization, work in process, and throughput time, an energy‐oriented production plan is set up. The electrical energy is procured based on this plan and the associated load profile. Deviations from the forecast and the purchased amount of electricity lead to high penalties, as they can destabilize the energy system. For manufacturing companies, this means that machine failures and other unexpected events must be dealt with in a structured manner to avoid these penalty costs. This paper presents an approach to selecting, classifying, and integrat-ing suitable measures from existing risk treatment paths into the production schedule. The selection of measures is based on a hybrid multi‐criteria decision‐making method in which the three relevant criteria, namely, cost, energy flexibility, and risk reduction, are weighted by applying both an analytic hierarchy process and entropy, and they are then prioritized according to multi‐attribute utility theory. In the following, the subdivision into preventive and reactive measures is made in order to choose between the modification of the original plan or the creation of backup plans. With the help of mathematical optimization, the measures are integrated into the production schedule by mini-mizing the cost of balancing energy. The approach was implemented in MATLAB® and validated using a case study in the foundry industry.