## 2 State of the Art
### Risk Management and Energy-Oriented PPC  
Since failures, in general, can have far-reaching negative effects on the performance of a production system as well as on the manufacturing costs of the products, many articles offer a structure for the causes and effects of malfunctions as well as approaches for situational fault management. According to [PERSON] and [PERSON] [7], faults are events that have an effect on a process with a deviation from what was intended to occur. [PERSON] [8] distinguishes between those faults which originate from the process and those that influence the process from outside. The causes are often used to further classify faults. A distinction is made between equipment-related, personnel-related, material-related, information-related, and order-related causes of failure by various authors [9; 10; 11; 12; 13]. Every cause of failure can be linked to its effects on a production system. An allocation of causes and effects, which also takes into account deviations in the electrical load profile, was worked out by [PERSON] [13]. In his contribution, a system is presented with which deviations in energy-flexible production systems can be counteracted with situational measures. [PERSON] et al. [14] introduce an approach for cost-based online scheduling to enable reactions to short-term changes and thus makes a contribution to fault management in energy-flexible production systems. Risk management is characterized in particular by the fact that it also takes into account the probability of occurrence of the event when dealing with faults [15]. Many risk management approaches in the field of production systems are mostly based on the risk management process described in DIN ISO 31,000 [15] with risk identification, risk analysis, risk assessment, and risk treatment, whereby individual process steps are partially combined or sub-processes are supplemented. Various frameworks and approaches were developed specifically for the manufacturing sector. For example, the framework for risk management developed by [PERSON] [16] enables key risk indicators in the manufacturing sector to be searched for and identified. Specific approaches can also be found in the area of PPC, such as [PERSON] et al. [17], who add production risks to a classic PPC system in order to make predictions about impending risk situations and to take these into account in the planning process. If the energy consumption and energy costs in the production environment are to be considered in particular, specific work can also be found for this. [PERSON] et al. [18] simulate disruptions in order to investigate their effects on the energy flexibility and costs of an energy-optimal production plan. The energy-optimized plan serves as an input variable for the subsequent simulation of faults. The changes in the production plan caused by disruptions lead to changed load profiles and thus also to changed electricity costs. The influence of disruptions is ultimately examined on the basis of the change in electricity costs and serves as a basis for decision-making for future investments in energy-oriented production. [PERSON] et al. [19] integrate energy as a limited resource within the framework of energy-oriented production control. Exceeding the available energy resources is possible, but it is associated with disproportionately high costs. Taking into account the predominant goal in production control of adhering to delivery deadlines, the authors consider the fluctuations in energy consumption associated with the production process. The aim is to minimize the deviations from the planned load profile. [PERSON] [20] introduces smart energy-aware manufacturing plant scheduling. By proposing a new multi-objective robust optimization for a factory microgrid, the approach can be considered risk-based, as it considers the conditional value-at-risk. [PERSON] et al. [21] illustrate the simultaneous evaluation of sustainability dimensions, containing environmental and occupational risks with an industrial case from the metal-mechanic sector.