The expansion of renewable energies and the concomitant compensatory measures, such as the expansion of the electricity grid, the installation of energy storage facilities, or the flexibilization of demand, lead to a more elaborated energy supply system. Furthermore, the technological development of small power plants has further progressed, and many novel technologies have achieved grid parity. For manufacturing companies, the integration of renewable generation plants at their own site therefore represents a promising strategy for being both technically independent of the electricity grid and autonomous of price policy decisions and volatile market prices. This paper outlines the existing decentralized, renewable power generation technologies, their energetic modeling, and a hybrid optimization methodology for their dimensioning that uses mixed integer linear programming (MILP) and linear programming (LP) problem formulation. Finally, the introduced dimensioning method is applied to an exemplary manufacturing company that is assumed to be in the central part of Germany and located in the metalworking sector. The company has an electricity demand of approximately 20,000 MWh/a. The optimization results in a maximum expansion of PV and the use of CHP to cover the base load leading to a promising energy cost reduction of almost 20%.

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Automated Fiber Placement (AFP) is a widely used production process for the manufacturing of large scale CFRP parts. However, the occurrence of manufacturing defects such as gaps or overlaps is still a common problem in today’s AFP production environments. This study investigates the effect of different defect configurations on the mechanical performance (i.e., tensile strength, flexural strength, and shear strength) of AFP laminates. The results are then linked to the data generated “inline” by a ply inspection system. We use the Pearson correlation in order to relate the measured defect volume to the strength of samples containing different types of defects. A clear knockdown in tensile strength was found for specimens with gaps or overlaps that caused a high amount of fiber undulations in the laminate. The sensor data analysis showed a similar trend. Specimens with a high defect volume had significantly lower values for the tensile strength. A correlation coefficient of −0.98 between these two values was calculated. The obtained results are a promising step towards automated quality inspection for the AFP process.

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