Advanced product and process design through methodological analysis and forecasting of energy consumption in manufacturing

Abstract

Energy and resource efficiency is becoming an important factor in manufacturing, helping to avoid bottleneck situations in times of sparse resources. Sustainable products are promising new improvements and are attracting customers more than ever. In the automotive industry, the assessment of the environmental impact of a product in use phase is already common practice. In contrast, the manufacturing phase often lacks detailed data. Product and process designers can benefit from reference data serving assessments, whether improvements were achieved compared to theoretical average values. This is most relevant for complex manufacturing processes like injection molding with non-linear relationships toward the degree of optimality. The paper presents a systematic approach for realizing and using a knowledge base facilitating advanced product/ process design decisions. This knowledge base can be used to verify energy related hypothesis, enabling to create design rules and identifying weak points in processes. With an increasing database, energy consumption of similar new/planned products can be forecasted. The approach facilitates to assess decisions and investments in efficiency measures from an ecological and economical point of view, also serving as basis for detailed internal and external reports. It was applied and validated for production of plastic parts in the automotive industry.