Systematic literature review of decision support models for energy-efficient production planning. (November 2016) - Biel, Konstantin; Glock, Christoph H.
Highlights: A framework for classifying energy-efficient production planning models is proposed. The integration of energy efficiency from the modeling perspective is stressed. Existing models rarely incorporate renewable energy sources or energy storages. The relationship between emissions and energy consumption is often oversimplified. Most models consider predetermined energy pricing instead of real-time pricing. Abstract: Following the scarcity of resources, rising energy prices, and an increasing awareness of the role manufacturing plays in the generation of greenhouse gas emissions, the consumption of energy has more and more been the subject of research on production planning over the last decade. Even though recent years have witnessed a dramatic increase in the number of works published in this area, several related research questions have been opened up without sufficiently linking research approaches and research insights. The aim of this paper is to investigate the links between these questions and to highlight how the modeling approaches developed for different manufacturing systems, energy pricing policies, and energy efficiency criteria can benefit from each other and lead to more advanced energy-efficient production planning approaches. Therefore, this paper provides a review of the state-of-the-art of decision support models that integrate energy aspects into mid-term and short-term production planning of manufacturing companies. The paper first highlights the increasing importance of energy consumption in manufacturing and shows how considering energy consumption in production planning can contribute to more energy-efficient production processes. Subsequently, the paper outlines the review methodology used and descriptively analyzes the sampled papers. Afterwards, the selected papers are categorized according to the production planning tasks considered. From this classification, gaps in the existing literature are derived and potential areas for future research are suggested.