This lecture is designed for participants to gain a better understanding of the methods and tools for energy and resource efficiency management in manufacturing operations.
About the Speaker
Professor Dr.-Ing. Christoph Herrmann is Full Professor and Director at the Institute of Machine Tools and Production Technology (IWF) / Sustainable Manufacturing and Life Cycle Engineering at Technische Universität Braunschweig. In 2011, his team together with colleagues from Fraunhofer and industry partners has won the German Resource Efficiency Award from the Federal Ministry of Economics and Technology, Germany. In 2013 the lecture “Product and Life Cycle Management” was rewarded with the LehrLEO award by the TU Braunschweig as the best lecture in the bachelor degree programme. Professor Herrmann has conducted various industry and research projects in the context of life cycle engineering and sustainable manufacturing on national and international level. His research interests comprise the development of models, methods and tools for a total life cycle management. He has been involved in research projects considering e.g. life cycle design, energy and resource efficiency in production, service management as well as information and process management in order to close product and material loops.
The followings are some of his projects:
- EMC2-Factory – Eco Manufactured transportation means from Clean and Competitive
- EnHiPro – Improving energy and auxiliary material efficiency in production
- ProGRess – Design of energy and resource efficient process chains using the example of aluminum die casting
Different studies have underlined the significant potential for improving the energy and resource efficiency in manufacturing companies–numbers range from 10 to 40% of possible savings that can be achieved even with available technology. In this lecture, a comprehensive methodology consisting out of seven steps as well as latest tools based on a holistic factory perspective will be discussed.
Macro-Analysis: given that no detailed data is available in a first step, the macro-analysis focuses on more general information based on cumulative consumption information for the company as a whole, e.g. from (energy) bills. This gives first priorities, e.g. regarding the relevance of different energy carriers. A load profile of a company (also available from energy supplier) can also give important indication of the base load of consumption (e.g. weekend, night) as well as the relevance of energy peaks and their influence on the energy costs (e.g. through peak surcharges).
Energy Portfolio: for breaking down overall energy consumption into single consumer the method of the energy portfolio is proposed. While using available data on nominal values and operating times, the idea is to derive distinctive classifications of consumers which lead to different strategies and priorities for further procedure. However, the energy portfolio is also a valuable method for continuous application through integration of updated data.
Measurement: deriving the appropriate measuring strategy is a major cornerstone of the concept. Based on the prioritization of the energy portfolio an easy-to-handle decision tree is proposed to derive the most suiting type of data acquisition (permanent measurement, single measurement, using nominal values).
Modeling/Analysis: after the acquisition of data, the transfer into comprehensible models is a crucial step to analyze and understand energy and resource consumption behavior. On machine level this means to allocate consumption to different states of the machines or to different product being produced. In an ideal case (e.g. mathematical) models can be derived which allow to estimate the consumption behavior with sufficient accuracy. On a system level, the logic interdependencies of processes and flows within the factory can be modeled which gives further insight into system energy and resource flows and serves also as structured data backbone. Furthermore, energy oriented simulation approaches enable to consciously take into account the dynamic inter-dependencies within the factory system in order to improve the energy efficiency.
Identification and Evaluation of measures: based on process and system models, the identification and also the strongly connected evaluation of improvement potentials are easily possible. Through changing parameters of the model different scenarios regarding the embodiment and impact of improvement measures can be considered.
10.00am Technical Lecture by Professor Christoph Herrmann
Who Should Attend
RI Researchers, University Professors/students, Managers and Industry Partners from industry.
Registration for this lecture is free of charge. Seats are available on a first-come, first-served basis. Please click here to reserve a place.
For technical enquiries and collaboration: Dr Song Bin, Email: bsong@SIMTech.a-star.edu.sg; Tel: 6793 8223
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