Energy Planning of Manufacturing Systems with Methods-Energy Measurement (MEM) and Multi-Domain Simulation Approach

Abstract:

Article Preview

Energy costs play a decisive role in the operation costs of automotive production companies. Therefore, energy planning in an early conception and planning stage becomes an important topic. This is because the early conception and planning stage has the greatest potential to influence the energy consumption of manufacturing technologies since about 70-80 % of the energy costs are committed during this stage. However, lifetime cost and specifically energy consumption are currently not a determining factor at this stage. The reason is that the prediction of energy costs for complex manufacturing systems are challenging. Previous research approaches in the area of energy planning are limited to detailed planned production. A standardized approach to determine the energy consumption rates at an early stage does not exist. In this context, the EffiPLAS project has therefore proposed to solve this challenge. The aim of this project is to develop a Methods-Energy Measurement approach with elementary energy elements to support the planning process at an early stage, and to develop a modular simulation model for calculating the energy consumption of industrial robots, which complements the energy prediction. In this paper, the basic concept of elementary energy units and their value determination techniques is presented, and the simulation model is outlined. The developed approach will help to predict the prospective energy consumption of complex production equipment so that energy costs can be accounted for in an improved manner within a life-cycle costing comparative analyses.

Info:

Periodical:

Edited by:

Jörg Franke and Sven Kreitlein

Pages:

53-59

Citation:

M. Bornschlegl et al., "Energy Planning of Manufacturing Systems with Methods-Energy Measurement (MEM) and Multi-Domain Simulation Approach", Applied Mechanics and Materials, Vol. 655, pp. 53-59, 2014

Online since:

October 2014

Export:

Price:

$41.00

* - Corresponding Author

[1] ISO 50001: 2011, Energy management systems - Requirements with guidance for use, Beuth, Berlin, (2011).

[2] M. Bornschlegl, I. Paulus and M. Bregulla, From energy to key indicators - The key indicator development chain, ATZ worldwide, 115/5 (2013), 42-46.

DOI: https://doi.org/10.1007/s38311-013-0061-3

[3] C. Rush and R. Roy, Analysis of cost estimating processes used within a concurrent engineering environment throughout a product life cycle, in: 7th ISPE International Conference on Concurrent Engineering: Research and Applications, Technomic Inc., Lancaster, 2000, pp.58-67.

[4] International Energy Agency (IEA), World Energy Outlook 2013, OECD Publishing, Paris, (2013).

[5] German Federal Statistical Office, Data on energy price trends - Long-time series - April 2014, http: /www. destatis. de/DE/Publikationen/Thematisch/Preise/Energiepreise/EnergyPriceTrendsPDF_5619002. pdf?_blob=publicationFile, Accessed: 05. 06. (2014).

[6] M. R. Raupach and et al., Global and regional drivers of accelerating CO2 emissions, Proceedings of the National Academy of Sciences, 104/24 (2007), 10288-10293.

DOI: https://doi.org/10.1073/pnas.0700609104

[7] T. Mitrova, Review of the global and Russian energy outlook up to 2040, Energy Strategy Reviews, 2/3-4 (2014), 323-325.

DOI: https://doi.org/10.1016/j.esr.2013.12.001

[8] U.S. Geological Survey, Mineral commodity summaries 2014, http: /minerals. usgs. gov/minerals/pubs/mcs/2014/ mcs2014. pdf, Accessed: 10. 06. (2014).

[9] Die Bundesanstalt für Geowissenschaften und Rohstoffe, Energiestudie 2013 - Reserven, Ressourcen und Verfügbarkeit von Energierohstoffen, http: /www. bgr. bund. de/DE/Themen/Energie/Downloads/Energiestudie_2013. pdf? _blob=publicationFile&v=5, Accessed: 20. 05. (2014).

[10] European Parliament & Council, Directive 2010/75/EU of the European Parliament and of the Council on Industrial Emissions (integrated pollution prevention and control), http: /eur-lex. europa. eu/LexUriServ/LexUriServ. do? uri=OJ: L: 2010: 334: 0017: 0119: en: PDF, Accessed: 03. 06. (2014).

[11] European Commission Climate Action, Emissions Trading System (EU ETS), http: /ec. europa. eu/clima/policies/ ets/index_en. htm, Accessed: 03. 06. (2014).

[12] M. Bornschlegl, M. Drechsel, S. Kreitlein and J. Franke, Holistic Approach to Reducing CO2 Emissions along the Energy-Chain (E-Chain), in: Sustainable Automotive Technologies 2013, Springer, Cham, 2014, pp.227-234.

DOI: https://doi.org/10.1007/978-3-319-01884-3_23

[13] M. Drechsel, M. Bornschlegl, S. Spreng, M. Bregulla and J. Franke, A new approach to integrate value stream analysis into a continuous energy efficiency improvement process, in: IECON 2013 - 39th Annual Conference of the IEEE Industrial Electronics Society, IEEE, Piscataway, 2013, pp.7502-7507.

DOI: https://doi.org/10.1109/iecon.2013.6700382

[14] M. Groth, Die Relevanz von Ökobilanzen für die Umweltgesetzgebung am Beispiel der Verpackungsverordnung, Working Paper Series in Economics 184, University of Lüneburg, Institute of Economics, Lüneburg, (2010).

[15] M. Schmidt, Carbon Accounting zwischen Modeerscheinung und ökologischem Verbesserungsprozess, Controlling & Management, 57/1 (2010), 32-37.

DOI: https://doi.org/10.1007/s12176-010-0011-5

[16] J. Franke, S. Kreitlein, F. Risch and S. Guenther, Energy-efficient production strategies and technologies for electric drives, in: 2013 IEEE International Conference on Industrial Technology (ICIT), IEEE, Piscataway, 2013, p.1898-(1903).

DOI: https://doi.org/10.1109/icit.2013.6505967

[17] D. Meike and L. Ribickis, Industrial robot path optimization approach with asynchronous fly-by in joint space, in: 2011 IEEE International Symposium on Industrial Electronics (ISIE), IEEE, Piscataway, 2011, pp.911-915.

DOI: https://doi.org/10.1109/isie.2011.5984280

[18] J. Engelmann, Methoden und Werkzeuge zur Planung und Gestaltung energieeffizienter Fabriken, Diss., TU Chemnitz, Chemnitz, (2009).

[19] Paryanto, M. Brossog, J. Kohl, J. Merhof, S. Spreng and J. Franke, Energy consumption and dynamic behavior analysis of a six-axis industrial robot, Procedia CIRP, 2014 (accepted).

DOI: https://doi.org/10.1016/j.procir.2014.10.091

[20] M. Bornschlegl, M. Bregulla and J. Schweiger, Powermanagement in der Automobilproduktion, in: Forschungsbericht 2010, HAW Ingolstadt, Ingolstadt, 2011, pp.72-73.

[21] H. B. Maynard, G. J. Stegemerten, and J. L. Schwab, Methods-time measurement, McGraw-Hill, New York, (1948).

[22] C. Mose and N. Weinert, Evaluation of process chains for an overall optimization of manufacturing energy efficiency, in: Advances in Sustainable and Competitive Manufacturing Systems, Springer, Cham, 2013, pp.1639-1651.

DOI: https://doi.org/10.1007/978-3-319-00557-7_132

[23] Paryanto, J. Merhof, M. Brossog and C. Fischer, An integrated simulation approach to the development of assembly system components, Advanced Materials Research, 769 (2013), 19-26.

DOI: https://doi.org/10.4028/www.scientific.net/amr.769.19

[24] Paryanto, M. Brossog, J. Merhof and J. Franke, Mechatronic behavior analysis of a customized manufacturing cell, in: Proceedings of the 7th World Conference on Mass Customization, Personalization, and Co-Creation, Springer, Cham, 2014, pp.389-399.

DOI: https://doi.org/10.1007/978-3-319-04271-8_33