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Computer Applications in Eco-efficiency Assessment in Logistics
1
Central Mining Institute, Department of Energy Saving and Air Protection, Laboratory of Technologies and Products Eco-Efficiency Analyses
2
Silesian University of Technology, Faculty of Organisation and Management
Online publication date: 2013-12-04
Management 2013;17(2):232-244
KEYWORDS
ABSTRACT
Computer Applications in Eco-efficiency Assessment in Logistics The goal of this study is to present computer applications in eco-efficiency assessment in Logistics based on Umberto for Ecoefficiency software. The study defines the major components of eco-efficiency analysis like: Life Cycle Assessment (LCA) and Material Flow Analysis (MFA). According to ISO 14045:2012 eco-efficiency assessment is a quantitative management tool which enables the study of life-cycle environmental impacts of a product system along with its product system value for a stakeholder. Within eco-efficiency assessment, environmental impacts are evaluated using Life Cycle Assessment (LCA). The eco-efficiency methodology is proposed with using Umberto for Eco-efficiency software. Therefore, this article presents the results of Life Cycle Assessment according to methods used in Umberto software on the case study of valuation of the different logistic possibilities. The results of this study can be used as the first step in performing a full cradle-to-grave eco-efficiency that includes all phases of the logistics system.
REFERENCES (19)
1.
Bloemhof-Ruwaard JM, Krikke H, van Wassenhove LN. (2004), ORModels for Eco-Eco Closed Loop Supply Chain Optimization. In Dekker R, Fleischmann M, Inderfurth K, van Wassenhove LN, editors. Reverse Logistics: Quantitative Models for Closed-Loop Supply Chains. Springer/ Verlag: 357-379.
2.
Burchart-Korol D., Czaplicka-Kolarz K., Kruczek M. (2012), Eco-effi ciencyand eco-effectiveness concepts in supply chain management, Carpathian Logistics Congress, Jesenik 2012.
3.
Burchart-Korol D. (2013): Life Cycle Assessment of Steel Production in Poland. A Case Study. Journal of Cleaner Production, 54 (1), 235-243.
4.
CML Guinee J.B. et al. (2000), An operational guide to LCA. Preliminary version, Leiden: CML, 2000; http://www.leidenuniv.nl/inter....
5.
CML (2001), Characterisation factors of CML. Version 1.00, Leiden: CM L, Januar 2001; http://www.leidenuniv.nl/inter....
6.
Hellweg S., Doka G., Goran, F., Hungerbuhler H. (2005), Assessing theeco-effi ciency of end-of-pipe technologies with the environmental cost effi ciencyindicator: A case study of solid waste management. Journal of Industrial Ecology 9 (4), 189-203.
7.
Kobayashi Y., Kobayashi H., Hongu A., Sanehira K. (2005), A practicalmethod for quantifying ecoeffi ciency using eco-design support tools. Journal of Industrial Ecology, 9 (4), 131-144.
8.
Krikke, H., Bloemhof-Ruwaard, J.M., van Wassenhove, L.N. (2003), Currentproduct and closed-loop supply chain design with an application to refrigerators. International Journal of Production Research, 41 (16), 3689-3719.
9.
Kuosmanen, T., Kortelainen, M. (2005),. Measuring eco-effi ciency ofproduction with data envelopment analysis. Journal of Industrial Ecology, 9 (4), 59-72.
10.
Page B., Wohlgemuth V. (2005), Linking economic optimisation and simulationmodels to environmental material fl ow networks for eco-effi ciency. In: Hilty, L.M., Seifert, E.K., Treibert, R. (Eds.), Information Systems for Sustainable Development. Idea Group Publishing, Hershey, 94-108.
11.
Page B., Wohlgemuth V., Raspe M. (2008), Material Flow Analysis for Eco-Effi ciency with Material Flow Network Reference Models - Concepts and CaseStudy, iEMSs 2008: International Congress on Environmental Modeling and Software Integrating Sciences and Information Technology for Environmental Assessment and Decision Making.
12.
Pimpisut D., Page B., Spehs T., Wohlgemuth V. (2007), An EnvironmentalManagement Information System for Eco-Effi ciency of Agro-Industries inThailand based on Material Flow Networks. In: O. Hryniewicz, et.al. (Eds.): Proc. 21 st Intern. Conf. Informatics for Environmental Protection. Warsaw, Poland, 12-14th Sept. 2007, Shaker Publ., Aachen, pp. 219-227.
13.
Quariguasi Frota Neto J., Walther G., Bloemhof 1., van Nunen J.A.E.E., Spengler T. (2009), A methodology for assessing eco-effi ciency in logisticsnetworks, European Journal of Operational Research, 193, 670-682.
14.
Saniuk A., Jakabova M., Babcanova D. (2011), New solutions in enterprisemanagement, in: Innovations in information management systems, Monograph, (ed. by Anna Saniuk, Sebastian Saniuk), Wyd. Instytutu Informatyki i Zarządzania Produkcją Uniwersytetu Zielonogórskiego, Zielona Góra , s. 44-61, ISBN: 978-83-933843-0-3.
15.
Saniuk A., Witkowski K., Saniuk S. (2013), Management of production ordersin metalworking production, 22nd International Conference on Metallurgy and Materials - METAL 2013, TANGER, Czech Republic, Brno, CD-ROM, ISBN: 978-80-87294-39-0.
16.
Scholz, R.W., Wiek, A. (2009), Operational eco-effi ciency: Comparing fi rms’environmental investments in different domains of operation. Journal of Industrial Ecology 2005, 9 (4),155-170.
17.
Spengler T. A methodology for assessing eco-effi ciency in logistics networks, European Journal of Operational Research, 193, 670-682 http://www.ifu.com.
18.
Wang Y., Zhu X., Lu T., Jeeva A.S. (2013), Eco-effi cient based logisticsnetwork design in hybrid manufacturing/ remanufacturing system in low-carboneconomy, Journal of Industrial Engineering and Management JIEM, 6, 200-214.
19.
Wohlgemuth V., Page 8., Kreutzer W. (2006), Combining discrete eventsimulation and material fl ow analysis in a component-based approach toindustrial environmental protection, Environmental Modeling & Software, 21, 1607-1617.
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| eISSN: | 2299-193X |
| ISSN: | 1429-9321 (1997-2019) |
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