Grey Decision Making as a tool for the classification of the sustainability level of remanufacturing companies Paulina Golinska * , Monika Kosacka, Rafal Mierzwiak, Karolina Werner-Lewandowska Poznan University of Technology, 61142 Poznan, Poland article info Article history: Received 31 January 2014 Received in revised form 3 October 2014 Accepted 12 November 2014 Available online 20 November 2014 Keywords: Remanufacturing process Sustainability assessment Performance indicators Operational excellence Decision making Grey Decision Making (GDM) abstract Remanufacturing facilitates multiple usages of products by providing several life cycles and contributes to more sustainable societies by the reduction of raw materials and energy consumption. Previous studies on sustainability assessment in remanufacturing focus predominantly on the life cycle design and the life cycle engineering approach. There is a research gap regarding the assessment of remanufacturing operational excellence as far as sustainability issues are concerned. The problem in the application of the principles of sustainable development in everyday business operations is the lack of clearly defined sustainability indicators, which might be used in the assessment of remanufacturing activities. In this paper authors present a set of indicators which are used as the criteria for sustainability assessment and to address company classification. Authors define three classes of companies, which respond to the different sustainability levels. The aim of this paper is to provide a new tool for decision making based on Grey Decisions Making. This tool helps in classifying the current state of remanufacturing operations, and then identifying and prioritizing operations in the company which need improvement actions. The au- thors present the numerical example in order to explain the decision making process and indicate how the application of Grey Decision Making (GDM) can contribute towards more sustainable societies. © 2014 Elsevier Ltd. All rights reserved. 1. Introduction In a competitive environment the companies have to improve their performance systematically. With the increasing importance of sustainability, companies are forced to enter two new elements into their competitive strategy (besides Profitability) namely Peo- ple and Planet (the 3Ps). Application of the sustainability policy in companies can be defined as the better utilization of resources in a way which does not interfere with the natural environment and the surrounding communities. In order to better identify the current situation of companies and to find the optimization potential, there is a need for a matrix of performance measures. The sustainability measures should allow for the assessment of the company performance in the three di- mensions as proposed by Brundtland Commission (WCED, 1987): economic, ecological, social. The main reason for using performance measures is that they create possibilities for decision-makers to gain knowledge about what happens in the company at present and to direct future ac- tions (Elg, 2007). Strong measures help to make decision making towards more sustainable societies and should be (Feng and Joung, 2009): understandable, relevant, comparable, reliable/usable, data accessible, with logic structure/simple. In the remanufacturing sector many companies fall under the category of small and medium enterprises (SMEs). They have limited resources (both human and financial) to implement com- plex performance measurement systems. SMEs need some guide- lines for decision making on how to identify optimization potentials and how to derive and implement them based on sus- tainability indicators (e.g. resource consumption, impact on climate/health/environment) (VDI, 2006). It is important for SMEs to have effective decision support tools for a goal-oriented analysis and then the implementation of appropriate measures for increasing their sustainability. The research questions are defined as: Q1) Which indicators can be used in SMEs for the assessment of the sustainability level, without adding additional reporting workload? * Corresponding author. Poznan University of Technology, Faculty of Engineering Management, Strzelecka 11, 60965 Poznan, Poland. Tel.: þ48 605045190. E-mail addresses: paulina.golinska@put.poznan.pl (P. Golinska), monika. kosacka@doctorate.put.poznan.pl (M. Kosacka), rafal.mierzwiak@put.poznan.pl (R. Mierzwiak), karolina.werner@put.poznan.pl (K. Werner-Lewandowska). Contents lists available at ScienceDirect Journal of Cleaner Production journal homepage: www.elsevier.com/locate/jclepro http://dx.doi.org/10.1016/j.jclepro.2014.11.040 0959-6526/© 2014 Elsevier Ltd. All rights reserved. Journal of Cleaner Production 105 (2015) 28e40