Karolina Werner-Lewandowska

Sustainability Indicators System for Remanufacturing

Legal regulations enforce the companies to search for the ways to reuse their end-of-use or end-of-life products. Additionally, more and more companies start to perceive the closing of the life cycles loops as an additional area of income. Remanufacturing facilitates multiple usage of the value-added from new production by several life cycles. It helps to reduce work effort and energy and it has big potential for cost savings. There is a research gap regarding the assessment of remanufacturing operational excellence. The application of the principles of sustainable development in everyday business operations is problematic, as there is a lack of the clearly defined sustainability indicators, which might be used in the assessment of remanufacturing activities. The majority of the companies which are involved in the remanufacturing operations are small and medium sized (SME). Very often operations in these companies are organized by rule-of-thumbs. The aim of this chapter is to provide sustainability assessment framework so called Sustainability Indicators System for Remanufacturing (SISR) based on the literature review and remanufacturing process characteristics revealed from case studies.

The Mixed Method for Sustainability Assessment of Remanufacturing Process Using Grey Decision Making

Sustainability assessment is not an easy task especially in case of small and medium size remanufacturing companies. The remanufacturing process is characterized by high level of uncertainty regarding its timing, quality and quantity of its outputs. Our previous literature studies have showed that there is lack of a simple method for assessment of sustainability dedicated to SMEs in remanufacturing sector. The challenge is to combine the expert’s knowledge and the numerical data. The aim of this chapter is to present a mixed method for assessing the sustainability with the use of Grey Decision Making. The application of the Grey Decision Making (GDM) allows carrying out of the assessment process in a quantifiable way, even with uncertain and incomplete data. The proposed method aims to assess the class of the sustainability, to identify the weaknesses in current operations and then to facilitate making priorities for the improvements action which should to be taken in order to achieve a better sustainability class. The chapter presents also IT tools which was designed to facilitate the assessment process.

The Roadmap for Improving Sustainability in Remanufacturing Operations

Remanufacturing allows to save and reuse the resources which were incorporated to the product in the primary production. Many authors have reported the economic and environmental benefits of remanufacturing. However, there is limited literature on how to improve the remanufacturing operations to make them more sustainable on the shop floor level. The goal of this chapter is to present the roadmap for improvement of sustainability in remanufacturing operations. The roadmap aims to guide small and medium sized remanufacturing enterprises (RSMEs) on how to improve usage of their resources to achieve higher level of sustainability. The authors describe the methodology which is applied, in order to construct the roadmap considering ecological, economic and social aspects.

Methodology of Assortment Analysis in Companies with a Wide Range of Products for Building the Flexibility of Customer Service

The aim of the chapter is to present the methodology of the analysis of assortment in companies with a wide range of products and diversified customer service strategies (Make to order, Make to stock, Assembly to order). The authors performed ABC/XYZ analysis (logistical criteria of the segmentation), analysis of technological similarity coefficient in terms of process times in both horizontal and vertical terms. A statistical software has been used for analysis purposes. Then the selected data have been used in the simulation of production-logistics process (FlexSim 7 Simulation Software) for multi-department companies with diversified customer service strategies. The validation of the methodology was based on an analysis of the correlation between the indicators adopted for the evaluation of simulation results with the results of statistical analysis. The chapter ends with general conclusions on the results of the work and the comments on their application in business practice.