Published in 2019
- Resource efficiency analysis of lubricating strategies for machining processes using life cycle assessment methodology
Life Cycle Assessment
- Authors: Alessio Campitelli, Jorge Cristóbal, Julia Fischer, Beatrix Becker, Liselotte Schebek
- Journal: Journal of Cleaner Production
- The enhancement of resource efficiency in the manufacturing industry is a major key to achieve sustainable development. The purpose of this paper is to investigate the resource efficiency of metal working processes using different lubrication strategies: flood lubrication (FL) and minimum quantity lubrication (MQL). Life Cycle Assessment (LCA) is a suitable methodology to assess the resource efficiency. In this paper a LCA is carried out for three different materials: aluminium, steel and cast iron. The process related data had been provided by practical measurements on state of the art machines and missing data derived from literature and expert interviews. The used input and output data for the inventory analysis is documented in this paper. In a hotspot analysis using LCA, fourteen impact categories from CML 2001 had been analysed. Finally, parameters with a high influence on the resource efficiency of machining processes were examined. The results of the LCA show that the significant parameters causing high environmental impacts are electricity, compressed air and FL oil. The comparison of the machining processes using FL and MQL technologies reveals that most of the analysed processes have a higher environmental impact using FL instead of MQL. This is mainly due to the high energy consumption for the lubricating pump and also because of the higher consumption of lubricants compared to MQL. Furthermore, the generation of hazardous waste, in form of used oil and used filter fleece also contributes. The MQL-technology requires less electricity and lubrication oil and avoids hazardous waste. However, the results show that the compressed air consumption of MQL is significantly higher compared to FL-related processes. Through this study, new and specific LCA datasets for drilling and milling for three working materials including two lubricating strategies (FL and MQL) are generated for further research.
Published in 2018
- A Framework for Self-Evaluation and Increase of Resource-Efficient Production through Digitalization
- Authors: Sebastian Haag, Christoph Bauerdick, Alessio Campitelli, Reiner Anderl, Eberhard Abele, Liselotte Schebek
- Journal: Procedia CIRP
- Modern sensor technology and decreasing hardware costs enable the collection of a wide range of data. Nonetheless, the collection of data itself does not generate value. The collected data must be processed and analysed. Many small and medium-sized enterprises already collect a number of data. However, there is no definite strategy, which data needs to be collected in order to acquire relevant insights into processes. The enormous potential of data analysis and the current lack of its implementation caused the development of this framework. It will assist enterprises to evaluate their own level of digitalization to assess resource use.