The automotive industry is the world's largest manufacturing activity, characterized by complex production processes and some energy-intense processes which use a significant quantity of raw materials. The production processes responsible for the highest energy end-use take place in the paint shop. Depending on the type of paint-shop processes, the energy use can account for up to 75 % of the plant's total energy end-use. This study aims to contribute to an enhanced understanding of the complexity of adopting decarbonization measures and to provide support for planning and decision-making in practice. By adopting a bottom-up perspective, a longitudinal case study was conducted on a state-of-the-art automotive paint-shop between November 2019 and March 2023. To achieve the study's aim, a bottom-up methodology was developed comprising several steps: i) analysis of decarbonization measures, ii) mapping of process energy use and CO2 emissions, and iii) economic analysis. The data-based methodology is flexible and can be applied in different automotive paint-shops. Main findings show that i) incremental energy efficiency measures have the fastest adoption level, with relatively high savings potential, and most of these are cost effective; ii) radical process innovation measures have a higher savings potential, but long-term adoption levels due to the radical innovations required in the supply chain, and the highly specialized knowledge needed in the pre-treatment process; and iii) the primary drivers for implementing the measures are to achieve the climate targets and establish a leading position in the sector, rather than focusing primarily on the cost-effectiveness of the measures.
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Andrei et al. (2024) studied this question.
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