Sustainable Manufacturing Practices for Zero-Emission Vehicles: Analyzing the Role of Predictive Analytics in Achieving Carbon Neutrality

Abstract

Reducing production-related carbon dioxide emissions is a crucial prerequisite for achieving the European goal of carbon neutrality by 2050. This study provides an overview of possible emissions by using a current vehicle and the corresponding expressions, as well as the options that need to be addressed. Since industry contributes significantly to global greenhouse gas emissions, the effect of manufacturing emissions on all stages of a vehicle’s lifecycle is noticeable.

Predictive maintenance is called "new oil," and the application of advanced analytics is considered the driving source of a fundamental change at the production site. In addition to the early prediction of defects and the reduction of downtime and lower repair costs, one possible application is dealing with increased demand for zero-emission vehicle production to gain carbon neutrality in manufacturing. This essay aims to address sustainable manufacturing practices regarding zero-emission vehicles. The focus of the research is placed on the car industry, but the presented research could be utilized as the basis of application in any common car production. Since vehicle manufacturing is more pollution-inclined than the vehicle’s use, it is essential to find an energy source that will sustain this industry's growth and, at the same time, respect the environment and keep pollutants practically zero. This is why, in this essay, electric-powered vehicles are outlined to substitute cars powered by conventional internal combustion drives, as they do not consume liquids and do not emit CO2 or other harmful gases. In addition to the benefits in terms of the environment, they are cleaner and generally healthier for the people who use them and eco-friendly, which is the goal of the project from every perspective of modern society. The application of advanced analytics is suitable not merely for energy development or sustainability; precisely, the intelligence could also be used in the production of systems. However, if power is a kind of energy, this paper will focus on its application in aspects of car industry production. The overall aim can be defined as an analysis of the benefits and downsides of using predictive analytics to improve the environmental aspects of the production domain by providing cleaner cars. The importance of corresponding illustrations is emphasized, and the essay ends with the connection between the importance of the industry’s contribution from an environmental point of view and the necessity for sustainability aspects.