Stagnation has no place in the modern industrial world, especially when it comes to quality. To remain successful in a competitive environment, any company must improve on all levels, including quality, which is a key index to measure its performance. The sources of waste, failure and non-quality are the real obstacles to production and its quality, so it is necessary to identify and remedy them. Improving production quality (quality approach) requires a particular attention to processes and operational organization, in particular by redefining technical support (thanks to new technologies) and by implementing adapted quality tools. The control at the end of the production line is essential to ensure the manufacturing quality of each product. Quality control can be fully automated but human verification is also very often undertaken by qualified operators. Rising production and raw material costs are creating a growing need for automated quality control throughout the production chain. It is an essential tool to reduce manufacturing errors and therefore waste at the end of the chain. The research work presented in this article aims to establish a model allowing the company to enter the industry 4.0 (or industry of the future) through the automation of quality control to improve their reliability by freeing themselves from human errors related to the repetitive nature of these tasks. to measure the quality index of production within the industrial chains. Indeed, the conformity of products cannot yet be guaranteed directly without measurement. This last one (conformity measurement) allows to locate and follow the evolution of a parameter in time, to analyze it on a given period, to correlate it with other related values and to act to improve it in order to control and adjust the production process in real time; This decision support model is based on the fuzzy logic theory, it consists in modeling the relevant decision criteria which influence the quality of the production, which are: the rate of conformity, the rate of reworked product and the rate of non-conforming product but accepted under exemption. Thus, determine the most predominant factor. For the validation of this proposed model, an experimental study was conducted to control the production quality in an automotive parts manufacturing line. The proposed model meets the desired objective and is therefore retained as a model to ensure the quality of a manufactured product.