Research on industrial product quality and safety risk assessment under the background of big data

Abstract

According to the current industrial technology development situation, in order to ensure product quality and safety implementation of safety risk management, according to the key products, key industries, key regions for risk monitoring and analysis assessment, can be found as soon as possible, the quality and safety risks of industrial products, effectively solve the related problems. Nowadays, after entering the background of big data era, industrial product quality inspection institutions have gradually accumulated a large amount of testing data and operation experience after daily inspection work. Without in-depth analysis and effective mining of these data, it is difficult for these contents to generate effective value. Therefore, it is necessary to build a scientific product quality and safety risk assessment model, so as to accurately identify risk information in massive data information and help department employees to do a good job in risk assessment research. In this paper, on the basis of understanding the status quo of risk assessment and management of industrial product quality and safety in the environment of big data, and according to the technical characteristics of big data, the risk assessment model of industrial product quality and safety is deeply discussed. The final experimental results show that the model design can provide an effective basis for industrial product managers to make decisions.