The compensation and correction effect of AI on executant in modern large-scale industry

Abstract

Artificial intelligence is defined as "a machine that has the ability to simulate learning characteristics or intelligent features that can be accurately described". This paper explores the compensatory effect of AI in industrial production on employees' task completion based on the intelligent scrap grading system of two steel enterprises in China, Tangshan Iron & Steel and Chengde Iron & Steel. This paper provides a detailed overview of the scrap grading application, a detailed description of the key processes such as quality inspection, unloading and settlement, and an analysis of the multi-layer information collection design, anti-cheating design, security design, and information storage and traceability design of the intelligent grading system. The differences between the intelligent scrap grading system and the traditional manual grading are systematically organized in the context of specific cases in Tangshan Iron & Steel and Chengde Iron & Steel. The application of artificial intelligence in the judgmental work task better compensates for the completion of the task. In this paper, using specific cases from two steel companies, Tangshan Iron & Steel and Chengde Iron & Steel, it was found that the average of deducted weights increased by 41.94 kg, or about 9.9% of the magazine deducted weight, after the adoption of the intelligent scrap grading system. At the same time, the use of the intelligent grading system also causes a reduction in the standard deviation of the deducted weight within a single day in the same steel Department, and artificial intelligence can help workers compensate for the structural low deducted weight of vehicles. In order to identify the paths that lead to the increase of buckling weight level and the decrease of buckling weight standard deviation, this paper made further analysis using data from two major steel companies and proved the existence of two paths. First, there is an emotional quality check by quality inspection personnel in the quality inspection process, and the intelligent grading system reduces the power rent-seeking tendency of quality inspection personnel. After the introduction of intelligent grading system, it is easier to exist "acquaintance" relationship with the provincial supplier's weight deduction results increased more significantly. The second intelligent rating system is more significant for the full load state correction effect, can help quality inspection personnel to make better real-time decisions to achieve the compensation effect of the completion of the task. In order to further illustrate the effect produced after the application of artificial intelligence to industrial production, this paper conducted a series of robustness tests. This paper constructs "pseudo-policy shocks" with one-month and two-month processing times in advance. The empirical results show that the intervention effects of both the "pseudo-policy shock" experiment with a one-month advance and the "pseudo-policy shock" experiment with a two-month advance are not statistically significant, and even show that the weight deduction results are not significant at all. The intervention effect was not statistically significant, and even showed that the weight deduction result was reduced after "using the scrap smart system". In this paper, the ratio of the deducted weight result to the total weight of the truck load of scrap was selected for testing. The adoption of the Smart Scrap Grading System by steel companies effectively reduces the variance of 0.632 and reduces the variability between the grading results. This paper also analyzes the function of the intelligent grading system to reduce the emotional quality and help check the cheating behavior of suppliers using the deduction rate, and confirms again the existence of the function of the intelligent grading system to reduce the emotional quality of employees; and the application of artificial intelligence in industrial production to make up for the shortcomings in employee grading, so that the "full-load operation state The application of artificial intelligence in industrial production makes up for the shortcomings in staff grading, and makes it possible to effectively check the cheating behavior of suppliers even under "full-load operation".