Research On The Causes And Early Warning Of Human Error In Lathe Processing Based On Improved HFACS

The mechanical manufacturing industry is a basic economic development industry in China.Lathe processing is a common basic operation mode in mechanical manufacturing.The quality,accuracy,and efficiency of lathe processing are increasing.However,in this development process,problems such as the increased risk of lathe processing and reduced operating efficiency caused by human errors are still widespread.Therefore,in order to reduce the damage caused by human errors to people and equipment and improve the efficiency of lathe processing operations,it is necessary to pay attention to the study of human errors in the process of lathe design.The key to the study of human error in lathe processing is to analyze the causes and give early warning.Therefore,this study refers to the causes of human errors in other industries and the safety evaluation of machining.Based on the improved HFACS model,the specific causes of human errors in lathe machining are explored from multiple dimensions,and a safety early warning model is established.The main research work of this paper is as follows:(1)Previous work on human error research is reviewed,and specific theoretical models and methods applicable to human error analysis in lathe machining are studied and screened.Characteristics of lathe machining operations,lathe operator error accidents,and lathe operator error psychology and behavior are analyzed;(2)A Human Factors Error Analysis Classification Framework for Lathe Machining Accidents(HEACF-LMA)model was constructed.Based on the characteristics of lathe machining operations and the analysis of lathe operators’behavior and psychology,the HFACS model was improved and the HEACF-LMA model,which is more suitable for analyzing lathe machining operations from multiple dimensions,was established,and the factor reliability and classification consistency of the model were tested.The test results indicate that the model has certain reliability and feasibility;(3)The causes of human error for lathe machining operators were extracted.A fault tree was compiled for the different turner errors collected to obtain specific patterns of turner error behavior and the causes of explicit human errors.The results were analyzed in conjunction with the HEACF-LMA model and the critical task flow of the turners to obtain the underlying causes of turner errors and the logical relationships between the factors.Then,the human error causes obtained from the analysis of each accident case were summarized,and the specific causes of turner errors in the lathe machining process were finally identified;(4)According to the causes of human error in lathe processing,the safety early warning index system of human error in lathe processing is established.The safety status score of the obtained secondary indicators is used as the input of the neural network security early warning model,and the human error accident level is used as the output of the early warning model,and the vehicle worker error neural network security early warning model is established.Then,six lathe processing operators from a mechanical processing enterprise in Shaanxi were selected as application cases to verify the feasibility of the early warning model.This paper introduces the human factor analysis classification system,fault tree model,error and fault model,and SRK behavior model into the lathe machining field.Through three levels:analysis of human error formation mechanism of lathe machining operations,analysis of error behavior patterns and extraction of human error causes,the causes of human errors during lathe machining operations are analyzed and summarized,and a neural network safety warning model is established based on the factors obtained.Through model monitoring and early warning of human error behavior,the occurrence of unsafe accidents is prevented to improve the lathe processing ability and reduce the operation risk.It also provides some reference for the later research on lathe equipment design,lathe processing efficiency,mechanical manufacturing safety analysis,and lathe processing human error accident data collection.