Research On Planning Of Piston Production Line Based On Job Fatigue Degree

With the development of automobile industry, the variety of consumer demand and the increasingly fierce competition, the piston types are more and more, piston shape is more complicated, the machining precision requirement is more high, and a large amount of manual labor are consumed when piston batch replacing, so as to increase the fatigue degree of workers, even possibility make workers face the various occupation hazard, decline production, result in injury or death accidents, to cause inestimable economic losses for the enterprise and the society. Therefore, this paper takes the job fatigue degree of piston production as the breakthrough point, studies the planning design of piston production line, to reduce the job fatigue degree of workers, and make the planning design and running of piston production line more reliable, efficient, and ultimately improve the rapid reaction capability of piston enterprises on the product and labors market.After analyzing on the processing route of piston and main processes, the job fatigue evaluation system of piston production line is advanced and the job fatigue multiple quantitative model is established. The results show that operation difficulty is the most important factor to affect the fatigue for the piston production line, followed by mental load, force load, and operational posture. And the oxygen saturation experiment also demonstrates that the evaluation quantitative models can show the job fatigue level of the production line.Aimed at the process of piston production, the clustering way is built based on job fatigue such as processing requirements, processing method, positioning and clamping to realize the job fatigue features clustering of the piston minimum process, in order to achieve the process planning model where the similar job fatigue level process units don’t cluster taking the process complexity and difficulty as the control target, so as to effectively reduce the process time and job fatigue. Taken piston production line A as an example, the results show that:the production line B after recombinated based on the time balanced, whose total job fatigue degree decreases from42.8636to37.6619, and job fatigue loads between different processes are more balanced.Combined with the goals of balancing and optimization, a new balancing model of piston production line establishes based on the job fatigue; the fatigue smoothness coefficients SI and balancing delay rate Ω are introduced to reflect the degree of load balancing and the quantity of workers. For balanced time-based production line B, a model was established based on the job fatigue, and solved by Genetic Algorithm to design the new production line C. The results show that:the number of workers is at least5based on the job fatigue balanced production line C, and both SI and Ω are lower than that of the production line B, and the job fatigue loads of workers has been improved. Simulating and analyzing the production line A, B, C, the results show that: SI of the production line C is484.1, lower than that of B, decreased by83.57%; the standard deviation of job fatigue degree is722.8176and most balanced; the standard deviation of effective job fatigue is47.72, and most balanced; the production capacity is highest; and the total energy consumption is1776.60Kcal, lower than that of the production line B.A multi-objective optimization model of piston production line is advanced based on job fatigue with the application of logistics and staffing optimization theory, which is solved by Genetic Algorithm and simulated by DELMIA software. The results show that:for the new piston production line C, an covers area is128.95m2, lower than that of A, and decreased by61.11m2; job fatigue degree is5899.0589, compared with the original production line A, decreased by36.67%; according to analyzing the equipment utilization, labor utilization, area utilization, material transmission cost and energy consumption of different layout forms and using the Analytic Hierarchy Process, the different layouts’ optimization results of the logistics cost and the job fatigue degree are obtained; if θ1,θ2values changed, the logistics optimization goals and job fatigue optimization goals of different layouts are transformed, and the obtained whole optimal layout styles will be different.