基于作业疲劳度的活塞生产线规划研究
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摘要
由于汽车行业的发展、消费者需求的多变性和市场竞争的需要,活塞品种越来越多,形状越来越复杂,加工精度要求越来越高,批次更换时耗费大量的手工劳动,作业难度增加,工人的疲劳程度也越来越大,由此面临的各种职业危害可能性也日益增大,生产率降低、生产质量下降、严重时甚至发生工伤甚至死亡事故等,给企业和社会造成不可估量的经济损失。因此,论文以活塞生产性作业疲劳度为切入点,对活塞生产线的规划设计研究,以减少工人作业疲劳度、使活塞生产线的规划设计和运行更加可靠、有效,最终提高活塞企业对产品市场和劳动力市场变化趋势的快速反应能力。
基于活塞工艺路线以及主要工序操作分析,提出活塞生产线的作业疲劳评价体系,建立作业疲劳多指标量化模型。结果表明：在活塞生产线上,作业难度是影响作业疲劳的最主要因素,依次为心理负荷、用力负荷、作业姿势,同时利用血氧饱和度实验证实了该评价量化模型能够反映活塞生产线上的作业疲劳程度。
通过对活塞加工工艺过程的分析,建立以加工要求、加工方法、定位方式和夹紧方式为作业疲劳特征的聚类方式,实现活塞最小工艺单元的作业疲劳特征聚类,达到以工序复杂程度和难度为控制目标的同类作业疲劳程度工艺单元不能聚类的工艺规划建模,从而有效降低工序作业时间和作业疲劳。通过对生产线A进行工艺分析聚类,结果表明：重新组合后基于时间均衡的新生产线B总的作业疲劳度指数由42.8636减少到37.6619,且不同工序间的作业疲劳负荷较为均衡。
结合生产线平衡优化目标,建立了基于作业疲劳度的活塞生产线平衡新模型,引入了作业疲劳度平滑系数SI和平衡延迟率Ω用来反映作业疲劳负荷平衡程度和作业人员的数量。针对新生产线B,建立基于作业疲劳度的生产线平衡模型,利用遗传算法求解,构建新生产线C。结果表明：新生产线C的工人数量最少为5人,作业疲劳度平滑系数和平衡延迟率均比生产线B降低,工人的作业疲劳负荷得到了改善。对原生产线A,新生产线B和新生产线C进行仿真分析,结果表明：生产线C上作业疲劳平滑率为484.10,比生产线B降低83.57%,工人疲劳负荷最均衡,标准差为722.8176,有效作业疲劳得到均衡,标准差为47.72,生产能力最高,能耗总量为1776.60Kcal,低于生产线B,且工人能耗均衡,标准差为20.2650Kcal。
应用物流优化和人员配置优化的基本思想,结合生产线布局的优化目标,提出了基于作业疲劳的活塞生产线多目标优化模型,利用遗传算法进行求解,并采用DELMIA软件按照不同的布局形式对其进行仿真。结果表明：利用新模型求解得到的布局C,与原生产线A相比,占地面积为128.95m2,比原生产线A减少了61.11m2；作业疲劳度为5899.0589,比原生产线A降低36.67%；通过对不同的布局形式下设备利用率、工人工时利用率、面积利用率、物料传输成本以及能量消耗量分析；利用层次分析法,得到不同布局形式下的物流成本和作业疲劳度优化结果。调整θ1,θ2的取值,各种不同布局形式下物流优化目标和作业疲劳优化目标随之改变,所获得的全局最优的布局形式也会不同。
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.
基于活塞工艺路线以及主要工序操作分析,提出活塞生产线的作业疲劳评价体系,建立作业疲劳多指标量化模型。结果表明：在活塞生产线上,作业难度是影响作业疲劳的最主要因素,依次为心理负荷、用力负荷、作业姿势,同时利用血氧饱和度实验证实了该评价量化模型能够反映活塞生产线上的作业疲劳程度。
通过对活塞加工工艺过程的分析,建立以加工要求、加工方法、定位方式和夹紧方式为作业疲劳特征的聚类方式,实现活塞最小工艺单元的作业疲劳特征聚类,达到以工序复杂程度和难度为控制目标的同类作业疲劳程度工艺单元不能聚类的工艺规划建模,从而有效降低工序作业时间和作业疲劳。通过对生产线A进行工艺分析聚类,结果表明：重新组合后基于时间均衡的新生产线B总的作业疲劳度指数由42.8636减少到37.6619,且不同工序间的作业疲劳负荷较为均衡。
结合生产线平衡优化目标,建立了基于作业疲劳度的活塞生产线平衡新模型,引入了作业疲劳度平滑系数SI和平衡延迟率Ω用来反映作业疲劳负荷平衡程度和作业人员的数量。针对新生产线B,建立基于作业疲劳度的生产线平衡模型,利用遗传算法求解,构建新生产线C。结果表明：新生产线C的工人数量最少为5人,作业疲劳度平滑系数和平衡延迟率均比生产线B降低,工人的作业疲劳负荷得到了改善。对原生产线A,新生产线B和新生产线C进行仿真分析,结果表明：生产线C上作业疲劳平滑率为484.10,比生产线B降低83.57%,工人疲劳负荷最均衡,标准差为722.8176,有效作业疲劳得到均衡,标准差为47.72,生产能力最高,能耗总量为1776.60Kcal,低于生产线B,且工人能耗均衡,标准差为20.2650Kcal。
应用物流优化和人员配置优化的基本思想,结合生产线布局的优化目标,提出了基于作业疲劳的活塞生产线多目标优化模型,利用遗传算法进行求解,并采用DELMIA软件按照不同的布局形式对其进行仿真。结果表明：利用新模型求解得到的布局C,与原生产线A相比,占地面积为128.95m2,比原生产线A减少了61.11m2；作业疲劳度为5899.0589,比原生产线A降低36.67%；通过对不同的布局形式下设备利用率、工人工时利用率、面积利用率、物料传输成本以及能量消耗量分析；利用层次分析法,得到不同布局形式下的物流成本和作业疲劳度优化结果。调整θ1,θ2的取值,各种不同布局形式下物流优化目标和作业疲劳优化目标随之改变,所获得的全局最优的布局形式也会不同。
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.
引文
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