制造系统人力配置优化建模与研究
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摘要
封装测试制造业通常以月为周期根据人机比手动实现人力资源配置,此流程造成大量手动工作量,更因产量需求和人员出勤变化导致人力配置需求预测的低准确性。因此,本文将介绍一种新的方法,它基于线性规划模型并以班次工作量为依据,消除因产量需求变化和人员出勤的影响提高预测准确性。在半导体行业日常运作中实行这种方法的关键是如何使它更接近生产线实际情况,包括人机干涉,考虑实际可用人员、设备等。本文介绍的是一种以工作量为依据实现班次人力配置的自动整合系统,在实现交叉培训和复合技能人员的前提下,这种解决方案可以优化一个区域,甚至整个工厂的人力配置。作为计算机整合系统,配置方案用到的线性规划方程将由iLOG CPLEX软件提供的线性规划求解器帮助求解,大大降低了手动工作量,使以班次为周期的配置计算成为可能,从而极大消除了在制品和设备波动对人力配置的影响,使得人力配置在微管理下更合理。模型使用工厂物理排队论建立自调节模型解决人机干涉问题。模型将验证特定人力配置下的设备能力损失是否能为当前状态所担负。当设备能力不足以维持产能需求时,系统会增加人力并重新模拟计算。此循环将一次次求解可能的配置方案直到得到可行结果。系统为终端用户开发了友好的图形用户界面以帮助使用者方便的输入数据,如当前班次的可用人数、目标产量、设备转换计划等。时时数据将有助于得到更可靠的配置方案,系统能在两分钟内计算并输出数据表直接建议生产主管哪位员工配置在哪个指定工位上,提高班次人力配置和复合技能生产人员交叉支持有效性。本以工作量为基础的人力配置方案不仅适用于半导体制造业,也同样有助于提高其他行业的工厂人力管理效能。
In ATM manufactory, the HC is manually allocated basing on MMR by monthly. This process cause a lot of manual work loading, furthermore, the HC forecast process will introduce low accuracy because of the demand variation and worker absenteeism! Here, we will introduce a new method using work loading allocation with the Goal Programming Model by shiftily, which improves the accuracy by eliminate the impact of the demand variation and worker absenteeism. The difficulties to implement this tool to daily operation in the semi-conductor industry are how to make this tool more close to line real situation with considering about the interference of machine, available HC, machine availability, ect. This paper will introduce an integrated automatic tool, which allocate the shiftily HC base on the work loading. This solution can optimize the one area HC, even one factory HC, as a cell to full utilize the cross-training and SJF resource. This tool works out the solution by goal programming with a strong line programming solver provided by the iLOG CPLEX? software. As a computer integrated tool, it can get the result by shiftily with low manual work loading, furthermore, the shiftily simulation can also eliminate the impact on HC allocation from the WIP fluctuation and machine readiness, which make the HC arrangement more reasonable by micro-management. As for man-machine interference problem, the solution given by tool has been verified by a self-adjustment model, which is developed by the factory physics queuing theory. The model will verify the machine capacity lose base on the HC allocation and check if this capacity lose is affordable by current situation. When machine capacity is not enough to support this shift loading, and system will increase the HC and do a simulation again. This loop will work out the probable solution again and again until we get the doable result. A friendly GUI is developed to end user. GUI help the end user easily input the current shift information such as the available HC, current shift goal, machine conversion plan, ect. This help solver get the real-time information and workout the more reliable solution. As a result, the tool will output a matrix to advise supervisors which labor allocates to which specific work station directly. It has been demonstrated that the tool can work out the HC allocation solution within 2 min, and this solution can help shift to allocate the labor more effectively and improve the efficiency of the SJF and cross-module supporting. The work loading allocation method is not only suitable for semi-conductor industry, but also workable in other manufactory model to help the factory management HC more efficiently.
In ATM manufactory, the HC is manually allocated basing on MMR by monthly. This process cause a lot of manual work loading, furthermore, the HC forecast process will introduce low accuracy because of the demand variation and worker absenteeism! Here, we will introduce a new method using work loading allocation with the Goal Programming Model by shiftily, which improves the accuracy by eliminate the impact of the demand variation and worker absenteeism. The difficulties to implement this tool to daily operation in the semi-conductor industry are how to make this tool more close to line real situation with considering about the interference of machine, available HC, machine availability, ect. This paper will introduce an integrated automatic tool, which allocate the shiftily HC base on the work loading. This solution can optimize the one area HC, even one factory HC, as a cell to full utilize the cross-training and SJF resource. This tool works out the solution by goal programming with a strong line programming solver provided by the iLOG CPLEX? software. As a computer integrated tool, it can get the result by shiftily with low manual work loading, furthermore, the shiftily simulation can also eliminate the impact on HC allocation from the WIP fluctuation and machine readiness, which make the HC arrangement more reasonable by micro-management. As for man-machine interference problem, the solution given by tool has been verified by a self-adjustment model, which is developed by the factory physics queuing theory. The model will verify the machine capacity lose base on the HC allocation and check if this capacity lose is affordable by current situation. When machine capacity is not enough to support this shift loading, and system will increase the HC and do a simulation again. This loop will work out the probable solution again and again until we get the doable result. A friendly GUI is developed to end user. GUI help the end user easily input the current shift information such as the available HC, current shift goal, machine conversion plan, ect. This help solver get the real-time information and workout the more reliable solution. As a result, the tool will output a matrix to advise supervisors which labor allocates to which specific work station directly. It has been demonstrated that the tool can work out the HC allocation solution within 2 min, and this solution can help shift to allocate the labor more effectively and improve the efficiency of the SJF and cross-module supporting. The work loading allocation method is not only suitable for semi-conductor industry, but also workable in other manufactory model to help the factory management HC more efficiently.
引文
[1] Gert Zulch, Sven Rottinger, Thorsten Vollstedt, A simulation approach for planningand re-assigningof personnel in manufacturing, International Journal of Production Economics, 2004, 90:265-277
[2] Jannes Slomp, Jos A.C. Bokhorst, Eric Molleman, Cross-training in a cellular manufacturing environment, Computers & Industrial Engineering, 2005, 48:609-624
[3] H.A. Eiselt, Vladimir Marianov, Employee positioning and workload allocation, Computers & Operations Research, 2008, 35:513-524
[4] Viviana I. Cesani, Harold J. Steudel, A study of labor assignment flexibility in cellular manufacturing systems, Computers & Industrial Engineering, 2005, 48:571-591
[5]侯文皓,多单元柔性制造系统的人机比建模与仿真[J],工业工程与管理,2005.6,37-41
[6]胡宗武,工业工程—原理、方法与应用,上海:上海交通大学出版社,2003.2
[7]周三多,管理学第二版,北京:北京高等教育出版社,2005.11
[8] Jason Huang, Hsin Chen Wu, Direct Labor Headcount Model Study for Semiconductor Fab Operation, Taiwan Semiconductor Manufacturing Company, 2002, 2:98-110
[9] Jie Gao, Mitsuo Gen, Linyan Sun, A hybrid of genetic algorithm and bottleneck shifting for multiobjective flexible job shop scheduling problems, Computers & Industrial Engineering, 2007, 53:149-162
[10] Gerard M Campbell, Cross-utilization of workers whose capabilities differ, Management Science, 1999, 45(5):722-732
[11] Katsundo Hitomi, Historical trends and the present state of the US industry and manufacturing, Technovation, 2005, 25:673-681
[12] Jonathan F. BARD, Staff scheduling in high volume service facilities with downgrading, IIE Transactions, 2004, 36:985-997
[13] Yuval Cohen, Gad Vitner, Subhash Sarin, Work allocation to stations with varying learning slopes and without buffers, European Journal of Operational Research, 2008, 184:797–801
[14] Y. Naveh, Workforce optimization: Identification and assignment of professional workers using constraint programming, IBM Journal of Research &Development, 2007, 51(3):263-279
[15] M. Gronalt, R.F. Hartl, Workforce planning and allocation for mid-volume truck manufacturing, International Journal of Production Research, 2003, 41(3): 449-463
[16] L. Franchini, E. Caillaud, P. Nguyen, Workload control of human resources to improve production management, International Journal of Production Research, 2001, 39(7):1385-1403
[17]布雷弗格三世,实施6西格玛,北京:机械工业出版社,2004.1
[18]彼得德鲁克,管理的实践,北京:机械工业出版社,2001.1
[19]王长琼,物流系统工程,北京:中国物资出版社,2004.1
[20]石金涛,现代人力资源开发与管理第二版,上海:上海交通大学出版社,2001.9
[21]朱道立,龚国华,罗齐,物流和供应链管理,上海:复旦大学出版社,2001.4
[2] Jannes Slomp, Jos A.C. Bokhorst, Eric Molleman, Cross-training in a cellular manufacturing environment, Computers & Industrial Engineering, 2005, 48:609-624
[3] H.A. Eiselt, Vladimir Marianov, Employee positioning and workload allocation, Computers & Operations Research, 2008, 35:513-524
[4] Viviana I. Cesani, Harold J. Steudel, A study of labor assignment flexibility in cellular manufacturing systems, Computers & Industrial Engineering, 2005, 48:571-591
[5]侯文皓,多单元柔性制造系统的人机比建模与仿真[J],工业工程与管理,2005.6,37-41
[6]胡宗武,工业工程—原理、方法与应用,上海:上海交通大学出版社,2003.2
[7]周三多,管理学第二版,北京:北京高等教育出版社,2005.11
[8] Jason Huang, Hsin Chen Wu, Direct Labor Headcount Model Study for Semiconductor Fab Operation, Taiwan Semiconductor Manufacturing Company, 2002, 2:98-110
[9] Jie Gao, Mitsuo Gen, Linyan Sun, A hybrid of genetic algorithm and bottleneck shifting for multiobjective flexible job shop scheduling problems, Computers & Industrial Engineering, 2007, 53:149-162
[10] Gerard M Campbell, Cross-utilization of workers whose capabilities differ, Management Science, 1999, 45(5):722-732
[11] Katsundo Hitomi, Historical trends and the present state of the US industry and manufacturing, Technovation, 2005, 25:673-681
[12] Jonathan F. BARD, Staff scheduling in high volume service facilities with downgrading, IIE Transactions, 2004, 36:985-997
[13] Yuval Cohen, Gad Vitner, Subhash Sarin, Work allocation to stations with varying learning slopes and without buffers, European Journal of Operational Research, 2008, 184:797–801
[14] Y. Naveh, Workforce optimization: Identification and assignment of professional workers using constraint programming, IBM Journal of Research &Development, 2007, 51(3):263-279
[15] M. Gronalt, R.F. Hartl, Workforce planning and allocation for mid-volume truck manufacturing, International Journal of Production Research, 2003, 41(3): 449-463
[16] L. Franchini, E. Caillaud, P. Nguyen, Workload control of human resources to improve production management, International Journal of Production Research, 2001, 39(7):1385-1403
[17]布雷弗格三世,实施6西格玛,北京:机械工业出版社,2004.1
[18]彼得德鲁克,管理的实践,北京:机械工业出版社,2001.1
[19]王长琼,物流系统工程,北京:中国物资出版社,2004.1
[20]石金涛,现代人力资源开发与管理第二版,上海:上海交通大学出版社,2001.9
[21]朱道立,龚国华,罗齐,物流和供应链管理,上海:复旦大学出版社,2001.4