【作者】 刘绘珍；

【导师】 张湘伟；

【作者基本信息】 广东工业大学 ， 管理科学与工程， 2012， 博士

【摘要】 改革开放30多年来,我国中小制造企业发展迅猛,成为推动经济快速发展、提供社会就业的重要力量。然而随着全球金融危机影响的逐步蔓延,各国贸易保护主义逐步升级,我国沿海地区众多中小制造企业赖以生存的出口市场出现明显萎缩。多品种、小批量、变化莫测的需求,人工成本快速增加、原材料价格上涨、人民币汇率上升等不利因素,是众多中小制造企业当前面临的严峻挑战。在复杂多变的运营环境下,如何求得生存和发展,是众多中小制造企业迫切需要解决的的难题。订单式生产(MTO)是不少中小企业为应对复杂多变的需求环境,降低运营风险的重要运营模式；人工作业系统(MOS)因其较少的设备投资,对需求变化具较强的适应能力,因而成为我国众多中小制造企业主要采用的生产系统结构模式。面对复杂多变的运营环境下,从降低成本、增加柔性、满足需求等角度,研究MTO/MOS的员工组织与优化、计划调度的理论和方法,是关系到中小制造企业生存和发展的重要问题。本文从如下四方面对MTO/MOS进行研究：(1)MOS组织模式。针对MOS的结构和特点,分析了生产实践中常用的三种静态组织模式,构建了不同条件下各种组织模式计划期产出量模型。借助算例从数值上分析不同模式在不同条件下的优劣。(2)工人多技能配置。比较分析了负荷平衡模型和技能链模型两类模式,并运用这两种模型分析了工人技能量最优配置,结果显示：当任务需求波动较小时,采用负荷平衡模型,所需培训技能总人次较小；反之,采用技能链模型效果更佳。优化结果还发现：随着需求波动的加大,采用技能链模型所需培训技能总人次增加比较缓慢,具有更好的稳健性。(3)工人需求量配置。首先分析了影响工人数量的三个因素：生产的波动性、工人多岗使用、以及加班和临时用工；其次,基于上面三个因素,以总成本最小为目标函数,建立了以工人需求量为决策变量的两阶段优化模型,分别采用积分和嵌套遗传算法求解两作业小组和多作业小组构成的模型,并用两作业小组的优化结果验证了嵌套遗传算法的有效性。结果表明：随着工人成本的增加,作业小组最优工人需求量随之减少,而总成本增加；随着效率因子的降低,工人数量将会增加,同时总成本也将增大。(4)订单任务调度优化。研究了订单任务的静态和动态调度优化问题。首先,基于模糊交货期和随机加工时间,提出采用遗传算法求解订单任务调度问题；其次,考虑人工作业系统较好的柔性,借鉴单机调度的理论方法,提出了一个启发式算法IEDD;最后,借助GA算法和IEDD规则,通过仿真研究了MTO/MOS的调度优化问题,并与传统启发式算法EDD、STR、CR和SPT进行比较分析,结果表明,本文提出的GA算法和IEDD方法更为有效。此外,借助双边匹配的思想,同时考虑生产成本和客户满意度,利用GA算法对订单任务调度问题进行多目标优化。最后,对全文所做的工作进行了总结,并对未来的研究方向进行了展望。本课题的研究得到到国家自然科学基金资助项目：订单式生产人工作业系统(MTO/MOS)组织与优化研究(70971026)的支持。更多还原

【Abstract】 Since the reform and opening up for over 30 years, Chinese small and medium-sized manufacturing enterprises have developed rapidly, becoming the important strength to promote the development of economy rapidly and provide social employment. However, with the impact of the global financial crisis spreading and countries trade protectionism upgrading gradually, the export market that small and medium-sized manufacturing enterprises in our coastal areas lived on atrophy obviously. Serious challenges that many small and medium-sized manufacturing enterprises face today include such negative factors as various, small batch and unpredictable demand, the rapid increase of labor costs, raising prices of raw materials and the rise of RMB exchange rate. How to seek for survival and development in the complex operating environment is the problem that small and medium-sized manufacturing enterprises need to be urgently solved.Make to Order (MTO) is an important operation mode that many small and medium-sized enterprises used to cope with the needs of the complex and changeable environment and reducing the operation risk. Manual Operation System (MOS) has become the production system structure mode and our small and medium-sized manufacturing enterprises mainly used for its less equipment investment and strong adaptability to the change of need. Facing the complex operating environment, studing the theory and methods of MTO/MOS employee organization and optimization and planning scheduling from the aspects of lower cost, increasing flexibility, meeting the demand are of great importance to the survival and development of small and medium-sized manufacturing enterprises. This paper studies MTO/MOS from the following four aspects:(1) Organization mode of MOS. According to the structure and characteristics of MOS, this paper analyzes three kinds of commonly used static organization mode in the production practice, building different plan period output models in all kinds of the organization under different conditions. This paper analyzes the pros and cons of different mode numerically under different conditions with an example. (2) Workers multi-skills configuration. This paper compares CP-cherry picking with SC-skill chaining, and analyzes the optimal allocation of workers’skills by these two modes. The optimization results show that the lesser the task demand fluctuation is, the fewer skills need to be trained by CP-cherry picking, otherwise by SC-skill chaining. The optimization results also find that with the increase of demand fluctuation, the total of skills need to be trained increases slower by SC-skill chaining which is more effective.(3) Workers demand configuration. First, This paper analyzes three influence factors on the number of workers:the volatility of the production, cross-training workers, and work overtime and temporary employment; Secondly, based on the above three factors, with the objective function of minimum total cost, this paper sets up a two-stage optimization model for decision variable with the demand of workers. This paper solves the models composed by two and much operation teams respectively by the integral and nested genetic algorithm and verifys the effectiveness of nested genetic algorithm by the optimized results of the two operation teams. The results show that, with the increased cost of workers, the optimal operation team workers’demand decrease, and the total cost increase; with the efficiency factors lower, the number of workers will increase, and the total cost will also increase.(4) Order task scheduling. This paper studies the static and dynamic scheduling problems of the order task. First based on the fuzzy due date and random processing time, this paper puts forward solving order task scheduling problem by genetic algorithm; Second, taking the well flexibility of artificial operation system into consideration, this paper puts forward a heuristic algorithm IEDD from the scheduling theory method; Finally, with the aid of the GA algorithm and IEDD rules, this paper studies the scheduling problem of MTO/MOS through simulation, and compares with the traditional heuristic algorithm EDD, STR, CR and SPT, which show that the GA algorithm and IEDD method proposed in this paper are more effective.In addition, with the thought of bilateral matching, and considering the cost of production and customer satisfaction, multi-objectively optimizing the order task scheduling problem is studied by GA algorithm.Finally, summarize the whole text, and the future research direction is given. This research is supported by the national natural science funds projects:research on optimization and organization of make to order and manual operation system (70971026).更多还原