变扰动强度下柔性装配作业车间调度性能分析

柔性装配作业车间是柔性作业车间的一类现实化扩展,其调度问题既要考虑复杂的加工路径柔性,还要考虑零件间的装配关联约束,以及由其带来的关联零件生产进度协同难题.首先给出了柔性装配作业车间调度问题的数学模型;然后考虑现实生产中普遍存在的随机扰动,采用了完全反应式与预测-反应式两类动态调度策略,并提出了相应的优先度规则算法和周...     

考虑设备预维护的柔性作业车间调度节能优化方法

随着能源成本的飙升和环境日益恶化,实现节能生产的策略越来越受到制造企业的关注.在车间实际生产调度过程中,机床设备的故障与维护会影响车间调度方案的顺利执行,进而导致出现车间加工资源冲突、能耗增大和完工时间延长等问题.为减少实际柔性作业车间加工过程中出现由于机床故障而导致加工中断的情况,提出一种考虑设备预维护的柔性作业车间调度节能优化方法.分析考虑设备预维护的柔性作业车间能耗特性,建立考虑设备预维护的柔性作业车间调度节能优化模型,设计机床预维护策略,并在此基础上提出一种启发式框架下的调度算法对节能优化模型进行求解,通过不同方案的对比分析,验证所提方法的有效性.     

成组生产方式下生产调度和设备维护的多目标联合决策问题

针对成组生产方式下单机系统对生产调度和设备预防性维护的迫切关注,提出一种集成优化模型,以满足成组生产方式下的零件加工和设备维护需求。该集成优化模型除考虑加工同种零件、同零件族的不同种零件以及不同零件族应具备的学习遗忘效应外,还提出一类考虑设备运行的劣化效应,对设备采取完美维护方式的预防性维护,当突发故障发生时采取小修方式。为了满足生产调度和设备预防性维护的双重需求,该集成优化模型以最小化总完工时间和维修成本为多目标,并利用遗传算法对模型进行求解。通过算例分析表明了该集成优化模型的可行性和有效性。     

多层级装配作业车间等量分批策略与调度算法

针对多层级装配作业车间中差异化零部件的加工装配进度协同极为困难的问题,通过零部件合理分批来提升车间的流动性,进行更灵活的进度协同并缩短生产周期,给出了此类车间最小化Makespan的分批调度模型;提出加工/装配阶段的分批策略,以及基于可行域搜索的改进型遗传算法,其初始种群生成及交叉变异考虑了批量变化带来的约束动态性,能够始终保证进化过程中染色体的合法性.通过实验验证了算法的基础性能,揭示了4种分批策略对不同产品结构的适应性,并验证了协同复杂性导向策略的效果.     

考虑衰退的流水车间生产与预防性维护集成调度方法

为有效解决流水车间生产与预防性维护的集成调度问题,提出考虑设备衰退的基于改进人工蜂群算法的集成调度方法。对具有设备衰退特征的流水车间集成调度问题域进行了描述,并以最小化完工时间和最小化维护成本为优化目标建立了数学规划模型。针对生产与维护两个决策变量,提出改进双目标人工蜂群算法。该算法融合改进的基于分类排序的Pareto遗传算法的快速排序规则,引入局域禁忌搜索策略和概率接受准则以提高搜索性能。仿真实验表明了该算法的可行性和有效性。     

机器混合故障下柔性作业车间鲁棒调度方法

柔性作业车间机器在生产过程中时常发生退化故障和突发故障，针对这种混合故障，考虑用预防性维护来防止退化故障，通过插入缓冲时间的方式来吸收突发故障的影响。分别以工序最终完工时间期望值和各工序加工完成时间的延迟总和期望值为质和解的鲁棒性指标，建立柔性作业车间鲁棒性调度优化模型，并设计引入混合故障概率矩阵的改进遗传算法对模型求解，联合决策工序加工顺序、预防性维护位置和缓冲时间位置，同时优化调度方案的鲁棒性。最后通过数值实验与对比分析验证了此鲁棒调度方法能有效应对车间混合故障造成的扰动。     

个性化定制车间生产-物流协同调度框架与算法研究

为解决个性化定制车间生产-物流协同动态调度问题,提出一个完全反应式调度信息-物理系统框架。在该框架基础上,提出一种“单步”调度算法并重点设计了一个综合考虑客户满意度、设备利用率与能耗的任务优先级计算规则。由于“单步”调度算法每次只考虑当前一步的生产或物流任务的调度,生产-物流协同能力较弱,所以为了弥补该缺陷,又在其基础上提出一种综合考虑生产与物流两步任务调度的“双步”调度算法。针对车间内可能发生的设备故障等扰动,设计抗扰动机制以增强两算法的抗扰动能力。仿真试验结果表明,“单步”调度算法虽然优于传统调度规则但却不如“双步”调度算法;后者能在一定扰动情况下,更好地配置生产与物流资源,且在“工件平均提前/拖期成本”指标上表现尤为出色,更能适应个性化定制场景。     

考虑动态资源和工件批量约束的柔性车间生产调度

针对实际车间生产调度过程中车间设备资源受上一调度周期剩余任务影响、工件批量和加工路径柔性等问题,构建考虑设备动态负荷和工件批量约束的柔性车间生产调度模型。提出双层嵌套式遗传算法:外层遗传算法确定工件批量划分和各子批零件的工艺路径,并设计一种基于设备优选法的解码算子来确定个体对应的批量划分中各子批零件的工艺路径;内层遗传算法确定外层遗传算法个体所对应的工件分批和加工路径约束下的调度方案,调度方案的完工时间和超出交货期时间将反馈到外层遗传算法中,用于综合评估当前分批和加工路径方案的性能,实现综合优化。最后在柔性调度标准案例10×10案例基础上增加批量、交货期、设备资源等约束,对所提模型和算法进行测试,结果表明所提算法在对工件进行合理分批和工艺路径确定的同时,能够优化调度结果,满足产品交货期和设备资源约束。     

基于多目标混合殖民竞争算法的设备维护与车间调度集成优化

在制定调度计划时考虑设备预防性维护可以提高设备利用率和资产效率。首先,依据实际制造车间生产环境,在每台机器的可靠度降低到阈值的时候安排预防性维护,建立柔性作业车间设备预防性维护与调度集成优化的数学模型,以最小化最大完工时间、总生产成本和平均总维修成本为目标。然后,提出一种多目标混合殖民竞争算法求解该模型,设计相应的编码、解码、殖民国家同化过程以及多目标混合殖民竞争算法的流程,并采用改进加权TOPSIS方法在获得的Pareto解集中选择满意解,以达到提高设备的可靠性、按期交货和节省成本的目的。最后通过具体实例验证提出策略的可行性和有效性。     

成组方式下考虑故障率限制的生产调度模型

针对成组生产方式下的单机加工系统,提出一类考虑设备故障率限制的生产调度优化模型,以贴近实际加工情况。该优化模型以最小化总完工时间和总维护成本为目标,除考虑与相似度相关的生产设置时间和加工零件的学习遗忘效应外,还考虑了设备劣化效应,并采用预防性维护和小修相结合的混合维护方式,基于故障率阈值,采取适当的预防性维护以有效避免维护不足或过量,对于批量加工过程中的设备突发故障则采用基于役龄的小修。根据优化模型的数学特征,利用遗传算法求解模型。通过算例数值结果表明所提出的优化模型可在避免维护不足或过量的同时,进一步减少维护成本和缩短完工时间。     

An adaptive approach to dynamic scheduling in knowledgeable manufacturing cell

To overcome deficiency in the global capacity of a single dispatching rule, it is vital to select a dispatching rule in real time for dynamic scheduling. Among the studies addressing the method for selecting dispatching rules, few have no requirements for domain knowledge or accurate training example, which is hard to acquire from the real production system. In this paper, a new learning algorithm, along with the presentation of an adaptive scheduling control policy, is proposed to obtain the dynamic scheduling knowledge effectively, and different dispatching rules are selected to schedule the jobs in the machine buffer according to the current transient state of the system. Case studies are given to illustrate the validity of the scheduling control policy.     

基于Agent的芯片制造生产线动态调度方法研究

基于智能体技术,提出了芯片制造生产线动态调度新方法,实现了投料调度、工件调度与设备维护调度的集成。首先,给出了基于智能体的动态调度模型,该模型中包括管理智能体、投料智能体、工件智能体、设备智能体、运输智能体与人员智能体。投料智能体用于实现投料控制,工件调度通过工件智能体与设备智能体之间的协商实现,设备维护调度由设备智能体实现。通过智能体间的合作,能够实现投料控制、工件调度与设备维护调度的协同进行。然后给出了工件智能体与设备智能体问协商使用的协商协议（即带有时间约束的单步协商协议）,以及智能体决策中使用的调度算法（包括投料调度算法,工件调度算法与设备维护调度算法）。最后,通过实例,给出了方法的使用过程,并进行了模拟仿真。仿真结果表明,集成的调度方法能更好地优化模型的生产率、加工周期与设备利用率,最终提高准时交货率。     

Design of due-date oriented look-ahead batching rule in wafer fabrication

In wafer fabrication processes, batch processing accounts for over 30% of the overall processing time. And it’s a trade-off between machine utilization and wafer waiting time. Therefore, batch machines have become one of the constraint resources during wafer fabrication. How to maintain the utilization and reduce the waiting time are important tasks for production control. Plenty of research in the past several years focused on the dispatching rules of batch processing. According to many researchers, look-ahead batch dispatching rules outperform MBS on waiting times and machine utilization. The look-ahead batching rules that have been developed are DBH, NACH, MCR, and DJAH. However, these rules do not take the due-date information of wafers into consideration, and can’t accelerate the wafer’s fabrication that will not be completed before the due-date. This study will develop a due-date oriented look-ahead batching rule, namely LBCR, that considers the due-date and expects to raise delivery rates and reduce the average tardiness. Firstly, this study will modify those batching rules to fit the manufacturing environment of wafer fabrication. There are serial simulation tests on those batching rules under various kinds of factors in terms of environment, including traffic intensity, product numbers and product mix rate. Finally, this study will compare the five batching rules on different performance indicators. After the simulation and statistic analysis undertaken, LBCR does outperform other batch dispatching rules on due-date related performance indicators, such as tardy rate and average tardiness.     

A study on the weighted composite dispatching rule in modular production systems

Scheduling semi-conductor manufacturing process systems is a complicated and difficult job, due to such characteristics as re-entry into manufacturing processes, high uncertainty of processes, and products and technologies changing rapidly. The researchers have carried out many studies to find efficient techniques for semi-conductor manufacturing systems with a view to accomplishing the goals of systems, such as saving cycling time and increasing production quantity per unit time. The production flow in the semi-conductor industry has the most unique characteristics, which makes it difficult to plan production and to schedule semi-conductor manufacturing. Currently, the scheduling methods in semi-conductor assembly processes follow the dispatching rule on a simple first come first serve (FCFS) basis, and a backlog is operated as a buffer based on the daily production quantity. In this study, therefore, we will apply various dispatching rules on a real-time basis and verify the effect and result of exact scheduling through simulation, based on the assumption that competitive advantages in production come from efficient inventory control and exact scheduling.     

生产计划和预防性维修计划的统筹优化模型

在对两种计划独立决策模型分析的基础上,提出了一个统筹安排生产计划和设备的预防性维修计划的优化决策模型。模型参考生产设备的失效概率分布函数,将设备的失效时间估计以及设备的维修时间引入生产计划决策变量空间,将生产延误最小化作为决策目标。最后,对一个生产实例进行了对比分析,结果发现应用该决策模型比分别安排两种计划的决策使生产延误减少了近30％。     

A note on single-machine scheduling with learning effect and an availability constraint

Recent empirical studies in several industries have verified that unit costs decline as firms produce more of a product and gain knowledge or experience. This phenomenon is known as the “learning effect.” However, most of the papers assume that the machine is available at all times. In reality, the machine might become unavailable due to machine breakdowns or preventive maintenance during the scheduling period. Motivated by this, single-machine scheduling problems with considerations of the learning effect and machine availability are considered in this paper. It is shown that the shortest processing time rule provides the optimal schedules for the makespan and the total completion time minimization problems when jobs are assumed to be resumable. Moreover, mixed integer programming techniques are used to solve the problems when jobs are non-resumable.     

Single-machine-based production scheduling model integrated preventive maintenance planning

Manufacturing and production plants operate physical machine that will deteriorate with increased usage and time. Maintenance planning which can keep machines in good operation is thus required for smooth production. However, in previous research, production scheduling and maintenance planning are usually performed individually and not studied as an integrated model. In order to balance the trade-offs between them, this study proposes an integrated scheduling model by incorporating both production scheduling and preventive maintenance planning for a single-machine problem with the objective of minimizing the maximum weighted tardiness. In this model, a variable maintenance time subjected to machine degradation is considered. Finally, a numerical example using this improved production scheduling model is shown. The computational results prove its efficiency.     

Performance evaluation of priority dispatching rules in multi-level assembly job shops with jobs having weights for flowtime and tardiness

The problem of scheduling in dynamic shops is an important operational problem in view of its complexity and significance in terms of associated costs of scheduling. While a number of research studies have investigated the problem of scheduling in flow shops and job shops, only some attempts have been done to study the problem of scheduling in assembly job shops that manufacture multi-level jobs. The problem of scheduling in dynamic assembly job shops with jobs having weights for holding and tardiness of jobs deserves due attention. In this study an attempt has been made to propose new priority dispatching rules that minimize the performance measures related to weighted flowtime and weighted tardiness of jobs. The existing unweighted dispatching rules have been modified in view of the consideration of weights for flowtime and tardiness of jobs. The performances of the (modified) existing dispatching rules and the proposed dispatching rules are compared through exhaustive simulation experiments with the consideration of a number of different experimental settings involving due-date setting, utilization levels and types of job structures. The proposed dispatching rules are found to perform better than the existing ones in most experimental settings and with respect to a number of measures of performance.     

飞机复合材料部件装配调度算法研究

以优化飞机复合材料部件装配顺序、缩短部件装配时间为目标,构建了复合材料部件装配调度模型,提出了一种启发式算法与禁忌搜索算法相结合的调度算法（HTA-AJSP）,并对其进行了优化,通过采用变邻域搜索和禁忌规则,很好地避免了算法搜索陷入局部最优。通过分析与实例验证,并与启发式算法和局部搜索算法进行比较,所提出的算法在产品装配调度优化问题上取得了比较满意的效果,缩短了装配周期,提高了装配效率。     

飞机复合材料部件装配调度算法研究

以优化飞机复合材料部件装配顺序、缩短部件装配时间为目标,构建了复合材料部件装配调度模型,提出了一种启发式算法与禁忌搜索算法相结合的调度算法(HTA-AJSP),并对其进行了优化,通过采用变邻域搜索和禁忌规则,很好地避免了算法搜索陷入局部最优。通过分析与实例验证,并与启发式算法和局部搜索算法进行比较,所提出的算法在产品装配调度优化问题上取得了比较满意的效果,缩短了装配周期,提高了装配效率。