Information-Based Dynamic Manufacturing System Scheduling

Information about the state of the system is of paramount importance in determining the dynamics underlying manufacturing systems. In this paper, we present an adaptive scheduling policy for dynamic manufacturing system scheduling using information obtained from snapshots of the system at various points in time. Specifically, the framework presented allows for information-based dynamic scheduling where information collected about the system is used to (1) adjust appropriate parameters in the system and (2) search or optimize using genetic algorithms. The main feature of this policy is that it tailors the dispatching rule to be used at a given point in time to the prevailing state of the system. Experimental studies indicate the superiority of the suggested approach over the alternative approach involving the repeated application of a single dispatching rule for randomly generated test problems as well as a real system. In pa ticular, its relative performance improves further when there are frequent disruptions and when disruptions are caused by the introduction of tight due date jobs and machine breakdown—two of the most common sources of disruption in most manufacturing systems. From an operational perspective, the most important characteristics of the pattern-directed scheduling approach are its ability to incorporate the idiosyncratic characteristics of the given system into the dispatching rule selection process and its ability to refine itself incrementally on a continual basis by taking new system parameters into account.     

基于Agent和工作流的跨企业协同制造支持系统

通过分析跨企业协同制造业务过程,提出基于Agent的柔性工作流驱动的跨企业协同制造支持平台,其核心是一组自主交互的智能Agent,通过Agent之间的协作实现协同制造任务建模、制造任务动态调度与分配、制造资源管理及制造过程管理等功能。讨论了系统结构设计、关键技术及系统实现,并以航空发动机企业间协同制造为例进行验证。系统表现了较好的模块化特性、柔性和开放性,并可能在敏捷供应链及扩散制造方面获得进一步应用。     

A mixed dispatching rule approach in FMS scheduling

Short-term scheduling in flexible manufacturing systems (FMSs) is a difficult problem because of the complexities and dynamic behavior of FMSs. To solve this problem, a dispatching rule approach is widely used. In this approach, however, a single dispatching rule is usually assigned for all machines in a system during a given scheduling interval. In this paper, a mixed dispatching rule which can assign a different dispatching rule for each machine is proposed. A search algorithm which selects an appropriate mixed dispatching rule using predictions based on discrete event simulation is developed for this approach. The search algorithm for the mixed dispatching rule is described in detail. The effectiveness (in meeting performance criteria) of the mixed dispatching rule and the efficiency of the search algorithm relative to exhaustive search (complete enumeration) is demonstrated on an FMS model. The mixed dispatching rule approach performs up to 15.9% better than the conventional approach, and is 4% better on average. The statistical significance of the results is dicussed.     

Makespan minimization for m-machine permutation flowshop scheduling problem with learning considerations

Increased complexity of current manufacturing systems together with dynamic conditions and permanent demands for flexible and robust functionality makes their management and control very difficult and challenging. Workflow simulation is an effective approach to investigate dynamic workflow scheduling policies and evaluate the overall manufacturing system performance. The results attained in simulation model can give directions on how to maximize system output when selecting an appropriate scheduling practice for a real system. In this paper, we investigate the abilities of multi-agent systems in combination with dynamic dispatching rules and failure handling mechanisms to manage dynamic environment conditions (such as machine failures) for systems in the production automation domain. We measure system robustness by systematically assessing the total system performance (e.g., number of finished products) in a number of representative test cases. We use an agent-based simulation environment, MAST, which has been validated with real-world hardware to strengthen the external validity of the simulation results. We investigated the performance of a re-scheduling component which uses four different policies that define how to adjust the system schedule in case of machine disturbances/failures. In the context of the empirical study the Complete Rerouting re-scheduling policy outperformed all other policies.     

基于节拍平衡的高柔性数控单元调度研究

为提高柔性数控单元生产效率,提出一种基于工序平衡的高柔性数控单元调度方法。第一阶段,根据产品生产工艺和设备生产能力进行工艺路线规划,在考虑生产约束、生产准备时间、工艺柔性和设备产能的基础上,构建产品节拍平衡优化目标,获得其最优加工视图组合;第二阶段,基于工序平衡的结果,在考虑产品换线时间的基础上构建整单调度模型,并采用遗产算法求解。最后,将所提调度方法在某壳体产品高柔性数控生产单元进行应用研究,并与分批量调度模型进行了比较分析。研究表明,所提出的工序平衡的柔性数控单元整批量调度方法可以有效缩短单元的制造周期,提高单元控设备利用率。     

Dynamic dispatching for interbay material handling by using modified Hungarian algorithm and fuzzy-logic-based control

Semiconductor Wafer Fabrication System (SWFS) is one of the most complicate discrete processing systems in the world. As the wafer size grows from 200 to 300 mm and then to 450 mm in recent years, the interbay automated material handling system (AMHS) has been widely adopted. How to improve the overall efficiency of interbay material handling has therefore become a critical and urgent problem to be solved. However, the large-scale, dynamic and stochastic production environment significantly substantiates the complexity of the scheduling problem. Aiming to meet the demands of adaptive adjusting, efficient scheduling and multiple-objective optimization, a dynamic dispatching method based on modified Hungarian algorithm is proposed. The system parameters, including cassette due date, cassette waiting time, and system load are simultaneously considered, and furthermore the multi-parameters’ weight coefficients are adjusted dynamically by using the fuzzy-logic-based control. Discrete event simulation models are constructed with the eM-Plant software to evaluate the proposed approach. Experimental results show that the proposed dynamic dispatching method improves the system efficiency in terms of mean delivery time, mean waiting time and so on. Meanwhile, the proposed dispatching method has a better comprehensive performance such as the robustness compared to conventional vehicle dispatching approaches.     

基于遗传算法的多资源作业车间智能优化调度

提出一种基于遗传算法的调度算法，用于解决作业车间的加工受到机床、操作工人和机器人等多种生产资源制约条件下的优化调度。以生产周期为目标进行的优化调度，将遗传算法和分派规则相结合，通过交叉、交异等遗传操作，得到目标的最优或次优解。最后对算法进行了仿真研究，并给出了算法运行结果，仿真结果表明该算法是可行的。     

Dynamic control of flexible manufacturing systems

Flexible manufacturing systems (FMSs) are a relatively new technological and organisational approach to helping companies respond to real-time marketing conditions for their production. Under a proposal of the National Bureau of Standards the FMSs are subdivided into virtual manufacturing cells in a dynamic manner, on the basis of group technology.A method of dynamic optimisation for the design of manufacturing processes, capacity balancing and checking, and also production scheduling or rescheduling in virtual manufacturing cells is described. It can be used during real-time production control in FMSs.     

Differentiated preemptive dispatching for automatic materials handling services in 300 mm semiconductor foundry

Highly automated materials handling in 300 mm semiconductor manufacturing is one of the biggest concerns to foundry practitioners because effective coordination among efficient manual operations has been the core competence in their 200 mm manufacturing successful stories. It is still very challenging to provide almost no-wait transport to hot lots (high priority lots) in an automatic materials handling production environment. This paper proposes an effective overhead hoist transport (OHT) dispatching rule, differentiated preemptive dispatching (DPD) policy, to reduce the possible blocking effects during the transportation of hot lots in a 300 mm OHT system. The dispatching objective is to minimize the delivery time of hot lots while minimizing the impact to the transport of normal lots. Simulation experiments based on realistic data from a local 300 mm foundry fab are conducted. Numerical results demonstrate that the DPD rule can effectively expedite the movements of hot lots. The proposed DPD rule is very useful to hot lots management and shop floor control functions, like scheduling and dispatching, in a 300 mm fab-wide automated production environment.     

A developed production control and scheduling model in the semiconductor manufacturing systems with hybrid make-to-stock/make-to-order products

Semiconductor manufacturing systems are one of the most complex production systems and this complexity increases when these systems produce both make-to-stock (MTS) and make-to-order (MTO) products in order to improve the production system utilization. To deal with this complexity, we present a dynamic production control and scheduling model for a semiconductor shop (fab) with hybrid MTS/MTO production environment. The proposed model encompasses two major modules: release module and dispatching module. The release module deals with two issues: prioritizing the MTS and MTO products in the job pool and determining when and which products can be released into the shop floor. The only considered issue of dispatching module is to prioritize the MTS and MTO products in the queue of each workstation whenever a machine becomes idle. To evaluate the proposed model, different performance measures for MTS and MTO products are considered. Moreover, a number of numerical experiments have been conducted by simulation studies. Simulation studies indicate that the proposed model outperforms other related well-known production control and scheduling policies in the literature.     

离散制造业产品能耗限额制定的复杂特性及制定策略

产品能耗限额对于加强产品制造过程能量消耗管理、监控和提高能量效率均十分重要。目前,钢铁、化工等流程制造行业的产品能耗限额制定已有不少成熟方法,并从国家层面制定了一些主要产品的能耗限额指标;但对于量大面广的离散制造业产品,由于其能耗规律的复杂性和动态变化性,其能耗限额制定非常困难。目前我国还没有一项国家层面的离散制造业产品能耗限额。基于离散制造业产品制造能耗特点的分析,揭示离散制造业产品能耗限额制定的分布式多数量制造系统关联性等复杂特性。在此基础上,针对规格品种繁多的一般产品即绝大多数产品,提出产品与制造系统的关联能耗限额制定策略;针对个别量大面广、能量消耗总量巨大、制造设备、工艺和制造流程相对比较成熟和确定的特定产品,提出统一能耗限额制定策略;并给出关联能耗限额制定和统一能耗限额制定的具体策略。上述特性和策略为离散制造业产品能耗限额制定这一难题提供了一种总体解决思路。     

AGV schedule integrated with production in flexible manufacturing systems

Flexible manufacturing systems (FMS) comprise, automated machine tools, automated material handling, and automated storage and automated retrieval systems (AS/RS) as essential components. Effective sequencing and scheduling of the material handling systems (MHS) can have a major impact on the productivity of the manufacturing system. The material handling cannot be neglected while scheduling the production tasks. It is necessary to take into account the interaction between machines, material handling systems and computer. In this context, this paper attempts to link the operation of automated guided vehicles (AGV) with the production schedule and suggests a heuristic algorithm that employs vehicle dispatching rules (vdr) for conflict resolution. The vdrs considered in this paper are: shortest operation time (SPT), longest operation time (LPT), longest travel time (LTT) and shortest travel time (STT). The performance of the vdrs in the proposed heuristic is compared with makespan criteria. The results show that the STT provides the best solutions compared to other vdrs.     

纸箱混合生产过程的生产作业计划体系结构

生产作业计划是混合企业CIMS实施的关键环节之一。本文在总结和分析国内外生产作业计划的发展和应用现状的基础上，以纸箱生产行业为例，研究了混合型企业生产流程的特点，生产作业计划的特点，研究现状状与体系结构。     

Simulation based energy-resource efficient manufacturing integrated with in-process virtual management

As energy efficiency is one of the key essentials towards sustainability, the development of an energy-resource efficient manufacturing system is among the great challenges facing the current industry. Meanwhile, the availability of advanced technological innovation has created more complex manufacturing systems that involve a large variety of processes and machines serving different functions. To extend the limited knowledge on energy-efficient scheduling, the research presented in this paper attempts to model the production schedule at an operation process by considering the balance of energy consumption reduction in production, production work flow (productivity) and quality. An innovative systematic approach to manufacturing energy-resource efficiency is proposed with the virtual simulation as a predictive modelling enabler, which provides real-time manufacturing monitoring, virtual displays and decision-makings and consequentially an analytical and multidimensional correlation analysis on interdependent relationships among energy consumption, work flow and quality errors. The regression analysis results demonstrate positive relationships between the work flow and quality errors and the work flow and energy consumption. When production scheduling is controlled through optimization of work flow, quality errors and overall energy consumption, the energy-resource efficiency can be achieved in the production. Together, this proposed multidimensional modelling and analysis approach provides optimal conditions for the production scheduling at the manufacturing system by taking account of production quality, energy consumption and resource efficiency, which can lead to the key competitive advantages and sustainability of the system operations in the industry.     

A dispatching rule-based hybrid genetic algorithm focusing on non-delay schedules for the job shop scheduling problem

Job shop scheduling is an important decision process in contemporary manufacturing systems. In this paper, we aim at the job shop scheduling problem in which the total weighted tardiness must be minimized. This objective function is relevant for the make-to-order production mode with an emphasis on customer satisfaction. In order to save the computational time, we focus on the set of non-delay schedules and use a genetic algorithm to optimize the set of dispatching rules used for schedule construction. Another advantage of this strategy is that it can be readily applied in a dynamic scheduling environment which must be investigated with simulation. Considering that the rules selected for scheduling previous operations have a direct impact on the optimal rules for scheduling subsequent operations, Bayesian networks are utilized to model the distribution of high-quality solutions in the population and to produce the new generation of individuals. In addition, some selected individuals are further improved by a special local search module based on systematic perturbations to the operation processing times. The superiority of the proposed approach is especially remarkable when the size of the scheduling problem is large.     

基于多代理机制的车间制造资源调度管理系统的研究

在分析车间制造资源调度特点的基础上,综合运用多代理机制、规则调度和消息通信机制等技术,建立了适应制造企业车间层生产环境的多代理模型结构。重点研究了多代理机制的实现、基于多代理结构下的通信机制和规则调度机制等关键技术,构建了基于客户机／服务器结构车间制造资源的调度管理系统的体系结构,研究了其工作流程和实现方法,并开发了基于多代理的车间制造资源调度管理仿真系统。     

An approach to process production reactive scheduling

Process manufacturing has some characteristics that make it different from other types of industry. In practice, there are many examples of process industrial settings where production resources are shared and there is no intermediate storage between two processing units. Perhaps the most important issue usually to be excluded from the academic discussion of process production scheduling/control problems is the uncertainty of the duration of real chemical processes. These properties of process manufacturing result in blocking, no-wait, and other constraints that must be taken into account during designing the production scheduling system. The first part of the paper addresses some features of process manufacturing and their influence on production scheduling. The main part of the paper analyzes the scheduling problems under the presence of typical process constraints and unpredictable process duration times and introduces a simple and reliable approach to avoid these problems. The proposed concept is presented on a case study of an industrial two-stage washing batch subprocess. It is considered that the presented approach would be relatively easy to implement in a process production scheduling system and that it can contribute to more effective process production scheduling.     

Declarative approach to cyclic steady state space refinement: periodic process scheduling

Problems of cyclic scheduling are usually observed in flexible manufacturing systems which produce multitype parts where the automated guided vehicle system plays the role of a material handling system, as well as in various other multimodal transportation systems where goods and/or passenger itinerary planning plays a pivotal role. The schedulability analysis of the processes executed in the so-called systems of concurrent cyclic processes (SCCPs) can be executed within a declarative modeling framework. Consequently, the considered SCCP scheduling problem can be seen as a constraint satisfaction problem. Such a representation provides a unified way for evaluating the performance of local cyclic processes as well as of multimodal processes supported by them. Here, the crucial issue is that of a control procedure (e.g., a set of dispatching rules), which would guarantee the cyclic behavior of the SCCP. In this context, we discuss the sufficient conditions guaranteeing the schedulability of both local and multimodal cyclic processes, and we propose a recursive approach in designing them.     

Attribute Selection for Neural Network-Based Adaptive Scheduling Systems in Flexible Manufacturing Systems

System attribute selection is an integral part of adaptive scheduling systems. Owing to the existence of irrelevant and redundant attributes in manufacturing systems, by selecting the important attributes, better performance or accuracy in prediction can be expected in scheduling knowledge bases. In this study, we first propose an attribute selection algorithm based on the weights of neural networks to measure the importance of system attributes in a neural network-based adaptive scheduling (NNAS) system. Next, the NNAS system is combined with the attribute selection algorithm to build scheduling knowledge bases. This hybrid approach is called an attribute selection neural network-based adaptive scheduling (ASNNAS) system. The experimental results show that the proposed ASNNAS system works very well, when measured by a variety of performance criteria, as opposed to the traditional NNAS system and a single dispatching strategy. Furthermore, the scheduling knowledge bases in the ASNNAS system can provide a stronger generalisation ability compared with NNAS systems under various performance criteria. ID="A1" Correspondence and offprint requests to: Dr C.-T. Su, Department of Industrial Engineering and Management, National Chiao Tung University, 1001 Ta Hsueh Road, Hsin-Chu, Taiwan. E-mail: ctsu@cc.nctu.edu.tw     

基于生物遗传算法的FMS生产调度算法

根据遗传算法,提出了一种FMS生产调度的新算法,该算法不仅适于FMS的静态调度问题,而且由于其计算复杂性低、计算量少的特点,同样也适于FMS的动态调度问题,有效地为解决自动化生产系统的生产调度问题提供了新方法.