An integrated scheme for process planning and scheduling in FMS

Process planning and scheduling are the two important manufacturing functions involved in any shop floor activities. As functional integration is essential to realize the benefits of computer integrated manufacturing, a scheme for integration of process planning and scheduling has been introduced in this paper. The proposed scheme can be implemented in a company with existing process planning and scheduling departments when multiple process plans remain available on the shop floor. It consists of two main modules, introduced in detail in this paper. They are process plan selection module and scheduling module.     

一种实用的单件小批量生产计划调度方法

结合某模具公司生产实际，以应用为出发点，提出了一种生产计划调度方法，该方法采用2层计划，第1层是基于MRP思想将任务分解到工序级，第2层进行车间作业计划，采用基于一组规则的启发式调度方法，将任务下达到各车间，由人工最后确认。     

Daily planning and scheduling system for the EDS process in a semiconductor manufacturing facility

Operations management in a complex manufacturing environment is practiced hierarchically: production planning and scheduling in sequence since the integrated approach is not efficient and practical. Production targets and allocation to the equipment are determined in the planning procedure by considering the only the critical factors, and the detailed scheduling is determined with more information needed to accomplish the production targets provided in the planning step. There is always, therefore, a gap between the planning and scheduling procedure, and some control parameters or factors are used to control those gaps. In this paper an approach connecting two procedures is suggested, which can be applied in the EDS (electrical die sorting) or the probe process in the semiconductor manufacturing. The EDS process requires very flexible operation management since the manufacturing processing time is relatively short and the supply of upstream fabrication and the demand of downstream assembly have to be met simultaneously. Daily planning and scheduling procedure are modeled to minimize the tester change-over within the daily target. Because of the relatively long setup change-over time, daily planning and scheduling have to be performed so that the time needed for the device and probe card change is minimized as possible. Mathematical programming is suggested for the problem, and the modified model is developed which can be solved in a practical computational time on a daily base. The scheduling heuristic with the planning data obtained from the suggested model, is designed, and their performance is evaluated through the computational experiment.     

成批生产计划调度的集成建模与优化

针对多品种批量生产类型,建立了调度约束的生产计划与调度集成优化模型。模型的目标函数是使总调整费用、库存费用及生产费用之和最小,约束函数包括库存平衡约束和生产能力约束,同时考虑了调度约束,即工序顺序约束和工件在单机上的加工能力约束,保证了计划可行性。该模型为两层混合整数规划模型,对其求解综合运用了遗传算法和启发式规则,提出了混合启发式求解算法。最后,针对某机床厂多品种批量生产类型车间进行了实例应用,对车间零件月份作业计划进行分解,得到各工段单元零件周作业计划,确定了零件各周生产批量与投产顺序。     

基于代理技术的分层计划编制调度

市场的竞争使企业的生产完全面向顾客 ,即以最低成本制造出顾客满意的产品。如何在这种模式下进行组织管理 ,包括如何组织动态联盟、如何重构车间和单元、如何安排生产计划、如何进行调度都是我们面临的问题。其中车间作业调度与控制技术是实现生产高效率、高柔性和高可靠性的关键 ,有效实用的调度方法和优化技术的研究与应用已成为先进制造技术实践的基础。本文对多品种、小批量的加工车间的生产计划的编制调度进行了研究与探讨 ,提出了基于代理技术的分层计划编制调度方法并用程序实现     

Integrated model for production planning and scheduling in a supply chain using benchmarked genetic algorithm

Production planning and scheduling is one of the core functions in manufacturing systems. Furthermore, this task is drawing even more attention in supply chain environments as problems become harder and more complicated. Most of the traditional approaches to production planning and scheduling have adopted a multi-phased, hierarchical and decompositional approach. This traditional approach does not guarantee a feasible production schedule. And even when capacity constraints are satisfied, it may generate an expensive schedule. In order to overcome the limitations of the traditional approach, several previous studies tried to integrate the production planning and scheduling problems. However, these studies also have some limitations, due to their intrinsic characteristics and the method for incorporating the hierarchical product structure into the scheduling model. In this paper we present a new integrated model for production planning and scheduling for multi-item and multi-level production. Unlike previous lot sizing approaches, detailed scheduling constraints and practical planning criteria are incorporated into our model. We present a mathematical formulation, propose a heuristic solution procedure, and demonstrate the performance of our model by comparing the experimental results with those of a traditional approach and optimal solution.     

Optimization of multi-objective integrated process planning and scheduling problem using a priority based optimization algorithm

For increasing the overall performance of modern manufacturing systems, effective integration of process planning and scheduling functions has been an important area of consideration among researchers. Owing to the complexity of handling process planning and scheduling simultaneously, most of the research work has been limited to solving the integrated process planning and scheduling (IPPS) problem for a single objective function. As there are many conflicting objectives when dealing with process planning and scheduling, real world problems cannot be fully captured considering only a single objective for optimization. Therefore considering multi-objective IPPS (MOIPPS) problem is inevitable. Unfortunately, only a handful of research papers are available on solving MOIPPS problem. In this paper, an optimization algorithm for solving MOIPPS problem is presented. The proposed algorithm uses a set of dispatching rules coupled with priority assignment to optimize the IPPS problem for various objectives like makespan, total machine load, total tardiness, etc. A fixed sized external archive coupled with a crowding distance mechanism is used to store and maintain the non-dominated solutions. To compare the results with other algorithms, a C-matric based method has been used. Instances from four recent papers have been solved to demonstrate the effectiveness of the proposed algorithm. The experimental results show that the proposed method is an efficient approach for solving the MOIPPS problem.     

Agent technology for collaborative process planning: a review

Agent technology has been considered as a promising approach for developing process planning systems and optimizing process plans in a distributed environment. A number of researchers have attempted to use agent technology in process planning for the purpose of integrating systems, tools and algorithms which are geographically distributed. In this paper, the historical background of agent technology is systematically reviewed. A comprehensive review of agent technology and its applications in manufacturing is presented including the applications of agent in scheduling, control, and enterprise integration and supply chain management. The focus of the paper is on how agent technology can be further developed in the support of collaborative process planning as well as its future research issues and directions in process planning. The current research directions in computer aided process planning (CAPP) and issues in traditional CAPP approaches are also discussed. Three agent-based approaches for process planning are presented. Finally, the key issues in developing agent-based collaborative process planning systems are summarized.     

Developing manufacturing control software: A survey and critique

The complexity and diversity of manufacturing software and the need to adapt this software to the frequent changes in the production requirements necessitate the use of a systematic approach to developing this software. The software life-cycle model (Royce, 1970) that consists of specifying the requirements of a software system, designing, implementing, testing, and evolving this software can be followed when developing large portions of manufacturing software. However, the presence of hardware devices in these systems and the high costs of acquiring and operating hardware devices further complicate the manufacturing software development process and require that the functionality of this software be extended to incorporate simulation and prototyping.This paper reviews recent methods for planning, scheduling, simulating, and monitoring the operation of manufacturing systems. A synopsis of the approaches to designing and implementing the real-time control software of these systems is presented. It is concluded that current methodologies support, in a very restricted sense, these planning, scheduling, and monitoring activities, and that enhanced performance can be achieved via an integrated approach.     

Disc jockeying [compact disc manufacture]

EMI manufactures compact discs and other recordings at a rate of up to a million copies a day. This in itself is not difficult; what makes it complicated is the variety of these recordings. As well as a back catalogue of more than 30,000 titles, the company has to produce and distribute about 9000 new releases, with all the time-critical marketing and the potential for unpredictable demand that this involves. In this environment, scheduling and schedule planning is obviously the key to keeping a factory running efficiently. Only by keeping the bottleneck moving from one machine to another is it possible to run all the stages at a reasonable percentage of their capacity. This process is managed by computer, using a software package called Rhythm. Meticulous forecasting, careful supply chain management and, above all, flexible dynamic job scheduling form the bedrock of an intricate but robust logistics operation, which is what allows the company to survive in a competitive market     

AMS生产计划、排程集成方法研究

在分析先进制造车间(Advanced Manufacturing Shopfloor，AMS)计划、排程问题产生背景的基础上，构造了AMS生产计划、排程问题的集成功能模型。结合此模型，建立了AMS的作业分批与计划排程的数学模型，给出了求解此类问题的算法，仿真实例说明了该方法的有效性。     

Integration of Process Planning and Scheduling Using Simulation Based Genetic Algorithms

Process planning and scheduling are traditionally regarded as separate tasks performed sequentially; but, if the two tasks are performed concurrently, greater performance and higher productivity of a manufacturing system can be achieved. Although several workers have addressed the process plan selection problem in recent years, their main approaches are to select process plans from plan alternatives by taking into account the similarities among process plans of the parts. In this paper, we propose a new approach to the integration of process planning and scheduling using simulation based genetic algorithms. A simulation module computes performance measures based on process plan combinations instead of process plan alternatives and those measures are fed into a genetic algorithm in order to improve the solution quality until the scheduling objectives are satisfied. Computational experiments show that the proposed method reduces significantly scheduling objectives such as makespan and lateness.     

高效精准混装作业调度策略研究

以汽车混装作业为研究对象，对照闭式生产，推导得出开式生产模式具有高效性的结论。研究了多产品混合装配时的投产序列调度和精准调控机理，认为只有投产序列和工位任务分配协同调度，才能使企业生产高效和调度作业精准。论述了该协同调度措施的层次实现策略，指出面向多产品混合装配工序，柔性装配和虚拟装配是策略实施的关键技术手段。     

An improved genetic algorithm for integrated process planning and scheduling

Process planning and scheduling are two of the most important functions involved in manufacturing process and they are actually interrelated; integration of the two is essential to improve the flexibility of scheduling and achieve a global improvement for the performance of a manufacturing system. In order to facilitate the optimization of process planning and scheduling simultaneously, a mathematical model for the integrated process planning and scheduling (IPPS) is established, and an improved genetic algorithm (IGA) is proposed for the problem. For the performance improvement of the algorithm, new initial selection method for process plans, new genetic representations for the scheduling plan combined with process plans and genetic operator method are developed. To verify the feasibility and performance of the proposed approach, experimental studies are conducted and comparisons are made between this approach and others with the makespan and mean flow time performance measures. The results show that the proposed approach on IPPS has achieved significant improvement in minimizing makespan and obtained good results for the mean flow time performance measure with high efficiency.     

Object-oriented and fuzzy-set-based approach for set-up planning

Set-up planning is not only a key element of computer-aided process planning (CAPP), but also a key factor for the integration of CAPP with computer-aided fixture planning (CAFP) and production planning and scheduling (PPS). In this work, an object-oriented and fuzzy-set-based approach is developed for set-up planning. Object-oriented technology is employed to represent set-up planning knowledge and generate alternative set-ups which can respond to the dynamic manufacturing resource and facilitate the CAPP/PPS integration. Based on fuzzy-set theory, a fuzzy evaluation function is proposed to produce optimal set-ups. Combined with a real project, a set-up planning system is developed to generate alternative and optimal set-up plans for the machining of prismatic parts.     

Manufacturing Resource Planning Technology Based on Genetic Programming Simulation

Network-based manufacturing is a kind of distributed system, which enables manufacturers to finish production tasks as well as to grasp the opportunities in the market, even if manufacturing resources are insufficient. One of the main problems in network-based manufacturing is the allocation of resources and the assignment of tasks rationally, according to flexible resource distribution. The mapping rules and relations between production techniques and resources are proposed, followed by the definition of the resource unit. Ultimately, the genetic programming method for the optimization of the manufacturing system is put forward. A set of software for the optimization system of simulation process using genetic programming techniques has been developed, and the problems of manufacturing resource planning in network-based manufacturing are solved with the simulation of optimizing methods by genetic programming. The optimum proposal of hardware planning, selection of company and scheduling will be obtained in theory to help company managers in scientific decision-making.     

制造企业生产计划调度与控制集成策略研究

传统的生产系统中,生产计划、调度与控制是分开进行的,生产信息的反馈周期长,生产调度缺乏必要的现场信息。通过分析生产系统的功能模型和信息模型,结合我国制造企业的实际情况,建立了生产管理系统的层式模块化结构。按照这种结构,构建企业的集成化生产管理系统,将会实现生产计划的实时调度以及生产过程的实时控制。实例证明,本文提出的方案是行之有效的。     

订单型企业多目标生产计划的制定及其调度

针对制定订单式小批量生产计划问题,提出了一种使用动态随机投入产出函数来制定多目标生产计划的方法。针对生产调度问题,提出了联合使用最长加工时间优先(LPT)与遗传算法(GA)的混合遗传算法(HGA)来求解混合流水线的调度,并给出了一种新的编码方法,选择了相应的交叉和变异方法。研究结果表明,该计划制造方法能较好地满足订单型企业的随机性要求,而且生产计划编制效率高。该编码方法在保证染色体合法性的同时也保证了算法本身的随机性。某轧辊厂的实际案例分析结果也验证了所提出的订单型企业多目标生产计划的制定及其调度方法的可行性。     

An effective multi-objective genetic algorithm based on immune principle and external archive for multi-objective integrated process planning and scheduling

Process planning and scheduling are two major sub-systems in a modern manufacturing system. In traditional manufacturing system, they were regarded as the separate tasks to perform sequentially. However, considering their complementarity, integrating process planning and scheduling can further improve the performance of a manufacturing system. Meanwhile, the multiple objectives are needed to be considered during the realistic decision-making process in a manufacturing system. Based on the above requirements from the real manufacturing system, developing effective methods to deal with the multi-objective integrated process planning and scheduling (MOIPPS) problem becomes more and more important. Therefore, this research proposes a multi-objective genetic algorithm based on immune principle and external archive (MOGA-IE) to solve the MOIPPS problem. In MOGA-IE, the fast non-dominated sorting approach used in NSGA-II is utilized as the fitness assignment scheme and the immune principle is exploited to maintain the diversity of the population and prevent the premature condition. Moreover, the external archive is employed to store and maintain the Pareto solutions during the evolutionary process. Effective genetic operators are also designed for MOIPPS. To test the performance of the proposed algorithm, three different scale instances have been employed. And the proposed method is also compared with other previous algorithms in literature. The results show that the proposed algorithm has achieved good improvement and outperforms the other algorithms.     

On-line integration of a process planning module with production scheduling

An approach to the on-line integration of process planning and production scheduling is reported. Based on a geometric modeller, a geometric analyser and a knowledge base, the process planner generates alternative process plans and provides automatic tool selection and calculation of the appropriate machining parameters. Time and cost estimations are input to the decision-making module in the production scheduling system that produces optimal scheduling decisions as well as a complete record of the actual state of the factory resources. An information flow, designed as a relational data model, maintains the interaction between the process planning and the production scheduling systems and provides the dynamic feedback to the process planner. Specific geometry features of the blank, the finished part and the cutting tools, and geometry features-based rules are stored in the database of a developed CAPP system by using a separate CAD interface. The integrated production planning and production scheduling system and the CAPP system were validated with rotational parts machining.