Cost based scheduling in a job shop environment

Scheduling is one of the most important issues in operations planning of a manufacturing system. In this paper a new scheduling strategy based on machine cost considerations has been proposed. A scheduling factor based on initial cost of a machine and its running cost has been developed. A scanning procedure has been implemented which prioritizes eligible workstations for each setup of a job based on the scheduling factor. Two measures of performance—idleness factor and idleness cost factor—have been developed. Computer simulation has been used to investigate the impact of various decision parameters on operating behavior of the system.     

A fuzzy integrated decision-making support system for scheduling of FMS using simulation

In the complex environment of an automated manufacturing system, decision-making is one of the most important and difficult tasks of a manager in general or a scheduler in particular. Flexible Manufacturing Systems (FMSs) are highly automated and expensive systems. The high investment cost of a FMS justifies the use of computer simulation support. This paper investigates the operational problems of FMSs through simulation, and different combinations of scheduling rules are evaluated by a fuzzy integrated decision-making support system.     

XPN-FMS: A CAD tool for FMS modeling, analysis, animation, and simulation using Petri nets and X window

We propose a CAD tool, XPN-FMS, which is primarily based on a unique Petri net (PN) synthesis method, called the knitting technique, developed by the authors. Petri net theory has been applied to specification, validation, performance analysis, control code generation, and simulation for manufacturing systems. The analysis of flexible manufacturing systems (FMSs) based on PNs suffers from the complexity problem of reachability analysis (Peterson, 1981). CAD tools are urgently needed. There is no existing CAD tool for FMSs as comprehensive as XPN-FMS, in the sense that the latter integrates the functions of drawing, analysis, reduction (Chao and Wang, 1992; Murata and Koh, 1980), synthesis, property queries, and animation of FMS operations in one software package. Using the X window graphical interface and animation, XPN-FMS makes the modeling and analysis of an FMS visualizable and easy to understand and manipulate. It lets a user draw the factory layout of an FMS on the screen of a monitor using the supplied tools. A corresponding PN model can also be drawn on the monitor screen. XPN-FMS can animate and simulate the overall operating process of the FMS. It is useful for FMS specification, validation, and exploration of different design alternatives, status monitoring, and control. Using XPN-FMS with various inputs and comparing the resulting outputs, the user can determine how to improve efficiency, reduce cost, and pinpoint bottlenecks. For the PN models of FMSs that are decision free, we extend the theory and algorithm of a unique matrix-based method (Chao and Wang, 1993b) to search for subcritical loops (including types A and B) and to support scheduling and dealing with transition periods. XPN-FMS implements this extended method to find the minimum cycle time, critical loop, subcritical loops, next critical loop, and scheduling ranges to avoid the transient period for static scheduling. This is implemented in XPN-FMS for the input sequence control.This project is partially funded by NJIT's Separately Budgeted Research Program. Portions of this article were presented in Chao, Chen, Wang, and Zhou (1992),Proceedings of the 1992 IEEE International Conference on Systems, Man, and Cybernetics, Chicago, Illinois, October 1992. The former name of the first author, which has appeared in some of his earlier publications, was Yuh Yaw.     

An efficient heuristic for scheduling batches of parts in a flexible flow system

Flexible manufacturing systems (FMSs) are a class of automated systems that can be used to improve productivity in batch manufacturing. Four stages of decision making have been defined for an FMS—the design, planning, scheduling, and control stages. This research focuses on the planning stage, and specifically in the area of scheduling batches of parts through the system.The literature to date on the FMS planning stage has mostly focused on the machine grouping, tool loading, and parttype selection problems. Our research carries the literature a step further by addressing the problem of scheduling batches of parts. Due to the use of serial-access material-handling systems in many FMSs, the batch-scheduling problem is modeled for a flexible flow system (FFS). This model explicitly accounts for setup times between batches that are dependent on their processing sequence.A heuristic procedure is developed for this batch-scheduling problem—the Maximum Savings (MS) heuristic. The MS heuristic is based upon the savings in time associated with a particular sequence and selecting the one with the maximum savings. It uses a two-phase method, with the savings being calculated in phase I, while a branch-and-bound procedure is employed to seek the best heuristic solution in phase II. Extensive computational results are provided for a wide variety of problems. The results show that the MS heuristic provides good-quality solutions.     

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.     

An intelligent operations scheduling system in a job shop

Scheduling jobs effectively under the consideration of actual loads on machines is one of the most complicated tasks in production control. The conventional scheduling methods fail because of the complexity of the tasks. To deal with the complexity, knowledge-based approaches to job shop scheduling have been attempted. This paper presents an interactive scheduling expert system, IOSS (Intelligent Operations Scheduling System), which performs both predictive and reactive scheduling. IOSS combines the knowledge-based scheduling method with the interactive scheduling method to generate a feasible schedule and to revise the existing schedule. It is based on opportunistic and interactive repair based problem solving within a blackboard architecture. To handle conflicting events, heuristics are applied from the order point of view. Flexible reaction management is possible while keeping the changes in the generated schedule to a minimum by adjusting the schedule for tardy operations or changes in job shop status. The effectiveness of the proposed concept is demonstrated by applying the developed system to an example case.     

On the path layout and operation of an AGV system serving an FMS

A major step in the design of an AGV system involves the choice of its layout. Three different AGV layouts serving the same FMS are compared in this paper: a bidirectional line, a bidirectional loop and a unidirectional loop. Different numbers of vehicles are tried by running an ECSL program written for the AGV/FMS simulation. Various velocities and scheduling policies are used which show that bidirectional layouts are more advantageous than unidirectional ones in general, although the latter have been rendered more competitive by the application of a control algorithm for the avoidance of blockages on the track. Scheduling policies, however, are proved to be a key issue. It is therefore necessary to refer any comparison of layouts to a particular scheduling policy. In addition, it was observed that a compromise between factors measuring AGV-layout performance has to be made when assessing layouts, since these factors often follow opposite trends.     

Experimental investigation of an FMS due-date scheduling problem: Evaluation of machine and AGV scheduling rules

Although extensive research has been conducted to solve design and operational problems of automated manufacturing systems, many of the problems still remain unsolved. This article investigates the scheduling problems of flexible manufacturing systems (FMSs). Specifically, the relative performances of machine and automated guided vehicle (AGV) scheduling rules are analyzed against various due-date criteria. First, the relevant literature is briefly reviewed, and then the rules are tested under different experimental conditions by using a simulation model of an FMS. The sensitivity to AGV workload, buffer capacity, and processing-time distribution is also investigated to assess the robustness of the scheduling rules.     

Scheduling decisions in FMS using a heuristic approach

The paper deals with the multilevel scheduling decisions of a Flexible Manufacturing System (FMS) to generate realistic schedules for the efficient operation of the FMS. The primary concern of an Operations Management System (OMS) for a FMS is production scheduling, Material Handling System (MHS) scheduling, Automated Storage/Retrieval System (AS/RS) operation and control and tool management. Scheduling is a critical issue and determines how efficiently the production resources are utilised and how the selected parts are affected in the system. In this paper, the integrated scheduling of FMS, namely, the production scheduling conforming with the MHS scheduling, is addressed. An enumerative heuristic is used, namely Giffler and Thompson, which is an evolutionary combining a Genetic Algorithm (GA) and a stochastic neighborhood search technique using a Simulated Annealing (SA) algorithm is employed.A. Noorul Haq received his PhD in Manufacturing Management from the Indian Institute of Technology (IIT), New Delhi, India, a Master of Engineering degree from Madras University, and a Bachelor of Engineering degree from Annamalai University, India. He is currently an assistant professor in the Department of Production Engineering, Regional Engineering College, Tiruchirappalli 620015, India. His research interests include aggregate production planning, facility layout and scheduling and optimisation techniques.T. Karthikeyan received his Master's degree from Bharathidhasan University. Currently, he is a research scholar in the Department of Production Engineering, Regional Engineering College, Tiruchirappalli 620015, India. His research interests includes facility layout, FMS and simulation.M. Dinesh received his bachelor's degree in engineering from Bharathiar University, India and is currently working on his master's degee in engineering in the Department Of Production Engineering, Regional Engineering College, Tiruchirappalli 620015, India. His current research interests are in optimisation techniques, facility layout and scheduling.     

具有机器学习能力的智能车间调度系统

本文从制造领域发展趋势的角度出发，阐述优化设计车间调度系统的必要性，进而介绍一种具有机器学习能力的智能车间调度系统的设计     

Simulation for maintenance of an FMS: an integrated system of maintenance and decision-making

Flexible manufacturing systems (FMSs) are designed to produce a variety of different part types with high machine utilisation, so the maintenance technique is necessary and very important in an FMS. This paper discusses the maintenance problem in an FMS and its simulation, analyses the maintainability of a real FMS shop, and presents the architecture of an integrated system of maintenance and decision-making/scheduling for manufacturing shop control. The modelling and simulation of the maintenance activities in the shop are shown. The simulation program is written in SLAM II and the special subroutines are realised in Fortran. The interest is directed towards the use of the method of simulation for maintenance and decision-making in FMSs.     

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.     

基于零件虚拟工序队列的FMS动态调度研究

提出虚拟工序队列的概念,并在此基础上提出一种基于静态零件分批（静态调度）的ＦＭＳ动态生产调度方法,该算法充分考虑到ＦＭＳ的系统资源限制及零件运输等环节,能较好地解决生产调度中的设备负荷平衡,系统紧急事件发生（如机床故障,新零件加工等）,可替代加工工序等问题,且易于实现,具有较广泛的适应性。     

用于车间作业调度的粒子群优化算法

设计了两种不同实现方式的粒子群算法解决车间作业调度问题,即基于粒子位置矢量更新的实现方式和基于遗传操作的实现方式.同时选择一些典型的Job-Shop调度问题作为算法的试验对象,试验结果表明上述两种不同实现方式的粒子群算法在求解小规模调度问题时都能得到较好的结果,在求解较大规模调度问题时基于遗传操作的粒子群算法可以得到更好的结果.这一方面说明了上述两种不同实现方式的粒子群算法在求解调度问题上的有效性,同时也表明基于遗传操作的粒子群算法在求解较大规模调度问题上具有更大的优势.     

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.     

Integrating Flexible Process Plans with Scheduling in Flexible Manufacturing Systems

This paper highlights the importance of integration between process planning and scheduling in flexible manufacturing systems (FMS). An effective integration increases the potential for enhanced system performance and enhanced decision making A framework that integrates flexible process plans with off-line (predictive) scheduling in FMS is presented. The flexibility in process planning, including process flexibility, sequence flexibility, and alternative machine tools, is discussed. The proposed framework consists of four integrated stages with the objective of reducing the completion time. The integrated stages include: 1. Machine tool selection. 2. Process plan selection. 3. Scheduling. 4. Re-scheduling modules. In addition, the paper proposes a new approach, namely the Dissimilarity Maximisation Method (DMM), for selecting the appropriate process plans for a part mix where parts have alternative process plans. The recursive structure of the framework provides a different approach, namely overlapping schedules, which considers a longer scheduling period as comprising several short scheduling periods. Knowing that neither the process plans nor the planned (predicted) schedules are truly followed on the shop floor, the related literature and the corresponding approaches are compared in order to envisage new approaches for closing the gap between process planning and scheduling.     

A flexible artificial neural network–fuzzy simulation algorithm for scheduling a flow shop with multiple processors

One of the most popular approaches for scheduling manufacturing systems is dispatching rules. Different types of dispatching rules exist, but none of them is known to be globally the best. A flexible artificial neural network–fuzzy simulation (FANN–FS) algorithm is presented in this study for solving the multiattribute combinatorial dispatching (MACD) decision problem. Artificial neural networks (ANNs) are one of the commonly used metaheuristics and are a proven tool for solving complex optimization problems. Hence, multilayered neural network metamodels and a fuzzy simulation using the α-cuts method were trained to provide a complex MACD problem. Fuzzy simulation is used to solve complex optimization problems to deal with imprecision and uncertainty. The proposed flexible algorithm is capable of modeling nonlinear, stochastic, and uncertain problems. It uses ANN simulation for crisp input data and fuzzy simulation for imprecise and uncertain input data. The solution quality is illustrated by two case studies from a multilayer ceramic capacitor manufacturing plant. The manufacturing lead times produced by the FANN–FS model turned out to be superior to conventional simulation models. This is the first study that introduces an intelligent and flexible approach for handling imprecision and nonlinearity of scheduling problems in flow shops with multiple processors.     

Holonic Concept Based Methodology for Part Routeing on Flexible Manufacturing Systems

A flexible manufacturing system (FMS) is designed to achieve good productivity and low cost. The success of an FMS depends largely on effective production scheduling and control. However, it has been found that current manufacturing scheduling and control algorithms lack the flexibility to handle interruptions or resource breakdowns; hence, system performance drops dramatically and abruptly when interruptions occur. This research develops a computer-simulation-based framework of FMS scheduling and control system using the holonic concept. This framework can maintain stability and flexibility while accommodating system disturbance, increase throughput, reduce part flow-time and work-in-process inventory, and balance workload among identical workstations. The significance of this research is the investigation of an innovative approach to revolutionary advances of control technologies for advanced manufacturing systems, and to the revitalisation of control and scheduling algorithms used by existing FMSs. A case study has been provided to substantiate the effectiveness of this proposed framework.     

生产调度的启发式规则研究综述

启发式规则是求解生产调度问题比较简单有效的方法,与其他生产调度算法相结合,在过去50多年里得到了深入研究和广泛应用。首先综述了国内外对生产调度启发式规则的研究状况,阐述了启发式规则及其分类,介绍了启发式规则性能评价指标和鲁棒性,进一步分析了新提出的启发式规则。在总结启发式算法的基础上,给出了启发式规则应用于智能优化调度算法的一般性框架。最后展望了生产调度启发式规则的进一步研究方向。     

A genetic algorithm for energy-efficiency in job-shop scheduling

Many real-world scheduling problems are solved to obtain optimal solutions in term of processing time, cost, and quality as optimization objectives. Currently, energy-efficiency is also taken into consideration in these problems. However, this problem is NP-hard, so many search techniques are not able to obtain a solution in a reasonable time. In this paper, a genetic algorithm is developed to solve an extended version of the Job-shop Scheduling Problem in which machines can consume different amounts of energy to process tasks at different rates (speed scaling). This problem represents an extension of the classical job-shop scheduling problem, where each operation has to be executed by one machine and this machine can work at different speeds. The evaluation section shows that a powerful commercial tool for solving scheduling problems was not able to solve large instances in a reasonable time, meanwhile our genetic algorithm was able to solve all instances with a good solution quality.