A genetic algorithm for scheduling flexible manufacturing systems

General job shop scheduling and rescheduling with alternative route choices for an FMS environment is addressed in this paper. A genetic algorithm is proposed to derive an optimal combination of priority dispatching rules pdrs (independentpdrs one each for one Work Cell WC), to resolve the conflict among the contending jobs in the Giffler and Thompson GT procedure. The performance is compared with regard to makes-pan criteria and computational time. The optimal WCwise-pdr is proved to be efficient in providing optimal solutions in a reasonable computational time. Also, the proposed GA based heuristic method is extended to revise schedules on the arrival of new jobs, and on the failure of equipment to address the dynamic operation mode of flexible manufacturing systems. An iterative search technique is proposed to find the best route choice for all operations to provide a feasible and optimal solution. The applicability and usefulness of the proposed methodology for the operation and control of FMS in real-time are illustrated with examples. The scope of the genetic search process and future research directions are discussed.     

Resource-requirements planning in flexible manufacturing systems

In this paper, we address the problem of planning the requirements of some of the important resources in flexible manufacturing systems. Specifically, we model the problem of estimating the required numbers and types of machines and tools in the context of a cellular layout. A two-stage procedure is developed which first forms the part families, using the complete-linkage clustering method based on a new similarity index defined in terms of the tooling requirements, and then subsequently estimates the resource requirements to manufacture the part families using an integer programming model. Several variations of the model are discussed and a numerical example is given.     

Knowledge-based workcell attribute oriented dynamic schedulers for flexible manufacturing systems

The economy of production in flexible manufacturing systems (FMS) depends mainly on how effectively the production is planned and how the resources are used. This requires efficient and dynamic factory scheduling and control procedures. This paper addresses two knowledge-based scheduling schemes (work cell attribute oriented dynamic schedulers WCAODSs) to control the flow of parts efficiently in real-time for FMS in which the part-mix varies continually with the planning horizon. The present work employs a hybrid optimisation approach in the generalised A1 framework. A genetic algorithm that provides an optimal combination of a set of priority dispatching rules, one for each work cell WC (WCwisepdr set), for each of the problem instances characterised by their WC attributes, is used for generating examples. The WC attributes reflect the information about the operating environment of each individual WC. Two inductive learning algorithms are employed to learn the examples, and scheduling rules are formulated as a knowledge base. The learning algorithms employed are: the Genetic CID3 (Continuous Interactive Dichotomister3 algorithm extended with genetic program for weight optimisation) and the Classification Decision Tree algorithm. The knowledge base obtained through the above learning schemes generates robust and effective schedules intelligently with respect to the part-mix changes in real-time, for makespan criteria. The comparison made with a GA-based scheduling methodology shows that WCAODSs provide solutions closer to the optimum.     

Object-oriented approach of MCTPN for modelling Flexible manufacturing systems

Manufacturing industry is facing a stricter challenge than ever before owing to the rapid change in market requirements. Flexible manufacturing systems (FMSs) have a much greater capability than traditional fixed-type production systems for coping with the rapid change. In this paper, a modified coloured-timed Petri net (MCTPN) is developed to model the dynamic activities in an FMS. The MCTPN provides an object-oriented and modular method of modelling manufacturing activities. It includes colour, time, modular and communication attributes. The features of object-oriented modelling allow the FMS to be modelled with the properties of classes, objects, and container trees. Since the system activities can be encapsulated and modularised by the proposed MCTPN, the manufacturing systems can be easily constructed and investigated by the system developers. It makes the concept of software IC possible for modelling complex FMSs. Once all of the MCTPN objects are well defined, the developers need to consider only the interfaces and operations relating to the MCTPN objects. In order to demonstrate the capability of the proposed MCTPN, the FMS in the Manufacturing Automation Technology Research Center (MATRC) of the National Taiwan University will be stimulated and justified by using the proposed MCTPN along with the G2 expert system.     

Recursive newton-euler formulation for flexible dynamic manufacturing analysis of open-loop robotic systems

The main objective of this paper is to develop a recursive formulation for the flexible dynamic manufacturing analysis of open-loop robotic systems. The nonlinear generalized Newton-Euler equations are used for flexible bodies that undergo large translational and rotational displacements. These equations are formulated in terms of a set of time invariant scalars, vectors and matrices that depend on the spatial coordinates as well as the assumed displacement fields. These time invariant quantities represent the dynamic manufacturing couplings between the rigid body motion and elastic deformation. This formulation applies recursive procedures with the generalized Newton-Euler equations for flexible bodies to obtain a large, loosely coupled system equation describing motion in flexible manufacturing systems. The techniques used to solve the system equations can be implemented in any computer system. The algorithms presented in this investigation are illustrated using cylindrical joints for open-loop robotic systems, which can be easily extended to revolute, slider and rigid joints. The recursive Newton-Euler formulation developed in this paper is demonstrated with a robotic system using cylindrical mechanical joints.     

Management of product variety in cellular manufacturing systems

In today’s markets, non-uniform, customized products complicate the manufacturing processes significantly. In this paper, we propose a cellular manufacturing system design model to manage product variety by integrating with the technology selection decision. The proposed model determines the product families and machine groups while deciding the technology of each cell individually. Hedging against changing market dynamics leads us to the use of flexible machining systems and dedicated manufacturing systems at the same facility. In order to integrate the market characteristics in our model, we proposed a new cost function. Further, we modified a well known similarity measure in order to handle the operational capability of the available technology. In the paper, our hybrid technology approach is presented via a multi-objective mathematical model. A filtered-beam based local search heuristic is proposed to solve the problem efficiently. We compare the proposed approach with a dedicated technology model and showed that the improvement with the proposed hybrid technology approach is greater than 100% in unstable markets requiring high product varieties, regardless of the volumes of the products.     

Real-time scheduling with deadlock avoidance in flexible manufacturing systems

The dynamic nature of manufacturing makes rescheduling essential in today's complex production environment, particularly in flexible and re-configurable systems. Research on optimising schedules, which includes deadlock avoidance, is rather limited. Furthermore, the deadlock problem is mostly ignored in research on rescheduling. A rescheduling algorithm, that uses time petri-nets and the minimal siphons concept, was developed to deal with sources of disturbance such as machine breakdowns in real-time. The algorithm guarantees a deadlock-free new schedule. The existence of alternative routes, availability of material handling facilities and the limitation of buffer capacities were taken into consideration. The developed algorithm modifies only the affected portion of the original schedule, rather than rescheduling all jobs, in order to limit changes to the original schedule and reduce the impact on the response time.The effect of flexible routing, machine breakdowns, machine downtime, routing criterion and the use of the dispatching rule on the performance of manufacturing systems was studied. The systems performance was measured by the average flow time, the makespan and the average machine utilisation. The results indicate that utilising the system routing flexibility in real-time rescheduling, while avoiding deadlocks, improves system performance. Moreover, routing the interrupted operation to an alternative machine, based on the minimum expected completion time rather than the least utilised machine criterion, resulted in better performance.     

Analysis of the number of automated guided vehicles required in flexible manufacturing systems

In this paper we examine some of the general principles and analysis methods that are used to design an automated material handling system. The paper focuses on one type of automated handling system that seems especially suitable for automation in discrete-product manufacturing. These types of automated handling systems are called automated guided vehicle systems. These systems are most applicable for the automation of low-and medium-volume handling situations, where the routeing of materials is more individualised. For guided vehicles, a new quantitative method for analysing these systems is developed in the paper. Examples are presented to demonstrate the method.     

Recursive Newton–Euler formulation for flexible dynamic manufacturing analysis of open-loop robotic systems

The main objective of this paper is to develop a recursive formulation for the flexible dynamic manufacturing analysis of open-loop robotic systems. The nonlinear generalized Newton–Euler equations are used for flexible bodies that undergo large translational and rotational displacements. These equations are formulated in terms of a set of time invariant scalars, vectors and matrices that depend on the spatial coordinates as well as the assumed displacement fields. These time invariant quantities represent the dynamic manufacturing couplings between the rigid body motion and elastic deformation. This formulation applies recursive procedures with the generalized Newton–Euler equations for flexible bodies to obtain a large, loosely coupled system equation describing motion in flexible manufacturing systems. The techniques used to solve the system equations can be implemented in any computer system. The algorithms presented in this investigation are illustrated using cylindrical joints for open-loop robotic systems, which can be easily extended to revolute, slider and rigid joints. The recursive Newton–Euler formulation developed in this paper is demonstrated with a robotic system using cylindrical mechanical joints.     

Design of cellular manufacturing systems using objective functional clustering algorithms

Cellular manufacturing (CM) has emerged as an alternative to conventional batch-type manufacturing owing to the former's capability of reducing set-up times, in-process inventories and throughput times. It provides the basis for implementation of just-in-time (JIT) and flexible manufacturing systems (FMS). The machine-part group formation is an important issue in the design of CMSs. This paper presents objective functional clustering algorithms for cell formation problems in the design of cellular manufacturing systems. A deterministic objective functional algorithm (hard clustering) and a fuzzy objective functional algorithm (fuzzy clustering) are used to form the part families and machine cells simultaneously. A collection of data sets from open literature is used to test these algorithms. A software package has been developed to verify the implementation.     

A methodology for investigating effects of cell size on operational flexibility in flexible manufacturing systems

There are two aspects to cell formation in flexible manufacturing systems, cell sizing or deciding on the optimum number of machines to be allocated to each cell, and then allocation of specific machines to each cell. Although the latter problem has been investigated extensively there is a paucity of published work on the former. This paper discusses the effects of cell sizing on operational flexibility.Operational flexibility is that aspect of flexibility that enables manufacturing systems to respond with speed and efficiency to changes in the manufacturing environment while maintaining an effective level of control.     

Part spectrum based methodology for cell sizing in flexible manufacturing systems

This paper describes a part spectrum based methodology which enables the determination of an optimum size for flexible manufacturing cells. The methodology incorporates a systems approach in that it enables the sizing of cells to achieve specified manufacturing objectives while maintaining a realistic level of flexibility and an acceptable level in terms of complexity of control.The proposed methodology for cell sizing is based on two component characteristics: processing time and number of operations. Furthermore, it is generalised in its implementation in that the effects of case specific factors such as processing sequence of components and location of machines in relation to each other are negated.The validation of the proposed methodology for cell sizing using data obtained from manufacturing companies implementing flexible manufacturing systems is also described.     

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.     

采用Cellular automaton法模拟动态再结晶过程的研究

结合金属塑性成形过程的冶金学原理,给出了一种新的模拟动态再结晶过程的元胞自动机(Cellular automaton,CA)模型,用来模拟塑性变形过程中动态再结晶过程。再结晶晶粒的生长速度与再结晶驱动力成正比, 再结晶驱动力取决于晶界能和位错密度。在一个增量步内,根据动态再结晶晶粒生长速度确定与其相邻原胞转变 概率。采用本模型对不同温度、应变速度、应变条件下的动态再结晶过程进行了模拟,模拟结果与试验结果以及 经验公式得到的结果相一致。本模型也可用于再结晶动力学、微观组织和织构变化过程的模拟。     

An integration architecture for flexible manufacturing cells

A modern flexible manufacturing cell (FMC) usually consists of several distributed control systems, including machining centres and material handling systems. Modelling an FMC to evaluate its design and performance, and translating the resulting models into operational programs are complex, but critical steps in implementing an FMC. This paper represents an architecture for the design, integration, and implementation of an FMC. The primary focus is on defining the process and functional requirements of the system, designing the system using high-level abstraction tools that ensure system integration and effective communication with users and implementors, and using efficient algorithms and effective interfaces for implementing real-time process control.     

Evaluation of dispatching rules for cellular manufacturing

In this paper, the effects of various dispatching rules on the operation and performance of cellular manufacturing systems (CMS) are evaluated. When the study of a CMS considers the automated material handling, it is crucial to reduce the gridlock probability (i.e., the probability of an unsuccessful load transfer attempt occurring in the interface point between the intercell and intracell handling system). Preventing an unsuccessful load transfer is critical for the operation of the entire system as a blockage between the automated guided vehicle (AGV) and the overloaded cell results in a total system shutdown. The gridlock probability is influenced by the dispatching rule used to schedule the load transfers in the system. Therefore, in order to reduce this probability it is necessary to use a dispatching rule that will decrease the number of waiting loads in the transfer spurs. The main objective of the paper presented herein is to identify a dispatching rule that maintains the system operational at all times. A group of dispatching rules, including the first come first served (FCFS), shortest imminent operation (SI), longest imminent operation (LI), most remaining operations (MRO), shortest processing time (SPT), shortest remaining process time (SR), and a newly developed rule proposed by the authors, loads with the minimum number of processing first (MNP), are tested and evaluated with respect to whether the capacity of the transfer spurs of the cells is exceeded. This paper presents a simulation model of a cellular manufacturing system, which is used to further explore the effects of the dispatching rules on the system performance. The results show superior performance of the newly proposed MNP rule.     

Tool addition strategies for flexible manufacturing systems

The allocation of tools to machines determines potential part routes in flexible manufacturing systems. Given production requirements and a minimum feasible set of tools, the decision of how to fill vacant slots in tool magazines to maximize routing flexibility is shown to be a minimum cost network flow problem for the cases when routing flexibility is a function of the average workload per tool aggregated over tool types, or of the number of possible routes through the system. A linear programming model is then used to plan a set of routes for each part type so as to minimize either the material handling requirement or the maximum workload on any machine. The impact of these tool addition strategies on the material handling and workload equalization is investigated and computational results presented. The advantage of the overall approach is computational simplicity at each step and the ability to react to dynamic changes.This article is based upon work supported by the National Science Foundation under Grants No. DMC 85–44993 and DDM 92–15432.This work was done by the author while visiting the SIE Department of the University of Arizona.     

制造资源柔性集聚与区域集群制造模式研究

制造资源配置出现了集中与分散相混合的区域柔性集聚趋势。制造资源的区域柔性集聚所形成的区域集群制造 模式,实现了制造资源集中配置和分散配置的有机均衡,将制造资源集中配置的规模经济优势和制造资源分散配置的灵 活性有机结合起来,成为高效的制造模式。     

Evaluating the design of flexible manufacturing systems

Evaluating the design of flexible manufacturing systems is complex. Developing a measure of performance useful for evaluating alternate designs continues to be interesting. Here, total productivity of the system is proposed as an appropriate measure. Specification of parameters based upon strategic considerations for this measure are discussed. Finally, the usefulness of the measure is demonstrated through an example.     

A framework for capacity planning and machine configuration in flexible assembly systems

We consider the problem of simultaneously determining the number of machines (and/or workers), the assignment of tasks (and related tools and components) to these machines, and the number of jobs circulating in a flexible assembly system (FAS), to satisfy steady-state throughput requirements for a family of similar products at minimum cost. We focus on situations where there are precedence relations among the various tasks, as is common in assembly systems. We present a framework for solving this problem based on a heuristic decomposition approach which involves the solution of only a few types of sub-problems. We demonstrate the efficiency and effectiveness of the overall procedure using a number of example problems.