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.     

混合生产中作业计划体系研究

对于兼有离散和连续生产特征的混合生产行业,由于其计划体系的复杂性和多样性,尚未形成成熟的具有通用意义的应用方案。分析了混合生产的特征和混合生产计划体系的特点,提出了研究混合生产计划体系的思路,构建了该作业计划体系框架并描述了功能要求及信息联系,研究了前连续后离散这种混合生产模式的作业计划排程问题的离散制造与连续制造分解逻辑,并以毛纺织行业为背景,进行了连续生产环节计划排程优化算法研究,探讨了毛纺织混合生产计划体系对物料清单、工艺路线等基础数据管理的增强要求。     

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.     

Batch sizes and lead-time performance in flexible manufacturing systems

Production lead-time performance in flexible manufacturing systems is influenced by several factors which include: machine groupings, demand rates, machine processing rates, product batching, material handling system capacity, and so on. Hence, control of lead-time performance can be affected through the manipulation of one or more of these variables. In this article, we investigate the potential of batch sizing as a control variable for lead-time performance through the use of a queueing network model. We establish a functional relationship between the two variables, and incorporate the relationship in an optimization model to determine the optimal batch size(s) which minimizes the sum of annual work-in-process inventory and final inventory costs. The nonlinear batch sizing problem which results is solved by discrete optimization via marginal analysis. Results show that batch sizing can be a cheap and effective variable for controlling flexible manufacturing system throughput.     

Scheduling tasks and vehicles in a flexible manufacturing system

Due to their increasing applicability in modern industry, flexible manufacturing systems (FMSs), their design, and their control have been studied extensively in the recent literature. One of the most important issues that has arisen in this context is the FMS scheduling problem. This article is concerned with a new model of an FMS system, motivated by the practical application that takes into account both machine and vehicle scheduling. For the case of a given machine schedule, a simple polynomial-time algorithm is presented that checks the feasibility of a vehicle schedule and constructs it whenever one exists. Then a dynamic programming approach to construct optimal machine and vehicle schedules is proposed. This technique results in a pseudopolynomialtime algorithm for a fixed number of machines.     

Optimal strip sequencing strategies for flexible manufacturing operations in two and three dimensions

In this paper, optimal strip strategies are developed for a variety of two-dimensional and three-dimensional sequencing problems arising in flexible manufacturing. These strategies are appropriate for CNC drilling operations, NC punching operations, and circuit board population, for example. Seven different metrics are considered.     

A decision-making approach to the operation of flexible manufacturing systems

This paper introduces a generic decision-making framework for assigning resources of a manufacturing system to production tasks. Resources are broadly defined production units, such as machines, human operators, or material handling vehicles; and tasks are activities performed by resources. In the specific context of FMS, resources correspond to individual machines; tasks correspond to operations to be performed on parts. The framework assumes a hierarchical structure of the system and calls for the execution of four consecutive steps to make a decision for the assignment of a resource to a task. These steps are 1) establishment of decision-making criteria, 2) formation of alternative assignments, 3) estimation of the consequences of the assignments, and 4) selection of the best alternative assignment. This framework has been applied to an existing FMS as an operational policy that decides what task will be executed on which resource of this FMS. Simulation runs provide some initial results of the application of this policy. It is shown that the policy provides flexibility in terms of system performance and computational effort.     

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.     

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.     

多产品环境下的一种递阶生产计划系统

为求解多产品环境下带顺序相关调整时间(成本)的递阶生产计划问题,提出了一个两层模型.上层的综合生产计划模型求得各产品类在各时段的生产计划,下层的族分解模型则将上层得到的计划分解到所属的各产品族.为避免当族分解模型中各产品族间的调整时间较大时,上层得到的综合计划不可行,将调整上层计划所带来的额外费用集成到族分解模型的目标函数中,从而可以最优地调整得到综合计划.最后,利用某模具制造企业的数据进行了验证,结果表明,所提出的递阶生产计划模型比整体的方法求解规模小,比传统的递阶生产计划模型的成本低.     

Loading problems with tool management in flexible manufacturing systems: A few integer programming models

In automated production systems like flexible manufacturing systems (FMSs), an important issue is to find an adequate workload for each machine for each time period. Many integer linear programming (ILP) models have been proposed to solve the FMS loading problems, but not all of them take tools into account. Those that do not consider tooling are quite unrealistic, especially when setup times are important with respect to processing times. When tool loading has to be handled by the model, the load assignment may have to be changed completely.In this article we consider FMSs with a tool management of the following type: the system works in time periods whose durations are fixed or not; and tools are loaded on the machines at the beginning of each time period and stay there for the whole time period. Tool changes may occur only at the end of each time period when the system is stopped.We present some integer programming models for handling these situations with several types of objectives. Emphasis is laid on the ILP formulations. Computational complexities are discussed.     

现代桑性制造技术及其发展

通过分析柔性制造系统的关键技术和发展研究方向，展望了现代柔性制造系统的发展趋势，进而阐述了柔性制造系统在先进制造业中的重要作用及其发展的深远意义。     

A heuristic algorithm for the loading problem in flexible manufacturing systems

The paper considers the loading problem in flexible manufacturing systems (FMSs). This problem involves the assignment to the machine tools of all operations and associated cutting tools required for part types that have been selected to be produced simultaneously. The loading problem is first formulated as a linear mixed 0–1 program with the objective to minimize the greatest workload assigned to each machine. A heuristic procedure is presented in which an assignment of operations to machine tools is obtained by solving a parameterized generalized assignment problem with an objective function that approximates the use of tool slots required by the operations assigned to the machines. The algorithm is coded in FORTRAN and tested on an IBM-compatible personal computer. Computational results are presented for different test problems to demonstrate the efficiency and effectiveness of the suggested procedure.     

Developing a computer control system for a flexible manufacturing cell

This article focuses on the development of a computer control system for a flexible manufacturing cell. The paper outlines the various modules that are required for a computer control system and elaborates on the development of some of these modules. This is part of an ongoing research project at the University of the Witwatersrand. The aim of the project is to demonstrate the viability of flexible manufacturing systems to South African industry. Thus the main constraints of the project were cost, ease of implementation, and ease of maintainability. This necessitated the use of existing machinery and of computer systems and software that were readily available and already familiar to industry.     

柔性制造系统中的运输机械

论述了柔性制造系统中使用的有轨和无轨自动输送车的特点、结构、功能及控制系统。     

Selecting technology for investment in flexible manufacturing

Flexible manufacturing (FM) has progressed to the stage where the concepts and the available technology are well established and proven. Investment in FM can be very profitable, but must be aimed at achieving clearly defined objectives. This article describes the scope of FM and shows that the required technical specification is determined by the nature of the potential benefits.The ability to quantify all the potential benefits of FM in financial terms means that investment should not be made without a financial evaluation, but should be treated as any other investment decision. Advice is given to show companies how to identify the companywide benefits of FM and to relate these to the required technology before selecting potential suppliers.     

A specification language for planning and fault recovery in manufacturing systems

This paper presents the syntax and semantics of a component-oriented rule-based language for specifying the formal models of manufacturing systems. A model captures the state of a component of the system in a set of first-order logic predicates, and it captures the semantics of the operations performed by this component in a set of rules that determine the preconditions and postconditions of an operation. The models are then used to plan the sequence of operations of each class of jobs to be manufactured by these systems. A plan-oriented fault detection and correction strategy is proposed. This strategy can automatically handle any combination of faults that may occur when monitoring the operations of manufacturing systems. A fault-tree is consulted prior to executing the scheduled operations of a plan, and the faults that affect the execution of these operations are handled subsequently. Resuming the original cyclic schedule is attempted, whenever feasible. As a proof of concept, a prototype implementation of both the main constructs of the component-oriented rule-based language and the planning and fault-recovery algorithms presented in this paper have been completed. This prototype is implemented on a Unix-based system in the Ada programming language. The specification of a manufacturing system is first expressed in the proposed language. These statements are then translated into Ada code. This code is next compiled by a Verdix Ada compiler and is executed in order to create and populate the model data structure of the system. A detailed plan of execution and a set of fault-recovery plans may then be derived for a job to be manufactured on this system.     

Decision learning about production control as machines break down in a flexible manufacturing system

During manufacturing, there are many situations that can affect production performance. Such situations include machine breakdowns, rush orders, order changes, and order delays. When such issues occur, one has to make decisions to try to maintain production efficiency.Human decisions tend to be too late and incomplete in such contingencies. Thus a system that can make better decisions in time to maintain production performance is needed. To achieve this objective, the intelligent decision system described in this paper integrates artificial intelligence, an optimization technique, and simulation to solve such problems. The decision-making logic of the intelligent decision system is described by event graphs. It imitates the manner of human thinking.Self-learning of the decision-making process is used to strengthen the decision quality. In this study, a method of rule induction is applied to build up the self-learning system. There are two subsystems included in this system. One is rule generation and the other is knowledge management. A case for machine breakdowns is presented and discussed. A series of tests designed to validate the self-learning system are presented. These demonstrate that a rule induction method is suitable for constructing the self-learning.     

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.     

Genetic algorithm-based integrated production planning considering manufacturing partners

This paper deals with an integrated production planning problem in the presence of manufacturing partners. In this environment, although most of the products and parts are produced in local plants, they can also be purchased from any desirable manufacturing partners at reasonable costs. The objective of this study is to provide efficient integrated production plans for both local plants with finite production capacity and manufacturing partners, while minimizing the total production costs. For solving this problem, we formulated an integrated production planning problem by modifying a multi-level lot-sizing (MLLS) problem, and proposed an efficient genetic-algorithm-based heuristic for minimizing the costs of production, inventory, and subcontracting with manufacturing partners. The proposed heuristic consists of a unique chromosome structure, a chromosome-generation method, and genetic operators. The experimental analysis shows that the proposed heuristic generates quite good solutions at low computational costs, in comparison with a commercial optimization package.