Development and evaluation of feature-focused dynamic routing policy

This paper reports on a development of feature-focused dynamic routing policy and its evaluation in a flexible manufacturing systems (FMS) simulation framework. The dynamic policy is based on an integrative methodology in which process planning system IMPlanner is integrated with FMS simulation module. IMPlanner’s rule-based system process selection system performs knowledge-intensive task of generating alternative processing options for each feature for parts in production plan. Generated alternative routings (process plan network) for each part are utilized in the FMS simulation module such that routing decision in FMS are made on periodic intervals by considering alternative processes for each feature and making decision based on the current system status and performance. The proposed framework has been evaluated in an experimental FMS simulation module, implemented in Arena, in which two performance criteria, machine utilization and WIP, were used to make routing decisions. The feature-focused approach is compared with traditional static decision-making, and its improved performance is demonstrated.     

Simultaneous scheduling of parts and automated guided vehicles in an FMS environment using adaptive genetic algorithm

Automated Guided Vehicles (AGVs) are among various advanced material handling techniques that are finding increasing applications today. They can be interfaced to various other production and storage equipment and controlled through an intelligent computer control system. Both the scheduling of operations on machine centers as well as the scheduling of AGVs are essential factors contributing to the efficiency of the overall flexible manufacturing system (FMS). An increase in the performance of the FMS under consideration would be expected as a result of making the scheduling of AGVs an integral part of the overall scheduling activity. In this paper, simultaneous scheduling of parts and AGVs is done for a particular type of FMS environment by using a non-traditional optimization technique called the adaptive genetic algorithm (AGA). The problem considered here is a large variety problem (16 machines and 43 parts) and combined objective function (minimizing penalty cost and minimizing machine idle time). If the parts and AGVs are properly scheduled, then the idle time of the machining center can be minimized; as such, their utilization can be maximized. Minimizing the penalty cost for not meeting the delivery date is also considered in this work. Two contradictory objectives are to be achieved simultaneously by scheduling parts and AGVs using the adaptive genetic algorithm. The results are compared to those obtained by conventional genetic algorithm.     

Simultaneous scheduling of parts and automated guided vehicles in an FMS environment using adaptive genetic algorithm

Automated Guided Vehicles (AGVs) are among various advanced material handling techniques that are finding increasing applications today. They can be interfaced to various other production and storage equipment and controlled through an intelligent computer control system. Both the scheduling of operations on machine centers as well as the scheduling of AGVs are essential factors contributing to the efficiency of the overall flexible manufacturing system (FMS). An increase in the performance of the FMS under consideration would be expected as a result of making the scheduling of AGVs an integral part of the overall scheduling activity. In this paper, simultaneous scheduling of parts and AGVs is done for a particular type of FMS environment by using a non-traditional optimization technique called the adaptive genetic algorithm (AGA). The problem considered here is a large variety problem (16 machines and 43 parts) and combined objective function (minimizing penalty cost and minimizing machine idle time). If the parts and AGVs are properly scheduled, then the idle time of the machining center can be minimized; as such, their utilization can be maximized. Minimizing the penalty cost for not meeting the delivery date is also considered in this work. Two contradictory objectives are to be achieved simultaneously by scheduling parts and AGVs using the adaptive genetic algorithm. The results are compared to those obtained by conventional genetic algorithm.     

Models for the process planning problem in flexible manufacturing systems

Two levels of the process planning problem may be distinguished: the local problem, i.e. the production of a single part, and the global problem concerned with the interdependence of a group of parts to be manufactured. At the local level, one is faced with the completeness and the proper sequencing of the required operations. This may be related to the set covering problem and to topological sorting, respectively. The global problem is more involved and two important models are discussed: the process selection model and the FMS scheduling model. The process selection model is formulated as a clique problem. The FMS scheduling model is described as a constrained travelling salesman problem, and for its decomposition cluster analysis is applied.     

面向FMS的计算机辅助工艺设计系统

介绍了一种以先进的柔性制造系统ＦＦＳ１５００－２为对象、针对墙板类零件的ＣＡＰＰ系统ＨＺＣＡＰ－ＡＰＴ总体结构，并提出一种描述零件信息的新方法。该系统以人机对话的方式输入零件的几何信息和工艺信息，由计算机自动生成零件的工艺文件和在ＦＦＳ１５００－２上加工的数控程序单。     

Multiple-Objective Scheduling for the Hierarchical Control of Flexible Manufacturing Systems

This paper presents a hierarchical approach to scheduling flexible manufacturing systems (FMSs) that pursues multiple performance objectives and considers the process flexibility of incorporating alternative process plans and resources for the required operations. The scheduling problem is solved at two levels: the shop level and the manufacturing system level. The shop level controller employs a combined priority index developed in this research to rank shop production orders in meeting multiple scheduling objectives. To overcome dimensional complexity and keep a low level of work-in-process inventory, the shop controller first selects up to three production orders with the highest ranking as candidates and generates all possible release sequences for them, with or without multitasking. These sequences are conveyed to the manufacturing system controller, who then performs detailed scheduling of the machines in the FMS using a fixed priority heuristic for routing parts of multiple types while considering alternative process plans and resources for the operations. The FMS controller provides feedback to the shop controller with a set of suggested detailed schedules and projected order completion times. On receiving these results, the shop controller further evaluates each candidate schedule using a multiple-objective function and selects the best schedule for execution. This allows multiple performance objectives of an FMS to be achieved by the integrated hierarchical scheduling approach.     

An inexact algorithm for part input sequencing and scheduling with side constraints in FMS

Consider a flexible manufacturing system that produces parts of several types. The FMS consists of several groups of pooled, identical machines, a materials handling system, and a set of nonconsumable resources. Each type of part has its own unique sequence in the execution of the operations. An inexact algorithm is presented that sequences and schedules the input of the parts in the FMS by considering constraints such as machine availabilities and other resources in the machine groups, the availability of the transport units, and so on. Primarily, the goal of the algorithm is to minimize makespan and, secondarily, to minimize turnaround time. Several strategies are discussed, and the results are reported. A real-life problem is described.     

A study of FMS part type selection approaches for short-term production planning

This research compares seven approaches from the literature to the selection of part types for simultaneous production over the next time horizon. A flexible approach to the selection of part types and the simultaneous determination of their mix ratios so as to balance aggregate machine workloads is presented. Constraints on tool magazine capacity are considered. Simulation studies are conducted on realistic, detailed models of flexible flow systems (FFSs) configured as pooled machines of equal sizes. The simulated settings are constructed to evaluate the impact of such factors as blocking, transportation, buffer utilizations, and fixture requirements and limitations of various types.One of the goals of this study is to encourage industry to relax, for those FMS types for which the procedure is appropriate, what is essentially an artificial constraint: that tool changing be isolated in time, to a period between batches. For other types of FMSs, batching may be appropriate.The results indicate that using the flexible approach enables the system to be more highly utilized. It is also observed that the batching approaches tend to require more fixtures of each type than the flexible approach. The system utilizations for the batching approaches seem to be more sensitive to restrictions on the number of fixtures of each type. Further research needs are also discussed.     

Real-Time Manipulation of Alternative Routeings in Flexible Manufacturing Systems: A Simulation Study

This paper presents the results of a simulation study of a typical flexible manufacturing system (FMS) that has routeing flexibility. The objective is this study is to test the effectiveness of the dissimilarity maximisation method (DMM) for real-time FMS scheduling. DMM is an alternative process plan selection method developed for routeing selection in off-line FMS sched-uling. An integrated framework that consists of a computer simulation model, which mimics a physical system, a C++ module, and a linear program solver is used to evaluate the effects of various operational control rules on the system performance. The hypothetical FMS employed in this study consists of seven machining centres, a loading and an unloading area, and six different part types. Owing to the existence of identical machining centres in the system, the part types have alternative routeings. For selecting an incoming part and later routeing it to a machining centre for its next operation, three control rules, namely, first-in first-out/first available (FIFO/FA), equal probability loading (EPL), and dissimilarity maximisation method/first-in first-out (DMM/ FIFO) are used. In this study, DMM is 1. Used as a real-time decision-making tool to select routeings for the parts that are in the system. 2. Tested and benchmarked against FIFO/FA and EPL. The results show that DMM/FIFO outperforms FIFO/FA and EPL on system throughput. Other measures such as average waiting time, average transportation time, and percentage utilisation rates are also investigated to provide insights for the effectiveness of the DMM rule for real-time FMS control applications.     

Macro-capp: A prototype capp system for an FMS

This paper deals with the role, advantages, problems and solution techniques for the implementation of dynamic Computer Aided Process Planning (CAPP) systems in a Felxible Manufacturing system (FMS). A large variety of part features for both rotational and prismatic parts are considered. A custom group technology coding technique is designed and implemented to describe part profile to system software concisely and comprehensively. The part profile code is assimilated by the system interactively. A prototype CAPP system was designed for a pseudo FMS containing multiple machining centres. The system described develops process plans that consider both alternative routes and methods to manufacture a part. Heuristic knowledge was implemented to choose between alternatives with flowtime minimization as the objective function. The system was tested and its outputs validated with respect to both prismatic and rotational parts.     

Production planning of a flexible manufacturing system in a material requirements planning environment

Early flexible manufacturing system (FMS) production planning models exhibited a variety of planning objectives; typically, these objectives were independent of the overall production environment. More recently, some researchers have proposed hierarchical production planning and scheduling models for FMS. In this article, we examine production planning of FMS in a material requirements planning (MRP) environment. We propose a hierarchical structure that integrates FMS production planning into a closed-loop MRP system. This structure gives rise to the FMS/MRP rough-cut capacity planning (FMRCP) problem, the FMS/MRP grouping and loading (FMGL) problem, and the FMS/MRP detailed scheduling problem.We examine the FMRCP and FMGL problems in detail and present mathematical programming models for each of these problems. In particular, the FMRCP problem is modeled as a generalized assignment problem (GAP), and a GAP-based heuristic procedure is defined for the problem. We define a two-phase heuristic for the FMGL problem and present computational experience with both heuristics. The FMRCP heuristic is shown to solve problems that exhibit a dependent-demand relation within the FMS and with FMS capacity utilization as high as 99 percent. The FMGL heuristic requires very little CPU time and obtains solutions to the test problems that are on average within 1.5 percent of a theoretical lower bound.This FMS/MRP production planning framework, together with the resulting models, constitutes an important step in the integration of FMS technology with MRP production planning. The hierarchical planning mechanism directly provides for system-level MRP planning priorities to induce appropriate production planning and control objectives on the FMS while simultaneously allowing for necessary feedback from the FMS. Moreover, by demonstrating the tractability of the FMRCP and FMGL problems, this research establishes the necessary groundwork upon which to explore systemwide issues pertaining to the coordination of the hierarchical structure.     

Scheduling optimisation of flexible manufacturing systems using particle swarm optimisation algorithm

The increased use of flexible manufacturing systems (FMS) to efficiently provide customers with diversified products has created a significant set of operational challenges. Although extensive research has been conducted on design and operational problems of automated manufacturing systems, many problems remain unsolved. In particular, the scheduling task, the control problem during the operation, is of importance owing to the dynamic nature of the FMS such as flexible parts, tools and automated guided vehicle (AGV) routings. The FMS scheduling problem has been tackled by various traditional optimisation techniques. While these methods can give an optimal solution to small-scale problems, they are often inefficient when applied to larger-scale problems. In this work, different scheduling mechanisms are designed to generate optimum scheduling; these include non-traditional approaches such as genetic algorithm (GA), simulated annealing (SA) algorithm, memetic algorithm (MA) and particle swarm algorithm (PSA) by considering multiple objectives, i.e., minimising the idle time of the machine and minimising the total penalty cost for not meeting the deadline concurrently. The memetic algorithm presented here is essentially a genetic algorithm with an element of simulated annealing. The results of the different optimisation algorithms (memetic algorithm, genetic algorithm, simulated annealing, and particle swarm algorithm) are compared and conclusions are presented .     

Design of loop layout in flexible manufacturing system using non-traditional optimization technique

Layout arrangement is important to achieve high productivity in flexible manufacturing system (FMS). This paper discusses the design of loop layout in FMS. The objective of the loop layout problem is the determination of the ordering of machines around a loop, to minimize the total number of loop traversals for a family of parts. This paper details the design, development and testing of particle swarm optimization (PSO) technique to solve the loop layout problem. The proposed method is validated with bench mark problems. The clearance between the machines is also considered in the design of loop layout. This aspect aids in selecting the best layout.     

大批量定制下的客户订单聚类分析

在假定订单池中的订单都是有利润的条件下,研究了如何实现订单的批量化处理方式,即将相似性大的订单作为一组进行批量生产,先分析各个产品的共性部件(包括标准件)和个性化部件,对于个性化部件,与客户协商是否可延迟交付,以便于与其他订单进行相似性比较,目的是为了批量化生产,在一定程度上减少产品的多样化。最后对后续的订单聚类进行了重点分析,并结合具体算例展示了其实际应用。     

FMS故障诊断网上专家系统的设计与实现

构造网上专家系统是FMS故障诊断研究和应用的发展趋势,对解决单机型专家系统所存在的“信息孤岛”问题提供了良好的解决方案。结合FMS运行设备的故障模式特点,深入分析了基于WEB的专家系统的体系结构和核心部件（推理机和知识库）的实现方法,提出模糊查询法以解决规则的“组合爆炸”问题,使系统诊断的成功率大大增加。ASP．NET是建立FMS故障诊断网上专家系统的优选工具。     

CIMS环境中的集成化工艺过程设计

介绍一个ＣＩＭＳ或ＦＭＳ环境下的集成化ＣＡＰＰ系统－ＴＨＣＡＰＰ，该系统以非回转体零件为加工对象，利用ＩＧＥＳ实现与ＣＡＤ／ＣＡＰＰ／ＣＡＭ的信息集成。工艺路线生成核心是创成式专家系统，推理机的控制策略以启发式搜索的估价函数为主，可自动选择定位夹紧面。工艺知识库为独立的、可维护的形式，根据ＣＩＭＳ车间的实际环境可获得多种工艺方案。     

FMS simulation model using PC-SIMSCRIPT-II.5

A SIMSCRIPT model is developed for the simulation of flexible manufacturing systems (FMS). The system consists of several workstations, and produces a known number of part types. The workstations are integrated with a materials handling system consisting of robots and AGVs. Each workstation has in-process inventory space of limited capacity where the parts can be stored before and after machining is completed at the workstations. The robots are flexible in the sense that they are capable of machine loading, AGV loading and transferring the parts across the workstations. The model has been implemented on an IBM PC-AT compatible using the PC-SIMSCRIPT-II.5 simulation package. The use of the model is demonstrated with the help of an example.     

动态配料系统的控制算法与仿真研究

通过对混凝土搅拌站动态配料系统的控制过程进行分析,依据动态配料称重系统和定量控制相结合的思想,在系统动态称重配料过程中引入泛逻辑学理论,设计了泛逻辑智能控制器。MATLAB仿真表明其控制器具有响应快、超调小、稳态精度高的优点。与PID控制算法比较,该系统的配料精度和速度都达到要求,整个系统的效率也得到了提高。     

Non-arbitrary approach to routing in a flexible manufacturing system

Routing for a flexible manufacturing system (FMS) has often been done by the application of predetermined dispatching rules to the system in a dynamic realtime manner. As the decisions are made in realtime, they are partly arbitrary. Another approach to this problem is to define a routing sequence in advance and download it to the computer controlling the FMS. The controlling computer would issue instructions to the various machines as prescribed by the predetermined sequence. By predetermining the sequence, it can be more closely examined and improved upon. Without the time constraint of realtime decision making, more intelligent routing decisions are possible.     

Simulation-based metamodels for the analysis of scheduling decisions in a flexible manufacturing system operating in a tool-sharing environment

This paper presents the salient aspects of developing simulation-based metamodels for scheduling a typical flexible manufacturing system (FMS) operating in a tool-sharing environment. A discrete-event simulation model of the FMS is developed for the purpose of experimentation. Seven scheduling rules from the literature are incorporated in the simulation model for part scheduling decision. The performance measures considered for analysis are mean flow time, mean tardiness, and percentage of tardy parts. Simulation experiments have been carried out for various scenarios arising out of the settings of the mean interarrival time of parts for processing in the system and due-date factor. The simulation results are used to develop regression-based metamodels. These metamodels have been subjected to systematic analysis. The metamodels are found to offer a good prediction of the performance of FMS within the domain of their definition.