Evaluation of routing flexibility of a flexible manufacturing system using simulation modelling and analysis

Routing flexibility is a major contributor of the flexibility of a flexible manufacturing system (FMS). The present paper focuses on the evaluation of the routing flexibility of an FMS with the dynamic arrival of part types for processing in the system. A typical FMS configuration is chosen for detailed study and analysis. The system is set at five different levels of routing flexibility. Operations of part types can be processed on alternative machines depending upon the level of routing flexibility present in the system. Two cases have been considered with respect to the processing times of operations on alternative machines. A discrete-event simulation model has been developed to describe the operation of the chosen FMS. The performance of the system under various levels of routing flexibility is analyzed using measures such as mean flow time, mean tardiness, percentage of tardy parts, mean utilisation of machines, mean utilisation of automatic-guided vehicles, and mean queue length at machines. The routing flexibility for producing individual part types has been evaluated in terms of measures such as routing efficiency, routing versatility, routing variety and routing flexibility. The routing flexibility of the system has been evaluated using these measures. The flexibility levels are ranked based on the routing flexibility measure for the system. The ranking thus obtained has been validated with that derived using fuzzy logic approach.     

Dissimilarity Maximization Method for Real-time Routing of Parts in Random Flexible Manufacturing Systems

This paper presents a dissimilarity maximization method (DMM) for real-time routing selection and compares it via simulation with typical priority rules commonly used in scheduling and control of flexible manufacturing systems (FMSs). DMM aims to reduce the congestion in the system by selecting a routing for each part among its alternative routings such that the overall dissimilarity among the selected routings is maximized. In order to evaluate the performance of DMM, a random FMS, where the product mix is not known prior to production and off-line scheduling is not possible, is selected for the simulation study. A software environment that consists of a computer simulation model, which mimics a physical system, a C++ module, and a linear program solver is used to implement the DMM concept. In addition to DMM, the simulation study uses two priority rules for routing (i.e., machine) selection and seven priority rules for selecting parts awaiting service at machine buffers. The results show (1) DMM outperforms the other two routing selection rules on production rate regardless of the part selection rule used, and (2) its performance is highly dependent on the part selection rules it is combined with.     

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.     

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.     

An integrated decision support system for FMS production planning and scheduling problems

This paper discusses planning and scheduling problems for efficient use of an FMS and presents an integrated decision support system for dealing with these problems.The decision support system, FMSDS (Flexible Manufacturing Systems Decision Support System), includes several modules: data handling module, part selection module, loading module, load adjusting module, scheduling module and simulation module.This paper suggests the solution methodology of each subproblem. Also, an integrated interface scheme between the subproblems is presented. The interface scheme considers the relationships between the subproblems and generates solutions using hierarchical and looping approaches.FMSDS is made up of six alternative models considering three loading objectives and two production order processing strategies. Performance comparison among the six alternatives is shown using the non-terminating simulation techniques.     

An Intelligent Decision Support System for Part Launching in a Flexible Manufacturing System

The effective control of flexible manufacturing systems (FMS) poses a major challenge to designers and the research community. In this paper, the framework of a unique decision support system to assist in the control of a FMS through intelligent part-launching is introduced. The proposed system makes usr of a new heuristic method based on the pull concept, and a neural network trained with data from a system simulation model, which in turn provides a desision about choosing a part to be launched into the FMS. The performance of the proposed heuristic method was tested against another popular heuristic method normally used in existing FMS via discrete event simulation models. Data sets from the simulation program of the proposed system were used to train the neural network, which can be used on the shop floor for realtime decision support. The output from the trained neural network is based on the same principle as the proposed heuristic method used in the simulation program. Therefore, the descision support provided by the neural network can be used for improved shop floor control.     

A production order-driven AGV control model with object-oriented implementation

To effectively manage the material handling in Flexible Manufacturing Systems (FMS), where a large amount of data is required in the dynamic decision-making, integrated control is needed to consider the overall production schedule. The focus of this research is on the development of an integrated Automated Guided Vehicle System (AGVS) control model that includes essential features like dynamic vehicle path determination and conflict-free routing. An object-oriented implementation of the AGVS model is proposed that forms the basis of systems integration with a production planning module such as MRP. Static and dynamic informational and functional models of the AGVS are developed. The system incorporates: (i) conflict-free shortest path routing procedures, and (ii) vehicle assignment rules or scheduling strategies. A prototype version of each of these has been developed for demonstrative purposes. This object-oriented modelling methodology provides the capability of rapid development and change. The approach has been demonstrated for a real manufactured product through simulation studies which confirm the superior performance of anticipatory AGVS control rules, even in a production orderdriven environment.     

Effects of routing flexibility, sequencing flexibility and scheduling decision rules on the performance of a flexible manufacturing system

This paper focuses on a simulation-based experimental study of the interaction among routing flexibility, sequencing flexibility and part sequencing rules in a typical flexible manufacturing system (FMS). Two scenarios are considered for experimentation. Three routing flexibility levels, five sequencing flexibility levels and four scheduling rules for part sequencing decision are considered for detailed investigation. The performance of the FMS is evaluated using various measures related to flow time and tardiness of parts. The simulation results are subjected to statistical analysis. The analysis of results reveals that deterioration in system performance can be minimized substantially by incorporating either routing flexibility or sequencing flexibility or both. However, the benefits of either of these flexibilities diminish at higher flexibility levels. Part sequencing rules such as earliest due date and earliest operation due date provide better performance for all the measures at higher flexibility levels.     

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.     

Performance Analysis of an FMS Operating Under Different Failure Rates and Maintenance Policies

Flexible manufacturing Systems (FMSs) typically operate at 70–80% utilization, which is much higher than the utilization of traditional machines that can operate with as low as 20% utilization. A result is that an FMS may incur four times more wear and tear than a traditional system. This requests the execution of effective maintenance plans on FMSs. While maintenance actions can reduce the effects of breakdowns due to wear-outs, random failures are still unavoidable. It is important to understand the implications of a given maintenance plan on an FMS before its implementation. This paper discusses a procedure that combines simulation and analytical models to analyze the effects of corrective, preventive, and opportunistic maintenance policies on the performance of an FMS. The FMS performance is measured by its operational availability index, which is determined using the production output rate of the FMS under a variety of time between failure distributions and different operational conditions. The effects of various maintenance policies on FMS performance are simulated and the results are compared to determine the best policy for a given system.     

Real-time control and scheduling of flexible manufacturing systems: An ordinal optimisation based approach

A unique real-time control and scheduling framework for flexible manufacturing systems (FMS) is presented in this paper. The framework enables the adoption of different scheduling policies for short-term intervals when responding to the dynamic changes of the FMS shop floor status. Each time when rescheduling is called for, standard clock (SC) simulation is first employed to evaluate the performance of a set of scheduling policies for a short planning horizon. The ordinal optimisation concept is then used to choose quickly the most desirable scheduling policy. Owing to the use of the standard clock technique and the ordinal optimisation concept, this framework accomplishes a dramatic reduction in the time needed for decision making, the essential requirement for real-time control. It is also found that as the scale of the problem increases, the decision-making time increases linearly rather than exponentially. These two important features indicate that this framework has the potential for being successfully implemented in real FMS settings. Although the framework cannot always guarantee the global best performance, the case study indicates that satisfactory performance results are always achieved by using this framework.     

Effectiveness of flexible routing control

Flexibility in part process representation and in highly adaptive routing algorithms are two major sources for improvement in the control of flexible manufacturing systems (FMSs). This article reports the investigation of the impact of these two kinds of flexibilities on the performance of the system. We argue that, when feasible, the choices of operations and sequencing of the part process plans should be deferred until detailed knowledge about the real-time factory state is available.To test our ideas, a flexible routing control simulation system (FRCS) was constructed and a programming language for modeling FMS part process plans, control strategies, and environments of the FMS was designed and implemented. In addition, a scheme for implementing flexible process routing called data flow dispatching rule (DFDR) was derived.The simulation results indicate that flexible processing can reduce mean flow time while increasing system throughput and machine utilization. We observed that this form of flexibility makes automatic load balancing of the machines possible. On the other hand, it also makes the control and scheduling process more complicated and calls for new control algorithms.     

基于遗传算法的工艺路线决策与优化

在已有的工艺路线决策优化研究的基础上,分析了工艺知识的特点,确定了基于特征的工艺知识表达方法,根据工艺知识间的约束关系,构建基于工艺约束的工艺路线决策空间,提高遗传算法的搜索能力。针对工艺路线决策的不确定性,建立了多目标优化函数,将遗传算法应用于工艺路线决策过程中。通过设计合理的基因编码规则、适应度函数、交叉、变异算法优化工艺路线。通过实例,介绍了利用遗传算法进行工艺路线决策和优化的过程。     

基于神经网络的直接优化控制

提出一种直接优化求解控制量的轨迹跟踪控制策略，无须知道系统的先验知识，基于神经网络在线实时辨识，反复迭代求解已知跟踪轨迹的一步最优控制量。几组非线性系统的仿真表明该算法具有简捷快速，适应面宽的特点。     

Dynamic rescheduling in FMS that is simultaneously considering energy consumption and schedule efficiency

The dynamic rescheduling problem in flexible manufacturing systems (FMS) has historically emphasized the schedule efficiency. However, energy consumption is a basic need for different purposes in manufacturing systems around the world. This paper proposes an innovative approach to study the dynamic scheduling problem in FMS, taking the objectives of minimum or maximum energy consumption into account. A new goal programming mathematical model, which considers the energy consumption and the schedule efficiency simultaneously, is presented for solving this problem. A rescheduling method based on the genetic algorithm is introduced to address the dynamic rescheduling problem in FMS. A period policy is selected to deal with the dynamic feature of the problem. Numerical experiments have been designed to test and evaluate the performance of the proposed model. The experimental results show that the minimum energy consumption model can save the energy consumption and enhance the schedule efficiency.     

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.     

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.     

Evaluation of the impact of information delays on flexible manufacturing systems performance in dynamic scheduling environments

The significance of the adverse effects of information delays (IDs) on flexible manufacturing system (FMS) performance is getting increasing attention from manufacturing systems managers, planners, schedulers, Enterprise Resource Planning software developers, and researchers because of their potential to disrupt production schedules. In this paper, we examine the extent of the adverse impact that IDs have on FMS performance. The FMSs are assumed to operate in a “review period” mode; i.e., the control decisions (e.g., sequencing and dispatching) are taken based on information monitored at predetermined intervals of time called “review periods”. The performance deterioration occurs due to the obsolescence of system status information. Key empirical findings based on extensive simulation experiments are: (1) IDs significantly degrade FMS performance for due date-based measures (mean tardiness and percent of jobs tardy); (2) IDs also degrade FMS performance for non-due date-based measures (mean flowtime and average machine utilization), albeit to a less severe degree; (3) routing flexibility, often regarded as a significant factor to influence FMS performance, is superseded by status review information delay.     

Simulation study of an AGV system in an FMS environment

A simulation program written in ECSL to simulate an AGV system serving an FMS is presented. It incorporates a special algorithm to enable ‘intelligent’ routing of the AGVs with minimum control requirements. The program was used to examine several parameters and scheduling/control disciplines affecting the AGV system's performance for a specific FMS. Results show that selection of an appropriate combination of parameter values can have a beneficial effect on the FMS.