Workload balance and part-transfer minimization in flexible manufacturing systems

Problems related to the flow management of a flexible manufacturing system (FMS) are here formulated in terms of combinatorial optimization. We consider a system consisting of several multitool automated machines, each one equipped with a possibly different tool set and linked to each other by a transportation system for part moving. The system operates with a given production mix. The focused flow-management problem is that of finding the part routings allowing for an optimal machine workload balancing. The problem is formulated in terms of a particular capacity assignment problem. With the proposed approach, a balanced solution can be achieved by routing parts on a limited number of different paths. Such a balancing routing can be found in polynomial time. We also give polynomial-time and-space algorithms for choosing, among all workload-balancing routings, the ones that minimize the global amount of part transfer among all machines.     

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.     

Reliability analysis of flexible manufacturing systems

High productivity is the primary goal of flexible manufacturing systems (FMSs) in which semi-independent workstations are integrated using automated material-transport systems and hierarchical local networks. Availability of various subsystems and of the system as a whole is a prerequisite for achieving functional integration as well as high throughput. An FMS also has inherent routing and operation flexibilities that provide it with a certain degree of fault tolerance. A certain volume of production can thus be maintained in the face of subsystem (i.e., machines, robots, material handling system, etc.) failures. In this article, we propose two reliability measures, namely, part reliability (PR) and FMS reliability (FMSR) for manufacturing systems and present algorithms to evaluate them. We also consider the dynamic or time-dependent reliability analysis as a natural generalization of the static analysis. The methods outlined use an algorithm that generates process-spanning graphs (PSGs), which are used to evaluate the reliability measures.     

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.     

A case study in FMS production planning and dispatching

The speedy development and extensive application of computers have helped play a significant role in a new technological revolution. The importance of FMS flexibility in producing a variety of products and adapting rapidly to customer requirements makes FMSs attractive. Further, FMSs are most appropriate for largevariety and medium- to high-volume production environments. However, the module of the FMS production planning system is not perfect. This paper focuses on a new scheme for FMS production planning and dispatching under the realistic assumptions promoted by a particular flexible manufacturing factory. Some practical constraints such as fixture uniqueness, limited tool magazine capacity, and a given number of pallets are considered. The simulation results indicate that the scheme provides a good production plan, according to the short-term plans from the MIS Department. Some conclusions are drawn and a discussion is presented.     

Performance Analysis of Flexible Manufacturing Systems with a Single Discrete Material-Handling Device

We present an analytical model for performance prediction of flexible manufacturing systems (FMSs) with a single discrete material-handling device (MHD). This configuration of FMS is significant for many reasons: it is commonly found in industry, it simplifies material-handling control, it is amenable to analytical modeling, and it forms a building block for more complex systems. Standard queueing models are inadequate to analyze this configuration because of the need to take into consideration many nontrivial issues such as state-dependent routing, interference from the MHD, and the analysis of the MHD. To account for state-dependent routing, we develop an iterative method that is built around mean value analysis. To analyze the MHD interference, we use two queueing network models. In the first, we ignore queueing at the MHD but model the interference from the MHD by inflating the station service times. The second network models the queueing for the MHD and estimates the blocking (inflation) times needed for the first model. By iterating between the two networks, we are able to predict the performance of this configuration of FMS. Our analytical estimates are validated against discrete event simulation and shown to be quite accurate for initial system design.     

Work flow control in the flexible flow line

This research involves the development and evaluation of a part flow control model for a type of flexible manufacturing system (FMS) called a dedicated flexible flow line (FFL). In the FFL, all part types flow along the same path between successive machine groups. The specific objective of the part flow control model for the FFL is to minimize makespan for a given set of parts produced in a FFL near-term schedule, given fixed available buffer constraints. The control model developed in this research involved the repeated, real-time execution of a mathematical programming algorithm. The algorithm attempts to release the right mix of parts at the tight time to keep the FFL operating smoothly. The focus of the approach is directed toward managing WIP buffers for each machine group queue. The algorithm specifically incorporates stochastic disturbance factors such as machine failures. Through a limited number of simulation experiments, performance of the control model is shown to be superior to other parts releasing and control methods reported in the literature.     

Towards an Integration of Process Planning and Production Planning and Control for Flexible Manufacturing Systems

This introduction article attempts to present some major issues relating to the integration of process planning and production planning and control (PPC) for flexible manufacturing systems (FMSs). It shows that the performance of an FMS can be significantly improved and FMS capabilities more effectively utilized by integrating process planning and PPC functions. The various types of flexibility to be planned and provided for in process planning and manufacturing are summarized in the article, as well as emerging conceptual frameworks for integration, along with their implementation requirements and problems. Distinctive elements that differentiate these frameworks, such as the extent of integration of process planning and PPC activities, number of alternative process plans, and the time at which numerical control programs are generated, are discussed, followed by a brief summary of the articles compiled for this special issue.     

The Effects of Scheduling Rules and Routing Flexibility on the Performance of a Random Flexible Manufacturing System

The increased use of flexible manufacturing systems to efficiently provide customers with diversified products has created a significant set of operational challenges for managers. Many issues concerning procedures and policies for the day-to-day operation of these systems still are unresolved. Previous studies in this area have concentrated on various problems by isolating or simplifying the systems under study. The primary objective of this study is to extend previous research by examining the effects of scheduling rules and routing flexibility on the performance of a constrained, random flexible manufacturing system (FMS). Other experimental factors considered are shop load, shop configuration, and system breakdowns. Within the bounds of this experiment, the results indicate that, in the presence of total routing flexibility, the effects of shop load, system breakdowns, and scheduling rules are significantly dampened. In particular, when total routing flexibility exists, the choice of scheduling rules is not critical. We also show that the behavior of scheduling rules in a more constrained FMS environment (i.e., where system breakdowns occur and material handling capability is limited) is consistent with the findings of previous research conducted under less constrained environments. Finally, results indicate that the shop configuration factor has little or no impact on a system's flow-time performance.     

Analysis of flexible manufacturing systems with distinct repeated visits: DrQ

This article examines the performance effects caused by repeated part visits at the workstations of a flexible manufacturing system (FMS). Such repeated part visits to the same workstations are commonly associated with fixture changes for machining complex parts, reclamping, and remounting or reorienting them. Since each of the repeated visits to a workstation may require different processing requirements, the resulting queueing network does not have a product form solution. We therefore develop an approximate mean value analysis model for performance evaluation of an FMS that may produce multiple part types with distinct repeated visits. We provide numerical examples and validate the accuracy of our solution algorithm against simulation. These examples show that the proposed model produces accurate throughput and utilization predictions with minimal computational efforts. These examples reveal that increasing the total pallet population may result in a reduction of the aggregate throughput, and that the FMS's performance could be more sensitive to the mix of pallets and part routes than to the total number of pallets. Our model will be of use, in particular, when managers wish to control individual operations (e.g., to adjust individual operation times to achieve economic savings in tool wear and breakage costs) or to investigate the performance implications of route changes due to alternate assignments of particular manufacturing tasks to certain workstations.     

Developing a Hybrid Programmable Logic Controller Platform for a Flexible Manufacturing System

In this article, we present the design and implementation of a flexible manufacturing system (FMS) control platform based on a programmable logic controller (PLC) and a personal computer (PC)-based visual man-machine interface (MMI) and data acquisition (DAS) unit. The key aspect of an FMS is its flexibility to adapt to changes in a demanding process operation. The PLC provides feasible solutions to FMS applications, using PC-based MMI/DAS, whereby PLCs are optimized for executing rapid sequential control strategies. PCs running MMI/DAS front-ends make intuitive operation interfaces, full of powerful graphics and reporting tools. Information from the PC can be distributed through a company's local area network or web using client-server technologies. Currently, with the convergence of underlying microprocessor technology and software programming techniques, many users find that PLCs provide a cost-effective solution to real-time control in small- to medium-sized process plants, especially when combined with supervisory PCs using hybrid systems. The major work of this article demonstrates that PLCs are responsive to rapid and repetitious control tasks, using PCs that present the flow of information automation and accept operator instructions, thereby providing the user a tool to modify and monitor the process as the requirements change.     

Modeling FMS with decision Petri nets

Decision point extended timed Petri nets or decision Petri nets (DPN) are introduced as an extended modeling framework for FMS performance evaluation. The decision point extension allows the explicit modeling of the control of the flow of tokens in timed Petri nets and hence represents the control of the flow of material, resources, and information in FMS. Further, the concept of a bounded transition is proposed to conveniently model the blocking logic in an FMS with limited buffer capacities. The motivation to present these conventions is to develop a user-friendly graphic model to represent FMS designs for analysis by discrete event simulation. DPN affords concise models that can be conveniently developed and easily transformed into discrete event simulation models. With the help of a simple FMS example, which includes a number of part types, loading rules, dispatching rules, and probabilistic branching (at an inspection station), we illustrate the DPN model development. As an illustration of the ease with which it can be tranformed into a simulation model, we have developed a generalized simulator called ROBSIM and outline here its methodological basis. The proposed concepts should be of interest to users of discrete event simulation in FMS design or elsewhere to tap the potential of basic Petri net concepts for graphic representation and specification purposes. In particular, our work should encourage other researchers to develop extensions relevant to their own areas of interest.     

Performance management in flexible manufacturing systems

This article treats several performance management decision problems in flexible manufacturing systems (FMSs). This work differs from a number of other studies in that we allow the processing rates at the machines to be varied, and the system has to meet a given throughput goal per unit time. The managerial decision options modeled here include part routing and allocation of tasks to machines, work-in-progress (WIP) levels, capacity expansions, tool-type selection, the setting of throughput goals, and multiperiod production planning. We discuss and explain the insights and implications, partly nonintuitive, gained from our investigations. Finally, extensive numerical evaluations are included to illustrate the economic and performance impact of the various performance management alternatives. These results demonstrate that substantial economic benefits can be achieved by careful tuning of the FMS operational parameters.     

Using topographic wetness index in vegetation ecology: does the algorithm matter?

Questions: How important is the choice of flow routing algorithm with respect to application of topographic wetness index (TWI) in vegetation ecology? Which flow routing algorithms are preferable for application in vegetation ecology? Location: Forests in three different regions of the Czech Republic. Methods: We used vegetation data from 521 georeferenced plots, recently sampled in a wide range of forest communities. From a digital elevation model, we calculated 11 variations of TWI for each plot with 11 different flow routing algorithms. We evaluated the performance of differently calculated TWI by (1) Spearman rank correlation with average Ellenberg indicator values for soil moisture, (2) Mantel correlation coefficient between dissimilarities of species composition and dissimilarities of TWI and (3) the amount of variation in species composition explained by canonical correspondence analysis. Results: The choice of flow routing algorithm had a considerable effect on the performance of TWI. Correlation with Ellenberg indicator values for soil moisture, Mantel correlation coefficient and explained variation doubled when the appropriate algorithm was used. In all regions, multiple flow routing algorithms performed best, while single flow routing algorithms performed worst. Conclusions: We recommend the multiple flow routing algorithms of Quinn et al. and Freeman for application in vegetation ecology.     

An Object-Oriented Approach for Flexible Manufacturing Control Systems Analysis and Design Using the Unified Modeling Language

In reacting to global competition and rapidly changing customer demands, industrial business organizations have developed a strong interest in flexible automation. The aim of flexible automation focuses on achieving agility in handling uncertainties from internal or external environments. Modeling complex structures, promoting reuse, and shortening the development time cycle are particularly significant aspects in the analysis and design of CIM systems, where heterogeneous elements have to be integrated in a complex control architecture. The design methodology for FMS control software involves the abstraction of an FMS and the estimation of the system performances. The aim of this activity is to suggest the optimal configuration of an FMS for given specifications, through simulation tools. In the software engineering field, object-oriented (OO) approaches have proven to be a powerful technique with respect to such aspects. The unified modeling language (UML), by using OO design methodologies, can offer reusability, extendibility, and modifiability in software design. Also, it bridges the gap that exists between the OO analysis and design area and the area of OO programming by creating an integrative metamodel of OO concepts. The specific goal of this paper is to formulate a new methodology for developing reusable, extendible, and modifiable control software for an FMS in an object-oriented environment. It is demonstrated that, with few diagrams, UML can be used to model such systems without being associated with other modeling tools.     

Scheduling algorithms for a two-machine flexible manufacturing system

The flexible manufacturing system (FMS) considered in this paper is composed of two CNC machines working in series—a punching machine and a bending machine connected through rollers acting as a buffer system of finite capacity. The main difference between the present problem and the standard two-machine flow shop problem with finite intermediate capacity is precisely the buffer system, which in our problem consists of two stacks of parts supported by rollers: the first stack contains the output of the punching machine, while the second stack contains the input for the bending machine. When the second stack is empty, the first stack may be moved over. Furthermore, the capacity of each stack depends on the particular part type being processed. The FMS can manufacture a wide range of parts of different types. Processing times on the two machines are usually different so that an unbalance results in their total workload. Furthermore, whenever there is a change of the part type in production, the machines must be properly reset—that is, some tools need to be changed or repositioned. A second important difference between the present problem and the usual two-machine flow shop problem is the objective. Given a list ofp part types to be produced in known quantities, the problem considered here is how to sequence or alternate the production of the required part types so as to achieve various hierarchical targets: minimize the makespan (the total time needed to complete production) and, for instance, compress the idle periods of the machine with less workload into a few long enough intervals that could be utilized for maintenance or other reasons. Although Johnson's rule is optimal in some particular cases, the problem addressed in the paper isNP-hard in general: heuristic procedures are therefore provided.     

A Genetic-Based Vision System for Cross-Functional Integration in Flexible Manufacturing: A Tutorial and Application

Machine vision has the potential to significantly impact both quality and productivity in automated manufacturing, due to its versatility, flexibility, and relative speed. Unfortunately, algorithmic development has not kept pace with advances in vision hardware technology, particularly in the areas of analysis and decision making. In this article, a tutorial is presented that explains how a genetic algorithm can be applied to vision systems for shape analysis and quality assessment. The control parameters for the algorithm are optimized by conducting experiments of Taguchi's approach to parameter design. The main objective behind this algorithm is to explain an application of the vision system that uses upstream design data of machined parts of different types for downstream metrology and quality decision making in the environment of flexible manufacturing. The part types used for demonstration are restricted to planar polygonal profiles generated by projecting 3D objects onto a 2D inspection plane. The input to the system is a set of boundary features of the part being analyzed, and the outputs from the system include the estimators of size, orientation, position, and out-of-profile error of the part. The system can analyze machined parts of different types without modifying software programs and parameter settings, which makes it generic and flexible, and is inherently suitable for on-line implementation in FMS environments.     

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.     

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.