A Dynamic Tool Requirement Planning Model for Flexible Manufacturing Systems

Despite their strategic potential, tool management issues in flexible manufacturing systems (FMSs) have received little attention in the literature. Nonavailability of tools in FMSs cuts at the very root of the strategic goals for which such systems are designed. Specifically, the capability of FMSs to economically produce customized products (flexibility of scope) in varying batch sizes (flexibility of volume) and delivering them on an accelerated schedule (market response time) is seriously hampered when required tools are not available at the time needed. On the other hand, excess inventory of tools in such systems represents a significant cost due to the expensive nature of FMS tool inventory. This article constructs a dynamic tool requirement planning (DTRP) model for an FMS tool planning operation that allows dynamic determination of the optimal tool replenishments at the beginning of each arbitrary, managerially convenient, discrete time period. The analysis presented in the article consists of two distinct phases: In the first phase, tool demand distributions are obtained using information from manufacturing production plans (such as master production schedule (MPS) and material requirement plans (MRP)) and general tool life distributions fitted on actual time-to-failure data. Significant computational reductions are obtained if the tool failure data follow a Weibull or Gamma distribution. In the second phase, results from classical dynamic inventory models are modified to obtain optimal tool replenishment policies that permit compliance with such FMS-specific constraints as limited tool storage capacity and part/tool service levels. An implementation plan is included.     

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 Simulation Study of an Object-Oriented Integration Testbed for Process Planning and Production Scheduling

Many studies on integration of process planning and production scheduling have been carried out during the last decade. While various integration approaches and algorithms have been proposed, the implementation of these approaches is still a difficult issue. To achieve successful implementation, it is important to examine and evaluate integration approaches or algorithms beforehand. Based on an object-oriented integration testbed, a simulation study that compares different integration algorithms is presented in this paper. Separated planning method and integrated planning methods are examined. Also, situations of both fixed and variable processing times are simulated, and useful results have been observed. The successful simulation with the object-oriented integration testbed eventually will be extended to include other new planning algorithms for examining their effectiveness and implementation feasibility.     

Object-Oriented Modeling for Flexible Manufacturing Systems

Object-oriented modeling provides a new way of thinking about flexible manufacturing systems, using models organized around real-world concepts. This paper describes how the object modeling technique can be used to develop integrated factory models that embrace factory process modeling as well as policy modeling. Such models can be used to assess how quickly a manufacturing organization can adjust its operations to meet changes in demands for products, consumer preferences, supplier quality, and lead times. These models also can be used as vehicles for studying the impact of introducing new product lines or new process technology without the disruption or expense of pilot projects or test setups.     

A Generic Model to Solve Tactical Planning Problems in Flexible Manufacturing Systems

This paper is an attempt to develop a generic modeling framework that addresses tactical planning problems of flexible manufacturing systems in a coherent manner. We propose a generic 0-1 mixed integer programming formulation, that integrates batching, loading, and routing problems with their critical aspects related to a system's performance. For this purpose, a thorough analysis is made to determine and relate system components, their attributes, and alternatives together with performance measures specific to tactical planning. This provided the justification to support our argument about generality of the model. A linear programming formulation is provided to approximate the mixed integer formulation proposed so as to overcome the problem's combinatorial complexity. The potential capability of the linear approximation proposed also is demonstrated via a small set of test problems.     

Re-Examining the Performance of MRP and Kanban Material Control Strategies for Multi-Product Flexible Manufacturing Systems

Material control schemes can be classified as push, pull, or hybrid strategies. This article compares the performance of MRP (push) and kanban (pull) for a multi-stage, multi-product manufacturing system. Using simulation experiments we analyze system performance under different product mixes and observe that in certain environments with advance demand information kanban-based pull strategies can lead to significant inefficiencies. In these environments MRP-type push strategies yield better performance in terms of inventories and service levels. We also study the impact of design parameters such as safety lead time and safety stock policies on system performance and observe that for low and medium values of system loads, safety lead time policies yield better system performance than safety stock policies. These insights can be helpful in designing efficient MRP-type push strategies in multi-product environments.     

Design Guidelines for Deadlock-Handling Strategies in Flexible Manufacturing Systems

Deadlock-free operation of flexible manufacturing systems (FMSs) is an important goal of manufacturing systems control research. In this work, we develop the criteria that real-time FMS deadlock-handling strategies must satisfy. These criteria are based on a digraph representation of the FMS state space. Control policies for deadlock-free operation are characterized as partitioning cuts on this digraph. We call these structural control policies (SCPs) because, to avoid deadlock, they must guarantee certain structural properties of the subdigraph containing the empty state; namely, that it is strongly connected. A policy providing this guarantee is referred to as correct. Furthermore, an SCP must be configurable and scalable; that is, its correctness must not depend on configuration-specific system characteristics and it must remain computationally tractable as the FMS grows in size. Finally, an SCP must be efficient; that is, it must not overly constrain FMS operation. We formally develop and define these criteria, formulate guidelines for developing policies satisfying these criteria, and then provide an example SCP development using these guidelines. Finally, we present an SCP that guarantees deadlock-free buffer space allocation for FMSs with no route restrictions.     

A New Cyclic Scheduling Algorithm for Flexible Manufacturing Systems

Flexible manufacturing system control is an NP-hard problem. A cyclic approach has been demonstrated to be adequate for an infinite scheduling problem because of maximal throughput reachability. However, it is not the only optimization criterion in general. In this article we consider the minimization of the work in process (WIP) as an economical and productivity factor. We propose a new cyclic scheduling algorithm giving the maximal throughput (a hard constraint) while minimizing WIP. This algorithm is based on progressive operations placing. A controlled beam search approach has been developed to determine at each step the schedule of the next operations. After presenting the main principles of the algorithm, we compare our approach to several most known cyclic scheduling algorithms using a significant existing example from the literature.     

Supervisory Control of Functionally-Expandable Manufacturing Systems

Supervisory controllers have traditionally coordinated the various resources of manufacturing systems, such as flexible manufacturing workcells, for the production of a priori set families of part types. This paper expands on this capability by allowing the control of the production of new part types side by side with previously defined and planned for nominal part types. The proposed basic workcell supervisory-control approach advocates the use of a pair of non-communicating independent supervisors, synthesized individually but working in concert, to achieve the production of existing and new part types: nominal and complementary supervisors, respectively. The nominal supervisor is responsible for controlling the behavior of the nominal system, producing the set of a priori planned-for part types, whereas the complementary supervisor controls the flow of the a priori unplanned-for new part types.     

Impact of Interruptions on Schedule Execution in Flexible Manufacturing Systems

Finite capacity scheduling software packages provide a detailed advance plan of production events. However, the execution of this advance plan is disrupted by a myriad of unanticipated interruptions, such as machine breakdowns, yield variations, and hot jobs. The alternatives available to respond to such interruptions include modifying the existing schedule, regenerating the complete schedule, or doing nothing and letting the production system gradually absorb the impact of the interruption. This article reports on a simulation study aimed at understanding the impact of an interruption on a schedule in order to build a knowledge base for intelligent selection of a response from a set of alternatives. The results of the experimental study are used to identify significant major factors and their interactions. The results are discussed to draw insights into the performance of a flexible manufacturing system following an interruption. The causes leading to particular performance anomalies are extensively discussed and mechanisms for propagation and absorption of the effect of interruptions in manufacturing systems are inferred. Practical implications for the development and implementation of schedules are deduced and areas for further research proposed. This study provides the groundwork necessary to proceed with the development of strategies for responding to interruptions.     

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.     

The Applications of Flexible Manufacturing Technologies in Business Process Reengineering

Through radical redesign of business processes and systems, policies, and organizational structures, the business process reengineering (BPR) effort was initiated in the manufacturing industry to seek performance breakthroughs. This paper describes a novel approach to the BPR, which applies flexible manufacturing systems (FMSs) design and analysis technologies, such as simulation, multicriteria decision support, and artificial intelligence (AI). These technologies are integrated to design and analyze specific FMS models related to the proposed technical and managerial changes in an industrial case. First, the literature is reviewed to obtain an understanding of the BPR concept and the role of FMS design and analysis in BPR. Second, a decision-making support system is developed to illustrate how the FMS design and analysis would affect BPR. Finally, a summary of the integrated approach practice in industry and conclusions are presented. The paper shows that the key to a successful BPR approach is the identification and analysis of specific proposed models. It also demonstrates that the integrated approach enables engineers to improve the efficiency of BPR.     

The Application and Evaluation of Banker's Algorithm for Deadlock-Free Buffer Space Allocation in Flexible Manufacturing Systems

Deadlock-free operation is essential for operating highly automated manufacturing systems. The seminal deadlock avoidance procedure, Banker's algorithm, was developed for computer operating systems, an environment where very little information regarding the future resource requirements of executing processes is known. Manufacturing researchers have tended to dismiss Banker's algorithm as too conservative in the manufacturing environment where future resource requirements are well defined by part routes. In this work, we investigate this issue by developing variants of Banker's algorithm applicable to buffer space allocation in flexible manufacturing. We show that these algorithms are not overly conservative and that, indeed, Banker's approach can provide very good operational flexibility when properly applied to the manufacturing environment.     

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.     

Design and Implementation of a Flexible Manufacturing Control System Using Neural Network

Design and implementation of a sequential controller based on the concept of artificial neural networks for a flexible manufacturing system are presented. The recurrent neural network (RNN) type is used for such a purpose. Contrary to the programmable controller, an RNN-based sequential controller is based on a definite mathematical model rather than depending on experience and trial and error techniques. The proposed controller is also more flexible because it is not limited by the restrictions of the finite state automata theory. Adequate guidelines of how to construct an RNN-based sequential controller are presented. These guidelines are applied to different case studies. The proposed controller is tested by simulations and real-time experiments. These tests prove the successfulness of the proposed controller performances. Theoretical as well as experimental results are presented and discussed indicating that the proposed design procedure using Elman's RNN can be effective in designing a sequential controller for event-based type manufacturing systems. In addition, the simulation results assure the effectiveness of the proposed controller to outperform the effect of noisy inputs.     

An Analytical Queueing Network Model for Flexible Manufacturing Systems with a Discrete Handling Device and Transfer Blockings

In this paper, we study job shop-like flexible manufacturing systems (FMSs) with a discrete material handling system (MHS). In such FMSs, the MHS is a critical device, the unavailability of which may induce transfer blockings of the machines. The FMS devices therefore are hierarchically structured into primary and secondary devices to manage such blocking and avoid deadlocks in these FMSs. For evaluating the quantitative steady-state performance of such FMSs, we propose an analytical queueing network model that relies on an approximate method proposed for analyzing computer systems with simultaneous possessions of resources. Such a model is obtained using the concept of passive resources and by aggregating the FMS workload data so that models are much more tractable. The analytical results are validated against discrete event simulation and shown to be very encouraging. We also show how to increase their robustness, especially under light workload conditions, by modifying an assumption of the method concerning service time distributions.     

Performance Evaluation of Flexible Manufacturing Systems with Finite Local Buffers: Fixed and Dynamic Routings

This article evaluates the performance of flexible manufacturing systems with finite local buffers and fixed or dynamic routing rules, and addresses the optimal design or system configuration problem of maximizing the system throughput. The costs include machine cost, part (or pallet) cost, and local buffers cost. First, the system throughputs and their behaviors are considered with both queueing network analysis and simulation, and it is shown for a fixed routing model that the system throughput in the case of finite local buffers is greater than in the case of infinite local buffers. For a fixed versus dynamic routing rule, it is also found that the throughput in the former case can be close to the one in the latter case by changing the setting parameters. Next, the design problems of maximizing the system throughput are considered numerically for fixed and dynamic routing cases. Then, it is seen that better combination of design variables is a class of the monotonicity in local buffers, service rates, and routing probabilities.     

A Decentralized Approach to Estimate Activity-Based Costs and Near-Optimal Resource Allocation in Flexible Manufacturing Systems

Flexible manufacturing systems (FMSs) can apply the efficiencies of large-scale production to small batch production. The coordination of FMS activities is a complex task; this paper presents a decentralized pricing mechanism that can be used to estimate the activity–based costs and manage the activities of the FMS efficiently. The pricing mechanism described in this paper does not require systemwide information to compute prices; instead, the pricing mechanism samples and uses the demand information at each CNC machine to compute rental prices at that machine. We derive the theoretical formula for rental prices supporting the optimal performance and propose simulation studies to estimate the rental prices for real-time price changes in a decentralized manner. Results from a preliminary simulation study indicate that stable rental prices can be estimated and significant improvements can be realized by using the pricing mechanism.     

A Heuristic Search Approach Using Approximate Solutions to Petri Net State Equations for Scheduling Flexible Manufacturing Systems

This paper proposes a new heuristic search approach based on an analytic theory of the Petri net state equations for scheduling flexible manufacturing systems (FMSs) with the goal of minimizing makespan. The proposed method models an FMS using a timed Petri net and exploits approximate solutions of the net's state equation to predict the total cost (makespan) from the initial state through the current state to the goal. That is, the heuristic function considers global information provided by the state equation. This makes the method possible to obtain solutions better than those obtained using prior works (Lee and DiCesare, 1994a, 1994b) that consider only the current status or limited global information. In addition, to reduce memory requirement and thus to increase the efficiency of handling larger systems, the proposed scheduling algorithm contains a procedure to reduce the searched state space.