A Genetic Algorithm Approach to the Scheduling of FMSs with Multiple Routes

Usually, most of the typical job shop scheduling approaches deal with the processing sequence of parts in a fixed routing condition. In this paper, we suggest a genetic algorithm (GA) to solve the job-sequencing problem for a production shop that is characterized by flexible routing and flexible machines. This means that all parts, of all part types, can be processed through alternative routings. Also, there can be several machines for each machine type. To solve these general scheduling problems, a genetic algorithm approach is proposed and the concepts of virtual and real operations are introduced. Chromosome coding and genetic operators of GAs are defined during the problem solving. A minimum weighted tardiness objective function is used to define code fitness, which is used for selecting species and producing a new generation of codes. Finally, several experimental results are given.     

Evaluating Virtual Cells and Multistage Flow Shops: An Analytical Approach

The implementation of cellular manufacturing can be carried out through the creation of manufacturing cells (i.e., groups of dissimilar machines dedicated to a set of part types that are placed in close proximity to one another) or virtual cells (i.e., the dedication of specific machines within the current departments to a prespecified set of part types). Typically, the former involves the reorganization of the shop floor and provides the operational benefit of reduced materials handling. On the other hand, the latter configuration is simpler to implement and easier to reconfigure in light of product demand changes, but it may not offer the same operational benefits. In this paper, we propose and validate analytical approximations for comparing the performance of virtual cells and multistage flow shops. Using these approximations and hypothetical data, we identify some key factors that influence the implementation of virtual cells in a multistage flow shop environment. We conclude with an application of our approximations to industrial data.     

A line-balancing strategy for designing flexible assembly systems

We present a rough-cut analysis tool that quickly determines a few potential cost-effective designs at the initial design stage of flexible assembly systems (FASs) prior to a detailed analysis such as simulation. It uses quantitative methods for selecting and configuring the components of an FAS suitable for medium to high volumes of several similar products. The system is organized as a series of assembly stations linked with an automated material-handling system moving parts in a unidirectional flow. Each station consists of a single machine or of identical parallel machines. The methods exploit the ability of flexible hardware to switch almost instantaneously from product to product. Our approach is particularly suitable where the product mix is expected to be stable, since we combine the hardware-configuration phase with the task-allocation phase. For the required volume of products, we use integer programming to select the number of stations and the number of machines at each station and to allocate tasks to stations. We use queueing network analysis, which takes into account the mean and variance of processing times among different products to determine the necessary capacity of the material-handling system. We iterate between the two analyses to find the combined solution with the lowest costs. Work-in-process costs are also included in the analysis. Computational results are presented.     

Steady-State Analysis and Scheduling of Cyclic Job Shops with Overtaking

A cyclic shop is a production system that repeatedly produces identical sets of parts of multiple types, called minimal part sets (MPSs), in the same loading and processing sequence. A different part type may have a different machine visit sequence. We consider a version of cyclic job shop where some operations of an MPS instance are processed prior to some operations of the previous MPS instances. We call such a shop an overtaking cyclic job shop (OCJS). The overtaking degree can be specified by how many MPS instances the operations of an MPS instance can overtake. More overtaking results in more work-in-progress, but reduces the cycle time, in general. We prove that for a given processing sequence of the operations at each machine, under some conditions, an OCJS has a stable earliest starting schedule such that each operation starts as soon as its preceding operations are completed, the schedule repeats an identical timing pattern for each MPS instance, and the cycle time is kept to be minimal. To do these, we propose a specialized approach to analyzing steady states for an event graph model of an OCJS that has a cyclic structure, which can keep the MPS-based scheduling concept. Based on the steady-state results, we develop a mixed integer programming model for finding a processing sequence of the operations at each machine and the overtaking degrees, if necessary, that minimize the cycle time.     

Modeling and design optimization of asynchronous flexible assembly systems with statistical process control and repair

This article presents the implementation of hybrid procedures involving the use of analytical performance evaluation techniques, discrete event simulation, and Monte Carlo optimization methods for the stochastic design optimization of asynchronous flexible assembly systems (AFASs) with statistical process control (SPC) and repair loops. AFASs are extremely complex and difficult to analyze in that such systems are subject to starvation and blocking effects, random jam occurrences at workstations, and splitting and merging of the assembly flow due to repair loops. Hence, an integrated approach simultaneously analyzing the interactions between product quality and optimal/near optimal system design is pursued. In the analytical analysis stage, a model based on GI/G/1 queueing network theory is used. In the Monte Carlo optimization stage, two alternative stochastic optimization approaches, namely, heuristic versions of stochastic quasigradient and simulated annealing algorithms, are implemented and compared in terms of their capabilities of solving complex AFAS design problems. The hybrid procedures presented appear to perform reasonably well in designing AFASs to reach a target production rate.     

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.     

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.     

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.     

Stable Earliest Starting Schedules for Cyclic Job Shops: A Linear System Approach

We consider a cyclic job shop where an identical mixture of parts of different types, called a minimal part set (MPS), is produced repetitively in the same processing order. The precedence relationships among events (start of operation) are represented by a directed graph that has a recurrent structure. Each operation starts as soon as all its preceding operations are complete (called earliest starting). There is a class of desirable schedules that has the minimum cycle time and an identical schedule pattern for every MPS. By using linear system theory on minimax algebra, we characterize the set of all possible such schedules. We develop an efficient algorithm to find one among such schedules that minimizes a performance measure related to work-in-progress inventory. We also discuss an application to a flexible manufacturing system.     

A note on productivity gains in flexible robotic cells

Flexible robotic cells combine the capabilities of robotic flow shops with those of flexible manufacturing systems. In an m-machine flexible cell, each part visits each machine in the same order. However, the m operations can be performed in any order, and each machine can be configured to perform any operation. We derive the maximum percentage increase in throughput that can be achieved by changing the assignment of operations to machines and then keeping that assignment constant throughout a lot's processing. We find that no increase can be gained in two-machine cells, and that the gain in three- and four-machine cells each is at most 14 \(\frac{2}{7}\)%.     

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.     

Vehicle dispatching for highly loaded semiconductor production considering bottleneck machines first

Semiconductor wafer fabrication lines can be characterized by re-entrant product flow, long production lead-time, large variety of production processes, and large capital investment. These distinctive characteristics make the flow control in the fab very complicated. Throughput rate and lead-time are among the most important performance measures. The throughput rate is usually determined by a bottleneck resource, and the lead-time depends on the machine utilization level and the amount of variability in the system. Due to the high efficiency of material handling and reduced particles, automated material handling systems such as automatic guided vehicles (AGVs), overhead hoist transporters (OHTs), and overhead shuttles (OHSs) are being widely used in wafer fabrication lines (wafer fabs) instead of human operators. Although a material handling system itself is seldom a bottleneck of production in a fab, it is important for that to effectively support the bottleneck machines to maximize the throughput and reduce production lead-time. This paper presents a vehicle dispatching procedure based on the concept of theory of constraints, in which vehicle dispatching decisions are made to utilize the bottleneck machines at the maximum level. Simulation experiments have been performed to compare the proposed vehicle dispatching procedure with existing ones under different levels of machine utilization, vehicle utilization, and local buffer capacity.     

Design and performance characteristics of a continuous multistage tower fermentor

The design of a continuous multistage tower fermentor is described. The fermentor consists of five stages separated by perforated plates. Each stage includes mechanical mixing provided by two disc turbine impellers and has its own impeller shaft with bearing assembly and flexible coupling that enables the operation of an arbitrary number of stages. The normal operation of this system enables the co-current flow of gas and liquid, but the system can function countercurrently as well. The purpose of this study was to examine the hydrodynamic performance, i.e., the pressure gradient along the tower, the mixing time, gas holdup, the residence lime distribution of the continuous phase, the value of the backflow coefficient, and the oxygen transfer rate under conditions usually used during fermentations. From the interrelations between parameters influencing the proper performance of this system, an optimal design of plate geometry for processes requiring high oxygen transfer rate was formulated.     

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.     

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.     

Analytical performance models for closed-loop flexible assembly systems

Flexible Assembly Systems (FASs), which form an important subset of modern manufacturing systems, are finding increasing use in today's industry. In the planning and design phase of these systems, it is useful to have tools that predict system performance for various operating conditions. In this article, we present such a performance analysis tool based on queueing approximation for a class of FASs, namely, closed-loop flexible assembly systems (CL-FASs). For CL-FASs, we describe iterative algorithms for computing steady-state performance measures, including production rate and station utilizations. These algorithms are computationally simple and have a fast convergence rate. We derive a new approximation to correct the mean delay at each queue. This improves the accuracy of performance prediction, especially in the case of small CL-FASs. Comparisons with simulation results indicate that the approximation technique is reasonably accurate for a broad range of parameter values and system sizes. This makes possible efficient (fast and computationally inexpensive) analysis of CL-FASs under various conditions.     

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.     

The optimal configuration and workload allocation problem in flexible manufacturing systems

In this article we consider the problem of determining the minimum cost configuration (number of machines and pallets) for a flexible manufacturing system with the constraint of meeting a prespecified throughput, while simultaneously allocating the total workload among the machines (or groups of machines). Our procedure allows consideration of upper and lower bounds on the workload at each machine group. These bounds arise as a consequence of precedence constraints among the various operations and/or limitations on the number or combinations of operations that can be assigned to a machine because of constraints on tool slots or the space required to store assembly components. Earlier work on problems of this nature assumes that the workload allocation is given. For the single-machine-type problem we develop an efficient implicit enumeration procedure that uses fathoming rules to eliminate dominated configurations, and we present computational results. We discuss how this procedure can be used as a building block in solving the problem with multiple machine types.     

A Comparison Between Machine Flexibility and Routing Flexibility

In this paper, we evaluate two types of flexibility, machine flexibility and routing flexibility, in terms of manufacturing performance in various shop environments. A simulation-based investigation was conducted to analyze the impact of these types of flexibility on the average flow time of parts under various job flow pattern conditions, which characterize the shop nature from a random job shop to a flow shop, operation time variance, setup time, and shop load. The experimental results show how these types of flexibility affect the average flow time of parts and which type is superior under what conditions. Management can obtain better insight and guidelines for determining priorities or the scale, or scope, of various decision items relating to design standardization, process and operations improvement, investment in new equipment and tools, and the like.     

Heuristics for the design of part-orienting systems

In many manufacturing systems, parts must be fed to automatic machines in a specific orientation. This is often accomplished by what are known as part-orienting systems (POSs). A POS consists of one or more separate devices that orient parts, usually with multiple orientations. A theoretical analysis along with the development of some heuristic algorithms is carried out in order to treat the problem of efficient selection and ordering of part-orienting devices that make up a POS. It is indicated that the size of such problems can be quite large in the context of flexible manufacturing systems which may require what are known as flexible part-orienting systems for their efficient operation. Computational experiments are performed in order to evaluate the relative performance of the heuristic algorithms.