An iterative approach to system setup problems in flexible manufacturing systems

System setup problems in flexible manufacturing systems deal with short-term planning problems such as part type selection, machine grouping, operation assignment, tooling, fixture and pallet allocation, and routing. In this article, we consider three of the subproblems: part type selection, machine grouping, and loading. We suggest a heuristic approach to solve the subproblems consistently with the objective of maximizing the expected production rate. The proposed procedure includes routines to generate all possible machine grouping alternatives for a given set of machines, to obtain optimal target workloads for each grouping alternative, and to allocate operations and tools to machine groups. These routines are executed iteratively until a good solution to the system setup problem is obtained. Computational experience is reported.     

Average-Cost Optimal Policies for an Unreliable Flexible Multiproduct Machine

This paper is concerned with optimal production planning on a single failure-prone flexible machine that produces N distinct part types. The machine is flexible in the sense that no setup is required for switching from production of one part type to another. We consider the problem of controlling production rates to minimize the expected long-run average cost of product surpluses over time. We assume constant unit holding and shortage costs and constant demand rates for the part types. Moreover, the costs are assumed to be the same for all products. We provide an explicit optimal solution for the problem.     

Analysis of a two-stage, flexible production system with unreliable machines, finite buffers and non-negligible setups

We analyze a Markov model of a two-stage production system capable of producing two part types. Each stage consists of an unreliable machine and the different stages are decoupled by two intermediate buffers of finite capacity, one for each part type. Unlike previous work, we specifically consider non-negligible machine setup times during changeovers and also assume that machine failure probabilities are dependent on the part type being produced. We assume that machine processing times, repair/failure times and setup times are exponentially distributed and may have different mean rates for each machine and for each part-type. We describe a solution method to evaluate the system performance that reduces the total number of equations to be solved from a multiplicative function to an additive function of buffer sizes. This model may then be integrated with a new decomposition method for analyzing longer lines. The results show the relative influence of different factors on system performance and thus provide guidance to the optimal choice of system parameters such as buffer sizes.     

Production Capacity Modeling of Alternative, Nonidentical, Flexible Machines

Analyzing the production capacity of a flexible manufacturing system consisting of a number of alternative, nonidentical, flexible machines, where each machine is capable of producing several different part types simultaneously (by flexibly allocating its production capacity among these part types), is not a trivial task. The production capacity set of such a system is naturally expressed in terms of the machine-specific production rates of all part types. In this paper we also express it in terms of the total production rates of all part types over all machines. More specifically, we express the capacity set as the convex hull of a set of points corresponding to all possible assignments of machines to part types, where in each assignment each machine allocates all its capacity to only one part type. First, we show that within each subset of assignments having a given number of machines assigned to each part type, there is a unique assignment that corresponds to an extreme point of the capacity set. Then, we propose a procedure for generating all the extreme points and facets of the capacity set. Numerical experience shows that when the number of part types is less than four, the size of the capacity set (measured in terms of the number of variables times the number of constraints) is smaller, if the capacity set is expressed in terms of the total production rates of all part types over all machines than if it is expressed in terms of the machine-specific production rates of all part types. When the number of part types is four or more, however, the opposite is true.     

Scheduling parallel machines with major and minor setup times

This article discusses the problem of scheduling a large set of parts on an FMS so as to minimize the total completion time. Here, the FMS consists of a set of parallel identical machines. Setup time is incurred whenever a machine switches from one type of part to another. The setup time may be large or small depending on whether or not the two part types belong to the same family. This article describes a fast heuristic for this scheduling problem and derives a lower bound on the optimal solution. In computational tests using random data and data from an IBM card test line, the heuristic archieves nearly optimal schedules.     

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.     

Planning the routing mix in FASs to minimize total transportation time

The routing mix problem in flexible assembly systems is considered. The problem consists of assigning the operations for each part to the machines, with the two objectives of balancing the machine workloads and minimizing the burden of the transportation system. These two objectives are sometimes conflicting, since the latter tends to support assigning operations to the same machine(s) as much as possible, and this may be bad for workload balancing. A linear programming problem is presented that, given a constraint on the workload of each machine, finds one solution that minimizes the overall time spent moving the parts from one machine to another. Since such a linear program may have an exponential number of variables, an efficient column generation technique to solve the problem is devised. The efficiency of the method is validated by experiments on a large number of random problems.     

A novel flexible model for lot sizing and scheduling with non-triangular,period overlapping and carryover setups in different machine configurations

This paper develops and tests an efficient mixed integer programming model for capacitated lot sizing and scheduling with non-triangular and sequence-dependent setup times and costs incorporating all necessary features of setup carryover and overlapping on different machine configurations. The model’s formulation is based on the asymmetric travelling salesman problem and allows multiple lots of a product within a period. The model conserves the setup state when no product is being processed over successive periods, allows starting a setup in a period and ending it in the next period, permits ending a setup in a period and starting production in the next period(s), and enforces a minimum lot size over multiple periods. This new comprehensive model thus relaxes all limitations of physical separation between the periods. The model is first developed for a single machine and then extended to other machine configurations, including parallel machines and flexible flow lines. Computational tests demonstrate the flexibility and comprehensiveness of the proposed models.     

Replanning and analysis of partial setup strategies in printed circuit board assembly systems

This paper considers the operation of component placement equipment for the assembly of printed circuit boards (PCBs) in a medium-volume, medium-variety manufacturing environment. It focuses on the setup management and operational planning issues associated with productive use of these expensive resources. The concept of replanning is introduced to adapt to changes in the production environment by explicitly considering the initial state of the system. The partial setup strategy is suggested as a means of efficient adaptation and as a strategy that subsumes other setup strategies encountered in practice and the literature. These concepts are applied to the optimization of a single-placement machine producing multiple products. The results of using partial setups are compared with other commonly used strategies. Experimental results suggest significant gains at the singlemachine level. Future research is being pursued to improve the solution procedures and extend these replanning concepts to the line level.     

PCB assembly scheduling with alternative nozzle types for one component type

The placement machine is the bottleneck of a printed circuit board (PCB) assembly line. The type of machine considered in this paper is the beam-type placement machine that can simultaneously pick up several components from feeders. It is assumed that the number of nozzle types (NTs) is less than the number of heads on the beam. The objective of the PCB assembly scheduling for a single placement machine is to minimize the cycle time based on the average machine operation time instead of the travelling distance. To minimize the cycle time, the number of turns and the number of pickups should be minimized. The PCB assembly scheduling is hierarchically decomposed into four problems: the nozzle assignment problem, the head allocation problem, the component type (CT) grouping problem and the pickup clustering problem, which are optimized successively and iteratively. First, the nozzle assignment problem considering alternative NTs for one CT is dealt with by the proposed genetic algorithm. For a given nozzle assignment solution, the head allocation problem is solved by a previously greedy heuristic to minimize the number of turns.Then, the CT grouping problem and the pickup clustering problem are solved by a proposed greedy heuristic and a modified agglomerative hierarchical clustering approach, respectively, to minimize the number of pickups. Numerical experiments are carried out to examine the performances of these proposed heuristic approaches. The importance of considering alternative NTs for one CT for the cycle time is also confirmed.     

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.     

Manufacturing and supply of monovalent oral polio vaccines.

A new polio vaccine was developed, produced and licensed by sanofi pasteur at the request of the World Health Organization (WHO) for mass immunization campaigns in endemic countries such as Egypt. The new vaccine, monovalent oral polio vaccine 1 or mOPV1, is currently used in Egypt as a critical part of a new WHO strategy to end polio type 1 transmission by the end of the year 2005 (types 2 and 3 polioviruses have already been eliminated from Egypt). To answer this specific need, an urgent program was mounted by Sanofi pasteur to manufacture 50million doses for Egypt, in close collaboration with WHO and National Regulatory Agencies (France and Egypt). The joint efforts between manufacturer, regulators and the WHO resulted in the quickest ever vaccine development and licensure and WHO pre-qualification. The production of mOPV was based on existing tOPV but with appropriate "change control" procedures to assure the quality of the product, and to distinguish mOPV from tOPV. Key success factors included clear and careful definition of the project; close collaboration between manufacturer, regulators and WHO; and commitment and motivation of staff. As a result, development and production of mOPV1 vaccine were carried out in a drastically reduced time period, leading to the release and delivery of the first 15 million doses of mOPV1 in April 2005.     

Scheduling unrelated parallel machines in semiconductor manufacturing by problem reduction and local search heuristics

We investigate a difficult scheduling problem in a semiconductor manufacturing process that seeks to minimize the number of tardy jobs and makespan with sequence-dependent setup time, release time, due dates and tool constraints. We propose a mixed integer programming (MIP) formulation which treats tardy jobs as soft constraints so that our objective seeks the minimum weighted sum of makespan and heavily penalized tardy jobs. Although our polynomial-sized MIP formulation can correctly model this scheduling problem, it is so difficult that even a feasible solution can not be calculated efficiently for small-scale problems. We then propose a technique to estimate the upper bound for the number of jobs processed by a machine, and use it to effectively reduce the size of the MIP formulation. In order to handle real-world large-scale scheduling problems, we propose an efficient dispatching rule that assigns a job of the earliest due date to a machine with least recipe changeover (EDDLC) and try to re-optimize the solution by local search heuristics which involves interchange, translocation and transposition between assigned jobs. Our computational experiments indicate that EDDLC and our proposed reoptimization techniques are very efficient and effective. In particular, our method usually gives solutions very close to the exact optimum for smaller scheduling problems, and calculates good solutions for scheduling up to 200 jobs on 40 machines within 10 min.     

Optimal rates of dispersal II. Diploid populations

The problem of how an individual should divide its progeny into dispersed and non-dispersed descendants is investigated for a number of haploid models. In each model, a unique optimal ratio of dispersed to non-dispersed has been found, where the type with this optimal strategy has a selective advantage over all other types. Although the survival ability of a dispersed offspring is reduced (compared to that of a non-dispersed offspring), the optimal strategy implies that a substantial part of the progeny will be dispersed.     

Optimal rates of dispersal I. Haploid populations

The problem of how an individual should divide its progeny into dispersed and non-dispersed descendants is investigated for a number of haploid models. In each model, a unique optimal ratio of dispersed to non-dispersed has been found, where the type with this optimal strategy has a selective advantage over all other types. Although the survival ability of a dispersed offspring is reduced (compared to that of a non-dispersed offspring), the optimal strategy implies that a substantial part of the progeny will be dispersed.     

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.     

Machine Sharing in Manufacturing Systems: Total Flexibility versus Chaining

In this paper, we compare the operational performance of two machine-sharing configurations: total flexibility and chaining. We show that chaining captures most of the benefits of total flexibility while limiting the number of part types processed on any individual machine to only two. We examine the relative desirability of the two configurations under varying buffer sizes, loading conditions, number of machines, and setup times, as well as for different control policies. For nonzero setups times, we show that chained configurations can outperform fully flexible ones. This particularly is the case when either the number of machines or length of setup times is high. We also find that the effect of the system size on performance diminishes with the number of machines. This means that multiple smaller chains can perform almost as well as a single long one. Our results are consistent with the recent findings of Jordan and Graves (1995), who examined the economic benefits of chaining relative to full flexibility.     

DNA polymerase programmed with a hairpin DNA incorporates a multiple-instruction architecture into molecular computing

Parallelism is one of the major advantages of molecular computation. A large number of data encoded in DNA molecules can be processed simultaneously by molecular biology techniques, although only a single set of instructions has been implemented in a solution. We have developed a computing machine, called the "whiplash" machine, which is made of DNA polymerase and a hairpin DNA. This machine simulates a finite state machine, executing its own instructions encoded in the DNA moiety, and would thus be applicable to multiple-instruction operation in a solution. In the present study, we explored the feasibility of this novel type of parallelism by applying the whiplash machine in a computation of the directed Hamiltonian path problem. The possible paths in a given graph were represented with different instruction sets, which were then implemented separately by whiplash machines in a test tube. After an autonomous operation of the machines, only the machine that implemented the instruction set corresponding to the Hamiltonian path was recovered from the tube. On the basis of the efficiency of machine operation, which was experimentally determined, 10(10) different instruction sets could be implemented simultaneously in a 1-ml solution.     

Tool addition strategies for flexible manufacturing systems

The allocation of tools to machines determines potential part routes in flexible manufacturing systems. Given production requirements and a minimum feasible set of tools, the decision of how to fill vacant slots in tool magazines to maximize routing flexibility is shown to be a minimum cost network flow problem for the cases when routing flexibility is a function of the average workload per tool aggregated over tool types, or of the number of possible routes through the system. A linear programming model is then used to plan a set of routes for each part type so as to minimize either the material handling requirement or the maximum workload on any machine. The impact of these tool addition strategies on the material handling and workload equalization is investigated and computational results presented. The advantage of the overall approach is computational simplicity at each step and the ability to react to dynamic changes.     

A comparative study of FMS tool allocation and part type selection approaches for a varying part type mix

Hankins and Rovito (1984) examined the impact of different tool policies on cutting tool inventory levels and spindle utilization for a flexible manufacturing system (FMS). This study provides a broader perspective of the impact of tool allocation approaches on flow times, tardiness, percent of orders tardy, machine utilization, and robot utilization. Part type selection procedures have been suggested for the FMS prerelease planning problem. However, very little research has specifically evaluated the part type selection procedures across different tool allocation approaches. Also, with the exception of Stecke and Kim (1988, 1991) no other known study has provided any insights on what tool allocation approaches are appropriate when processing different mixes of part types. This research is devoted to addressing those issues. Three tool allocation approaches, three production scheduling rules, and three levels of part mix are evaluated in this study through a similation model of a flexible manufacturing system. The specific impacts of the tool approaches, their interaction effects with the part type selection rules, and their effectiveness at different part type mix levels are provided through the use of a regression metamodel.