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.     

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 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.     

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.     

Schedule efficiency in a robotic production cell

In this paper, we analyze the efficiency of a given robot movement schedule for the case of a flow shop robotic production cell withm different machines, one input conveyor, and one output conveyor. We begin with the case of one-robot cells and extend our results to multirobot cells. The paper studies the efficiency of a movement schedule for identical parts by defining a movement network associated with this schedule. This network models any cell layout and applies to multirobot cells. Using the movement network, we propose two cycle time evaluation methods, the first using linear programming and the second based on finding a longest path. The latter method generates a procedure to obtain an analytical formula for the cycle time. We extend the proposed methods to study the efficiency of a given input sequence (schedule) for different parts, that is, to determine the sequence processing time. The results obtained here allow us to quickly evaluate the efficiency of any given feasible movement schedule, for identical or different parts.     

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.     

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.     

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.     

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.     

Scheduling of FMSs with information delays: A simulation study

Practitioners and academicians throughout the world recognize the crucial role played by flexibility within manufacturing organizations, especially those engaged in small batch manufacture. However, although the concept of flexibility has begun to attract increased attention, its interaction with information integration and automation has not captured due attention. For example, it almost always has been assumed that a real-time control mechanism is available for exploiting routing flexibility on the shop floor. While this may be true for FMSs, it generally is not so for the vast majority of conventional manufacturing systems with varying levels of information integration and automation. The lack of a fully integrated and automated control mechanism within such semi-automated flexible manufacturing systems (SAFMSs) would eventually cause delays in the availability of shop status information. In this paper, we study the impact that defined modes of information delay have on the performance of a hypothetical SAFMS through detailed simulation experiments. Given that the level of routing flexibility is a controllable design parameter, our interest is in determining the impact that information delays have on decisions pertaining to the selection of appropriate levels of routing flexibility. To highlight the impact of information delays within the SAFMS, the Taguchi experimental design procedure is adopted as a performance evaluation and analysis vehicle, using makespan as a measure of performance. Simulation results indicate the presence of a system specific tolerance limit, operation below which minimizes performance loss.     

Impact of Routing Flexibility on the Performance of an FMS—A Simulation Study

The evolving manufacturing environment is characterized by a drive toward increasing flexibility. One possible manifestation of flexibility within an FMS is in the form of routing flexibility. Providing this typically is an expensive proposition, and system designers therefore aim to provide only the required levels commensurate with a given set of operating conditions. This paper presents a framework based on a Taguchi experimental design for studying the nature of the impact of varying levels of routing flexibility on the performance of an FMS. Simulation results indicate that increases in routing flexibility, when made available at the cost of an associated penalty on operation processing time, is not always beneficial. There is an optimal flexibility level, beyond which system performance deteriorates, as judged by the makespan measure of performance. It is suggested that the proposed methodology can be used in practice for not only setting priorities on specific design and control factors but also for highlighting likely factor level combinations that could yield near-optimal shop performance.     

The mTOR regulated RNA-binding protein LARP1 requires PABPC1 for guided mRNA interaction

The mammalian target of rapamycin (mTOR) is a critical regulator of cell growth, integrating multiple signalling cues and pathways. Key among the downstream activities of mTOR is the control of the protein synthesis machinery. This is achieved, in part, via the co-ordinated regulation of mRNAs that contain a terminal oligopyrimidine tract (TOP) at their 5′ends, although the mechanisms by which this occurs downstream of mTOR signalling are still unclear. We used RNA-binding protein (RBP) capture to identify changes in the protein-RNA interaction landscape following mTOR inhibition. Upon mTOR inhibition, the binding of LARP1 to a number of mRNAs, including TOP-containing mRNAs, increased. Importantly, non-TOP-containing mRNAs bound by LARP1 are in a translationally-repressed state, even under control conditions. The mRNA interactome of the LARP1-associated protein PABPC1 was found to have a high degree of overlap with that of LARP1 and our data show that PABPC1 is required for the association of LARP1 with its specific mRNA targets. Finally, we demonstrate that mRNAs, including those encoding proteins critical for cell growth and survival, are translationally repressed when bound by both LARP1 and PABPC1.     

Performance Comparison of Some Classes of Flexible Flow Shops and Job Shops

Flexible manufacturing systems (FMSs) for two-stage production may possess a variety of operating flexibilities in the form of tooling capabilities for the machines and alternative routings for each operation. In this paper, we compare the throughput performance of several flexible flow shop and job shop designs. We consider two-stage assembly flow shops with m parallel machines in stage 1 and a single assembly facility in stage 2. Every upstream operation can be processed by any one of the machines in stage 1 prior to the assembly stage. We also study a similar design where every stage 1 operation is processed by a predetermined machine. For both designs, we present heuristic algorithms with good worst-case error bounds and show that the average performance of these algorithms is near optimal. The algorithms presented are used to compare the performance of the two designs with each other and other related flexible flow shop designs. It is shown, both analytically and experimentally, that the mode of flexibility possessed by a design has implications on the throughput performance of the production system.     

Periodic reconfiguration of general-purpose fixtures in a dedicated FMS

Fixtures dedicated to a given part type in an FMS can sometimes become bottlenecks to some FMSs as demand variability increases. Past research indicates that the increased operating flexibility associated with general-purpose fixtures may be a key to the efficient scheduling of even those FMSs dedicated to producing a small number of part types over a known planning horizon. However, the increased time required to reconfigure general-purpose fixtures to meet current demand may also create a bottleneck in the loading area. Increases in the defect rate associated with improper fixture assembly and part alignment are also possible. One solution may be to reconfigure general-purpose fixtures off line according to specific demand schedules for the period, and then to treat them as “pseudo-dedicated” fixtures until the next period. This would utilize some of the flexibility associated with general-purpose fixtures, while reducing the negative drawbacks associated with incremental loading time and alignment errors. The research reported in this article simulates an existing FMS, using fixtures dedicated to individual part types, and compares the results to those collected using a group of general-purpose fixtures that are reconfigured each week, based on current demand for each part type, and used in a pseudo-dedicated fashion. Three simulation experiments are run with increasing coefficients of variation in the input distributions used to generate demand. Performance is measured by system throughput, proportion of parts tardy, and average tardiness. The simulation results show that while overall system performance decreases as the level of demand mix variability increases, this negative impact is significantly less severe when using pseudo-dedicated, general-purpose fixtures.     

Rule-based production planning in flexible manufacturing systems

Production planning in flexible manufacturing may require the solution of a large-scale discrete-event dynamic stochastic optimization problem, due to the complexity of the system to be optimized, and to the occurrence of discrete events (new orders and hard failures). The production planning problem is here approached for a multistage multipart-type manufacturing shop, where each work cell can share its processing time among the different types of parts. The solution of this problem is obtained by an open-loop-feedback control strategy, updated each time a new event occurs. At each event time, two coupled problems are solved: 1) a product-order scheduling problem, conditioned on estimated values of the production capacities of all component work cells; and 2) a production-capacity planning problem, conditioned on predefined sequences of the product orders to be processed. In particular, the article aims at defining a production planning procedure that integrates both analytical tools, derived from mathematical programming, and knowledge-based rules, coming from experience. The objective is to formulate a hybrid (knowledge-based/analytical) planning architecture, and to analyze its use for multicell multipart-type manufacturing systems.