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.     

A new branch and bound algorithm for loading problems in flexible manufacturing systems

Loading problems in flexible manufacturing systems involve assigning operations for selected part types and their associated tools to machines or machine groups. One of the objectives might be to maximize the expected production rate (throughput) of the system. Because of the difficulty in dealing with this objective directly, a commonly used surrogate objective is the closeness of the actual workload allocation to the continuous workload allocation that maximizes throughput. We test several measures of closeness and discuss correlations between these measures and throughput. Using the best measure, we show how to modify an existing branch and bound algorithm which was developed for the case of equal target workloads for all machine groups to accommodate unequal target workloads. We also develop a new branch and bound algorithm which can be used for both types of problems. The efficiency of the algorithm in finding optimal solutions is achieved through the application of better branching rules and improved dominance results. Computational results on randomly generated test problems indicate that the new algorithm performs well.     

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.     

A concurrent development tool for flexible assembly systems

Global competition and the rapid pace of technological change now require the almost continual introduction of product upgrades by any manufacturer. Thus, such a manufacturer is likely to market older and newer versions of a product simultaneously, not to mention niche-specific editions of any product upgrade. An increasingly successful response to this product proliferation is the implementation of flexible assembly systems. In the context of a flexible assembly system (FAS), the ability to estimate the impact of various product and process options on the maximal level of system output becomes crucial to managing the ever-changing product mix. This paper presents a tool for such impact estimation that can facilitate concurrent development and engineering. Experience with an actual FAS is the basis for the reported results. The tool is a specialized combination of discreteevent computer simulation, experimental design, and regression analysis. Application of the tool assumes FAS use with a cellular manufacturing philosophy. Thus, uncluttered process flow for a family of products in the sense of group technology places the focus on potential bottlenecks. The new tool here models the impact of process and product options on bottleneck and, hence, FAS behavior.     

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.     

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.     

A loop layout design problem for flexible manufacturing systems

The interconnection pattern of the processing modules of a computerized manufacturing system affects its performance. In this article, we discuss a set of requirements that the interconnection network should satisfy. Subsequently, we concentrate on a simple and popular architecture, the loop network. The problem we address is to design the layout of the system so that the number of machines that the part types cross in their manufacturing process is minimized. We formulate the problem mathematically and solve it by a heuristic that obtains consistently better results than an earlier popular method.     

A heuristic algorithm for the loading problem in flexible manufacturing systems

The paper considers the loading problem in flexible manufacturing systems (FMSs). This problem involves the assignment to the machine tools of all operations and associated cutting tools required for part types that have been selected to be produced simultaneously. The loading problem is first formulated as a linear mixed 0–1 program with the objective to minimize the greatest workload assigned to each machine. A heuristic procedure is presented in which an assignment of operations to machine tools is obtained by solving a parameterized generalized assignment problem with an objective function that approximates the use of tool slots required by the operations assigned to the machines. The algorithm is coded in FORTRAN and tested on an IBM-compatible personal computer. Computational results are presented for different test problems to demonstrate the efficiency and effectiveness of the suggested procedure.     

A decision-making approach to the operation of flexible manufacturing systems

This paper introduces a generic decision-making framework for assigning resources of a manufacturing system to production tasks. Resources are broadly defined production units, such as machines, human operators, or material handling vehicles; and tasks are activities performed by resources. In the specific context of FMS, resources correspond to individual machines; tasks correspond to operations to be performed on parts. The framework assumes a hierarchical structure of the system and calls for the execution of four consecutive steps to make a decision for the assignment of a resource to a task. These steps are 1) establishment of decision-making criteria, 2) formation of alternative assignments, 3) estimation of the consequences of the assignments, and 4) selection of the best alternative assignment. This framework has been applied to an existing FMS as an operational policy that decides what task will be executed on which resource of this FMS. Simulation runs provide some initial results of the application of this policy. It is shown that the policy provides flexibility in terms of system performance and computational effort.     

A model management systems approach to manufacturing systems design

Manufacturing systems design involves the solution of a complex series of interrelated problems. This complexity will increase in the future as manufacturing practices change to meet increased global competition. Research within manufacturing systems design has mainly been focused on finding improved models for solving particular problems, or extending existing modeling techniques. This has resulted in numerous modeling tools being available to support manufacturing systems design. However, little research work has been carried out into consolidating the existing theories and models. As a result, a large body of this work has not been applied in industry. Model management has evolved as a research area which investigates methods for storing, modifying, and manipulating models. This article describes a prototype model management system for manufacturing systems design. The objective here is not to develop “another” decision support system for manufacturing design, but to illustrate, through the development of a prototype system, a number of key ideas of how concepts from the area of model management systems can be used to support manufacturing systems design. The prototype model management system utilizes the structured modeling framework and uses an extended version of the structured modeling language. An important aspect of the prototype model management system is the incorporation of the model development task, thus allowing the system to be easily updated and adapted. The prototype system was evaluated using a range of queueing network models for manufacturing systems design.     

A model for the minimum cost configuration problem in flexible manufacturing systems

This paper presents a mathematical programming model to help select equipment for a flexible manufacturing system, i.e., the selection of the types and numbers of CNC machines, washing stations, load/unload stations, transportation vehicles, and pallets. The objective is to minimize equipment costs and work-in-process inventory cost, while fulfilling production requirements for an average period. Queueing aspects and part flow interactions are considered with the help of a Jacksonian-type closed queueing network model in order to evaluate the system's performance. Since the related decision problem of our model can be shown to be NP-complete, the proposed solution procedure is based on implicit enumeration. Four bounds are provided, two lower and two upper bounds. A tight lower bound is obtained by linearizing the model through the application of asymptotic bound analysis. Furthermore, asymptotic bound analysis allows the calculation of a lower bound for the number of pallets in the system. The first upper bound is given by the best feasible solution and the second is based on the anti-starshaped form of the throughput function.     

Batch sizes and lead-time performance in flexible manufacturing systems

Production lead-time performance in flexible manufacturing systems is influenced by several factors which include: machine groupings, demand rates, machine processing rates, product batching, material handling system capacity, and so on. Hence, control of lead-time performance can be affected through the manipulation of one or more of these variables. In this article, we investigate the potential of batch sizing as a control variable for lead-time performance through the use of a queueing network model. We establish a functional relationship between the two variables, and incorporate the relationship in an optimization model to determine the optimal batch size(s) which minimizes the sum of annual work-in-process inventory and final inventory costs. The nonlinear batch sizing problem which results is solved by discrete optimization via marginal analysis. Results show that batch sizing can be a cheap and effective variable for controlling flexible manufacturing system throughput.     

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.     

Specification methods for material-handling control algorithms in flexible manufacturing systems

Good methods are needed to specify, test, and debug material-handling control logic. This article surveys a number of representative methods for defining and describing control algorithms for programmable material-handling equipment used in flexible manufacturing systems. The methods are evaluated with regard to their suitability for communication between people and as bases for interfaces to automatic program generators. It is concluded that no single method is entirely satisfactory. Three methods (position diagrams, function block diagrams, and operation networks) have potential to be combined into an effective hybrid approach that minimizes the need for the user to switch between various conceptual models.     

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.     

Economics and success factors of flexible manufacturing systems: The conventional explanation revisited

This article analyzes costs and relative benefits of several hundred flexible manufacturing systems (FMSs) in the world. The analyses are based on the computerized data bases, which make it easy to correlate different cost and benefit indicators with each other and to look for regular patterns and tendencies in the applications. Both investment cost distributions and the system complexity distributions are analyzed. The relative benefits and advantages and their relationships are shown. Finally, technical and economic explanations for successful implementation strategies are given. The results show that there are two classes of economically successful systems. The small-scale and technically compact systems are usually used in small-batch production for the replacement of semimanual production. The main benefits are increased capacity and productivity as well as quality improvements. The large-scale and technically complex systems are used in large-volume production for the replacement of fixed automation and transfer lines. The benefits are mainly due to the increased potential for flexibility and capital savings.     

A dynamic heuristic-based algorithm to part input sequencing in flexible manufacturing systems for mass customization capability

In the increasingly competitive global markets, enterprises face challenges in responding to customer orders quickly, as well as producing customized products cost-effectively. This paper proposes a dynamic heuristic-based algorithm for the part input sequencing problem of flexible manufacturing systems (FMSs) in a mass customization (MC) environment. The FMS manufactures a variety of parts, and customer orders arrive dynamically with order size as small as one. Segmental set functions are established in the proposed algorithm to apply the strategy of dynamic workload balancing, and the shortest processing time (SPT) scheduling rule. Theoretical analysis is performed and the effectiveness of the algorithm in dynamic workload balancing under the complex and dynamic environment is proven. The application of the algorithm is illustrated by an example. The potential of its practical applications to the FMSs in make-to-order (MTO) supply chains is also discussed. Further research is provided.     

Comparison of mixed integer linear programming models for the resource-constrained project scheduling problem with consumption and production of resources

This paper addresses an extension of the resource-constrained project scheduling problem that takes into account storage resources which may be produced or consumed by activities. To solve this problem, we propose the generalization of two existing mixed integer linear programming models for the classical resource-constrained project scheduling problem, as well as one novel formulation based on the concept of event. Computational results are reported to compare these formulations with each other, as well as with a reference method from the literature. Conclusions are drawn on the merits and drawbacks of each model according to the instance characteristics.     

Fun in facets: A flexible new tool for population genomics in R

The landscape of analytical tools for population genomics continues to evolve. However, these tools are scattered across programming languages, making them largely inaccessible for many biologists. In this issue of Molecular Ecology Resources, Hemstrom and Jones, 2022 (Mol Ecol Resour; 962) introduce a new R package, snpR. This package combines a large number of existing analyses, to provide a one-stop shop for population genomics. F-statistics, admixture analyses, effective population size inferences, genome-wide association studies (GWAS), and parentage analyses are all implemented natively within the package. A variety of third-party software can also be run without leaving the R environment. The authors pay particular attention to data structure – avoiding redundancy – and allowing analyses to be run across multiple sample or single-nucleotide polymorphism (SNP) groupings. Because of its great accessibility and wide range of analyses, snpR has the potential to become a favourite within the Molecular Ecology community.