Machine-component group formation: an heuristic method for flexible production cells and flexible manufacturing systems

This paper provides an heuristic for the planning and study of machine-component groups in flexible production cells and flexible manufacturing systems. The problem of group formation defined on master-component process routes is undertaken in terms of minimum differences between masters and maximum combinations of masters. Group formation is a ‘hard’ combinatorial problem subject to exponential growth of complexity as the number of decision-making variables increases. The heuristic is designed to search the solution space of the problem in monotone-increasing order of solution costs so as to avoid the enumeration of solutions for cost minimization.     

A loading and dispatching problem in a random flexible manufacturing system

A scheduling problem in a flexible manufacturing system (FMS) is considered to be a composite of two interdependent tasks: loading and sequencing. Formulations are presented for the loading problem with two objectives:

(i) minimization of the system workload unbalance, and

(ii) minimization of system unbalance and the number of late jobs;

including constraints such as the number of tools slots with duplications, unique job routing, nonsplitting of jobs and machine capacity. For both the objectives, heuristic methods are developed and performance is compared with the exact mixed integer programming solutions. A simulation model is developed for investigating the system performance for the problem of minimizing the system unbalance using heuristic and sequential loading methods in conjunction with four—FIFO, SPT, LPT and MOPR—dispatching rules.     

Production planning for flexible flow systems with limited machine flexibility

A flexible manufacturing system (FMS) is highly capital-intensive and FMS users are concerned with achieving high system utilization. The production planning function for setting up an FMS prior to production should be developed in order to make the most of the potential benefits of FMSs. We consider two production planning problems of grouping and loading a flexible flow system, which is an important subset of FMSs where the routing of parts is unidirectional. We show that considering this routing restriction as well as limited machine flexibility strongly affects both the solution techniques and the quality of the solutions. Because of the complexity of the problem, we present a heuristic approach that decomposes the original problem into three interrelated subproblems. We show that the proposed approach usually finds a near-optimum solution and is superior to an approach that exists in the literature of FMS production planning. We also introduce effective heuristic methods for two new subproblems that arise because of the unidirectional flow precedence and flexibility constraints. Computational results are reported and future research issues are discussed.     

Solving the n-job 3-stage flexible flowshop scheduling problem using an agent-based approach

In this paper, a general methodology of agent-based manufacturing systems scheduling, incorporating game theoretic analysis of agent cooperation is presented to solve the n-job 3-stage flexible flowshop scheduling problem. The flowshops are flexible in the sense that a job can be processed by any of the identical machines at each stage. Our objective is to schedule a set of n jobs so as to minimize the makespan. We perform error bound analysis using the lower bound estimates developed in the literature as a datum for comparing the agent-based scheduling solutions with other heuristic solutions. The results of the evaluation show that the agent-based scheduling approach outperforms existing heuristics for the majority of the testing problems.     

Strategic configuration of flexible electronics assembly facilities facing stochastic requirements

Flexible configuration of manufacturing facilities is a key strategy for efficiently improving market responsiveness and market share in the face of uncertain future product demand. Flexible facility configurations can produce an efficient production system that allows higher capacity utilization given uncertainty in product demand and mix. The aim of this paper is to consider the alternative choices of flexible equipment available at the strategic planning level and to make decisions about the facility design and configuration that best suits the specific needs of the manufacturing system under consideration. A chance constrained mixed integer programming model for strategic configuration and capacity planning of flexible multiple-stage production facilities under time-varying production requirements is introduced in this paper. It is an integrated model that determines the number of assembly lines required, the flexible automation levels required in each line, capacity levels, and product assignments/reassignments for a multiple-stage production system, considering the stochastic nature of the demand. A two-step heuristic based on genetic algorithms is proposed and tested. Experimental results indicate that the two-step heuristic performs well in terms of both computation speed and solution accuracy.     

Experimental investigation of flexible manufacturing system scheduling decision rules

This paper reports the results of an experimental investigation of scheduling decision rules for a dedicated flexible manufacturing system. A simulation model of an existing flexible manufacturing system (FMS) comprised of 16 computer numerical controlled machines (CNC) was constructed using actual operation routings and machining times to evaluate the performance of various part loading and routing procedures. The results indicate that FMS performance is significantly affected by the choice of heuristic parts scheduling rules.     

A within-cell utilization based heuristic for designing cellular manufacturing systems

The initial stage in the facilities design of cellular manufacturing systems involves the identification of part families and machine groups and forming cells possessing specific manufacturing capabilities. A new heuristic for the part family/machine group formation (PF/MGF) problem is presented in this paper. The distinguishing feature of this heuristic is its consideration of several practical criteria such as within-cell machine utilization, work load fractions, maximum number of machines that are assigned to a cell, and the percentage of operations of parts completed within a single cell. Computational results, based on several examples from the literature, show that this heuristic performs well with respect to more than one criteria. The heuristic also clarifies the source of various arguments in the literature concerning the ‘goodness’ of the solutions obtained by other researchers. An application of the heuristic to a large sample of industrial data involving 45 workcentres composed of 64 machines, and 305 parts is given, and the usefulness of the heuristic for trading-off several objectives is illustrated.     

Optimal design of flexible production lines with unreliable machines and infinite buffers

Despite the increasing use of automated manufacturing systems, combining flexible technology, only a few models for designing such systems are available. This paper presents a model for the determination of the profit-maximizing configuration of workstations (both machine types and number) along a flexible production line with unreliable machines and infinite buffers. A mixed integer programming formulation of the problem is introduced and an optimal solution algorithm is developed. For large scale problems a heuristic procedure is presented.     

Hybrid manufacturing/remanufacturing lot-sizing and supplier selection with returns,under carbon emission constraint

This paper addresses a lot-sizing problem in manufacturing/remanufacturing systems. The studied system is a single manufacturing line where both regular manufacturing and returns remanufacturing processes are carried out, with different set-up costs for each process. We consider also a returns collection phase from customers/distributors with deterministic returns quantities at each period of the planning horizon. The environmental aspect is assumed in this study by considering a carbon emission constraint for the manufacturing, remanufacturing and transportation activities. A mixed integer programming model to minimise the management cost and meet the customer’s needs under different manufacturing constraints is proposed. Otherwise, An adaptation of the well-known Silver and Meal (SM) heuristic and two hybrid method approaches (HM1 and HM2) providing approximates solutions are developed. The mixed integer model was tested on Cplex (Software optimizer), and the obtained results were compared with the ones provided by the adapted heuristic SM and the hybrid methods. The numerical analyses show that hybrid methods provide good-quality solutions in a moderate computational time. The proposed model establishes a collegial and an integrated process that sets values, goals, decisions and priorities along the considered supply chain while taking into account the environmental aspect.     

Aggregate line capacity design for PWB assembly systems

In a multi-product, flexible manufacturing environment, line capacity of printed wiring board (PWB) assembly systems may need to be adjusted at the beginning of each aggregate planning period because of demand fluctuation over multiple periods. A model of production planning and equipment changeover scheduling at the aggregate level is developed. In the described model, three kinds of equipment changeover methods, i.e. adding machine, removing machine and transferring machine, are involved. Because the model is a large-scale integer programming problem, it cannot be solved directly. A solution approach is developed, which first solves a recursive linear programming problem to obtain a rough set of machines to be added and a rough set of machines to be removed for each machine line in each period, then applies a branch and bound heuristic to the rough sets to obtain near-optimal solutions to the equipment changeover scheduling problem. Computational studies show the financial benefit both on capital cost and equipment changeover costs.     

Tool handling and scheduling in a two-machine flexible manufacturing cell

In this paper we examine the issue of tool management in a flexible manufacturing cell. The type of system considered here is typical of mechanical manufacturing, in which large metallic parts are loaded on the machines and are not moved until processing completion. The architecture of the cell is characterized by the absence of on-board tool magazines on the machines. Although this permits the continuous maintenance and inspection of the tools and typically results in cost and workspace savings, it calls for more complex tool handling procedures. We present a heuristic to address the overall problem of assigning parts to machines, sequencing parts on each machine, and synchronizing tool movements. The results indicate that our method provides near-optimal solutions in terms of makespan and mean flow time. Further, we observe that the solution procedure is at least one order of magnitude faster than the approach currently used and also results in a much better mean flow time.     

Solving the machine-loading problem in a flexible manufacturing system using a combinatorial auction-based approach

The next generation manufacturing system is conceived to be intelligent enough to take decisions and automatically adjust itself to situations such as variations in production demand and machine breakdowns. The manufacturing control system must have the intelligence to ensure real time operational control by interacting with different manufacturing subsystems. One of the prominent methodologies to deal with the problem of distributed manufacturing systems is the auction-based heuristic control strategy in which various entities bid themselves, accept bids and make selection amongst bids. The present paper addresses the flexible manufacturing system machine-loading problem where job selection and operation allocation on machines are to be performed such that there is a minimization of system unbalance and a maximization of throughput. The methodology of winner determination using the combinatorial auction process is employed to solve the flexible manufacturing system machine-loading problem. In the combinatorial auction, allowing bidding on a combination of assets offers a way to enhance the efficiency of allocating the assets. The performance of the proposed approach is tested on 10 sample problems and the results thus obtained are compared with the existing models in the literature.     

Jobs and tool sequencing in an automated manufacturing environment

A practical approach is presented for determining the sequence of jobs and tools in the magazine that would be required to process the jobs in an automated manufacturing environment. Each job has to be completed before a given due date. The magazine has a limited capacity necessitating setups which increase the lead times, Processing jobs also requires an appropriate fixture. Setting up a fixture also contributes to the setup times. A heuristic procedure is developed which determines the above sequences while minimizing the total setup and processing times. The performance of the heuristic is checked against optimal solutions for small-size problems while bounds are obtained (based on statistical lower bounding procedures) on the optimal solution for large-size problems. Computational results are provided for 155 test problems.     

A priority rule-based constructive heuristic and an improvement method for balancing assembly lines with parallel multi-manned workstations

Assembly lines of big-size products such as buses, trucks and helicopters are very different from the lines studied in the literature. These products’ manufacturing processes have a lot of tasks most of which have long task times. Since traditional assembly line models including only one worker in each station (i.e. simple assembly lines) or at most two workers (two-sided assembly lines) may not be suitable for manufacturing these type of products, they need much larger shop floor for a number of stations and long product flow times. In this study, an assembly line balancing problem (ALBP) with parallel multi-manned stations is considered. Following the problem definition, a mixed integer programming formulation is developed. A detailed study of priority rules for simple ALBPs is also presented, and a new efficient constructive heuristic algorithm based on priority rules is proposed. In order to improve solutions found by the constructive heuristic, a genetic algorithm-based solution procedure is also presented. Benchmark instances in the literature are solved by using the proposed mathematical programming formulation. It has been seen that only some of the small-size instances can be solved optimally by this way. So the efficiency of the proposed heuristic method is verified in small-size instances whose optimal solutions are found. For medium- and big-size instances, heuristics’ results and CPU times are demonstrated. A comparative evaluation with a branch and bound algorithm that can be found in the literature is also carried out, and results are presented.     

Tabu search-based algorithm for the TOC product mix decision

The theory of constraints (TOC) is a management philosophy that maximizes profits in a manufacturing plant with a demonstrated bottleneck. The product mix decision is one application of TOC that involves determination of the quantity and the identification of each product to produce. However, the original TOC heuristic is considered to produce unrealizable solution when a manufacturing plant has multiple resource constraints. This paper presents a tabu search-based TOC product mix heuristic to identify optimal or near optimal product mix for small problem instances under conditions where the original TOC heuristic failed. The tabu search-based TOC product mix heuristic is further used to solve large problem instances typical of practical manufacturing scenario. The experimental results for small to medium size problem show that the tabu search-based TOC heuristic compares favourably with those of optimal methods. Large size problems for which optimal methods have not been established in terms of feasibility in computation times were also solved in reasonable times with good quality solutions, thus confirming that the proposed approach is appropriate for adoption by production planners for the product mix problem in the manufacturing industry.     

A heuristic procedure for loading problems in flexible manufacturing systems

The loading problem in a flexible manufacturing system (FMS) is viewed as selecting a subset of jobs from a job pool and allocating the jobs among machines. In this paper a heuristic solution to the loading problem has been suggested by developing the concept of essentiality ratio for the objective of minimizing the system unbalance and thereby maximizing the throughput. The proposed heuristic is tested on ten problems and the results show that the algorithm developed is very reliable and efficient.     

Locating cells with bottleneck machines in cellular manufacturing systems

Because of bottleneck machines, the assignment of machine-cells to locations is interrelated with the machines' relative locations, and it makes the problem complicated to solve optimally. This paper prescribes an assignment of machine-cells to linear locations in order to minimize the inter-cell material handling cost incurred due to bottleneck machines in a cellular manufacturing system. This problem is formulated as a quadratic assignment problem (QAP). The optimal results can be obtained for a limited size of QAP. A 3-pair comparison heuristic is devised to partially overcome the dimensional problem for solving a large example. Later, an improvement heuristic called the 'bubble search' technique is developed to obtain a better solution, followed by the development of a lower bound on the QAP problem. Numerical examples are presented to illustrate the two heuristic procedures. A comparison between the optimal and heuristic solutions is also provided to evaluate the performance of the heuristics. Empirical tests conducted on two sets of data yield impressive test results.     

Production planning for flexible manufacturing systems with multiple machine types: A practical method

We study three important production planning problems for flexible manufacturing systems (FMSs) that consist of multiple types of machines. Namely we address machine grouping, workload allocation among machine groups, and batch sizing that maximize system throughput, when part types are selected for the upcoming production period. This differs from earlier related works in that earlier works give either only qualitative characteristics of the optimum solution or provide a solution method for FMSs consisting of only one type of flexible machine. In this paper, we provide both the optimum and heuristic methods to simultaneously solve the three problems for realistic FMSs. Computational results show that the heuristic method always finds the optimum solution at a fraction of computation time and that batch sizing can significantly affect throughput. Development of the heuristic method is necessary since the optimum method can be time-consuming for a moderate size of problems.     

Mathematical modelling and heuristic approaches to operation scheduling problems in an FMS environment

This paper addresses an operation scheduling problem with the objective of minimizing total tardiness in a flexible manufacturing system with setup time consideration. The addressed problem is first described as a 0?1 integer programming model, and is then solved optimally. Subsequently, a heuristic is proposed to solve the problem in an acceptable running time. The heuristic begins on a schedule generator called ESCH to obtain an initial solution; then two procedures are designed to improve the solution quality. One is a sequence-improving procedure (SIP) for determining a better performance schedule from a certain routing plan; the other is a routing-exchanging procedure (REP) for selecting a good routing plan. Both procedures are achieved by simulated annealing. Computational experiments show that the proposed simulated annealing based heuristic performs well with respect to solution accuracy and efficiency.     

A constructive heuristic algorithm for concurrently selecting and sequencing jobs in an FMS environment

This paper deals with the concurrent solution of the loading and scheduling problems in a flexible manufacturing system ( FMS) environment. It is assumed that the FMS environment has production planned periodically and each job in the system has a number of operations to be processed on flexible machines. A heuristic approach using a constructive scheduling method is developed to solve the FMS loading and scheduling problems concurrently. The computational results are compared to an existing procedure that considers a hierarchical approach with a similar problem environment. The comparison study shows a significant improvement over the existing hierarchical procedure. This experiment indicates that a concurrent solution approach can solve the FMS loading and scheduling problems very effectively.