A simulated annealing procedure for single row layout problems in flexible manufacturing systems

In this paper we address a layout problem in flexible manufacturing systems (FMSs). A layout type that has been extensively implemented in FMSs is the single row machine layout. In such a configuration machines are arranged along a straight track with a material handling device moving jobs from one machine to another. The single row layout problem (SRLP) deals with the optimal arrangement of the machines for the above configuration. We propose a simulated annealing (SA) heuristic for the solution of SRLP. Extensive computational results, and ways to improve the performance of the SA algorithm through parameter fine-tuning procedures, are reported.     

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.     

MIP-based fix-and-optimise algorithms for the parallel machine capacitated lot-sizing and scheduling problem

This paper examines the capacitated lot-sizing and scheduling problem (CLSP) with sequence-dependent setup times, time windows, machine eligibility and preference constraints. Such a problem frequently arises in the semiconductor manufacturing industry by which this paper is motivated. A mixed integer programming (MIP) model is constructed for the problem. Two MIP-based fix-and-optimise algorithms are proposed in which the binary decision variables associated with the assignment of machines are first fixed using the randomised least flexible machine (RLFM) rule and the rest of the decision variables are settled by an MIP solver. Extensive experiments show that the proposed algorithms outperform the state-of-the-art MIP-based fix-and-optimise algorithms in the literature, especially for instances with high machine flexibility and high demand variation.     

Maximising profit for multiple-product,single-period,single-machine manufacturing under sequential set-up constraints that depend on lot size

The classical problem of order acceptance/rejection in make-to-order environments, when aiming to maximise profit with machine set-ups is extended in this paper to multiple set-ups depending on manufacturing batch size. In this case, if the manufacturing batch is larger than certain product-dependent bounds, not only is the initial set-up required but also periodic reset-ups are in order, generating sub-batches of the same order, such as tool resharpening and machine recalibration. A network formulation provides the basis for identifying effective algorithms to obtain a solution to the problem. A binary programming model (BPM) and a dynamic programming formulation (DPF) are proposed to solve the problem to optimality. In addition, two heuristics are developed to obtain lower bounds on maximum profit: each attempt to maximise customer satisfaction under production time restrictions, and to provide an extension to the classical knapsack problem. Numerical experimentation shows that computational time is not an issue when BPM and heuristics are applied, but the cost of commercial solvers for BPM algorithms might be problematic. However, if the aim is to code the DPF in-house, the curse of dimensionality in dynamic programming must be addressed, although dynamic programming does yield a full sensitivity analysis, which is useful for decision-making.     

Integrated design of the block layout and aisle structure by simulated annealing

In a manufacturing layout, it is widely agreed that the design of the layout and aisles for material handling needs to be considered simultaneously. This paper presents an integrated method to optimize the manufacturing layout and aisle structure by simulated annealing. In the method, the layout design problem is represented as a slicing floorplan and the slicing lines in the floorplan are used as the aisle structure for the material-handling system. A new representation for a sliced floorplan is provided so that it can be handled by simulated annealing to perform the optimization. The method minimizes the material-handling cost, which is calculated by the aisle distances between delivery stations, while designing the aisle structure at the same time.     

Selecting the nozzle assortment for a Gantry-type placement machine

Electronics manufacturing systems employ increasingly multi-head gantry machines, where several vacuum nozzles are used simultaneously in pick-and-place operations to insert components on bare PCBs. Their use includes several options that have an impact on the overall manufacturing speed of the machine. In the present paper we address the problem of selecting the nozzles for this kind of a gantry machine, which is an important subproblem of the larger scheduling problem of multi-head gantry machines. Nozzles come in different types, and different types of components may require different types of nozzles in their placing. We address first a case where a single PCB type is manufactured and the only limitation on the number of nozzles is given by the capacity of the placement head. Then we discuss the case where there is a budget limitation on the total cost of the nozzles we can buy. We show that both of these problems can be solved optimally by the means of efficient greedy algorithms. We also discuss the case of selecting nozzles when manufacturing multiple different PCB types.     

Minimizing the total machine workload for the wafer probing scheduling problem

The Wafer Probing Scheduling Problem (WPSP) is a practical generalization of the parallel-machine scheduling problem, which has many real-world applications, particularly, in the Integrated Circuit (IC) manufacturing industry. In the wafer probing factories, the jobs are clustered by their product types, which must be processed on groups of identical parallel machines and be completed before the due dates. The job processing time depends on the product type, and the machine setup time is sequentially dependent on the orders of jobs processed. Since the wafer probing scheduling problem involves constraints on job clusters, job-cluster dependent processing time, due dates, machine capacity, and sequentially dependent setup time, it is more difficult to solve than the classical parallel-machine scheduling problem. In this paper, we consider the WPSP and formulate the WPSP as an integer programming problem to minimize the total machine workload. We demonstrate the applicability of the integer programming model by solving a real-world example taken from a wafer probing shop floor in an IC manufacturing factory.     

Sharing clearances to improve machine layout

This paper considers a double-row layout problem with shared clearances in the context of semiconductor manufacturing. By sharing some clearances, reductions in both layout area and material handling cost of approximately 7–10% are achieved. Along with minimal clearances for separating adjacent machines, clearances that can be shared by adjacent machines are considered. The shared clearances may be located on either or both sides of machines. A mixed integer linear programming formulation of this problem is established, with the objective to minimise both material flow cost and layout area. A hybrid approach combining multi-objective tabu search and heuristic rules is proposed to solve it. Computational results show that the hybrid approach is very effective for this problem and finds machine layouts with reduced areas and handling costs by exploiting shared clearances.     

The part mix and routing mix problem in FMS: a coupling between an LP model and a closed queueing network

In the near future many companies will face the problem of the optimal use of newly installed manufacturing technology (e.g. a flexible manufacturing system or FMS). Very often this will involve decisions on what parts to produce using the new system (the part mix problem) and how to produce these parts (the routing mix problem). We show that traditional operational research tools such as linear programming and queueing network theory are well suited to tackle these problems. In particular, LP models are combined with queueing network models in an iterative procedure. As such the strengths of both techniques can be exploited in making optimal use of the part mix and routing mix flexibility of the FMS.     

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.     

Tabu search for the job-shop scheduling problem with multi-purpose machines

In this paper we study the following generalization of the job-shop scheduling problem. Each operation can be performed by one machine out of a set of machines given for this operation. The processing time does not depend on the machine which has been chosen for processing the operation. This problem arises in the area of flexible manufacturing. As a generalization of the jobshop problem it belongs to the hardest problems in combinatorial optimization. We show that an application of tabu search techniques to this problem yields excellent results for benchmark problems.Supported by Deutsche Forschungsgemeinschaft, Project JoP-TAG     

Loading and control policies for a flexible manufacturing system

An experimental investigation of operating strategies for a computer-controlled flexible manufacturing system is reported. The system is a real one, consisting of nine machines, an inspection station and a centralized queueing area—all interconnected by an automatic material-handling mechanism. The operating strategies considered involve policies for loading (allocating operations and tooling to machines) and real-time flow control. A detailed simulation was employed to test alternatives. The results are different from those of classical job shop scheduling studies, showing the dependence of system performance on the loading and control strategies chosen to operate this flexible manufacturing system. Loading and control methods are defined that significantly improve the system's production rate when compared to methods which were previously applied to the system. Finally, some conclusions are presented concerning the control of these automated systems.     

Integrated design of cellular manufacturing systems in the presence of alternative process plans

In this paper we consider a generalized group technology problem of manufacturing a group of parts in which each part can have alternative process plans and each operation in these plans can be performed on alternative machines. The objective is to model and analyse how alternative process plans influence the resource utilization when the part families and machine groups are formed simultaneously. Accordingly, we develop three integer programming models to successively study the effect of alternative process plans and simultaneous formation of part families and machine groups. An illustrative example is included.     

Object-oriented modelling of manufacturing information system for collaborative design

Object-oriented technology has been widely acclaimed as offering a revolution in computing that is resolving a myriad of problems inherent in developing and managing organisational information processing capabilities. Although its foundations arose in computer programming languages, object-oriented technology has implications for a wide range of business computing activities including: programming, analysis and design, information management, and information sharing. The problematic issues in the development of manufacturing software systems are related to the various characteristics of manufacturing systems, which are wide, dynamic and complex. Design for manufacturing (DFM) is the integrated practice of designing components while considering their manufacturability, and its benefits are widely acknowledged in the industry. A model has been developed using object oriented technology, after analysing the fundamental elements necessary for modelling manufacturing and process planning framework used in collaborative design and manufacturing in machine tool manufacturing. The main components of this model are: process planning model (PPM), manufacturing activity model (MAM), manufacturing resource model (MRM) and manufacturing cost and time model. We are using ontologies in conjunction with specific conceptual models, which can contribute to improve the interoperability between these models. The performance of this model is shown by means of one real world case. The developed manufacturing information based design tool integrated with an intelligence design system can be used for collaborative design and manufacturing, which will support machine tool designers’ to achieve cost effective and timely design.     

Jobshop lot streaming with routing flexibility,sequence-dependent setups,machine release dates and lag time

Lot streaming is a technique of splitting production lots into smaller sublots in a multi-stage manufacturing system so that operations of a given lot can overlap. This technique can reduce the manufacturing makespan and is an effective tool in time-based manufacturing. Research on lot streaming models and solution procedures for flexible jobshops has been limited. The flexible jobshop scheduling problem is an extension of the classical jobshop scheduling problem by allowing an operation to be assigned to one of a set of eligible machines during scheduling. In this paper we develop a lot streaming model for a flexible jobshop environment. The model considers several pragmatic issues such as sequence-dependent setup times, the attached or detached nature of the setups, the machine release date and the lag time. In order to solve the developed model efficiently, an island-model parallel genetic algorithm is proposed. Numerical examples are presented to demonstrate the features of the proposed model and compare the computational performance of the parallel genetic algorithm with the sequential algorithm. The results are very encouraging.     

A part-and-tool assignment method for the workload-balance between machines and the minimisation of tool-shortage occurrences in an FMS

In this paper, we look into the loading problem of a flexible manufacturing system (FMS) that is made up of several identical flexible manufacturing machines (CMMs). These machines are capable of different operations as long as the required tools are provided to them. The loading problem studied in this paper is a pre-release problem that deals with the pre-assignment of parts and tools before the process of an FMS begins. There are two objectives that one would like to achieve. They include minimising the number of tool-shortage occurrences and balancing the workload between machines. Since one cannot directly minimise the number of tool-shortage occurrences at the current pre-release stage, a surrogate objective of minimising the total tool-capacity shortage (TTCS) is adopted. Furthermore, because of the ‘tool movement policy’ assumption, our loading problem only involves assigning parts and tools to each machine. In this paper, we propose a part-and-tool assignment method that combines fuzzy c-means, SA (simulated annealing), and an optimal tool-assignment algorithm. The proposed part-and-tool assignment method is designed to be interactive. Because of this interactive nature, human designers can experiment with different evaluation criteria or reset the parameters of SA to look for alternative solutions. An example is given which illustrates the proposed part-and-tool assignment method. From the example, one can see that the proposed method is very efficient and effective in finding good-quality solutions.     

The machine layout within a TFT-LCD bay with a multiple-stacker crane in-line stocker

In this paper, we study the machine layout problem in a TFT-LCD (thin-film transistor liquid-crystal display) bay with a multiple-stacker crane in-line stocker. Unlike other material-handling systems, such as automated guided vehicles and conveyors that only have a transportation function, in-line stockers have both transportation and storage functions. They rely on stacker cranes to perform their transportation function. The in-line stocker in a TFT-LCD bay is often divided into zones. Each zone is served by a stacker crane. Due to its multiple-zone in-line stocker, solving a TFT-LCD bay's machine layout requires us to determine not only the positions of the machines, but also the zone division design. The objectives include the minimisation of total flow distance and the workload balance between stacker cranes. We propose a layout procedure that adopts heuristic and mathematical approaches to assist us in accomplishing the aforementioned tasks. An example problem mimicking a real-case problem was solved to illustrate the proposed layout procedure. The layout design found by the proposed layout procedure was validated with computer simulations. It was also compared with layouts obtained by approaches proposed by other researchers. The simulation and comparison results demonstrate the capability of the proposed layout method in producing a feasible and good machine layout in a TFT-LCD bay with a multiple-stacker crane in-line stocker.     

Minimisation of non-machining times in operating automatic tool changers of machine tools under dynamic operating conditions

In many optimisation studies, it is assumed that problem related data does not change once the generated solution plan or schedule is currently in use. However, majority of real-life manufacturing problems are time-varying in their nature due to unpredictable events such as changes in lot sizes, fluctuating capacities of manufacturing constraints, changes in costs or profits. A problem, which contains at least one of these feature is referred as dynamic optimisation problem (DOP) in the related literature. The present study introduces a practical industrial application of a DOP, emerging particularly in flexible manufacturing systems (FMSs), where numerically controlled machine tools with automatic tool changers are employed. It is already known in FMSs that minimisation of non-machining times is vital for an efficient use of scarce resources. Therefore, fast response to possible changes in production is crucial in order to attain flexibility. In this context, first, a benchmarking environment is created by making use of already published problems and by introducing dynamic events. Next, effective strategies, including simulated annealing (SA) algorithm along with SA with multiple starts are developed for the introduced problem. Numerical results show that the developed SA with multiple starts is a promising approach for the introduced problem.     

An efficient local search heuristic for the double row layout problem with asymmetric material flow

The double row layout problem (DRLP) consists of arranging a number of rectangular machines of varying widths on either side of a corridor to minimize the total cost of material handling for products that move between these machines. This problem arises in the context of many production environments, most notably semiconductor manufacturing. Because the DRLP contains both combinatorial and continuous aspects, traditional solution approaches are not well suited to obtain solutions within a reasonable time. Moreover, previous approaches to this problem did not consider asymmetric flows. In this paper, an effective local search procedure featuring linear programming is proposed for solving the DRLP with asymmetric flows (symmetric flows being a special case). This approach is compared against several constructive heuristics and solutions obtained by a commercial mixed integer linear programming solver to evaluate its performance. Computational results show that the proposed heuristic is an effective approach, both in terms of solution quality and computational effort.     

Modeling and analysis of a manufacturing cell formation problem with fuzzy mixed-integer programming

Cell formation (CF) has received much attention from academicians and practitioners because of its strategic importance to modern manufacturing practice. In this paper a sophisticated mixed-integer programming (MIP) model is proposed to simultaneously form manufacturing cells and minimize the cost of dealing with exceptional elements. Also, we illustrate how a fuzzy mixed-integer programming (FMIP) approach can be used to solve the CF problem in a fuzzy environment, propose a new fuzzy operator, and examine the impact of different membership functions and operators on computational performance. Our study shows that FMIP not only provides a better and more flexible way of representing the problem domain, it also leads to improved overall performance.