A cut-tree-based approach for clustering machine cells in the bidirectional linear flow layout

This paper considers the joint cell clustering-layout problem where machine cells are to be located along the popular bidirectional linear material flow layout. The joint problem seeks to minimize the actual intercell flow cost instead of the typical measure that minimizes the number of intercell movements when the layout problem is excluded from the clustering process. Owing to the computational difficulty, a three-phase approach is proposed using the cut-tree-network model to solve this joint problem. The cell clustering and layout problem is transformed into a multi-terminal network flow model. A cut tree is constructed and partitioned into a number of subgraphs via the selected primary path. Each subgraph is a clustered cell and their locations are assigned to the layout sequence by comparing the cut capacities. Thus, the proposed approach concurrently determines the machine cells and their relative sequences in the bidirectional linear flow layout. Computational procedures are illustrated and additional experiments, with data adapted from the literature, are performed to demonstrate the viability of the approach.     

Cellular machine layout based on the Segmented Flow Topology

This paper introduces a facility layout design procedure for converting an existing manufacturing system with a predefined aisle structure to a cellular manufacturing system based on the 'segmented flow topology' (SFT) developed by Sinriech and Tanchoco. The proposed procedure is aimed at finding the best machine grouping, along with the locations of pick-up and delivery stations and machine layout for each cell based on an existing facility. The objective is to minimize the total material handling cost. In contrast to previous work in this area, the proposed design procedure takes into account both distance and material flow in forming machine clusters. In addition, a revised cost model for material handling system, which accounts for different aspects of capital and operating cost, is presented.     

Design and scheduling of hybridmulti-cell flexible manufacturing systems

The objective of this paper is to minimize machine duplication by increasing its utilization, minimize intercell moves, simplify the scheduling problem and increase the flexibility of the manufacturing system. An integrated approach of design and scheduling alternative hybrid multi-cell flexible manufacturing systems (MCFMSs) in four steps will be presented in this paper. The first step is the implementation of branch and bound techniques which provide tools to design group technology (GT) cells. The second step is balancing the inter-cell workload of GT cells which leads to a hybrid MCFMS with better utilization of the machines. The problem of the exception machines and their utilization and workload balance will be solved within the MCFMScentre. Thus the performance of GT cells can be improved by transferring workloads from a congested (bottleneck) machine in one cell to an alternative one, a less congested (exception) machine in another cell within a group of GT cells forming a MCFMS centre. The third step is the group scheduling; a proposed heuristic method will be used for the scheduling of a family of parts with the objective of minimizing the maximum completion time of each part. The problem of scheduling under MCFMS can be reduced by considering the scheduling of each family of parts. Finally, the flexibility of the system will be enhanced by selecting appropriate machine tools and flexible material handling equipments. This approach is both effective and efficient-it has generated a hybrid MCFMS centre which includes several alternatives, for some benchmark problems in much shorter time than algorithms previously reported in the literature. In addition, the method is conceptually simple and easy to implement.     

Intelligent layout planning for rapid prototyping

Significant savings in cost and time can be achieved in rapid prototyping (RP) by manufacturing multiple parts in a single setup to achieve efficient machine volume utilization. This paper reports the design and implementation of a system for the optimal layout planning of 3D parts for a RP process. A genetic algorithm (GA) based search strategy has been used to arrive at a good packing layout for a chosen set of parts and RP process. A two stage approach has been proposed to initially short-list acceptable orientations for each part followed by the search for a layout plan which optimizes in terms of final product quality and build time. The GA uses a hybrid objective function comprising of the weighted measures like part build height, staircase effect, volume and area-of-contact of support structures. In essence it captures the key metrics of efficiency and goodness of packing for RP. The final layout plan is produced in the form of a composite part CAD model which can be directly exported to a RP machine for manufacturing. Design methodology of the system has been presented with some representative case studies.     

Designing multi-product lines: job routing in cellular manufacturing systems

An operation sequence-based method which integrates intra-cell layout cost with cell formation to minimize the total cost of the materials flow and machine investment is developed here for designing a cellular manufacturing system. The method comprises three distinct approaches: part-family formation, cell-formation, and layout configuration. In the first phase, an operation sequence-based similarity coefficient is applied in a p-median model to group the parts to form part families with similar operation sequences. In the second phase, machine assignment to part families is determined where a trade-off between potential inter-cell movement cost due to the. bottleneck machine and the potential benefit of assigning bottleneck machines to certain part-family is considered. In the third phase, intra-cell layout is determined for each cell so as to refine the initial layout of the cell further. Numerical examples are employed to demonstrate the mechanism of the procedure throughout all phases. A comparative study is also performed to support the present method     

Cluster first-sequence last heuristics for generating block diagonal forms for a machine-part matrix

Before detailed cell design analyses, rearranging the binary (or 0-1) machine-part matrix into a compact block diagonal form (BDF) is useful for controlling combinatorial explosion during subsequent decision-making involving machine duplication, subcontracting, intercell layout design, etc. Several authors have shown that a compact BDF corresponds to the implicit clusters in both dimensions being expressed as row and column permutations. A traditional approach for solving this problem has been to obtain the two permutations independently by solving the permutation problem in each dimension as a (unidimensional) travelling salesman problem (TSP). This paper describes cluster first-sequence last heuristics which combine the properties of the minimal spanning tree (MST) (clusters only) and TSP (sequence only) for improved permutation generation. The BDFs obtained with these heuristics were compared with those obtained using the TSP, linear placement problem (LPP), single linkage cluster analysis (SLCA), rank order clustering (ROC) and occupancy value (OV) algorithms. The ratio of variances (β), which was the variance along the minor axis (V_Y) divided by the variance along the major axis (V_x) of the BDF, was used to evaluate the compactness of all the BDFs without assuming any explicit knowledge of the clusters in either dimension.     

PRODUCTION PLANNING DECISIONS IN FLEXIBLE MANUFACTURING SYSTEMS WITH RANDOM MATERIAL FLOWS

In this paper, we consider the FMS planning problem of determining optimal machine workload assignments in order to rninimize mean part flow time. We decompose this problem into the subproblems of first forming machine groups and next assigning operations to these groups. Three types of grouping configurations—no grouping, partial grouping and total grouping—are considered. In both no grouping and partial grouping, each machine is tooled differently. While each operation is assigned to only one machine in no grouping, partial grouping permits multiple operation assignments. On the other hand, total grouping partitions the machines into groups of identically-tooled machines; each machine within a group is capable of performing the same set of operations. Within this grouping framework, we consider three machine loading objectives—minimizing the total deviation from the optimal group utilization levels, minimizing part travel and maximizing routing flexibility, for generating a variety of system configurations.

A queueing network model of an FMS is used to determine the optimal configurations and machine workload assignments for the no grouping and total grouping cases. It is shown that under total grouping, the configuration of M machines into G groups that minimizes flow time is one in which the sizes of the machine groups are maximally unbalanced and the workload per machine in the larger groups is higher. This extends previous results on the optimality of unbalancing both machine group sizes and machine workload to the mean flow time criterion.

A simulation experiment is next conducted to evaluate the alternative machine configurations to understand how their relative performance depends upon the underlying system characteristics, such as system utilization level and variation among operation processing times. We also investigate the robustness of these configurations against disruptions, such as machine unreliability and variation in processing batch sizes. While different configurations minimize mean flow time under different parameter values, partial grouping with state-dependent part routing performs well across a wide range of these values. Experimental results also show that the impact of disruptions can be reduced by several means, such as aggregating operations of a part to be performed at the same machine, in addition to providing routing flexibility.     

Efficient algorithm for cell formation with sequence data,machine replications and alternative process routings

Cell formation is an important problem in the design of a cellular manufacturing system. Despite a large number of papers on cell formation being published, only a handful incorporate operation sequence in intercell move calculations and consider alternative process routings, cell size, production volume and allocating units of identical machines into different cells. Modelling the above factors makes the cell formation problem complex but more realistic. The paper develops a model and solution methodology for a problem of cell formation to minimize the sum of costs of intercell moves, machine investment and machine operating costs considering all the factors mentioned above. An algorithm comprised of simulated annealing and local search heuristics has been developed to solve the model. A limited comparison of the proposed algorithm with an optimal solution generated by complete enumeration of small problems indicates that the algorithm produces a solution of excellent quality. Large problems with 100 parts and 50 machine types are efficiently solved using the algorithm.     

Cell formation and layout designs in a cellular manufacturing environment a case study

This paper presents the application of a recent integrated approach for the design of cellular manufacturing, addressing, concurrently, all three phases of the design namely parts/machines grouping, intra-cell and inter-cell layout designs to a white-goods manufacturing company. It provides a platform to investigate the impact of the cell formation method on intra-cell and inter-cell layout designs, and vice versa, by generating multiple efficient layout designs for different cell partitioning strategies. This approach enables the decision-maker to have wider choices with regard to the different numbers of cells and to assess various criteria such as travelling cost, duplication of machines and space requirement against each alternative.     

A multi-objective procedure for labour assignments and grouping in capacitated cell formation problems

A hierarchical methodology for the design of manufacturing cells is proposed, which includes labour-grouping considerations in addition to partmachine grouping. It is empirically driven and designed for an interactive decision environment, with an emphasis on fast execution times. The method synthesizes the capabilities of neural network methods for rapid clustering of large partmachine data sets, with multi-objective optimization capabilities of mathematical programming. The procedure includes three phases. In Phase I, part families and associated machine types are identified through neural network methods. Phase II involves a prioritization of part families identified, along with adjustments to certain load-related parameters. Phase III involves interactive goal programming for regrouping machines and labour into cells. In machine grouping, factors such as capacity constraints, cell size restrictions, minimization of load imbalances, minimization of intercell movements of parts, minimization of new machines to be purchased, provision of flexibility, etc. are considered. In labour grouping, the functionally specialized labour pools are partitioned and regrouped into cells. Factors such as minimization of hiring and cross-training costs, ensuring balanced loads for workers, minimization of intercell movements of workers, providing adequate levels of labour flexibility, etc. are considered in a pragmatic manner.     

Design of distributed layouts

Distributed layouts are layouts where multiple copies of the same department type may exist and may be placed in non-adjoining locations. In this paper, we present a procedure for the design of distributed layouts in settings with multiple periods where product demand and product mix may vary from period to period and where a relayout may be undertaken at the beginning of each period. Our objective is to design layouts for each period that balance relayout costs between periods with material flow efficiency in each period. We present a multi-period model for jointly determining layout and flow allocation and offer exact and heuristic solution procedures. We use our solution procedures to examine the value of distributed layouts for varying assumptions about system parameters and to draw several managerial insights. In particular, we show that distributed layouts are most valuable when demand variability is high or product variety is low. We also show that department duplication (e.g., through the disaggregation of existing functional departments) exhibits strong diminishing returns, with most of the benefits of a fully distributed layout realized with relatively few duplicates of each department type.     

Genetically assisted optimization of cell layout and material flow path skeleton

A continuous plane manufacturing cell layout and intercell flow path skeleton problem formulation involving rectilinear distances between cell input/output stations is mapped to a genetic search space. Certain properties of such a search space are exploited to design a very efficient method for reduction of a mixed-integer programming problem formulation to an iterative sequence of linear programming problems. This paper reports theoretical and computational insights for efficiently finding good solutions for the above problem formulation, taking advantage of the solution structure and the search stage. The scores of the objective function on a set of test cases indicate better solutions than those previously reported in the literature. The empirical results based on multiple runs also suggest that the method generates final results that are not dependent on the quality of the initial solution; hence the solution search seems to be more global than many of the previous approaches.     

Reducing flow between manufacturing cells: a sensitivity analysis

We evaluate the sensitivity of cellular manufacturing performance to a reduction in intercell flow. Results from our simulation experiment indicate that the performance of cellular shops operating with lower run time variability, smaller batch sizes, longer setup times and larger reductions in setup times due to dedication, has a greater sensitivity to a reduction of intercell flow. In these scenarios, it would be easier to justify an investment in additional machines or specialized tooling required to reduce the level of intercell flow.     

Batch sizing with controllable production rates in a multi-stage production system

In this paper, a comprehensive model is presented for cell formation and layout design in cellular manufacturing systems (CMS). The proposed model incorporates an extensive coverage of important operational features and especially layout design aspects to determine optimal cell configuration and Intra and Inter-cell layout in CMS. Hence, proposed integrated approach attempts to design intra and inter-cell layout and material handling flow path structure simultaneously. We examine the great potential benefits of providing these features consist of routing flexibility, operation sequence, machine capacity, considering number of cells as a decision variable, un-equal dimension of machines, free machines and cells orientation, and considering pickup and drop off station for each cell. In order to show the effects and important of integrated design in the CMS, two approaches, sequentially and integrated, have been investigated and demonstrate the integrated approach improve the quality of obtained solution. The proposed model is a mixed integer non-linear programme. Linearisation procedures are proposed to transfer it into a linearised mixed integer programming formulation. Computational results are presented with the linearised formulation. We presented several enhancements in terms of valid inequalities and extensions to the proposed model in order to improve its computational performance. Finally, concluding remarks are provided.     

The cost of eliminating exceptional elements in group technology cell formation

Many researchers have suggested methods for the formation of machine cells/part families in group technology. However, few of these methods have addressed the possible existence of exceptional elements (EE) in a reasonable manner. EE can be the result of bottleneck machines whose processing is needed by parts assigned to more than one part family. They can also be caused by parts that require processing on machines assigned to more than one machine cell. The existence of EE in cell formation solutions is a nontrivial problem that requires interaction between machine cells intended to be independent for production efficiency. This paper presents a systematic method for identifying opportunities for reducing the number of intercell transfers caused by the existence of EE. The method recognizes how each EE in a cell formation solution may be involved in the creation of intercell transfers. The sequence of operation in each part routeing is also considered. The method then analyses the costs associated with alternative actions for the removal of the EE. The result is a prioritized list (based on relative cost-effectiveness) of the EE-removal actions. The method recognizes that interdependencies exist among EE: actions taken to eliminate one EE may have an effect on others as well. The process is demonstrated with an example.     

Grouping and placement of machine cells

We consider a real-world machine grouping and layout problem in which the objective is not only to identify machine cells and corresponding part families but also to determine a near-optimal layout of machines within each cell and the cells themselves. The three-stage approach developed incorporates materials flow considerations while determining machine groups, considers alternative process plans, exploits part routing information and allows the user to perform sensitivity analysis. The menu-driven, interactive program has been applied to four test problems and an industrial problem. Our experience with applying the approach to the industrial problem is also reported.     

GA-based integrated approach to FMS part type selection and machine-loading problem

Part type selection and machine loading are two interrelated subproblems in production planning of flexible manufacturing systems. The total solution requires a simultaneously combined approach to avoid the possible conflicts between the two sets of individually obtained solutions. A strict mixed-integer programming (MIP) model that integrates part type selection and machine loading together is formulated. The MIP takes into account the constraints such as magazine capacity, tool life, available machine time, etc. The objective is to minimize the difference between maximum and minimum workloads of all the machine resources in each batch. A genetic algorithm-based method is developed to obtain the solution of the problem effectively. Concepts of virtual job and virtual operation are introduced in the encoding scheme, and a chromosome is composed of both these strings. Among each chromosome, the partition symbol list is mainly used to handle the part type selection problem, while the virtual job list mainly used to cope with the loading problem. Special crossover and mutation operators are designed to adapt to the problem. Our approach can simultaneously balance the workloads in different batches. At last, illustrative examples are presented, and a comparison between standard MIP algorithm and a genetic algorithm method is given.     

The value of the shortest loop covering all work centers in a manufacturing facility layout

In this study we develop mathematical models to design circular material flow systems. We first develop a tight formulation to find the shortest loop covering all work centers within a manufacturing facility layout. The shortest loop is an attractive solution for most types of conveyors and power-and-free systems, where the length of the flow path is the major driver of the total cost. We develop a primal as well as a dual graph formulation and discuss their one-to-one correspondence in node-edge as well as in connectivity constraints. Our solution times outperform other optimization models available for the facility layout shortest loop design problem. We then approach trip-based material handling, such as automated guided vehicle systems, where the total loaded and empty trip distance is the major driver of the total cost. The problem in these systems evolves into concurrent design of the loop, pickup and dropoff station, and the empty vehicle dispatching policies. On the foundation of the shortest loop model, we propose a decomposition heuristic for design of trip-based flow systems. Computational results indicate that the heuristic provides high quality and robust solutions.     

Manufacturing cell design with alternative routings in generalized group technology: reducing the complexity of the solution space

In the presence of alternative routings, the manufacturing cell design involves the solution of a large number of (simple) cell-formation problems. We present a bounding scheme which examines all combinations of alternative routings and solves only a few cell-formation problems, thereby limiting the solution space which is searched heuristically. This leads to increased reliability for the solutions obtained. The resulting algorithm is shown to be applicable for problems arising in practice frequently, when the initial design includes relatively few exceptional elements, and machine duplication and/or genuine multiple process plans are used correctively, to eliminate the remaining intercellular traffic.     

Easing the implementation and change of manufacturing software systems

The software systems that underpin contemporary manufacturing enterprises can become the single most inflexible part of an enterprise, constraining a business that has to evolve. This paper describes an approach to manufacturing software system creation which supports system evolution. It is based on the notion that raising the level of the computing infrastructure through the use of a domain machine, can remove the need to transform the clear abstractions and decomposition identified during design into the incomprehensible maze of programming language constructs which prove difficult to maintain.

The paper provides a comparison between two implementations of a system to control a printed circuit board manufacturing line, one based on a conventional approach and the other based on the authors manufacturing domain machine. Ease of change enabled by the domain machine is illustrated through measuring the degree of modification required to each system when incorporating a new solder paste print machine in the production line.