Introducing new parts into existing cellular manufacturing systems based on a novel similarity coefficient

Over the last three decades, designing cellular manufacturing systems (CMS) still centres on assigning machines to machine cells and parts to part families. This task ends after assigning these part families to the appropriate machine cells. In the past, testing CMS was evaluated according to the efficiency of clustering, but actual testing of CMS after installation is still unexplored. Introducing one or more new parts (products) into CMS without any changes in the installation of the cells during processing of the current parts is a new concept to be considered and evaluated. Transferring these systems from traditional ideologues to advanced ideologues (agile systems) is highly desired. This concept can be considered as part (product) flexibility in CMS. To address this concept, a new similarity coefficient between the new part and the existing manufacturing cell will be created. New productivity and flexibility measurements in CMS will also be suggested. A new strategy for accepting a new part into CMS will be proposed based on machine utilization and flexibility in the cells, cell utilization and flexibility in the system, product flexibility (system flexibility), and similarity of this part with existing manufacturing cells. A complete analytical example will be presented.     

Manufacturing cells' design in consideration of various production factors

A cell formation problem is introduced that incorporates various real-life production factors such as the alternative process routing, operation sequence, operation time, production volume of parts, machine capacity, machine investment cost, machine overload, multiple machines available for machine types and part process routing redesigning cost. None of the cell formation models in the literature has considered these factors simultaneously. A similarity coefficient is developed that incorporates alternative process routing, operation sequence, operation time and production volume factors. Although very few studies have considered the machine capacity violated issue under the alternative process routing environment, owing to the difficulties of the issue discussed here, these studies fail to deal with the issue because they depend on some unrealistic assumptions. Five solutions have been proposed here and are used to cope with this difficulty. A heuristic algorithm that consists of two stages is developed. The developed similarity coefficient is used in stage 1 to obtain basic machine cells. Stage 2 solves the machine-capacity violated issue, assigns parts to cells, selects process routing for each part and refines the final cell formation solution. Some numerical examples are used to compare with other related approaches in the literature and two large size problems are also solved to test the computational performance of the developed algorithm. The computational results suggest that the approach is reliable and efficient in either the quality or the speed for solving cell formation problems.     

Book reviews

A practical problem of significant importance for many manufacturing systems is machine interference. Interference is undesirable and unnecessary machine idleness that is caused by allowing one (or more) operator(s) to tend several machines. When the service demands of machines are not synchronized, both operators and machines can experience interference. Interference obviously decreases the productivity of a manufacturing system. Most interference models are designed to attempt to minimize the cost of interference, or simply the interference itself.

In this paper, we survey the literature and classify various interference problems, models and associated assumptions, and solution techniques. Theoretical results are given. Industrial applications of the models that have been reported in the literature are also described. Finally, future applications of such interference models to robotics and flexible manufacturing systems are outlined.     

A comprehensive approach to operation sequence similarity based part family formation in the reconfigurable manufacturing system

The industrial sector of the twenty-first century faces a highly volatile market in which manufacturing systems must be capable of responding rapidly to the market changes, while fully exploiting resources. The reconfigurable manufacturing system (RMS) is a state of the art technology offering the exact functionality and capacity needed, which is built around a part family. The configuration of an RMS evolves over a period to justify the needs of upcoming part families. The foundation for the success of an RMS, therefore, lies in the recognition of appropriate sets of part families. In the present work the authors have developed a novel operation sequence based BMIM (bypassing moves and idle machines) similarity coefficient using longest common subsequence (LCS) and the minimum number of bypassing moves and the quantity of idle machines. The effectiveness of the developed similarity coefficient has been compared with the existing best similarity/dissimilarity coefficients available in the existing literature. An example set of parts has been classified using the developed similarity coefficient and average linkage hierarchical clustering algorithm. The developed approach can also be used very effectively for part family formation in the cellular manufacturing system.     

Cell formation problem with consideration of both intracellular and intercellular movements

The cellular manufacturing system (CMS) is a well-known strategy which enhances production efficiency while simultaneously cutting down the system-wide operation cost. Most of the researchers have been focused on developing different approaches in order to identify machine-cells and part-families more efficiently. In recent years, researchers have also focused their studies more scrupulously by collectively considering CMS with production volume, operation sequence, alternative routing or even more. However, very few of them have tried to investigate both the allocation sequence of machines within the cells (intra-cell layout) and the sequence of the formed cells (inter-cell layout). Solving this problem is indeed very important in reducing the total intracellular and intercellular part movements which is especially significant with large production volume.

In this paper, a two-phase approach has been proposed to tackle the cell formation problem (CFP) with consideration of both intra-cell and inter-cell part movements. In the first phase, a mathematical model with multi-objective function is formed to obtain the machine cells and part families. Afterwards, in the second phase, another mathematical model with single-objective function is presented which optimizes the total intra-cell and inter-cell part movements. In other words, the scope of problem has been identified as a CFP together with the background objective of intra-cell and inter-cell layout problems (IAECLP). The primary assumption for IAECLP is that only linear layouts will be considered for both intra-cell and inter-cell. In other words, the machine within cells and the formed cells are arranged linearly. This paper studies formation of two mathematical models and used the part-machine incidence matrix with component operational sequence.

The IAECLP is considered as a quadratic assignment problem (QAP). Since QAP and CFP are NP-hard, genetic algorithm (GA) has been employed as solving algorithm. GA is a widespread accepted heuristic search technique that has proven superior performances in complex optimization problems and further it is a popular and well-known methodology. The proposed algorithms for CFP and IAECLP have been implemented in JAVA programming language.     

The threshold value of group similarity in the formation of cellular manufacturing systems

Cellular manufacturing is an effective alternative to batch-type production systems where different products are intermittently produced in small lot sizes with frequent setups, large in-process storage quantities, long production lead times, decreasing throughputs, and complex planning and control functions. An effective approach to forming manufacturing cells and introducing families of similar parts, consequently increasing production volumes and machine utilisation, is the use of similarity coefficients in conjunction with clustering procedures. In a similarity coefficients-based approach, the results of the clustering analysis depend on the minimum admissible level of similarity adopted for the generic group of clustered items. This is the so-called threshold value of group similarity. The aim of this paper is to identify effective values of the threshold value of group similarity to help practitioners and managers of manufacturing systems form machine groups and related part families. The proposed threshold values for a given similarity coefficient are based on calculation of the percentile of aggregations generated by the adopted clustering algorithm. The importance of the proposed measure of group similarity has been demonstrated by experimental analysis conducted on a large set of significant instances of the cell formation problem in the literature. This analysis can also support the best determination of this percentile-based cut value especially when the number of manufacturing cells is not known in advance.     

Maintenance scheduling for a manufacturing system of machines with adjustable throughput

This paper considers the problem of analyzing and optimizing joint schedules of maintenance and throughput adjustment operations in manufacturing systems. The purpose of joint scheduling of maintenance and throughput changing operations is to maximize the cost benefits of maintenance operations in manufacturing systems in which some or all of the machines can execute their function under different process settings, resulting in different machine and system throughputs. Such a capability enables one to strategically slow down more degraded machines or accelerate freshly maintained machines so that production targets can be met and maintenance operations can be offset to times when they are less intrusive on the manufacturing process. A Monte-Carlo-simulation-based method is proposed for the evaluation of cost effectiveness of any schedule of maintenance and throughput changing operations, and a genetic-algorithm-based method is proposed to enable searching for schedules that would maximize the cost benefits of these operations. A matrix chromosome representation of the joint schedules of maintenance and throughput adjustment operations is introduced and several mechanisms of chromosome evolution and selection are proposed and analyzed in numerical simulations of such manufacturing systems. Results indicate a good ability for the newly proposed methods to achieve a tradeoff between cost benefits of production and losses due to maintenance operations through strategic allocation of maintenance and throughput changing actions.     

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.     

A heuristic algorithm to minimise the control places of a Petri net for the control of shared machines

This paper proposes a design methodology of a controller based on a Petri net for the shared machines of manufacturing systems. A conflict occurs when several manufacturing systems require the same shared machines at the same time. In this case, we have two issues; the scheduling of jobs on shared machines and the construction of a control procedure for scheduling. The scheduling of production on machines has been extensively studied over the past years by researchers. In this paper, our concern is not the scheduling problem but the construction of a control procedure for the production schedule. We propose a design of a Petri net based controller for the shared machines of manufacturing systems such that the number of control places in the Petri net is minimised. The experimental results show that the proposed algorithm performs better than an upper bound in terms of optimality. Also, the proposed algorithm is computationally more efficient than the optimal algorithm. Finally, we present the application of the proposed algorithm to a realistic batch process system shown in the literature.     

Machine cell formation for production management in cellular manufacturing systems

The formation of machine-part families is an important task in the design of cellular manufacturing systems. Manufacturing cell grouping has the effect of reducing material handing cost and work in process. Among the many methods utilized in machine cells formation, the similarity coefficient method is most widely used. Production sequence and product volumes, if incorporated properly in determining the machine cells, can enhance the quality of solutions and reduce the number of intercellular movements. Measures for cell formation based on operations sequence utilizing ordinal production data are few and have many limitations, such as counting the number of the trips for each individual part instead of counting the weights of the batches. A new ordinal production data similarity coefficient based on the sequence of operations and the batch size of the parts is introduced. Furthermore, a new clustering algorithm for machine cell formation is proposed. The new similarity measure showed more sensitivity to the intercellular movements and the clustering algorithm showed better machine grouping.     

Economic design of unit load-based FMSs employing AGVs for transport

A methodology to economically configure an automated guided vehicle based flexible manufacturing system (FMS) in terms of machine and material handling requirements is presented. The procedure uses the concept of simultaneous design to determine the number of machines required at each workstation in the FMS and the number of automated guided vehicles required to service the material handling needs of the system. The technique integrates decisions on machine requirements, vehicle requirement, and vehicle/container carrying capacity into a single cost model. Solution to the model automatically yields the best resource configuration for the shop that achieves the set production target while minimizing total manufacturing cost. A hybrid algorithm that combines numerical search, simulation, and statistical analysis is employed for solving the problem. The application of the design procedure is demonstrated with an example problem. Sensitivity analysis on machine and vehicle requirements due to changes in job attributes and unit transport quantities are also performed.     

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     

Towards a psychologically consistent cellular manufacturing system

In cellular manufacturing systems (CMSs), an operator plays an important role. Because operators work for long-time periods in a production area, an increase in job satisfaction and system productivity occurs if the consistency of operators’ personal characteristics are considered in the design of CMSs. In a CMS, a cell formation problem (CFP) focuses on grouping and allocating machines, part families and operators to manufacturing cells. This paper considers a decision-making style (DMS) as an operator’s personal characteristic index in a CFP for designing a psychologically consistent CMS. DMS influences not only the interaction between two operators, but also the work that operator does on a machine. Hence, this paper develops a novel multi-objective mathematical model for the CFP considering consistency between each two operators in each cell and consistency between operator and his/her assigned machine(s). Because of possibility of a change in the primary DMS of a person to the backup one, this paper tackles this issue by applying a probabilistic procedure. Two hybrid meta-heuristic algorithms are developed for the large-sized test problems. In addition, the PROMETHEE-II method is applied to select the best Pareto solution. Finally, a real case study is presented to show the applicability of the developed approach.     

A new approach to the cell formation problem with alternative processing routes and operation sequence

Cellular manufacturing (CM) is an important application of group technology in manufacturing systems. One of the crucial steps in the design of CM is the identification of part families and manufacturing cells. This problem is referred to as cell formation problem (CFP) in the literature. In this article, a solution approach is proposed for CFP, which considers many parameters such as machine requirement, sequence of operations, alternative processing routes, processing time, production volume, budget limitation, cost of machines, etc. Due to the NP-hardness of CFP, it cannot be efficiently solved for medium- to large-sized problems. Thus, a genetic algorithm (GA) is proposed to solve the formulated model. Comparison of the results obtained from the proposed GA to the globally optimum solutions obtained by Lingo Software and those reported in the literature reveals the effectiveness and efficiency of the proposed approach.     

Cellular manufacturing systems design with routing flexibility,machine procurement,production planning and dynamic system reconfiguration

This paper investigates the problem of designing cellular manufacturing systems with multi-period production planning, dynamic system reconfiguration, operation sequence, duplicate machines, machine capacity and machine procurement. An important aspect of this problem is the introduction of routing flexibility in the system by the formation of alternate contingency process routings in addition to alternate main process routings for all part types. Contingency routings serve as backups so as to effectively address the reality of part process routing disruptions (in the main routings) owing to machine breakdowns and allow the cellular manufacturing system to operate in a continuous manner even in the event of such breakdowns. The paper also provides in-depth discussions on the trade-off between the increased flexibility obtained versus the additional cost to be incurred through the formation of contingency routings for all parts. Some sensitivity analysis is also performed on some of the model parameters. The problem is modelled and solved through a comprehensive mixed integer programming formulation. Computational results presented by solving some numerical examples show that the routing and process flexibilities can be incorporated within the cellular manufacturing system design without significant increase in the system cost.     

Lockout/tagout and optimal production control policies in failure-prone non-homogenous transfer lines with passive redundancy

This paper considers a production problem for a transfer line subject to random failures and repairs, and differs from other studies on transfer lines. It considers a manufacturing system consisting of three machines (two machines with passive redundancy, and one in series with the previous ones) producing one part type. The control problem is subject to non-negative constraints on work-in-process (WIP). The decision variables are the production rates of two main machines and a standby machine, and influence the WIP levels, the inventory levels and the system's capacity, which is assumed to be described by a finite-state Markov chain. The objective of this paper is to minimise WIP and finished goods inventory costs; it also aims to respect the essential space–time during intervention on machine down, in order to minimise the possibility of the circumvention of protection devices or of the retraction of lockout/tagout procedures through a passive redundancy system. This paper therefore verifies the effect of passive redundancy on optimal stock levels. Given that an analytical or even a numerical solution of the problem is very difficult to find, and that we want to have a more realistic model for industries, we present a combined approach, which is presented based on a combination of analytical formalism, simulation modelling, design of experiments, and response surface methodology to optimise a transfer line with passive redundancy, producing one part type. The usefulness of the proposed approach is illustrated through a numerical example and a sensitivity analysis.     

Revisiting the cell formation problem: assigning parts to production systems

Before manufacturing cells can be identified from a population of parts and machines, the parts must be carefully analysed to determine the small subset of parts that are appropriate for cellular manufacturing. When this is not done it becomes very difficult to identify the cells because the algorithms that are used have high computational requirements and high space requirements. The computational requirements and space requirements for the rank order clustering algorithm and the similarity coefficient algorithm are determined. Other algorithms that have been proposed for solving the ‘cell formation problem’ are more elaborate than these and are therefore likely have higher computational and space requirements. A procedure for assigning parts to production systems is presented in this paper. An illustrative example, taken from an actual implementation, is described to show how the procedure can be used.     

Benchmark generation algorithm for stochastic mixed model assembly shop simulation and optimization

The Operations Research (OR) community have defined many deterministic manufacturing control problems mainly focused on scheduling. Well-defined benchmark problems provide a mechanism for communication of the effectiveness of different optimization algorithms. Manufacturing problems within industry are stochastic and complex. Common features of these problems include: variable demand, machine part specific breakdown patterns, part machine specific process durations, continuous production, Finished Goods Inventory (FGI) buffers, bottleneck machines and limited production capacity. Discrete Event Simulation (DES) is a commonly used tool for studying manufacturing systems of realistic complexity. There are few reports of detail-rich benchmark problems for use within the simulation optimization community that are as complex as those faced by production managers. This work details an algorithm that can be used to create single and multistage production control problems. The reported software implementation of the algorithm generates text files in eXtensible Markup Language (XML) format that are easily edited and understood as well as being cross-platform compatible. The distribution and acceptance of benchmark problems generated with the algorithm would enable researchers working on simulation and optimization of manufacturing problems to effectively communicate results to benefit the field in general.     

Virtual cell formation

The concept of a virtual cellular manufacturing system (VCMS), which operates very much like a traditional cellular manufacturing system (CMS), has attracted considerable attention in recent years. Unlike traditional cellular manufacturing systems, virtual cellular manufacturing systems are most suitable in production environments that experience frequent product mix changes. Whereas, in traditional CMS, the shop floor configuration is fixed, in VCMS the shop floor configuration changes in response to changes in product mix over time. Therefore, the life of a given shop floor configuration continues as long as the product mix remains relatively unchanged. Furthermore, whereas in traditional cellular manufacturing systems, a machine cell occupies a contiguous region of the shop floor, the same is not necessarily true with virtual cells. Virtual manufacturing cells are simply logical cells in which the machines belonging to the same cell need not occupy the same contiguous area. Because cell members are logical instead of physical, machines in a cell can be at any location on the floor. In this paper, we present a methodology for designing virtual manufacturing cells.     

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.