Multi-objective cell formation and production planning in dynamic virtual cellular manufacturing systems

This article presents a fuzzy goal programming-based approach for solving a multi-objective mathematical model of cell formation problem and production planning in a dynamic virtual cellular manufacturing system. In a dynamic environment, the product mix and part demand change over a planning horizon decomposed into several time periods. Thus, the cell formation done for one period may be no longer efficient for subsequent periods and hence reconfiguration of cells is required. Due to the variation of demand and necessity of reconfiguration of cells, the virtual cellular manufacturing (VCM) concept has been proposed by researchers to utilise the benefits of cellular manufacturing without reconfiguration charges. In a VCM system, machines, parts and workers are temporarily grouped for one period during which machines and workers of a group dedicatedly serve the parts of that group. The only difference of VCM with a real CM is that machines of the same group are not necessarily brought to a physical proximity in VCM. The virtual cells are created periodically depending on changes in demand volumes and mix, as new parts accumulate during a planning horizon. The major advantage of the proposed model is the consideration of demand and part mix variation over a multi-period planning horizon with worker flexibility. The aim is to minimise holding cost, backorder cost and exceptional elements in a cubic space of machine–part–worker incidence matrix. To illustrate the applicability of the proposed model, an example has been solved and computational results are presented.     

A possibilistic approach for designing hybrid cellular manufacturing systems

In this paper, a hybrid cellular manufacturing (HCM) system is presented in which the main sources of uncertainty, e.g. the demands of parts and unit costs are treated as fuzzy numbers in the form of possibilistic distributions. The basic concept of HCM is that high variation in demand might disturb cell efficiency, so forming cells with only those parts that have stable demand, will profit. Thus, to design stable and robust manufacturing cells, a two-phase method is proposed in which a fuzzy adaptive ranking method is first applied to identify those parts with low and non-repetitive demands (i.e. the special parts) which will then be assigned to a functional cell. Afterwards, an interactive possibilistic programming model is applied to cell formation of remaining regular parts while considering both part sequences and multiple routes. To show the capability and usefulness of the proposed method, an illustrative example is also provided. Finally, concluding remarks are reported.     

Multiple routeings and capacity considerations in group technology applications

This paper addresses the problem of manufacturing cell formation, given multiple part routeings, and multiple functionally similar workcentres. Cellular manufacturing is intended to facilitate production, and thus should be based on projected production requirements. The originality of the approach lies in considering both the manufacturing system as well as projected production, and distributing the demand among alternate routeings in order to obtain a better manufacturing cell design. The suggested choice of part routeings favours the decomposition of the manufacturing system into manufacturing cells in a way that minimizes part traffic, along with satisfying the part demand and workcentre capacity constraints. We show that the problem can be formulated as a linear programming type problem which simultaneously addresses two problems: (i) routeing selection, and (ii) cell formation. The common objective is to minimize the inter-cell traffic in the system. The proposed algorithm iteratively solves two problems. The first problem is formulated as a linear-programming problem, while the latter is approached by an existing heuristic bottom-up aggregation procedure, known as Inter-Cell Traffic Minimization Method (ICTMM), enhanced appropriately.     

Dynamic cellular manufacturing system design considering alternative routing and part operation tradeoff using simulated annealing based genetic algorithm

In this paper, an integrated mathematical model of multi-period cell formation and part operation tradeoff in a dynamic cellular manufacturing system is proposed in consideration with multiple part process route. This paper puts emphasize on the production flexibility (production/subcontracting part operation) to satisfy the product demand requirement in different period segments of planning horizon considering production capacity shortage and/or sudden machine breakdown. The proposed model simultaneously generates machine cells and part families and selects the optimum process route instead of the user specifying predetermined routes. Conventional optimization method for the optimal cell formation problem requires substantial amount of time and memory space. Hence a simulated annealing based genetic algorithm is proposed to explore the solution regions efficiently and to expedite the solution search space. To evaluate the computability of the proposed algorithm, different problem scenarios are adopted from literature. The results approve the effectiveness of the proposed approach in designing the manufacturing cell and minimization of the overall cost, considering various manufacturing aspects such as production volume, multiple process route, production capacity, machine duplication, system reconfiguration, material handling and subcontracting part operation.     

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 cell design: an integer programming model employing genetic algorithms

The design of a cellular manufacturing system requires that a part population, at least minimally described by its use of process technology (part/machine incidence matrix), be partitioned into part families and that the associated plant equipment be partitioned into machine cells. At the highest level, the objective is to form a set of completely autonomous units such that inter-cell movement of parts is minimized. We present an integer program that is solved using a genetic algorithm (GA) to assist in the design of cellular manufacturing systems. The formulation uses a unique representation scheme for individuals (part/machine partitions) that reduces the size of the cell formation problem and increases the scale of problems that can be solved. This approach offers improved design flexibility by allowing a variety of evaluation functions to be employed and by incorporating design constraints during cell formation. The effectiveness of the GA approach is demonstrated on several problems from the literature.     

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.     

Designing cellular manufacturing systems with dynamic part populations

The effectiveness of a cellular manufacturing system is sensitive to fluctuations in the demand for products and the product mix. This paper presents a new formulation of the part family/machine cell formation problem that addresses the dynamic nature of the production environment by considering a multi-period forecast of product mix and demand during the formation of part families and machine cells. The goal of the multi-period formulation is to obtain a cellular design that continues to perform well with respect to the design objectives as the part population changes with time.     

Impact of worker and shop flexibility on assembly cells

Flexibility can counter the negative effects of the loss of pooling synergy in cellular systems. In this study we define flexibility as the ability of assembly cells to reallocate resources to accommodate changes in family assignments (i.e. shop flexibility) and the ability of workers to move between cells (i.e. worker flexibility). We investigate the impact of shop and worker flexibility on different assembly cells faced with product mix variability over a wide range of experimental conditions. Three types of cellular shops are considered: strict cell shops (where each cell is dedicated to producing only one product family), flexible cell shops (where each cell can produce multiple product families), and hybrid cell shops (where some of the cells are strict and the rest are flexible). Results indicate that there is no cell shop that outperforms others, under all experimental environments. However, flexible cell shops showed significant advantages when the setup times were low, while hybrid cell shops provided an excellent alternative when setup times and the product mix unbalance were at ‘moderate to high’ levels. The strict cell shops demonstrated excellent performance when setup times were high, and the product mix unbalance was ‘minor’. Finally, the results suggest that in most cases, the implementation of only worker flexibility resulted in the majority of improvements with respect to the average percentage of jobs tardy.     

Performance comparison of virtual cellular manufacturing with functional and cellular layouts in DRC settings

This study investigates the performance of virtual cellular manufacturing (VCM) systems, comparing them with functional layouts (FL) and traditional, physical cellular layout (CL), in a dual-resource-constrained (DRC) system context. VCM systems employ logical cells, retaining the process layouts of job shops. Part family-based scheduling rules are applied to exploit the benefits of group technology while retaining the flexibility and functional synergies of the job shop. Past studies of VCM have been based entirely on single-resource-constrained (SRC) systems, i.e. as purely machine-limited systems, assuming that resources such as labour and tooling do not restrict the output. However, given the fact that labour forms a second major constraining resource, and many of the advantages associated with cellular manufacturing are derived from labour flexibility, it becomes necessary to extend the research to DRC systems. In this study, we assume several levels of labour flexibility in all three systems, in addition to other relevant factors such as lot size, set-up reduction, and labour assignment rules. It is shown that VCM can outperform efficiently operated FL and CL in certain parameter ranges, as preliminary research has shown so far. However, it is shown that CL tends to outperform both VCM and FL in the parameter ranges customarily advocated for CL, namely, low lot sizes, adequate levels of set-up reduction, cross training of workers, and worker mobility within cells.     

Design of dedicated,shared and remainder cells in a probabilistic demand environment

In this paper, a new layered cellular manufacturing system is proposed to form dedicated, shared and remainder cells to deal with the probabilistic demand, and later its performance is compared with the classical cellular manufacturing system. In the layered cellular design, each family may need more than one cell to cover capacity requirements. The proposed approach for layered cellular design involves five stages: (1) product clustering, (2) identifying number of cells and demand coverage probabilities, (3) determining cell types using the proposed heuristic procedure, (4) performing simulation to determine operating conditions and (5) statistical analysis to pick the best design configuration among layered cellular designs. Simulation and statistical analysis are performed to help identify the best design within and among both layered cellular design and classical cellular design. It was observed that as the number of part families increased, the number of machines needed to process the parts decreased first. Then the number of machines started to increase once again as the number of part families continued to increase. Another observation was that the average flow time and total WIP were not always the lowest when additional machines were used by the system. The last and the most important observation was that the layered cellular system provided much better results than the classical cellular system when high demand fluctuation was observed.     

Flexibility and manufacturing system design: An experimental investigation

Manufacturing industries today are faced with steady and unrelenting changes to the environment in which they operate. In order to survive and profit, manufacturing facilities must be designed such that they exhibit desirable system-level flexibility characteristics. The relationships between flexibility and manufacturing system design, however, remain largely unexplored. This paper investigates the effects of manufacturing system design on product, mix, production, and volume flexibilities, and on trade-offs between these flexibility types, for different product environments. Of particular concern is the determination of whether or not flexibility trade-offs can be avoided, and if so, how. Simulation experiments are performed to determine flexibility values for 16 different manufacturing system design 'approaches' and two levels of part processing flexibility. A total of 800 different manufacturing system/product set combinations are investigated. The results indicate that the effects of manufacturing system design on flexibility are not always intuitive, and that they can change depending upon the level of part processing flexibility present. In addition, however, they show that flexibility trade-offs are not inevitable: multiple flexibility types can be increased in value simultaneously through proper selection of the design approach.     

A sequence-based materials flow procedure for designing manufacturing cells

One of the most important problems in designing a cellular manufacturing system is the formation of machine cells and the grouping of parts. Most of the existing cell design procedures operate on a binary part-machine incidence matrix to identify block diagonality. Important factors such as part operation sequence and demand volume have not been commonly considered in past research. In this paper, a sequence-based materials flow procedure is developed to solve the cell formation problem. The new cell formation procedure is designed to consider operation sequences in accurately determining the costs of inter-cell movement, as well as forward and backward intra-cell movements. Extensive comparisons of the new cell formation procedure with the relevant existing procedures in the literature demonstrate the effectiveness of the new procedure.     

Capability-based distributed layout approach for virtual manufacturing cells

It is shown in the literature that in highly volatile manufacturing environments functional job shops and classical cellular manufacturing systems do not perform well. Classical cellular manufacturing systems are very sensitive to changing production requirements due to their limited flexibility. In order to adapt cellular manufacturing systems to volatile manufacturing environments, the virtual cellular manufacturing concept was proposed in the 1980s by the National Bureau of Standards in USA. This concept is similar to group technology where job families are processed in manufacturing cells. The main difference between a virtual cell and the classic cell is in the dynamic nature of the virtual manufacturing cell; whereas the physical location and identity of classic cell is fixed, the virtual cell is not fixed and will vary with changing production requirements. The virtual manufacturing cell concept allows the flexible reconfiguration of shop floors in response to changing requirements. In the literature, the formation and scheduling process of virtual cells are clearly explained and researched in detail. However, the layout issue is not addressed entirely. Virtual cells are generally formed over functionally divided job shops. Forming virtual cells over a functional layout may adversely affect the performance of a virtual cellular manufacturing system. There is a need to search for different layout strategies in order to enhance the performance. The distributed layout approach may be a better alternative for virtual cellular manufacturing applications. In this research paper, a novel capability-based approach is proposed for the design of distributed layouts. A simulated annealing based heuristic algorithm is developed from the distributed layout. The proposed approach is tested with a problem with real data. An example is also shown in order to give an idea about the superiority of a capability-based distributed layout over the functional layouts in forming virtual manufacturing cells.     

Configuration of cellular manufacturing systems using association rule induction

A cell-formation approach based on association rule induction is developed to find the effective configurations for cellular manufacturing systems. To gain the benefits of flexibility and efficiency, the manufacturing system is decomposed into several manageable subsystems by categorizing similar parts into part families and disparate machines into cells. It is advantageous to find the important associations among machines such that the occurrence of some machines in a machine cell will cause the occurrence of other machines in the same cell. Relationships among machines can be found from the process database by inducting association rules. By applying association rules to cell-formation problems, certain sets of machines (machine groups) that frequently process some parts together can be inducted. A data-mining technique referred to as association rule induction is used herein to find the association rules among machines from the process database. Seventeen data sets of various size and complexity were used to evaluate the effectiveness of the proposed cell-formation algorithm based on association rule induction. The performance of the proposed approach is compared with several existing techniques. From the computational results, the proposed approach shows its ability to find quality solutions.     

On the performance of hybrid multi-cell flexible manufacturing systems

Industrial experience has shown that it is virtually impossible to implement a large-scale flexible manufacturing system (FMS) without using the group technology manufacturing concept. However, grouping machines into product cells can limit the FMS flexibility. Thus when the production cells are not completely disjoint, problems under multi-cell flexible manufacturing systems (MCFMS) can be caused by changes in job mix and demand which lead to a workload imbalance both between cells and between machine centres within the same cell. The problems can be mitigated and shop performance improved by transferring workloads from a congested machine centre in one cell to an alternative, less congested machine centre in another cell. Such inter-cell workload transfer results in a hybrid MCFMS which is a cross between a parts similarity-based MCFMS and a process similarity-based MCFMS. Results of a simulation study carried out by the author show that inter-cell workload transfer is very effective in improving shop performance. This paper briefly describes the simulation study and discusses the implications of its results for the design and operation of FMSs. The operational viability, and economic feasibility of hybrid MCFMSs are also discussed in the paper.     

A simulation analysis of factors influencing the flexibility of cellular manufacturing

The performance of cellular manufacturing (CM) systems in a variable demand and flexible workforce environment has been examined using simulation modelling. Discrepancies between academicians and practitioners’ findings with respect to flexibility and uneven machine utilization in CM systems are discussed. The views of two parties were incorporated in simulation models to rectify the existing discrepancies. While the results of this study confirm the previous findings of academicians regarding the deterioration of the performance of CM in a variable product mix situation, it appears that those results may be significantly influenced by considering a flexible workforce. The simulation results show that the practice of using flexible crossed-trained operators can improve the flexibility of CM in dealing with an unstable demand and can reduce load imbalance inherent in machine dedication in manufacturing cells.     

Improving the performances of part dispatching based on multiple process plans using graph theory

An intrinsic characteristic for manufacturing a part is the existence of diverse processing routes. In this paper, we deal with the improvement of part dispatching performance based on the availability of multiple process plans of a machined part. Procedures to represent multiple process plans with a graphic representation are developed so as to facilitate the utilization of process plans. We propose a simulation model to test the impacts of multiple process plans on the performances of real time scheduling. The study shows that by applying the simulation model to multiple processes in the manufacturing of machined parts, the flexibility of the manufacturing system can be increased; the total production flow time can be reduced; and the efficient utilization of production resources is improved.     

A PSO-based approach to cell formation problems with alternative process routings

Group technology (GT) has been extensively applied to cellular manufacturing system (CMS) design for decades due to many benefits such as decreased number of part movements among cells and increased machine utilisation in cells. This paper considers cell formation problems with alternative process routings and proposes a discrete particle swarm optimisation (PSO) approach to minimise the number of exceptional parts outside machine cells. The approach contains two main steps: machine partition and part-routing assignment. Through inheritance and random search, the proposed algorithm can effectively partition machines into different cells with consideration of multiple part process routings. The computational results are compared with those obtained by using simulated annealing (SA)-based and tabu search (TS)-based algorithms. Experimental results demonstrate that the proposed algorithm can find equal or fewer exceptional elements than existing algorithms for most of the test problems selected from the literature. Moreover, the proposed algorithm is further tailed to incorporate various production factors in order to extend its applicability. Four sample cases are tested and the results suggest that the algorithm is capable of solving more practical cell formation problems.     

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.