Layout design in fractal organizations

Today's complex, unpredictable and unstable marketplace requires flexible manufacturing systems capable of cost-effective high variety–low volume production in frequently changing product demand and mix. In fractal organizations, system flexibility and responsiveness are achieved by allocating all manufacturing resources into multifunctional cells that are capable of processing a wide variety of products. In this paper, various fractal cell configuration methods for different system design objectives and constraints are proposed. These parameters determine the level of interaction between the cells, the distribution of different product types among the cells and the similarity of cell capabilities. A tabu-search-based method is proposed to optimize the product distribution to the cells and the arrangement of machines and cells on the shop floor. This optimization is performed for different fractal cell configuration methods and cell quantities. The quality of the resulting shop floor layouts is measured in terms of resource requirements and material movements. The results indicate that in fractal layouts, a trade-off is required between machine quantities and material travelling distance. It was generally possible to reduce travelling distances by increasing the degree of optimization on machine layout and product distribution for a specific product demand and mix.     

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.     

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.     

虚拟车间动态重构模型的研究

阐述了敏捷制造模式下，车间的功能除了具有常规的生产管理和控制功能外，还具有实现单元动态重构的功能和通过网络对外合作的功能。在分析了虚拟车间动态重构的系统的关键技术的基础上，提出了基于多代理机的虚拟车间动态重构模型，讨论了Ａｇｅｎｔ之间的协商机制。     

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.     

Designing group layout of unequal-area facilities in a dynamic cellular manufacturing system with variability in number and shape of cells

This paper presents a new mixed-integer non-linear programming model for designing the group layout (GL) of unequal-area facilities in a cellular manufacturing system (CMS) under a dynamic environment. There are some features that make the presented model different from the previous studies. These include: (1) manufacturing cells with variable numbers and shapes, (2) machine depot keeping idle machines, (3) machines of unequal-areas, (4) manufacturing cells with rectangle regular shapes established on the continuous shop floor and (5) integration of cell formation and GL as interrelated decisions involved in the design of a CMS in a dynamic environment. The objective function is to minimises the total costs of intra- and inter-cell material handling, machine overhead, machine relocation, machine processing, purchasing machines and forming cells. Since the problem is NP-hard, an efficient simulated annealing (SA) algorithm is developed to solve the presented model. The performance of this model is illustrated by two numerical examples. It is then tested using several test problems with different sizes and settings to verify the computational efficiency of the developed algorithm in comparison to the classical genetic algorithm (GA). The obtained results show that the quality of the solutions obtained by SA is better than GA.     

A comparison of focused cellular manufacturing to cellular manufacturing and job shop

The purpose of this study is to compare a focused cellular manufacturing environment with traditional cellular manufacturing, and job shop environments. We define focused cellular manufacturing as a configuration scheme that groups components by end-items and forms cells of machines to fabricate and assemble end-items. In addition, this research includes three levels of batch sizes and two levels of set-up times in its performance criteria which few researchers in this area have done. The results indicate that the focused cellular manufacturing scheme has a batching advantage. This advantage dominated the balanced machine utilization benefit of the job shop configuration scheme and out weighed the set-up time reduction advantage of the cellular manufacturing scheme for average end-item completion times and average work-in-process inventory levels. The cellular manufacturing and job shop schemes overcame the batch size advantage only when batch sizes were small or set-up times were large.     

Reconfiguration of a job shop to respond to product mix changes based on a virtual production system concept

Driven by intense global competition, governments, industry and academia in recent years have invested a considerable amount of resources to make production systems more efficient. However, in most cases, once a production system type is adopted for a shop, the operation mode of the shop remains the same over time. In today's environment where changes in product mix, production batch sizes and technology are common, what is required is a procedure that allows a shop to adapt or reconfigure its mode of operation based on the production instance at hand to achieve maximum efficiency. In the present paper, the application of a virtual production system is proposed to provide such flexibility and adaptability in production. A virtual production system has the capability of switching from one operation mode to another without actual physical reconfiguration of the shop and does this to maximize its operational efficiency. Such a virtual production system is examined. Experimental results for a set of example problems show that virtual production systems are superior to traditional production systems.     

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.     

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.     

Extended structured adaptive supervisory control model of shop floor controls for an e-Manufacturing system

The high cost and long development cycle of shop floor control systems and the lack of true system integration capabilities are identified as one of the most challenging obstacles in deploying e-Manufacturing systems. Overcoming these obstacles is essential for manufacturers to execute a make-to-order business model in order to stay competitive and remain profitable in the future. We propose a formal method to generate the desired control trajectories and provide true integration mechanisms for shop floor control systems. Using the proposed architecture can result in the development of an e-Manufacturing system capable of achieving a substantial reduction of both the high cost and long development cycle currently required to engineer shop floor control systems. By taking advantage of both the linear growth of the complexity function in a structured adaptive supervisory control model and the information-centric characteristics of a virtual production line in a manufacturing execution system, a formal model, which we call an extended structured adaptive supervisory control, for a discrete manufacturing system is introduced. A shop floor control system based on the extended structured adaptive supervisory control model is built for an industrial testbed system. The shop floor control system is fully tested and evaluated.     

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.     

A methodology for designing flexible cellular manufacturing systems

Cell formation in cellular manufacturing deals with the identification of machines that can be grouped to create manufacturing cells and the identification of part families to be processed within each cell. Dynamic and random variations in part demands can negatively impact cell performance by creating unstable machine utilizations. The purpose of this paper is to introduce and illustrate an interactive cell formation method that can be used to design 'flexible' cells. Flexibility in this context refers to routing flexibility (i.e., the ability for the cellular system to process parts within multiple cells) and demand flexibility (i.e., the ability of the cell system to respond quickly to changes in part demand and part mix). Through an experimental analysis using multiple data sets, we also validate the procedure and provide guidelines for parameter settings depending upon the type of flexibility of interest to the user. Finally, trade-offs and interdependences between alternative types of flexibility in the context of cellular systems are illustrated.     

A methodology for cellular manufacturing design

A two-phase methodology is presented as an aid to organizing job shop production in a cellular manufacturing system. The first phase (selection/assignment phase) selects the machines to be kept on the shop floor and assigns parts to the machines retained. The second phase (partition/reassignment phase) establishes a partition of the set of parts and corresponding cells of machines and reassigns some of the operations with a view to eliminating some intercell material movements. This phase is repeated until a partition meeting the operator's requirements is obtained. The results obtained with this method on several examples found in the literature are consistently equivalent to or even better than those hitherto proposed, in terms of intercell moves.     

Comparing functional and cellular layouts: A simulation study based on standardization

In the last decade, over two dozen simulation studies have focused on comparing cellular and functional layouts. The results reported by these studies vary widely, however. This remains true even when the key performance measure is flow time. These variations reflect the disparate manufacturing and operating environments, as well as differences in parts demands, set-up economies, overall loads and other factors. This work attempts to reduce the sources of variation due to different operating assumptions while retaining the variability associated with differences in part mix and demand characteristics. Instead of focusing on a single data source, this study uses a test bed of six problems extracted from the literature and ensures they share the same operational rules. The simulation results show that conversion to CMS can reduce flow times (relative to the job shop configuration) consistently across all data sets, provided the same operating rules and ranges for key parameter are used. We investigate the reduction in flow time while controlling for the key factors of set-up reduction, overall load on the system and batch size. We also assess the benefits of using transfer batches as a further factor in reducing flow time. Our overall conclusion is that set-up reductions in cells can overcome pooling losses, even under the conservative assumptions where batch size remain unchanged and the material transport times in the job shop are assumed to be negligible.     

Cellular manufacturing system design considering machines reliability and parts alternative process routings

Cell formation is an important problem in the design of cellular manufacturing systems (CMS). Most cell formation methods appeared in the literature assume that each part has one process plan, and all machines are 100% reliable with unlimited capacity. However, this is not realistic in manufacturing systems. Considering machines reliability in addition to machines capacity and machine duplicates during the part route selection process help to obtain better machine grouping and minimum total cost for CMS. Considering these factors in addition to operations sequence and production volumes makes the problem more complex but more realistic. Most of the methods appeared in the literature to solve such problems use mathematical programming procedures that take large amount of computational efforts. Procedures using similarity coefficient method are more flexible in incorporating various important production data and lend easily to computer applications. A new similarity coefficient equation that incorporates all these production factors is developed. Also, a procedure that captures the similarity between machine groups and minimises the total CMS cost is developed. The procedure utilises functional cells to eliminate intercellular moves and achieve ‘one-piece flow’ practise. The methodology is compared with other methods in the literature and found to be more effective.     

Enhancing smart shop floor management with ubiquitous augmented reality

This paper describes a framework for implementing Smart manufacturing Shop floor systems based on the Ubiquitous Augmented Reality technology (SSUAR). The proposed system makes use of data sharing between shop floor resources and a sensor network in order to optimise the production schedules for carrying out projects. The optimisation is performed in real-time and the production scheduling responds to new projects as well as the changing status of resources, such as machines and workers. Ubiquitous augmented reality interface has been developed and utilised as a user interface for the shop floor workers to receive information, instructions and guidance from the experts and manufacturing systems, and to update the systems on task parameters, such as estimated completion times, progress and machine status. A review of related work, methodology and implementation of the proposed system, and a case study are presented in this paper. Using this architecture, real-time scheduling of tasks in the smart shop floor can be achieved. The case study demonstrated the ability of SSUAR to integrate task scheduling with two-way communication between the system and the users.     

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.     

Improved design of CMS by considering operators decision-making styles

Cell formation is one of the oldest problems in cellular manufacturing systems (CMS) including assigning parts, machines and operators to cells. Cell manufacturing contains a number of cells where each cell is responsible for processing the family of similar parts. Another important aspect of cell formation is worker assignment to cells. Since operators work together in long periods, it is suggested to consider operators’ personal characteristics to increase their satisfaction and the productivity of system. This paper considers decision-making styles of operators (as an index of operator’s personal characteristics) and presents a new mathematical programming model for clustering parts, machines and workers simultaneously. The model includes two objectives; (1) minimization of intracellular movements and cell establishment costs, (2) minimization of decision-making style inconsistency among operators in each cell. The paper applies ε-constraint method for solving the problem and gathering non-dominated solutions such as Pareto optimal solutions. Furthermore, this paper uses common weighted multicriteria decision analysis (MCDA)-data envelopment analysis method to choose the best solution from the candidate Pareto optimal solutions that have been achieved by solving the mathematical model. A real case study is investigated to show the capability of the proposed model to design CMS in the assembly unit. The proposed design assists decision-makers to develop cellular systems with more operators’ satisfaction and productivity.     

Implementation of a demand-pull system in a job shop environment

This paper describes an implementation of JIT concepts in a medium-sized make-to-order manufacturing company. We develop a hybrid production control system for the company based on separating jobs with high production volumes following a standard routeing from relatively low-volume jobs with more complex routeings. The machines processing the high-volume standard-routeing jobs are treated as a virtual flow shop and controlled by a hybrid push/pull system, while the remainder of the floor is managed as a job shop. Initial tests have shown that this system can significantly improve throughput and simplify the production scheduling task. We believe that the system can be applied to a wide range of industries with similar characteristics. We also describe the testing of the system and the circumstances under which its implementation was discontinued, which indicate some of the difficulties faced by small manufacturers in implementing such systems.