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The literature is replete with models that examine various aspects of cellular manufacturing (CM), such as optimisation of cell layouts. However, many firms may realise zero to marginal returns from CM. Given this uncertainty, the manager should first determine the value of CM to the firm before deploying it. Although traditional valuation models employing discounted cash flow analysis allow for uncertainty, they treat future investments as fixed when computing the investment’s present value. The real options (RO) logic of valuation allows the manager to exercise the option to invest in or abandon a project based on expected outcomes. Future investments are thus options. This paper presents an RO model for CM migration that addresses whether a firm should migrate to CM; and it prescribes thesequenceof cell deployment, which has not been addressed in the literature. Our model is also much more transparent and accessible to practitioners, with an accompanying software tool for prospective users. Finally, we use simulation extensively to discover the drivers of the optimal cell deployment sequence. Our results show that there is a complex interplay between net present value, speed of cellularisation, inter-cell learning and volatility in terms of their influence on the cell sequence. [ABSTRACT FROM AUTHOR]

This paper presents the results of a simulation-based performance comparison between dynamic cellular (DC) manufacturing systems and two other well-known systems, namely classical cells (CC) and job shop systems (JS). The performance comparison is made at different levels of turbulence. The experiment contains 13 independent variables, most of them related to demand turbulence, and 17 dependant variables related to performance measure. A stochastic simulation model developed on Microsoft Visual FoxPro 5.0 was used in combination with LINDO (a linear/integer programming software) to obtain the initial results. In view of the large number of variables and the time required to run each experiment, a Taguchi plan was used to optimize the model. The results obtained from the analysis of variance indicate that dynamic cellular manufacturing systems are generally more efficient than classical cellular systems or job shop systems, especially with respect to the average and maximum throughput time, mean and maximum work-in-process, mean and maximum tardiness, and the total marginal cost for a given horizon. [ABSTRACT FROM AUTHOR]

We present a two-phase approach to design and analysis of manufacturing cells based on simulated experimentation and response surface methodology using a general manufacturing-cell simulation model. The first phase involves factor-screening simulation experiments to identity design and operational factors that have a significant effect on cell performance as measured by a comprehensive annual cost function. In the second phase of experimentation, we construct simulation (response surface) metamodels to describe the relationship between the significant cell design and operational factors ( the controllable input parameters) and the resulting simulation-based estimate of expected annual cell cost (the output response). We use canonical and ridge analyses of the estimated response surface to estimate the levels of the quantitative input factors that minimize the cell's expected annual cost. We apply this methodology to an assembly cell for printed circuit hoards. Compared to be current cell operating policy. the simulation metamodel-based estimate of the optimum operating policy is predicted to yield average annual savings of approximately $425 000, which is a 20% reduction in annual cost. In a companion paper, we detail the structure and operation of the manufacturing-cell simulation model. [ABSTRACT FROM AUTHOR]

We present a general manufacturing-cell simulation model for evaluating the effects of world-class manufacturing practices on expected cell performance. The modular structure of the simulation provides the flexibility to analyze a wide variety of manufacturing cells. We formulate a comprehensive annualized cost function for evaluation and comparison of alternative cell configurations. A case study involving assembly of printed circuit hoards illustrates the potential benefits of using this tool for cell design and analysis. The simulation model is intended for use in a two-phase approach to cell design that is based on simulated experimentation and response surface analysis as detailed in a companion paper. [ABSTRACT FROM AUTHOR]

This paper investigates possible implementations of the autonomous agents concept in flexible manufacturing control. The implementation issues and the effectiveness of different control architectures and algorithms are analyzed by means of a simulation model of a flexible job shop. Extensive experimental results are reported, allowing the evaluation of the trade-off between the degree of autonomy and system performance. [ABSTRACT FROM AUTHOR]

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 remains unchanged and the material transport times in the job shop are assumed to be negligible. [ABSTRACT FROM AUTHOR]

One of the underlying assumptions in cellular manufacturing is that product mix is relatively stable over time. In this paper, a procedure for the sensitivity analysis of the performance of a cellular manufacturing system with respect to changes in the product mix is presented and a flexibility range representing the capability of the system in dealing with these changes is determined using simulation modelling. The simulation results in this study show that as the changes in the product mix increase the superiority of the performance of the cellular manufacturing system to the corresponding job shop system diminishes. [ABSTRACT FROM AUTHOR]

An important element in the design and management of cellular manufacturing systems is the ability to determine capabilities. This paper describes a generic methodology of Capability Analysis (CA) which can be used for the integrated assessment of various capability factors. The main aspect of CA is the ability to compare different factors alongside one-another. This is done by determining priority confidence scores (PCS values) which are capability scores (measures of performance) represented as proportions of required capability scores adjusted to take into account improvement potential, factor importance and financial considerations. CA is used to form a recovery schedule of targets for improvement ranked in order of priority and is produced by ranking the PCS values for each capability level (cell, product, part, workstation and operation). Targets at a higher level can be broken down into more detailed targets at a lower level using the concept of transparency. The workings of CA are demonstrated using an example. [ABSTRACT FROM AUTHOR]

Cellular manufacturing systems (CMSs) are used when both production volume and product variety are at medium level. The fluctuations of volume and mix can reduce drastically the performance of classical CMSs. Therefore, several configurations have been proposed in literature as virtual manufacturing cells, fractal cells and remainder cells. This article investigates the cell-loading approaches in a manufacturing system composed of dedicated cells and a remainder cell. The remainder cell consists of machines that are able to manufacture all part families. The loading decision concerns the allocation of the parts to the remainder cell, instead of the dedicated cell. A simulation environment based on Rockwell Arena® has been developed to test the proposed approaches. The performance measures are evaluated in a very dynamic environment characterised by volume oscillations, mix fluctuations and machine failures. A classical CMS is used as a benchmark for the performance measures analysed. The simulation results show that the proposed policies lead to a better performance when market fluctuations occur. [ABSTRACT FROM AUTHOR]