A simulation analysis of the impact of family configuration on virtual cellular manufacturing

Past research has shown that it is possible to simultaneously achieve the setup efficiencies of traditional cellular manufacturing systems and the routeing flexibility of a job shop by viewing cells not as permanent, physical structures, but as temporary, 'virtual' entities. This research demonstrates that the advantages of virtual manufacturing cells can be obtained over a range of part family configurations. In particular, virtual cellular manufacturing is robust to changes in the number and size of families being processed. Further, the research shows that the benefits can be obtained under setup conditions impartial to a family-oriented part environment.     

Evaluation of scheduling strategies for a dynamic job shop in a tool-shared,flexible manufacturing environment

A two-phase approach is used to examine the impact of job scheduling rules and tool selection policies for a dynamic job shop system in a tool-shared, flexible manufacturing environment. The first phase develops a generalized simulation model and analyses 'simple' job scheduling rules and tool selection policies under various operating scenarios. The results from this investigation are then used to develop and analyse various bi-criteria rules in the second phase of this study. The results show that the scheduling rules have the most significant impact on system performance, particularly at high shop load levels. Tool selection policies affect some of the performance measures, most notably, proportion of tardy jobs, to a lesser degree. Higher machine utilizations can be obtained at higher tool duplication levels but at the expense of increased tooling costs and lower tool utilization. The results also show that using different processing time distributions may have a significant impact on shop performance.     

A low-cost approach to computer-integrated manufacturing in a small chemical unit

Many firms are considering CIM as a means of reducing costs and increasing quality. Sometimes, however, a major problem in this kind of project seems to be the high investments involved. In this paper a methodology for developing a low-cost CIM application is presented. The proposed methodology was successfully experimented in a small chemical unit of one of the leading producers of nylon in the world. The paper reports on the design and implementation of the computer-integrated manufacturing and the associated costs and benefits.     

Achieving Lean Objectives through RFID: A Simulation‐Based Assessment*

Lean concepts in manufacturing have focused on elimination of wastes within the business processes. This study investigates whether addition of radio frequency identification (RFID) technologies in the manufacturing process can complement Lean manufacturing. Specifically, will more accurate information from RFID‐based solutions help achieve the goals of Lean initiatives in manufacturing plant performance and, if yes, in what specific ways? The analysis is based on a comparison of the following three automatic identification technologies: existing (one‐dimensional) 1D barcode, 2D barcode, and the use of RFID in a real job‐shop environment where items are manufactured for meeting actual demand and also future forecast demand. We analyze the effect of information visibility in these settings by examining the various types of wastes that are typically addressed in Lean initiatives. The results of a discrete‐event simulation suggest that employing RFID in Lean manufacturing initiatives can reduce some wastes but not necessarily all types of waste. We observe an increase in overproduction waste in our setting, although other wastes are reduced with improved information visibility. Overall, our results indicate that manufacturing organizations should explore information visibility through RFID to enhance their Lean initiatives.     

Using expected values to simplify decision making under uncertainty

A simulation study examines the impact of a simplification strategy that replaces distributional attribute evaluations with their expected values and uses those expectations in an additive value model. Several alternate simplified forms and approximation approaches are investigated, with results showing that in general the simplified models are able to provide acceptable performance that is fairly robust to a variety of internal and external environmental changes, including changes to the distributional forms of the attribute evaluations, errors in the assessment of the expected values, and problem size. Certain of the simplified models are shown to be highly sensitive to the form of the underlying preference functions, and in particular to extreme non-linearity in these preferences.     

RFID as an Enabler of Improved Manufacturing Performance*

The use of radio frequency identification (RFID) versus bar coding has been debated with little quantitative research about how to best use RFID's capabilities and when RFID is more advantageous. This article responds to that need by qualitatively and quantitatively analyzing how RFID facilitates increased traceability and control in manufacturing, which in turn enables the use of more lot splitting and smaller lot sizes. We develop insights about operating policies (RFID vs. bar‐code tracking mechanisms, extent of lot splitting, and dispatching rules) and an operating condition (setup to processing time ratio) that affect the mean flow time and proportion of jobs tardy in a job shop. A simulation model is used to control factors in the experimental design and the output is evaluated using analysis of variance. The results show the following: (i) performance worsens when bar coding is used with extensive lot splitting, (ii) process changes such as extensive lot splitting may be required to justify RFID use instead of bar coding, (iii) the earliest operation due date dispatching rule offers an attractive alternative to other rules studied in previous lot splitting research, and (iv) the performance improvements with RFID and increased lot splitting are larger when the setup to processing time ratio is smaller. In a broader context, we fill a research void by quantitatively showing how RFID can be used as an advanced manufacturing technology that enables more factory automation and better performance along several dimensions. The article concludes by summarizing the results and identifying ideas for future research.     

Simulating Properties of the Likelihood Ratio Test for a Unit Root in an Explosive Second-Order Autoregression

This paper provides a means of accurately simulating explosive autoregressive processes and uses this method to analyze the distribution of the likelihood ratio test statistic for an explosive second-order autoregressive process of a unit root. While the standard Dickey-Fuller distribution is known to apply in this case, simulations of statistics in the explosive region are beset by the magnitude of the numbers involved, which cause numerical inaccuracies. This has previously constituted a bar on supporting asymptotic results by means of simulation, and analyzing the finite sample properties of tests in the explosive region.     

A goodness of fit test for multilevel survival data

No satisfactory goodness of fit test is available for multilevel survival data which occur when survival data are clustered or hierarchical in nature. Hence the aim of this research is to develop a new goodness of fit test for multilevel survival data and to examine the properties of the newly developed test. Simulation studies were carried out to evaluate the type ? error and the power. The results showed that the type I error holds for every combination tested and that the test is powerful against the alternative hypothesis of nonproportional hazards for all combinations tested.     

Kumaraswamy Marshall-Olkin Exponential distribution

In this paper, a new generalization of the Kumaraswamy distribution namely, the Kumaraswamy Marshall-Olkin Exponential distribution (KwMOE) is introduced and studied. Various properties are explored. The structural analysis includes various aspects such as limiting behaviour, shape properties, moments, quantiles, mean deviation, Renyi entropy, order statistics and stochastic ordering. Some useful characterizations of the family are also obtained. The method of maximum likelihood is used to estimate the model parameters. Monte Carlo simulation study is being conducted. An application to a real data set is presented for illustrative purposes.     

A Simulation Study of Some Biasing Parameters for the Ridge Type Estimation of Poisson Regression

This article proposes several estimators for estimating the ridge parameter k based on Poisson ridge regression (RR) model. These estimators have been evaluated by means of Monte Carlo simulations. As performance criteria, we have calculated the mean squared error (MSE), the mean value, and the standard deviation of k. The first criterion is commonly used, while the other two have never been used when analyzing Poisson RR. However, these performance criteria are very informative because, if several estimators have an equal estimated MSE, then those with low average value and standard deviation of k should be preferred. Based on the simulated results, we may recommend some biasing parameters that may be useful for the practitioners in the field of health, social, and physical sciences.