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We show that although overlapping batch quantiles (OBQ) is asymptotically very similar to overlapping batch means, its performance for finite sample sizes is not. We show that the bias, the variance and the mean-squared-error of OBQ are not smooth functions of the batch size but rather cyclic. The cyclic behavior of OBQ depends on the marginal distribution,(More)
Overlapping batch statistics estimate the variance of point estimators using overlapping batches (Schmeiser, Avramidis and Hashem 1990). In this paper we study sufficient conditions for the mean-squared-error (mse) consistency of overlapping batch variances (OBV). We show that both the bias and the variance of OBV go to zero as the sample size increases(More)
The objective of this panel session is to describe how and when manufacturing simulation practitioners should add to the value of projects by interfacing simulation analyses with other analyses such as optimization, layout/material flow, scheduling, robotic, and queuing. The panelists will discuss how each analytical tool adds value to the discrete-event(More)
In simulating material flow systems, due to the large number of entities and inventory related parameters involved, computer memory utilization, the simulation run speed and managing input and output are the major issues. In this paper, we introduce an innovative approach to resolve these issues. We devise a simulation model that utilizes variable arrays to(More)
In Section 3 we talk about our solution. In sections 4, 5 and 6 we talk about specific types of human errors in detail. In Section 7 we discuss our conclusions and recommendations. This paper focuses on the steps taken to minimize human error in simulation modeling in General Motors. While errors are costly and undesirable in any field, they are especially(More)
The objective of this panel session is to describe how and when manufacturing simulation practitioners should add to the value of projects by interfacing simulation analyses with other analyses such as optimization, layout/material flow, scheduling, robotic, and queuing. The panelists will discuss how each analytical tool adds value to the discrete-event(More)
A panel of simulation managers from manufacturing companies discuss the following six topics: (1) How are managers responsible for manufacturing best persuaded to try simulation? (2) How can capturing the benefits of simulation best be made a regular process? What are the roles of model databases and reuse, input databases, standardization, change(More)
This paper focuses on the steps taken to minimize human error in simulation modeling in General Motors. While errors are costly and undesirable in any field, they are especially harmful in simulation which has been struggling to gain acceptance in the business world for a long time. The solution discussed in this paper can be summarized as "enter the data(More)
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