Shannon R. Bowling

A MARKOVIAN APPROACH TO DETERMINING OPTIMUM PROCESS TARGET LEVELS FOR A MULTI-STAGE SERIAL PRODUCTION SYSTEM

Consider a production system where products are produced continuously and screened for conformance with their specification limits. When product performance falls below a lower specification limit or above an upper limit, a decision is made to rework or scrap the product. The majority of the process target models in the literature deal with a single-stage production system. In the real-world industrial settings, however, products are often processed through multi-stage production systems. If the probabilities associated with its recurrent, transient and absorbing states are known, we can better understand the nature of a production system and thus better capture the optimum target for a process. This paper first discusses the roles of a Markovian approach and then develops the general form of a Markovian model for optimum process target levels within the framework of a multi-stage serial production system. Numerical examples and sensitivity analysis are performed. 2003 Elsevier B.V. All rights reserved.

Tables of a Truncated Standard Normal Distribution: A Doubly Truncated Case

ABSTRACT As an extension to the singly truncated case, this article further examines a doubly truncated normal distribution. In this article, we consider both symmetric and asymmetric cases with two truncation points on the left and the right, and develop the tables of a truncated mean, a truncated variance, and a cumulative probability.

The Added Usefulness of Process Measures Over Performance Measures in Interface Design

Various studies concerning the application of usability evaluation methods have shown the usefulness of these testing methods. The objective of this study was to evaluate the added advantage of collecting process measures (data used to learn how and why an error occurred) over performance measures (data used to determine what went wrong) in interface design. The most salient finding of this study is that when used in the design/redesign process, performance data improved effectiveness (i.e., reduced the number of errors), whereas process measures data improved efficiency by reducing the time needed to complete tasks. The results from this study, as with any other usability study, should be of particular interest to the software industry, which is constantly trying to reduce development time and resources while improving user-friendly interface design.

An IntelliDrive application for reducing traffic congestions using agent-based approach

Traffic congestion on highways has increased dramatically in the last two decades. As more and more cars are put on the road each year, traffic congestion is becoming more complex and unpredictable than ever before as people try to avoid it by changing their schedules and routes. IntelliDriveSM is a suite of technologies and applications that use wireless communications to provide connectivity that can deliver transformational safety, mobility, and environmental improvements in surface transportation [11]. This paper will present an IntelliDrive agent-based model of traffic congestion and examine the impact of one vehicle on a system limited to a single traffic lane. The cars interaction is based on IntelliDrive vehicle-to-infrastructure communications. The mean speed of the cars is analyzed and the evolution of traffic congestion is observed with the passage of time. Can a single agent influence the dynamics of traffic flow on a complex network? Furthermore, can an “Intelligent-car” annul the oscillatory behavior (stop and go) resulting from the acceleration and deceleration of the other vehicles? Theoretical results are presented and a solution to reduce traffic congestions and also minimize accidents is also proposed, based on implementing one IntelliDrive-equipped vehicle, among a certain number of cars in a single-lane circuit. The approach that was finally selected and several other schemes that were considered are described.

Sensitivity analysis framework for large-scale system-of-systems applications

Sensitivity analysis (SA) is studying the impact input changes (nature and magnitude) have on outputs. The objective of this paper is to present a methodology to perform sensitivity analysis on a system dynamics simulation model that was developed in support of the Secure Border Initiative (SBI). Specifically the analysis will investigate Section 287(g) of The Illegal Immigration Reform and Immigrant Responsibility Act (1996). Due to the fact that the systems dynamics model used is a deterministic model, there was a need to induce variability using random sampling. The variability was propagated through the outputs and allowed the researchers to identify not only point estimates of what increases are required to bring the 287(g) policy to baseline values, but also calculate confidence bands. Implementing the 287(g) policy with no other system adjustments has a detrimental impact on performance in terms of fugitives and non-criminal removals.

Gender change in certain species - an agent-based modeling study

Biologists have found that certain creatures like frogs, orchids, and shrimp change their gender. Some research is proposing that species somehow know there is a gender imbalance and adjust the gender ratio accordingly. The mechanism in which the species change gender is unknown. Some scientists are suggesting that hormones are released which causes one type of reproductive organs to disappear and another type to appear. For organisms which display this phenomenon, apparently there are chemical triggers that respond to the number of members in a population. This will activate the gene(s) that will allow for the disintegration of one set of reproductive organs and the development of the other. The purpose of this paper is not to study how species technically change gender, but to explore how each individual in the population know the gender ratio and who decides who will change gender and who will not. This paper will build an agent-based model, using Netlogo©, to test the following hypothesis, “each individual in the collective does not have to know the gender ratio of the entire population in order to make decisions that will positively impact the collective.” Results show that individuals change their gender in accordance with their own needs. Regardless of the initial gender ratio and despite the fact that the individuals do not possess knowledge about the whole population, there will always be almost-equal number of males and females after a certain time.

Gender change in certain species: an agent-based modeling study

Biologists have found that certain creatures like frogs, orchids, and shrimp change their gender. Some research is proposing that species somehow know there is a gender imbalance and adjust the gender ratio accordingly. The mechanism in which the species change gender is unknown. Some scientists are suggesting that hormones are released which causes one type of reproductive organs to disappear and another type to appear. For organisms which display this phenomenon, apparently there are chemical triggers that respond to the number of members in a population. This will activate the gene(s) that will allow for the disintegration of one set of reproductive organs and the development of the other. The purpose of this paper is not to study how species technically change gender, but to explore how each individual in the population know the gender ratio and who decides who will change gender and who will not. This paper will build an agent-based model, using Netlogo©, to test the following hypothesis, “each individual in the collective does not have to know the gender ratio of the entire population in order to make decisions that will positively impact the collective.” Results show that individuals change their gender in accordance with their own needs. Regardless of the initial gender ratio and despite the fact that the individuals do not possess knowledge about the whole population, there will always be almost-equal number of males and females after a certain time.

Initiative mapping methodology for system-of- systems applications

In this paper, we propose developing a generic approach to handle different system-of-systems applications, including (1) a framework to map or classify initiatives based on their contribution to different capabilities and (2) introduce an optimisation-based methodology that selects combinations of initiatives that will maximise the contribution to the capabilities, and ultimately maximises the yield or benefit of the entire system. The approach will focus on using subject matter experts to obtain rankings of capabilities. The optimisation of initiative selection will utilise binary integer programming and desirability mapping to ascertain the overall effectiveness of the combined initiatives. After conducting multiple simulation runs at various budget constraints, the ‘heavy hitters’ are dominant and the ‘big losers’ time and time again are not chosen. The resulting selection is a subset of the total number of initiatives, and can be subsequently evaluated in greater detail than trying to evaluate the entire selection and all of the possible combinations.

EFFECT OF ERROR SEVERITY ON HUMAN TRUST IN HYBRID SYSTEMS

Computerized systems are often employed to support control and decision-making tasks in complex and dynamic environments. Trust or mistrust in these systems has been demonstrated to significantly affect operator performance. Consequently, errors of trust or mistrust may compromise system performance, with potentially disastrous results. Accordingly, trust should be considered in both the design and operation of human/machine systems. In order to do so, metrics and methods for the measurement of trust must be developed along with models of human performance that incorporate trust and related system variables. Current approaches to trust measurement rely solely on subjective metrics, which are based on different theoretical concepts of trust between humans that may not necessarily be as relevant to machines. Although researchers have been able to establish a relationship between trust and behavior, these models lack an analytic foundation. Therefore, the purpose of this research is to develop a quantitative approach that relates trust to changes in system parameters and severity of errors.

TASK ANALYSIS OF GENERAL AVIATION INSPECTION ACTIVITIES: METHODOLOGY AND FINDINGS

General Aviation (GA) constitutes a significant, but often ignored, portion of the aviation system. It is crucial that GA be reliable if we are to ensure the safety of the overall air transportation system. The inspection/maintenance system, which is responsible for identifying and fixing defects, is a key component of this system. For this reason, it is critical to have a sound inspection and maintenance system. In response to this need, this paper reports task analyses of aircraft inspection operations at geographically dispersed GA facilities operated under the Federal Aviation Regulation (FAR) Part 91, 135, and 145. Recommendations forthcoming from this analysis will be used to devise intervention strategies to improve inspection performance. As a first, this paper outlines the methodology used and the preliminary results obtained.