A reliability centered maintenance decision system for a discrete part manufacturing facility

This thesis develops and validates the framework of a specialized maintenance decision support system for a discrete part manufacturing facility. Its construction utilizes a modular approach based on the fundamental philosophy of Reliability Centered Maintenance (RCM). The proposed architecture uniquely integrates System Decomposition, System Evaluation, Failure Analysis, Logic Tree Analysis, and Maintenance Planning modules. It presents an ideal solution to the unique maintenance inadequacies of modern discrete part manufacturing systems. Well established techniques are incorporated as building blocks of the system's modules. These include Failure Mode Effect and Criticality Analysis (FMECA), Logic Tree Analysis (LTA), Theory of Constraints (TOC), and an Expert System (ES). A Maintenance Information System (MIS) performs the system's support functions. Validation was performed by field testing of the system at a Miami based manufacturing facility. Such a maintenance support system potentially reduces downtime losses and contributes to higher product quality output. Ultimately improved profitability is the final outcome. ^

The National Institute of Justice guide for eyewitness identification evidence: Can it improve juror decision-making?

Mistaken eyewitness identifications of innocent lead to more false convictions in the United States than any other cause. In response to concerns about the reliability of eyewitness evidence, the National Institute of Justice (NIJ) in 1999 published a Guide for the gathering and preservation of eyewitness evidence by law enforcement personnel. Previous research has shown that eyewitness identifications are more accurate when obtained using procedures recommended in the NIJ Guide. This experiment assessed whether informing jurors about the Guide can improve their ability to discriminate between eyewitness identifications likely to be accurate and those likely to be inaccurate and, if so, how to most effectively provide jurors with such information. ^ Seven hundred sixteen U.S. citizens who reported for criminal jury duty participated. Half of the participant jurors read a summary of an armed robbery trial in which the police followed the NIJ Guide when obtaining an eyewitness identification of the defendant. The other half read about an identical case in which the police did not follow the Guide. Jurors received information about the Guide from a court-appointed expert witness, one of the attorneys in the case, the trial judge, the judge in combination with one of the attorneys, or from no one (in the control groups). Jurors then rendered a verdict in the case and answered questions about the evidence in the case. ^ When an expert witness or the judge (either alone or in combination with one of the attorneys) informed jurors about the Guide, the jurors voted to convict defendants likely to be guilty and to acquit defendants likely to be innocent more often than did uninformed jurors assigned to a control group. These data suggest that informing jurors about the NIJ Guide using expert testimony or instructions from a judge will improve the quality and accuracy of jurors' verdict decisions in cases involving eyewitness identification evidence. However, more research is needed to determine whether the judge will remain an effective source of information about the Guide in a longer, more detailed trial scenario and to learn more about the underlying psychological processes governing the effects observed in this experiment. ^

Essays in environmental economic valuation and decision making in the presence of an environmental disaster

The first essay developed a respondent model of Bayesian updating for a double-bound dichotomous choice (DB-DC) contingent valuation methodology. I demonstrated by way of data simulations that current DB-DC identifications of true willingness-to-pay (WTP) may often fail given this respondent Bayesian updating context. Further simulations demonstrated that a simple extension of current DB-DC identifications derived explicitly from the Bayesian updating behavioral model can correct for much of the WTP bias. Additional results provided caution to viewing respondents as acting strategically toward the second bid. Finally, an empirical application confirmed the simulation outcomes. The second essay applied a hedonic property value model to a unique water quality (WQ) dataset for a year-round, urban, and coastal housing market in South Florida, and found evidence that various WQ measures affect waterfront housing prices in this setting. However, the results indicated that this relationship is not consistent across any of the six particular WQ variables used, and is furthermore dependent upon the specific descriptive statistic employed to represent the WQ measure in the empirical analysis. These results continue to underscore the need to better understand both the WQ measure and its statistical form homebuyers use in making their purchase decision. The third essay addressed a limitation to existing hurricane evacuation modeling aspects by developing a dynamic model of hurricane evacuation behavior. A household's evacuation decision was framed as an optimal stopping problem where every potential evacuation time period prior to the actual hurricane landfall, the household's optimal choice is to either evacuate, or to wait one more time period for a revised hurricane forecast. A hypothetical two-period model of evacuation and a realistic multi-period model of evacuation that incorporates actual forecast and evacuation cost data for my designated Gulf of Mexico region were developed for the dynamic analysis. Results from the multi-period model were calibrated with existing evacuation timing data from a number of hurricanes. Given the calibrated dynamic framework, a number of policy questions that plausibly affect the timing of household evacuations were analyzed, and a deeper understanding of existing empirical outcomes in regard to the timing of the evacuation decision was achieved.

Integrated Ecological Modeling and Decision Analysis Within the Everglades Landscape

Planning for complex ecosystem restoration projects involves integrating ecological modeling with analysis of performance trade-offs among restoration alternatives. The authors used the Everglades Landscape Model and Multi-Criteria Decision Analysis to explore the effect of simulated ecosystem performance, risk preferences, and criteria weights on the ranking of three alternatives to restoring overland sheet flow in the Everglades. The ecological model outputs included both hydrologic and water quality criteria. Results were scored in the decision analysis framework, highlighting the trade-offs between hydrologic restoration and water quality constraints. Given equal weighting of performance measures, the alternative with more homogenous sheet flow was preferred over other alternatives, despite evidence of some localized eutrophication risk.

Effect of child care subsidies on price and quality of care for low -income families

This dissertation examines the effect of regulations, resource and referral agencies, and subsidies on price and quality of care in child care centers. This research is based on a carefully developed conceptual framework that incorporates the factors affecting the demand and supply of child care. The first step in developing this framework is sketching out the structural equations. The structural equations help us understand the underlying behavior of individuals and firms making a decision. The exogenous variables are vector of attributes relating to family characteristics, child characteristics, regulations, subsidy, community characteristics and prices of inputs. Based on the structural equations, reduced form equations are estimated to find the effect of each of the exogenous variables on each of the endogenous variables. Reduced form equations help us answer public policy questions. The sample for this study is from the 1990 Profile of Child Care Settings (PCCS) data in which 2,089 center based programs were interviewed.^ Child/Staff Ratio (Group Level). Results indicate that among subsidies, only the state subsidy per child in poverty has a significant effect on the child/staff ratio at the group level. Presence of resource and referral agencies also increase the child/staff ratio at the group level. Also when the maximum center group size regulation for 25-36 months becomes more stringent, the child/staff ratio at the group level decreases.^ Child/Staff Ratio (Center Level). When the regulations for the maximum child/staff ratio for age groups 13-24 months and 37-60 months become lax, the child/staff ratio for the center increases. As the regulation for maximum group size for infants becomes stringent, the child/staff ratio decreases. An interesting finding is that as the regulations for maximum group size for age groups 13-24 months and 25-36 months become stringent, the child/staff ratio for the center increases. Another significant finding is that when a center is located in a rural area the child/staff ratio is significantly lower.^ Center Weighted Average Hourly Fees. Maximum group size regulations for age groups 25-36 months and 37-60 months have a negative effect on center hourly fee. Maximum child staff regulations for age groups 13-24 months and 37-60 months have a negative effect on center hourly fee. Maximum child staff regulations for age groups 0-12 months and 25-36 months have a positive effect on center hourly fee. Findings also indicate that the center average hourly price is lower when there is a resource and referral agency present. Cost adjusted prekindergarten funds and JOBS child care subsidies have a negative effect on average hourly fee. Cost adjusted social services block grant and state subsidy per child in poverty have a positive effect on the average hourly price. A major finding of this dissertation is the interaction of subsidy and regulatory variables.^ Another major finding is that child/staff ratio at the group level is lower when there is an interaction between geographic location and nature of center sponsorship. ^

Information systems to support decision-making in *construction owner organizations: A data warehousing approach

Construction organizations typically deal with large volumes of project data containing valuable information. It is found that these organizations do not use these data effectively for planning and decision-making. There are two reasons. First, the information systems in construction organizations are designed to support day-to-day construction operations. The data stored in these systems are often non-validated, non-integrated and are available in a format that makes it difficult for decision makers to use in order to make timely decisions. Second, the organizational structure and the IT infrastructure are often not compatible with the information systems thereby resulting in higher operational costs and lower productivity. These two issues have been investigated in this research with the objective of developing systems that are structured for effective decision-making. ^ A framework was developed to guide storage and retrieval of validated and integrated data for timely decision-making and to enable construction organizations to redesign their organizational structure and IT infrastructure matched with information system capabilities. The research was focused on construction owner organizations that were continuously involved in multiple construction projects. Action research and Data warehousing techniques were used to develop the framework. ^ One hundred and sixty-three construction owner organizations were surveyed in order to assess their data needs, data management practices and extent of use of information systems in planning and decision-making. For in-depth analysis, Miami-Dade Transit (MDT) was selected which is in-charge of all transportation-related construction projects in the Miami-Dade county. A functional model and a prototype system were developed to test the framework. The results revealed significant improvements in data management and decision-support operations that were examined through various qualitative (ease in data access, data quality, response time, productivity improvement, etc.) and quantitative (time savings and operational cost savings) measures. The research results were first validated by MDT and then by a representative group of twenty construction owner organizations involved in various types of construction projects. ^

Essays in Environmental Economic Valuation and Decision Making in the Presence of an Environmental Disaster

The first essay developed a respondent model of Bayesian updating for a double-bound dichotomous choice (DB-DC) contingent valuation methodology. I demonstrated by way of data simulations that current DB-DC identifications of true willingness-to-pay (WTP) may often fail given this respondent Bayesian updating context. Further simulations demonstrated that a simple extension of current DB-DC identifications derived explicitly from the Bayesian updating behavioral model can correct for much of the WTP bias. Additional results provided caution to viewing respondents as acting strategically toward the second bid. Finally, an empirical application confirmed the simulation outcomes. The second essay applied a hedonic property value model to a unique water quality (WQ) dataset for a year-round, urban, and coastal housing market in South Florida, and found evidence that various WQ measures affect waterfront housing prices in this setting. However, the results indicated that this relationship is not consistent across any of the six particular WQ variables used, and is furthermore dependent upon the specific descriptive statistic employed to represent the WQ measure in the empirical analysis. These results continue to underscore the need to better understand both the WQ measure and its statistical form homebuyers use in making their purchase decision. The third essay addressed a limitation to existing hurricane evacuation modeling aspects by developing a dynamic model of hurricane evacuation behavior. A household’s evacuation decision was framed as an optimal stopping problem where every potential evacuation time period prior to the actual hurricane landfall, the household’s optimal choice is to either evacuate, or to wait one more time period for a revised hurricane forecast. A hypothetical two-period model of evacuation and a realistic multi-period model of evacuation that incorporates actual forecast and evacuation cost data for my designated Gulf of Mexico region were developed for the dynamic analysis. Results from the multi-period model were calibrated with existing evacuation timing data from a number of hurricanes. Given the calibrated dynamic framework, a number of policy questions that plausibly affect the timing of household evacuations were analyzed, and a deeper understanding of existing empirical outcomes in regard to the timing of the evacuation decision was achieved.

Information systems to support decision-making in construction owner organizations : a data warehousing approach

Construction organizations typically deal with large volumes of project data containing valuable information. It is found that these organizations do not use these data effectively for planning and decision-making. There are two reasons. First, the information systems in construction organizations are designed to support day-to-day construction operations. The data stored in these systems are often non-validated, nonintegrated and are available in a format that makes it difficult for decision makers to use in order to make timely decisions. Second, the organizational structure and the IT infrastructure are often not compatible with the information systems thereby resulting in higher operational costs and lower productivity. These two issues have been investigated in this research with the objective of developing systems that are structured for effective decision-making. A framework was developed to guide storage and retrieval of validated and integrated data for timely decision-making and to enable construction organizations to redesign their organizational structure and IT infrastructure matched with information system capabilities. The research was focused on construction owner organizations that were continuously involved in multiple construction projects. Action research and Data warehousing techniques were used to develop the framework. One hundred and sixty-three construction owner organizations were surveyed in order to assess their data needs, data management practices and extent of use of information systems in planning and decision-making. For in-depth analysis, Miami-Dade Transit (MDT) was selected which is in-charge of all transportation-related construction projects in the Miami-Dade county. A functional model and a prototype system were developed to test the framework. The results revealed significant improvements in data management and decision-support operations that were examined through various qualitative (ease in data access, data quality, response time, productivity improvement, etc.) and quantitative (time savings and operational cost savings) measures. The research results were first validated by MDT and then by a representative group of twenty construction owner organizations involved in various types of construction projects.

Effect of child care subsidies on price and quality of care for low -income families

This dissertation examines the effect of regulations, resource and referral agencies, and subsidies on price and quality of care in child care centers. This research is based on a carefully developed conceptual framework that incorporates the factors affecting the demand and supply of child care. The first step in developing this framework is sketching out the structural equations. The structural equations help us understand the underlying behavior of individuals and firms making a decision. The exogenous variables are vector of attributes relating to family characteristics, child characteristics, regulations, subsidy, community characteristics and prices of inputs. Based on the structural equations, reduced form equations are estimated to find the effect of each of the exogenous variables on each of the endogenous variables. Reduced form equations help us answer public policy questions. The sample for this study is from the 1990 Profile of Child Care Settings (PCCS) data in which 2,089 center based programs were interviewed. Child/Staff Ratio (Group Level): Results indicate that among subsidies, only the state subsidy per child in poverty has a significant effect on the child/staff ratio at the group level. Presence of resource and referral agencies also increase the child/staff ratio at the group level. Also when the maximum center group size regulation for 25-36 months becomes more stringent, the child/staff ratio at the group level decreases. Child/Staff Ratio (Center Level): When the regulations for the maximum child/staff ratio for age groups 13-24 months and 37-60 months become lax, the child/staff ratio for the center increases. As the regulation for maximum group size for infants becomes stringent, the child/staff ratio decreases. An interesting finding is that as the regulations for maximum group size for age groups 13-24 months and 25-36 months become stringent, the child/staff ratio for the center increases. Another significant finding is that when a center is located in a rural area the child/staff ratio is significantly lower. Center Weighted Average Hourly Fees: Maximum group size regulations for age groups 25-36 months and 37-60 months have a negative effect on center hourly fee. Maximum child staff regulations for age groups 13-24 months and 37-60 months have a negative effect on center hourly fee. Maximum child staff regulations for age groups 0-12 months and 25-36 months have a positive effect on center hourly fee. Findings also indicate that the center average hourly price is lower when there is a resource and referral agency present. Cost adjusted prekindergarten funds and JOBS child care subsidies have a negative effect on average hourly fee. Cost adjusted social services block grant and state subsidy per child in poverty have a positive effect on the average hourly price. A major finding of this dissertation is the interaction of subsidy and regulatory variables. Another major finding is that child/staff ratio at the group level is lower when there is an interaction between geographic location and nature of center sponsorship.

Location Privacy Preferences : A Survey-Based Analysis of Consumer Awareness, Trade-off and Decision-Making

Peer reviewed

Location Privacy Preferences : A Survey-Based Analysis of Consumer Awareness, Trade-off and Decision-Making

Peer reviewed

Modulating membership grades to gain consensus for fuzzy set uncertainty values in a clinical decision support system

This paper deals with a very important issue in any knowledge engineering discipline: the accurate representation and modelling of real life data and its processing by human experts. The work is applied to the GRiST Mental Health Risk Screening Tool for assessing risks associated with mental-health problems. The complexity of risk data and the wide variations in clinicians' expert opinions make it difficult to elicit representations of uncertainty that are an accurate and meaningful consensus. It requires integrating each expert's estimation of a continuous distribution of uncertainty across a range of values. This paper describes an algorithm that generates a consensual distribution at the same time as measuring the consistency of inputs. Hence it provides a measure of the confidence in the particular data item's risk contribution at the input stage and can help give an indication of the quality of subsequent risk predictions. © 2010 IEEE.

Guideline-based decision support has a small, non-sustained effect on transthoracic echocardiography ordering frequency.

BACKGROUND: Guidance for appropriate utilisation of transthoracic echocardiograms (TTEs) can be incorporated into ordering prompts, potentially affecting the number of requests. METHODS: We incorporated data from the 2011 Appropriate Use Criteria for Echocardiography, the 2010 National Institute for Clinical Excellence Guideline on Chronic Heart Failure, and American College of Cardiology Choosing Wisely list on TTE use for dyspnoea, oedema and valvular disease into electronic ordering systems at Durham Veterans Affairs Medical Center. Our primary outcome was TTE orders per month. Secondary outcomes included rates of outpatient TTE ordering per 100 visits and frequency of brain natriuretic peptide (BNP) ordering prior to TTE. Outcomes were measured for 20 months before and 12 months after the intervention. RESULTS: The number of TTEs ordered did not decrease (338±32 TTEs/month prior vs 320±33 afterwards, p=0.12). Rates of outpatient TTE ordering decreased minimally post intervention (2.28 per 100 primary care/cardiology visits prior vs 1.99 afterwards, p<0.01). Effects on TTE ordering and ordering rate significantly interacted with time from intervention (p<0.02 for both), as the small initial effects waned after 6 months. The percentage of TTE orders with preceding BNP increased (36.5% prior vs 42.2% after for inpatients, p=0.01; 10.8% prior vs 14.5% after for outpatients, p<0.01). CONCLUSIONS: Ordering prompts for TTEs initially minimally reduced the number of TTEs ordered and increased BNP measurement at a single institution, but the effect on TTEs ordered was likely insignificant from a utilisation standpoint and decayed over time.

Essays in Empirical Operations Management: Bayesian Learning of Service Quality and Structural Estimation of Complementary Product Pricing and Inventory Management

This dissertation contributes to the rapidly growing empirical research area in the field of operations management. It contains two essays, tackling two different sets of operations management questions which are motivated by and built on field data sets from two very different industries --- air cargo logistics and retailing.

The first essay, based on the data set obtained from a world leading third-party logistics company, develops a novel and general Bayesian hierarchical learning framework for estimating customers' spillover learning, that is, customers' learning about the quality of a service (or product) from their previous experiences with similar yet not identical services. We then apply our model to the data set to study how customers' experiences from shipping on a particular route affect their future decisions about shipping not only on that route, but also on other routes serviced by the same logistics company. We find that customers indeed borrow experiences from similar but different services to update their quality beliefs that determine future purchase decisions. Also, service quality beliefs have a significant impact on their future purchasing decisions. Moreover, customers are risk averse; they are averse to not only experience variability but also belief uncertainty (i.e., customer's uncertainty about their beliefs). Finally, belief uncertainty affects customers' utilities more compared to experience variability.

The second essay is based on a data set obtained from a large Chinese supermarket chain, which contains sales as well as both wholesale and retail prices of un-packaged perishable vegetables. Recognizing the special characteristics of this particularly product category, we develop a structural estimation model in a discrete-continuous choice model framework. Building on this framework, we then study an optimization model for joint pricing and inventory management strategies of multiple products, which aims at improving the company's profit from direct sales and at the same time reducing food waste and thus improving social welfare.

Collectively, the studies in this dissertation provide useful modeling ideas, decision tools, insights, and guidance for firms to utilize vast sales and operations data to devise more effective business strategies.

Valuation of Ecosystem Services for Environmental Decision Making in South Florida

The Greater Everglades system imparts vital ecosystem services (ES) to South Florida residents including high quality drinking water supplies and a habitat for threatened and endangered species. As a result of the altered Everglades system and regional dynamics, restoration may either improve the provision of these services or impose a tradeoff between enhanced environmental goods and services and competing societal demands. The current study aims at understanding public preferences for restoration and generating willingness to pay (WTP) values for restored ES through the implementation of a discrete choice experiment. A previous study (Milon et al., 1999) generated WTP values amongst Floridians of up to $3.42 -$4.07 billion for full restoration over a 10-year period. We have collected data from 2,905 respondents taken from two samples who participated in an online survey designed to elicit the WTP values for selected ecological and social attributes included in the earlier study (Milon et al. 1999). We estimate that the Florida general public is willing to pay up to $854.1- $954.1 million over 10 years to avoid restrictions on their water usage and up to $90.8- $183.7 million over 10 years to restore the hydrological flow within the Water Conservation Area.