The goal of every program or project manager is to have a safe reliable product and to have an understanding of the residual risk of operating that product. Two very important systems engineering analysis tools to achieve those objectives are Hazard Analysis and Failure Modes and Effects Analysis. Sometimes seen strictly as Safety and Reliability tasks, these analyses are key to a successful program or project and require input from all stakeholders. When viewed in the Systems Engineering process, Safety and Reliability are truly specialty disciplines within Systems Engineering. Hazard Analysis is used to improve system safety while Failure Modes and Effects Analysis is used to identify ways to increase product reliability; both analyses are required to improve systems design and fully capture the risk for a system or program. Depending on how the analyses are scoped, there could be a perception of overlap and duplication of effort. This paper will present a systems engineering approach to show the need and benefits for performing both types of analyses. Both analysis processes are required to ensure that all possible hazardous conditions and failure modes have been identified and addressed to minimize overall risk to the program/project and to ensure a safe and reliable system. / text

In order to remain competitive in the global market businesses are under ever increasing pressure to ramp up production rates whilst simultaneously improving cost effectiveness to allow continued profitable growth. This requirement is particularly challenging in high value manufacturing which is characterised by expensive product and manufacturing systems and relatively low production volume. This thesis introduces a method for the design of robust and reliable manufacturing processes through the prevention of identified potential failure modes that is based on the principles of the existing Failure Mode Avoidance framework used for automotive system design. The tools and techniques that exist in the literature are reviewed in order to understand the best practice, and subsequently a Manufacturing Failure Mode Avoidance framework is designed. This framework is demonstrated through two unique case studies conducted in a real life manufacturing environment in order to validate its appropriateness to provide robust countermeasures to failure which will allow right first time manufacture. The outcomes of the implementations are discussed, conclusions drawn and opportunities for further research are provided.

Thesis advisor: Eric Dearing / Emerging research in developmental psychology and neuroscience suggests that childhood poverty is associated with high levels of exposure to multiple contextual risks, which cumulatively lead to persistent elevated stress levels that have a direct, as well an indirect (e.g., through parental processes), impact on child cognitive, academic, and socioemotional functioning (Evans & Kim, 2013). Such research has begun to change the way that scholars and practitioners envision the context of poverty, the persistence of the income-achievement gap, and the types of interventions that may be most effective in addressing disparities in children’s long-term educational success. However, research on the relations between poverty-associated stress and child outcomes is still in its infancy and many questions remain. In particular, it is unclear whether changing family economic circumstances matter, a question of concern for developmental science and public policy. Moreover, there is little work on moderators of relations between income, stress, and child outcomes, which could help identify factors that buffer children from the harm of stressful home environments. With longitudinal data from the Panel Study of Income Dynamics’ Child Development Supplement, the present study used fixed effects models to examine within-child associations between changes in family income, cumulative risk exposure (as measured by an index that includes a range of poverty-related stressors, such as economic strain, neighborhood crime, and physical and psychological home environments), and children’s cognitive, academic and socioemotional functioning. In addition, moderators of these associations were investigated in order to identify potential protective mechanisms and crucial levers for interventions and policy development. On the whole, findings were consistent with the cumulative stress model. On average, the estimated direct effects of changes in family income (i.e., prior to examining mediation or moderators) were not significant for changes in child outcomes. Yet, changes in income were, for the sample as a whole, indirectly related via changes in cumulative risk exposure: increases in income predicted decreases in cumulative risk exposure which, in turn, predicted improvements in achievement and declines in externalizing behavior. Additionally, these relations were moderated by child age, initial level of family income, and initial level of cumulative risk. / Thesis (PhD) — Boston College, 2017. / Submitted to: Boston College. Lynch School of Education. / Discipline: Counseling, Developmental and Educational Psychology.

The aim of this study was to analyze all business processes, to create a process map, analysis of risks in each process, their evaluation and to design solutions. The theoretical part describes methods of the practical analysis. These methods are flowcharts and FMEA.

Background: Stunting prevalence in children less than 5 years has remained stagnated in Peru from 1992 to 2007, with a rapid reduction thereafter. We aimed to assess the role of different predictors on stunting reduction over time and across departments, from 2000 to 2012. Methods: We used various secondary data sources to describe time trends of stunting and of possible predictors that included distal to proximal determinants. We determined a ranking of departments by annual change of stunting and of different predictors. To account for variation over time and across departments, we used an ecological hierarchical approach based on a multilevel mixed-effects regression model, considering stunting as the outcome. Our unit of analysis was one department-year. Results: Stunting followed a decreasing trend in all departments, with differing slopes. The reduction pace was higher from 2007–2008 onwards. The departments with the highest annual stunting reduction were Cusco (−2.31%), Amazonas (−1.57%), Puno (−1.54%), Huanuco (−1.52%), and Ancash (−1.44). Those with the lowest reduction were Ica (−0.67%), Ucayali (−0.64%), Tumbes (−0.45%), Lima (−0.37%), and Tacna (−0.31%). Amazon and Andean departments, with the highest baseline poverty rates and concentrating the highest rural populations, showed the highest stunting reduction. In the multilevel analysis, when accounting for confounding, social determinants seemed to be the most important factors influencing annual stunting reduction, with significant variation between departments. Conclusions: Stunting reduction may be explained by the adoption of anti-poverty policies and sustained implementation of equitable crosscutting interventions, with focus on poorest areas. Inclusion of quality indicators for reproductive, maternal, neonatal and child health interventions may enable further analyses to show the influence of these factors. After a long stagnation period, Peru reduced dramatically its national and departmental stunting prevalence, thanks to a combination of social determinants and crosscutting factors. This experience offers useful lessons to other countries trying to improve their children’s nutrition. / Revisión por pares

In the relatively sparse field of economics of prostitution, studies have in recent years investigated the relationship between prostitution legislation and the presence of sex trafficking. This study investigates the issue further by using both a cross country model with time fixed effects and a country fixed effect model to estimate the effect on the amount of sex trafficking of changing legislation to the so-called Nordic Model, something no other known study has managed to do. In contrast to what previous research has estimated, this thesis finds no significant effect on sex trafficking from changing legislation to the Nordic Model. The obvious difficulties of presenting reliable data on an illegal activity such as sex trafficking and the fact that few countries have changed their legislation to the Nordic Model are likely reasons to the insignificant results and cautions against a causal interpretation.

No description available.

An increase emphasis has been placed on the automotive industry to develop advanced technology vehicles which meet increasing strict government regulations and standards for emissions and fuel economy while maintaining the safety, performance, and consumer appeal of the vehicle. In response to these requirements, hybrid and electric vehicle technologies have become more complex as the necessity for vehicles with an overall better environmental impact. Modern engineers must understand the current methods used to analyze and evaluate risk with the new hybrid technologies to ensure the continued customer satisfaction and safety while meeting new government and agency standards. The primary goal of this work is to maintain consistent definitions, standards, and protocols for risk analysis using design failure modes and effects analysis. Throughout the entire automotive sector there exist standards for risk analysis and methods for analysis, however these models can be difficult to relate to the atmosphere under which educational competitions occur. The motor system case study within this work aims to allow the process for DFMEA to be simple and easily implemented and understood when it is appropriate to start. After defining the model, an electric motor system for hybrid vehicle is analyzed for mechanical and inverter system risks. The end result being a 32% reduction in motor system risk due to recommended actions for mitigating top motor systems risks for future motor system design and implementation, all to meet customer requirements. This work aims to provide an additional tool that when implemented will accelerate the next generation of automotive engineers. / Master of Science

No / Failure Mode and Effects Analysis (FMEA) is a proactive risk assessment tool used to identify potential vulnerabilities in complex, high-risk processes and to generate remedial actions before the processes result in adverse events. FMEA is increasingly used to proactively assess and improve the safety of complex health care processes such as drug administration and blood transfusion. A central feature of FMEA is that it is undertaken by a multidisciplinary team, and because it entails numerous analytical steps, it takes a series of several meetings. Composing a team of busy health care professionals with the appropriate knowledge, skill mix, and logistical availability for regular meetings is, however, a serious challenge. Despite this, information and advice on FMEA team assembly and meetings scheduling are scarce and diffuse and often presented without the accompanying rationale. The Multidisciplinary Team Assemble an eight-member team composed of clinically active health care staff, from every profession involved in delivery of the process—and who regularly perform it; staff from a range of seniority levels; outsider(s) to the process—and perhaps even to health care; a leader (and facilitator); and researchers. Scheduling Plan for 10–15 hours of team meeting time for first-time, narrowly defined FMEAs, scheduled as four to six meetings lasting 2 to 3 hours each, spaced weekly to biweekly. Meet in a venue that seats the team around one table and is off the hospital floor but within its grounds. Conclusions FMEA, generally acknowledged to be a useful addition to the patient safety toolkit, is a meticulous and time- and resource-intensive methodology, and its successful completion is highly dependent on the team members’ aptitude and on the facility’s and team members’ commitment to hold regular, productive meetings.

No / Objectives: To empirically compare 2 different commonly used failure mode and effects analysis (FMEA) scoring procedures with respect to their resultant failure mode scores and prioritization: a mathematical procedure, where scores are assigned independently by FMEA team members and averaged, and a consensus procedure, where scores are agreed on by the FMEA team via discussion. Methods: A multidisciplinary team undertook a Healthcare FMEA of chemotherapy administration. This included mapping the chemotherapy process, identifying and scoring failure modes (potential errors) for each process step, and generating remedial strategies to counteract them. Failure modes were scored using both an independent mathematical procedure and a team consensus procedure. Results: Almost three-fifths of the 30 failure modes generated were scored differently by the 2 procedures, and for just more than one-third of cases, the score discrepancy was substantial. Using the Healthcare FMEA prioritization cutoff score, almost twice as many failure modes were prioritized by the consensus procedure than by the mathematical procedure. Conclusions: This is the first study to empirically demonstrate that different FMEA scoring procedures can score and prioritize failure modes differently. It found considerable variability in individual team members' opinions on scores, which highlights the subjective and qualitative nature of failure mode scoring. A consensus scoring procedure may be most appropriate for FMEA as it allows variability in individuals' scores and rationales to become apparent and to be discussed and resolved by the team. It may also yield team learning and communication benefits unlikely to result from a mathematical procedure.