The manufacturing industry is shifting, entering a new era with smart and connected devices. The fourth industrial revolution (Industry 4.0) is promising increased growth and productivity by the Smart Factory and within the enabling technologies is Augmented Reality (AR). This is a technology that can be used to augment the reality with digital information. At the same time as the technology is introduced, errors in manufacturing are a problem which are affecting the productivity and the quality. The errors can be caused by humans and companies strive to eliminate the errors caused by humans. This research aims to find the main causes of human errors in assembly lines and thereafter explores whether AR is an appropriate tool to be used in order to address those issues. Based on a literature review that identified and characterized a preliminary set of root causes for human errors in assembly lines, these causes were empirically studied in an exercise that covered an in-depth case study at a multinational automotive company. Data in form of interviews and deviation reports have been used to identify the causing factors and the result showed that the main causes of human errors are the amount of thinking, deciding and searching for information which affected the cognitive load of the operator and in result their performance. Several interviews with experts in AR allowed to verify if this technology would be feasible to solve or mitigate the found causes. Besides that, in repetitive manual assembly operations, AR is better used showing the process in order to train new operators, at the same time as for experienced operators AR show information only when an error occurs and when there is a need of taking an active choice is more appropriate. Nevertheless, while theoretically able to managing human error when fully developed, the desired application makes the augmentation of visual objects redundant and increasingly complex for solving the identified causes of errors which questions the appropriateness of using AR systems. However, the empirical findings showed that for managing human errors, the main bottleneck of an AR system is the software and AI. / Den tillverkande industrin skiftar och går in i en ny era där smart och uppkopplad teknologi introduceras i de operativa delarna av tillverkningen. Denna fjärde industriella revolution (Industry 4.0) som den även kallas för med smarta fabriker, utlovar ökad produktivitet och tillväxt. Bland de teknologier som representeras i detta nya landskap återfinns Augmented Reality (AR), vilket är en teknik som används för att förstärka verkligheten med digital information. I samband med att denna nya teknik introduceras, är avvikelser i produktion ett problem som påverkar företags produktivitet och kvalitet. Den mänskliga faktorn är en bidragande del till detta problem och företag strävar efter att eliminera felen orsakade av människor. Denna studie syftar till att hitta orsakerna till att människor orsakar fel i produktion och därefter utforska om AR är ett lämpligt verktyg att använda för att råda bot på dessa orsaker och därmed eliminera felen. Genom en litteraturstudie har det identifierats ett antal faktorer som påverkar den mentala belastningen hos människor i produktionssammanhang. Dessa faktorer har därefter undersökts genom en fallstudie hos en multinationell tillverkare av kommersiella fordon. Datainsamling i form av intervjuer och avvikelsedata har använts för att identifiera de påverkande faktorerna och resultaten pekade på att behovet av att behöva tänka, leta efter information och fatta beslut påverkade den mentala belastningen mest. Intervjuer hölls med forskare och montörer för att definiera en lämplig AR funktion som sedan undersöktes genom flera intervjuer med forskare inom AR för att verifiera om AR är en lämplig teknik att använda för de identifierade orsakerna. I termer av AR i en arbetsmiljö med repetitiva aktiviteter efterfrågas en funktion som visualiserar fel för montörer som är erfarna medan det för oerfarna montörer är bättre med visualisering av hela arbetsprocessen. Men, trots att systemet i teorin är lämpligt att använda för att hantera orsakerna till att felen uppstår så är den efterfrågade funktionen överflödig då visualisering kommer visas väldigt sällan samt att tekniken är väldigt komplex. Detta gör att det går att ifrågasätta hela funktionen av att använda AR system i det fall som studerades. Dessutom visade sig tekniken vara olämplig att använda i den miljö fallet utspelar sig i på grund av svårigheter med artificiell intelligens (AI).

Introdução: A segurança é considerada um pilar da qualidade dos cuidados à saúde e seu sucesso depende do comprometimento individual e coletivo. Os ensinamentos teórico-práticos transferidos aos alunos acerca dessa temática garantem melhoria na assistência prestada. Objetivo: Avaliar o impacto de intervenção sobre segurança do paciente no conhecimento e atitude dos alunos de medicina. Metodologia: Trata-se de uma análise do tipo intervenção, não randomizado, com grupo único de comparação - antes e depois -, prospectivo e exploratório, com abordagem quantitativa, realizado com 98 estudantes do curso do 6º ano de Medicina da Faculdade de Medicina de Ribeirão Preto (FMRP-USP), São Paulo, Brasil. A coleta de dados ocorreu de janeiro a novembro de 2017, utilizando um questionário físico contemplando a caracterização dos alunos, bem como os aspectos conceituais e atitudinais sobre o erro humano e a segurança do paciente. Discussão: Como resultados, verificou-se o predomínio de estudantes do sexo masculino (62%) com a média de idade de 25,8 anos, enquanto, em relação aos aspectos conceituais evidenciou-se a melhoria do entendimento sobre a temática \"erro humano e segurança do paciente\", como se pode destacar nas assertivas \"Cometer erros na área da saúde é inevitável\", com média 4,0 na escala de Likert - mostrando que 70% dos alunos de medicina concordaram com a afirmação antes da intervenção educativa (pré-teste), sendo que, após a mesma (pós-teste), a média foi para 1,8 (68% discordaram). 42% dos estudantes (média de 3,6) ainda começaram concordando que \"para a análise do erro humano é importante saber as características individuais do profissional que cometeu o erro\", enquanto no pós-teste 59% deles (média de 2,3) discordaram. Conclusão: Conclui-se que os alunos, depois da intervenção educativa em sala de aula, conseguiram contemplar vários aspectos conceituais relacionados à segurança do paciente e às responsabilidades dos docentes e discentes frente à assistência. Porém, a intervenção educativa teve sua limitação quanto à evidência de mudanças nas atitudes dos alunos, uma vez que, a aprendizagem é considerada condição necessária, mas não suficiente, pois fatores contextuais e as características do próprio indivíduo podem influenciar a transferência efetiva do conhecimento, habilidades e atitudes para as atividades laborais. Nesse sentido, os próximos estudos podem levar em consideração a teoria dos fatores humanos, que não promete soluções instantâneas para a melhoria no cuidado prestado, mas pode fornecer uma riqueza de recursos para o progresso sustentável que minimizem erros e promovam uma cultura de segurança organizacional / Introduction: Safety is considered a pillar of the quality in health care and its success depends on both individual and collective commitment. The theoretical-practical teachings transferred to the students on this thematic assure improvements on the care provided. Aim: The aim is to evaluate the impact of interventions about patient\'s safety in the knowledge and actions of medical students. Methodology: It is an analysis from the interventional type, nonrandomized, with a single group of comparison - before and after-, prospective and exploratory, with quantitative approach, performed with 98 students of the 6º year of medical school from the Medical School of Ribeirão Preto (FMRP-USP), São Paulo, Brazil. The collection of data occurred from January to November 2017, using a questionnaire about the description of the students, as well as conceptual and attitudinal aspects about human error and patient\'s safety. Discussion: As results, there was a predominance of male students (62%) with average age of 25,8 years old, while, regarding to conceptual aspects, it was observed an improvement of the understanding about the thematic \"human error and patient\'s safety\", as it can be highlighted in the statement \"Making mistakes in health is inevitable\", with an average of 4,0 on Likert scale - showing that 70% of the medical students agreed with the statement before the educational intervention (pre-test), and after the intervention (after-test), the average dropped to 1,8 (68% disagreed). 42% of the students (average of 3,6 ) still began agreeing that \"for the analysis of the human error it is important to know individual characteristics of the professional who made the mistake\", while after-test 59% of them (average of 2,3) disagreed. Conclusions: It is concluded that after the educative intervention in classroom, they managed to contemplate several conceptual aspects related to patient\'s safety e to the responsibilities of the teachers and students involved on the assistance. However, the educative intervention had its limitation regarding the evidence of changes in the students\' attitudes, once that the learning process is considered a necessary condition, but it is not enough, due to contextual factors and individuals characteristics that may influence the effective transfer of knowledge, skills and attitudes to labor activities. So, the following essays may take into consideration the human factor theory, which doesn\'t promise instantaneous solutions to the improvement in the care provided, but may be able to provide a wealth of resources to sustainable progress that minimize errors and promote a culture of organizational safety

[pt] A maioria dos estudos existentes em controle de qualidade de processos focam no desempenho de máquinas e ferramentas. Assim, estes já contam com bons métodos para serem controlados. Contudo, erros humanos em potencial estão presentes em todos os processos industriais que contenham a relação homem-máquina, fazendo com que a necessidade de se avaliar a qualidade do desempenho humano seja de igual importância. A abordagem para se avaliar quão suscetível à falha humana estão tais processos baseiam-se em probabilidades de erro, supondo que o desempenho humano funciona da mesma maneira que o desempenho de máquinas, ou em PSFs (Performance Shaping Factors), variáveis representativas de características de desempenho humano. Embora esta última abordagem seja mais eficiente, ainda existem críticas a sua falta de contextualização: tais características são avaliadas separadamente uma das outras, e independentemente da tarefa que o operador esteja realizando. Sistemas de Inferência Fuzzy (SIFs) permitem que variáveis lingüísticas sejam avaliadas em conjunto, isto é, passa a ser possível criar um modelo que assimile as nuances da variação do comportamento de um PSF concomitantemente com a alteração de outro PSF. Dessa forma, a caracterização da confiabilidade humana, considerando que diversos PSFs afetam no desempenho dos demais, pode ser satisfeita ao se fazer uso de SIFs interligados seqüencialmente - SIFs hierárquicos. Para se contextualizar a caracterização da confiabilidade humana por tarefa realizada, necessita-se que os PSFs pertinentes a cada determinada tarefa sejam medidos novamente e realimentados ao sistema (desenvolvido nesta dissertação). O SIF geral (composto por nove camadas de SIFs hierárquicos) foi testado com dados hipotéticos e dados reais de operadores e tarefas de uma empresa do setor elétrico brasileiro. Os resultados encontrados foram satisfatórios e evidenciaram que a Lógica Fuzzy, na forma de SIFs hierárquicos, pode ser utilizada para caracterizar a confiabilidade humana, com a vantagem de fazê-lo enquanto seu contexto é considerado. / [en] Most of existing studies in quality control focus on machinery performance. There are effective and advanced control methods to deal with that. However, potential human errors are present in every industrial process operated by humans. Therefore, evaluating the quality of human performance becomes as important as evaluate machinery s. The approach to evaluate how much processes are susceptible to human error are based on error probabilities, by assuming that human performance is similar to machinery performance, or on PSFs (Performance Shaping Factors) – variables representing human features. Although this based approach is more efficient, there are still criticisms about its lack of context awareness: those features are evaluated separately from one another, and regardless of which task the employee is performing. Fuzzy Inference Systems (FISs) allow linguistic variables to be evaluated simultaneously, thus making it possible to develop a method that gathers the nuances of behavioral changes of a PSF whilst another PSF varies. With this method, and considering that different PSFs affect the performance of others, human reliability can be assessed through the use of sequentially interconnected FISs – Hierarchical Fuzzy Inference Systems. In order to contextualize this assessment by tasks, each of the PSFs that affects each task will have to be measured and fed into the system (as developed within this dissertation) once per task and per employee. The main FIS (which contains nine layers of hierarchical FISs) was tested by using both hypothetical and real data from operators and tasks of a Brazilian electricity company. Results were satisfactory and attested that Fuzzy Logic, in the form of hierarchical FISs, can be used to assess human reliability, with the advantage of also taking the context into account.

Submitted by Daniella Sodre (daniella.sodre@ufpe.br) on 2015-04-10T16:37:01Z No. of bitstreams: 2 TESE Rômulo Fernando Teixeira Vilela.pdf: 3159637 bytes, checksum: d8b68b1fd93d79fe6162c4abdd0b1aa0 (MD5) license_rdf: 1232 bytes, checksum: 66e71c371cc565284e70f40736c94386 (MD5) / Made available in DSpace on 2015-04-10T16:37:01Z (GMT). No. of bitstreams: 2 TESE Rômulo Fernando Teixeira Vilela.pdf: 3159637 bytes, checksum: d8b68b1fd93d79fe6162c4abdd0b1aa0 (MD5) license_rdf: 1232 bytes, checksum: 66e71c371cc565284e70f40736c94386 (MD5) Previous issue date: 2013-02-27 / Com os avanços em hardware, a engenharia de confiabilidade nos últimos 30 anos, tem nos mostrado equipamentos e sistemas complexos com níveis de falha muito baixos. Sistemas complexos na indústria nuclear, aeroespacial, química, elétrica entre outras possuem hoje em dia equipamentos e sistemas com níveis de confiabilidade que tem atendido adequadamente a sociedade. Entretanto, a operação e manutenção destes sistemas não dependem exclusivamente do desempenho intrínseco dos correspondentes equipamentos, dependem também da ação humana. Grandes acidentes no passado recente como Chernobyl, Bhopal, da nave Challenger e os grandes apagões no Brasil, colocaram em evidência a necessidade de redução do erro humano em sistemas complexos. A análise da confiabilidade humana surge assim como um apoio para a análise destes sistemas de operação e manutenção. Desde a década de 80 alguns avanços foram surgindo no estudo da confiabilidade humana. Técnicas como THERP, ATHEANA, CREAM e IDAC, se consolidaram ao longo do tempo como boas aplicações práticas para estudar, medir e prever o erro humano. Porém os fatores de desempenho utilizados em quase todas as técnicas supracitadas, tem se mostrado difíceis de serem estimados de um ponto de vista particular. Além disso, as particularidades do setor Hidroelétrico de Potência, definidas nos Procedimentos de Rede do Operador Nacional do Sistema (ONS) e nos instrumentos normativos da Agencia Reguladora ANEEL têm levado a necessidade de uma taxonomia que possa se adaptar a este importante e estratégico setor. Nesta tese, é proposta uma taxonomia e um modelo da sequência do processo de erro, para avaliação deste erro humano especificamente concebido para atender ao contexto de operação e manutencão do Sistema Hidroelétrico de Potência. Para ilustrar a nova taxonomia, foram coletados e analisados dados de cerca de dez anos de registro de erro humano de uma empresa de geração e transmissão de energia elétrica brasileira. Foram coletados 605 relatórios de desligamento por erro humano desde 1998 até 2009. Uma metodologia BBN-Base para a quantificação do erro humano é também discutida. A taxonomia e o modelo da sequência do processo de erro humano tanto quanto o modelo BBN-Based são ilustrados via um exemplo de uma aplicação no contexto de uma indústria Brasileira Hidroelétrica de Potência.-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------With advances in hardware reliability engineering in the last 30 years, we have seen equipment and complex systems with very low levels of failure. Complex systems in the nuclear industry, aerospatiale sector, chemical industries, electrical industries and others now have equipment and systems with levels of reliability that has adequately served the society. However, the operation and maintenance of these systems do not rely solely on intrinsec performance of the corresponding equipment, but they also depend on human action. Major accidents in the recent past such Chernobyl, Bhopal, the Challenger shuttle and major recent power blackouts in Brazil, highlighted the need to reduce human error in complex systems. The human reliability assessment emerges as a support to the analisys of the operation and maintenance of these type of systems. Since the late 80th some advances have emerged in the study of human reliability. Techniques such as THERP, ATHEANA, CREAM and IDAC, have been consolidated over time for the study, measure and prediction of human error. However performance shaped factors used in almost all the aforementioned techniques have proven difficult to be estimated from a practical standpoint. In addition, the specifics of the Hydroelectric Power Industry defined in the Grid Procedures of the National System Operator (Operador Nacional so Sistema, ONS) and the regulatory instruments of ANEEL (Agencia Nacional de Energia Eletrica) Regulatory Agency have led to the necessity of a taxonomy that can adapt for this important strategic sector. In this thesis, it is proposed a taxonomy and model of error sequence process for assessment of human error specifically designed to meet the context of operation and maintenance of Hydroelectric Power System. To illustrate the new taxonomy it was collected and analyzed data from about ten years of human error records related to the generation and transmission of Hydroelectric Power Company in Brazil. It was collected 605 reports by human error shutdown from 1998 to 2009. A BBN-Base methodology for the quantification of human error is also discusses. The taxonomy, model for error sequence process as well as the BBN-Based model are illustrated via an example of application in the context of the Brazilian Hydroelectric Power Industry.

Background: Low morale is classified as a latent condition for performance variability in safety-critical environments. Morale management may assist in the control of performance variability as part of a systems approach to safety. A context-specific model for measuring and managing morale with reference to followership in a safety-critical air traffic control (ATC) environment could not be found. Purpose/Aim: The purpose of this study was to develop a model that enables the measurement and management of air traffic controller (ATCO) team morale. Research Design: An exploratory sequential mixed method design was adopted. A census approach to sampling was used to conduct 21 focus group sessions as the qualitative phase, providing the definition and drivers of morale. The Measure of Morale and its Drivers (MoMaD) survey instrument was created from qualitative data, then administered to 256 ATCOs in the quantitative phase. Statistical methods included exploratory factor analysis, correlation and regression analysis to construct the final MoMaD model. Results: A context-specific definition of morale is provided and communication management, team cohesion, leadership interaction, staff incentive, staffing level, workplace health and safety and mutual trust were found to be the drivers of morale in a safety-critical ATC environment. A single-item measure of perceived morale reflected the state of context-specific ATCO team morale more accurately than an existing generalisable multi-item measure. Conclusion: This study contributes to the body of knowledge by integrating applicable aspects of morale, followership, performance variability and organisational culture and climate in safety-critical ATC environments into a new theoretical framework. The MoMaD instrument is presented as a context-specific model for measuring and managing ATCO team morale in an ATC environment. Recommendations: Future research opportunities include the possible influence of morale as a predictor of morale in safety-critical environments and the development of a context-specific multi-item measure of morale for integration into the MoMaD model. / Business Management / D. B. L.

Ett samhälle som snabbt förändras av digitaliseringens transformerande kraft är en omfattande och debatterad fråga i vår nutid. Trots de möjligheter den ger, kvarstår utmaningar, särskilt inom IT-säkerhet. Befintlig forskning betonar främst de tekniska aspekterna och försummar det avgörande mänskliga inslaget inom IT-säkerhet. Det rådande forskningsgapet belyser det mänskliga elementet som en betydande sårbarhet för att upprätthålla säkra digitala miljöer. Medan teknologiska skydd är nödvändiga visar de sig ofta otillräckliga utan hänsyn till mänskliga faktorer. Den tänkta studien syftar till att undersöka forskningsläget kring mänskliga faktorer inom IT-säkerhet. Genom en kvalitativ litteraturstudie som primär forskningsstrategi granskas och analyseras vetenskaplig forskning och litteratur systematiskt inom det valda ämnesområdet. Resultatet presenterar i vilken omfattning olika koncept relaterade till mänskliga faktorer inom IT-säkerhet undersöks. Studien bidrar således till en teoretisk kunskapsutveckling för att stärka och skydda digital information och infrastruktur genom att identifiera områden som forskningen är begränsad kring. Denna studie strävar efter att fylla forskningsgapet genom att belysa mänskliga sårbarheter inom IT-säkerhet och vilka koncept som bör undersökas vidare. På så sätt kan studien bidra till en holistisk förståelse av IT-säkerhet, med en balans mellan teknologiska och människocentrerade tillvägagångssätt. / A society rapidly transformed by the transformative power of digitization is a comprehensive and debated issue in our contemporary times. Despite the opportunities it presents, challenges persist, particularly in IT security. Existing research primarily emphasizes the technical aspects while neglecting the crucial human element within IT security. The current research gap highlights the human element as a significant vulnerability in maintaining secure digital environments. While technological safeguards are necessary, they often prove insufficient without consideration of human factors. The intended study aims to investigate the current state of research on human factors in IT security. Through a qualitative literature review as the primary research strategy, scientific research and literature within the chosen subject area are systematically examined and analyzed. The findings present the extent to which various concepts related to human factors in IT security are explored. Thus, the study contributes to theoretical knowledge development to strengthen and protect digital information and infrastructure by identifying areas where research is limited. This study seeks to fill the research gap by highlighting human vulnerabilities in IT security and which concepts should be further investigated. In doing so, the study may contribute to a holistic understanding of IT security, balancing technological and human-centered approaches.

Energy usage evaluation and condition monitoring for electric machines are important in industry for overall energy savings. Traditionally these functions are realized only for large motors in wired systems formed by communication cables and various types of sensors. The unique characteristics of the wireless sensor networks (WSN) make them the ideal wireless structure for low-cost energy management in industrial plants. This work focuses on developing nonintrusive motor-efficiency-estimation methods, which are essential in the wireless motor-energy-management systems in a WSN architecture that is capable of improving overall energy savings in U.S. industry. This work starts with an investigation of existing motor-efficiency-evaluation methods. Based on the findings, a general approach of developing nonintrusive efficiency-estimation methods is proposed, incorporating sensorless rotor-speed detection, stator-resistance estimation, and loss estimation techniques. Following this approach, two new methods are proposed for estimating the efficiencies of in-service induction motors, using air-gap torque estimation and a modified induction motor equivalent circuit, respectively. The experimental results show that both methods achieve accurate efficiency estimates within ¡À2-3% errors under normal load conditions, using only a few cycles of input voltages and currents. The analytical results obtained from error analysis agree well with the experimental results. Using the proposed efficiency-estimation methods, a closed-loop motor-energy-management scheme for industrial plants with a WSN architecture is proposed. Besides the energy-usage-evaluation algorithms, this scheme also incorporates various sensorless current-based motor-condition-monitoring algorithms. A uniform data interface is defined to seamlessly integrate these energy-evaluation and condition-monitoring algorithms. Prototype wireless sensor devices are designed and implemented to satisfy the specific needs of motor energy management. A WSN test bed is implemented. The applicability of the proposed scheme is validated from the experimental results using multiple motors with different physical configurations under various load conditions. To demonstrate the validity of the measured and estimated motor efficiencies in the experiments presented in this work, an in-depth error analysis on motor efficiency measurement and estimation is conducted, using maximum error estimation, worst-case error estimation, and realistic error estimation techniques. The conclusions, contributions, and recommendations are summarized at the end.