Submitted by Pedro Silva Filho (pfsilva@ipen.br) on 2017-11-21T11:45:58Z No. of bitstreams: 0 / Made available in DSpace on 2017-11-21T11:45:58Z (GMT). No. of bitstreams: 0 / O gerenciamento de riscos em uma instalação nuclear é necessário para a segurança de trabalhadores e de populações vizinhas. Parte desse processo é a comunicação dos riscos que propicia o diálogo entre gestores da empresa e moradores das áreas de risco. A população que conhece os riscos a que está exposta, como esses riscos são gerenciados e o que deve ser feito em uma situação de emergência tende a se sentir mais segura e a confiar nas instituições responsáveis pelo plano de emergência. Sem diálogo entre empresa e público, o conhecimento dos procedimentos a serem seguidos em caso de acidente não chega à população, ou quando chega, não há confiança dessas pessoas na sua eficácia. Em Angra dos Reis, no litoral sul do Estado do Rio de Janeiro, está a Central Nuclear Almirante Álvaro Alberto. No entorno dessa Central Nuclear existe uma população que, de acordo com o Plano de Emergência Externo (PEE/RJ), deverá ser evacuada ou ficar abrigada, caso ocorra um acidente na instalação. Um trabalho de comunicação de riscos entre esses moradores é necessário para que eles conheçam o plano de emergência e os procedimentos corretos para uma situação de emergência, além de buscar esclarecer dúvidas e mitos. Esse trabalho apresenta uma análise da comunicação dos riscos feita para a população local, a percepção que ela tem dos riscos e o grau de conhecimento do plano de emergência externo por parte dessas pessoas. / Tese (Doutorado em Tecnologia Nuclear) / IPEN/T / Instituto de Pesquisas Energéticas e Nucleares - IPEN-CNEN/SP

[ES] La tecnología nuclear para el uso civil genera más preocupación por la seguridad que muchas otras tecnologías que se usan a diario. La Autoridad Nuclear define las bases de cómo debe realizarse la operación segura de una Central Nuclear. De acuerdo a las directrices establecidas por la Autoridad Nuclear, una Central Nuclear debe analizar una envolvente de escenarios hipotéticos y comprobar de manera determinista que los criterios de aceptación para dicho evento se cumplen. El Análisis Determinista de Seguridad utiliza herramientas de simulación que aplican la física conocida sobre el comportamiento de la Central Nuclear para evaluar la evolución de una variable de seguridad y asegurar que los límites no se sobrepasan. El desarrollo de la tecnología informática, de los métodos matemáticos y de la física que envuelve el comportamiento de una Central Nuclear han proporcionado herra-mientas de simulación potentes que son capaces de predecir el comportamiento de las variables de seguridad con una importante precisión. Esto permite analizar escenarios de manera más realista evitando asumir condiciones conservadoras que hasta la fecha compensaban la falta de conocimiento modelado en las herramientas de simulación. Las herramientas conocidas como De Mejor Estimación son capaces de analizar even-tos transitorios en diferentes escalas. Además, emplean modelos analíticos de las dife-rentes físicas más detallados, así como correlaciones experimentales más realistas y actuales. Un paso adelante en el Análisis Determinista de Seguridad pretende combinar las diferentes herramientas de Mejor Estimación que se emplean para analizar las dis-tintas físicas de una Central Nuclear, considerando incluso la interacción entre ellas y el análisis progresivo a diferentes escalas, llegando a analizar fenómenos más locales si es necesario. Para este fin, esta tesis presenta una metodología de análisis multi-físico y multi-escala que emplea diferentes códigos de simulación analizando el escenario propuesto a dife-rentes escalas, es decir, desde un nivel de planta que incluye los distintos componentes, hasta el volumen de control que supone el refrigerante pasando entre las varillas de combustible. Esta metodología permite un flujo de información que va desde el análi-sis a mayor escala hasta el de menor escala. El desarrollo de esta metodología ha sido validado con datos de planta para poder evaluar el alcance de esta metodología y pro-porcionar nuevas líneas de trabajo futuro. Además, se han añadido los resultados de los distintos procesos de validación y verificación que han surgido a lo largo de este trabajo. / [CA] La tecnologia nuclear per a l'ús civil genera més preocupació per la seguretat que moltes altres tecnologies d'ús quotidià. L'Autoritat Nuclear defineix les bases de com ha de realitzar-se l'operació segura d'una Central Nuclear. D'acord amb les directrius establertes per l'Autoritat Nuclear, una Central Nuclear ha d'analitzar una envoltant d'escenaris hipotètics I comprovar de manera determinista que els criteris d'acceptació per a l'esdeveniment seleccionat es compleixen. L'Anàlisi Determinista de Seguretat utilitza eines de simulació que apliquen la física coneguda sobre el comportament de la Central Nuclear per avaluar l'evolució d'una variable de seguretat i assegurar que els límits no es traspassen. El desenvolupament de la tecnologia informàtica, els mètodes matemàtics i de la física que envolta el comportament d'una Central Nuclear han proporcionat eines de simulació potents amb capacitat de predir el comportament de les variables de seguretat amb una precisió significativa. Això permet analitzar escenaris de manera realista evitant assumir condicions conservadores que fins al moment compensaven la mancança de coneixement. Les eines de simulació conegudes com De Millor Estimació son capaces d'analitzar esdeveniment transitoris a diferent escales. A més, utilitzen models analítics per a les diferents físiques amb més detall així com correlacions experimentals més actualitzades i realistes. Un pas més endavant en l'Anàlisi Determinista de Seguretat pretén combinar les diferents eines de Millor Estimació que se utilitzen per analitzar les distintes físiques d'una Central Nuclear, considerant inclús la interacció entre ells i l'anàlisi progressiu a diferents escales, amb la finalitat de poder analitzar fenòmens locals. Per a aquest fi, esta tesi presenta una metodologia d'anàlisi multi-física i multi-escala que utilitza diferents codis de simulació analitzant l'escenari proposat a diferents escales, és a dir, des d'un nivell de planta que inclou els distints components, fins al volum de control que suposa el refrigerant passant entre les varetes de combustible. Esta metodologia permet un flux de informació que va des de l'anàlisi d'una escala major a una menor. El desenvolupament d'aquesta metodologia ha sigut validada i verificada amb dades de planta i els resultats han sigut analitzats a fi d'avaluar la capacitat de la metodologia i les possibles línies de treball futur. A més s'han afegit els principals resultats de verificació i validació que han sorgit en les distintes etapes d'aquest treball. / [EN] The nuclear technology for civil use has generated more concerns for the safety than several other technologies applied to the daily life. The Nuclear Regulators define the basis of how the Safety Operation of Nuclear Power Plants is to be done. According to these guidelines, a Nuclear Power Plant must analyze an envelope of hypothetical events and deterministically define if the acceptance criteria for these events is met. The Deterministic Safety Analysis uses simulation tools that apply the physics known in the behavior of the Nuclear Power Plant to evaluate the evolution of a safety varia-ble and assure that the safety limits will not be exceeded. The development of the computer science, the numerical methods and the physics involved in the behavior of a Nuclear Power Plant have yield powerful simulation tools that are capable to predict the evolution of safety variables which significant accuracy. This allows to consider more realistic simulation scenarios instead of con-servative approaches in order to compensate the lack of knowledge in the applied prediction methods. The so called Best Estimate simulation tools are capable to analyze the transient events in different scales. Furthermore, they account more detailed analytical models and experimental correlations. A step forward in the Deterministic Safety Analysis intends to combine the Best Estimate simulation tools of the different physics considering the interaction among them and analyzing the different scales, considering more local approaches if necessary. For this purpose, this thesis work presents a multi-scale and multi-physics methodology that uses different physics codes and has the aim of modeling postulated scenarios in different scales, i.e. from system models representing the components of the plants to the subchannel models that analyze the behavior of the coolant between the fuel rods. This methodology allows a flow of information where the output of one scale is used as input in a more detailed scale to predict a more local analysis of parameters, such as the Critical Power Ratio, which are of great importance for the estimation of safety margins. The development of this methodology has been validated against plant data with the aim of evaluating the scope of this methodology and in order to provide future lines of development. In addition, different results of the validation and verifi-cation yielded in the development of the parts of this methodology are presented. / Hidalga García-Bermejo, P. (2020). Development and validation of a multi-scale and multi-physics methodology for the safety analysis of fast transients in Light Water Reactors [Tesis doctoral]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/160135 / TESIS

Submitted by Pedro Silva Filho (pfsilva@ipen.br) on 2017-11-22T16:34:17Z No. of bitstreams: 0 / Made available in DSpace on 2017-11-22T16:34:17Z (GMT). No. of bitstreams: 0 / A cultura de segurança na área nuclear é definida como o conjunto de características e atitudes da organização e dos indivíduos que fazem que, com uma prioridade insuperável, as questões relacionadas à proteção e segurança nuclear recebam a atenção assegurada pelo seu significado. Até o momento, não existem instrumentos validados que permitam avaliar a cultura de segurança na área nuclear. Em vista disso, os resultados da definição de estratégias para o seu fortalecimento e o acompanhamento do desempenho das ações de melhorias tornam-se difíceis de serem avaliados. Este trabalho teve como objetivo principal desenvolver e validar um instrumento para a avaliação da cultura de segurança de organizações nucleares, utilizando o Instituto de Pesquisas Energéticas e Nucleares como unidade de pesquisa e coleta de dados. Os indicadores e variáveis latentes do instrumento foram definidos utilizando como referência modelos de avaliação de cultura de segurança da área da saúde e área nuclear. O instrumento de coleta de dados proposto inicialmente foi submetido à avaliação por especialistas da área nuclear e, posteriormente, ao pré-teste com indivíduos que pertenciam à população pesquisada. A validação do modelo foi feita por meio da modelagem por equações estruturais utilizando o método de mínimos quadrados parciais (Partial Least Square - Structural Equation Modeling PLS-SEM), no software SmartPLS. A versão final do instrumento foi composta por quarenta indicadores distribuídos em nove variáveis latentes. O modelo de mensuração apresentou validade convergente, validade discriminante e confiabilidade e, o modelo estrutural apresentou significância estatística, demonstrando que o instrumento cumpriu adequadamente todas as etapas de validação. / Tese (Doutorado em Tecnologia Nuclear) / IPEN/T / Instituto de Pesquisas Energéticas e Nucleares - IPEN-CNEN/SP

The nuclear industry has long relied upon bounding parametric analyses in predicting the safety margins of reactor designs undergoing design-basis accidents. These methods have been known to return highly-conservative results, limiting the operating conditions of the reactor. The Best-Estimate Plus Uncertainty (BEPU) method using a modernized version of the Code-Scaling, Applicability, and Uncertainty (CSAU) methodology has been applied to more accurately predict the safety margins of the Oregon State University Advanced Plant Experiment (APEX) facility experiencing a Loss-of-Feedwater Accident (LOFA). The statistical advantages of the Bayesian paradigm of probability was utilized to incorporate prior knowledge when determining the analysis required to justify the safety margins. RELAP5 Mod 3.3 was used to accurately predict the thermal-hydraulics of a primary Feed-and-Bleed response to the accident using assumptions to accompany the lumped-parameter calculation approach. A novel coupling of thermal-hydraulic and statistical software was accomplished using the Symbolic Nuclear Analysis Package (SNAP). Uncertainty in Peak Cladding Temperature (PCT) was calculated at the 95/95 probability/confidence levels under a series of four separate sensitivity studies. / Graduation date: 2013

According to Oliver (2002) the success of turnaround maintenances is measured in terms of the cost of completion, time, safety performance and the performance of the plant afterwards. The Escravos gas plant (EGP) is a gas processing plant that converts associated gas from Chevron owned crude oil wells to liquefied petroleum gas, natural gas and gas condensate (Chevron intranet. Website assessed on September 14, 2007). According to the EGP plant operations coordinator (See interview Appendix A), the plant undergoes a turnaround maintenance exercise once every two years. The major tasks done during these turnaround maintenances are 1. Change–out of three molecular sieve beds. 2. Servicing of three compressor turbines. 3. Servicing of expander turbo–machinery. 4. Clean–out of fired gas heater tubes and burners. 5. Tie–ins for major upgrades. The EGP management does not involve the contractor personnel that carry out the tasks in the management of the turnaround maintenance. The contractor’s personnel simply follow the work plans and instructions developed by the EGP management. The EGP turnaround management team consists of the coordinator who is the head of the turnaround maintenance team, shift supervisors, maintenance supervisors (rotating equipment maintenance supervisor, instrumentation and electrical maintenance supervisor, and static equipment maintenance supervisors), safety supervisors, maintenance planners, process engineers and construction supervisors. All these listed personnel in the preceding paragraph and the supervisors of the contractor teams participate in the pre–turnaround meetings which happen once a month for the first 10 months of the 12 months leading to the turnaround. The meeting frequency increases to once every two weeks during the last two months leading to the turnaround maintenance. The meeting is held daily during the turnaround maintenance and once every two weeks for the first month after the turnaround maintenance. During the preceding months to the turnaround maintenance, the work scope is defined, the job sequence outlined and schedules are developed. Resources requirements are detailed and procured. During the turnaround maintenance the focus of the turnaround meeting is to discuss potential deviations, observe at–risk behaviors and likely challenges. Plans are then made to address these deviations, challenges and at–risk behaviors. After the turnaround maintenance, “lessons learnt” are captured and the turnaround maintenance is closed out. According to the EGP coordinator (see interview in appendix A), the success of its turnaround maintenance is measured by the time used to complete the turnaround maintenance, the total recordable incident rate during the turnaround maintenance, the days away from work, the lost time injury(LTI) and the cost incurred. Poling et al noted that it is difficult to rate turnaround maintenance projects because no two turnaround maintenances strategies are exactly the same. They iterated that the most common tactics used is benchmarking and that benchmarking enables a company to measure and compare its performance against peer companies in a constructive and confidential manner. They pointed out that the quantitative differences computed between a plant and other similar plants using detailed data taxonomy can provide invaluable information regarding improvement opportunities. This is a way of effectively extending a “lessons learned” exercise across multiple companies. According to then however a critical attribute of effective reliability and maintenance benchmarking is the ability to compare disparate assets; but even small differences for similar plants can alter the value of the comparison. Existing literature indicate that the parameters the gas plant management use to rate the safety of its turnaround maintenance (i.e. the total recordable incident rate, the days away from work and the lost time injury)are reactive in nature. They are otherwise called lagging indicators. Lagging indicators are safety performance metrics that are recorded after the accident or incidents has occurred. For example lost time injury is any work related injury or illness which prevents that person from doing any work day after accident (E&P Consultancy Associates. Website assessed on June 15, 2009). In contrast the other group of metrics called pro–active metrics or leading indicators such as at–risk behaviors, near misses and preventive maintenance not completed are parameters that measure safety performance before accident occurs. Leading indicators gained popularity in the 1930’s after Heinrich postulate his iceberg theory (Wright, 2004). Heinrich’s used the iceberg analogy to explain reactive (lagging) and proactive (leading) indicators. Heinrich likened accident and at–risk behaviors to two parts of an Iceberg; the part you see above water and the part hidden under the water. The size of the iceberg above water is relatively small compared to that under water. The iceberg starts to grow under the water and only after they reach a certain size does part of the ice begin to appear above water. Heinrich believed that accidents are the result of root causes such as at–risk behaviors, inconsistencies, wrong policies, lack of training and lack of information. When the number of accidents that occur in an endeavor is measured you get relatively smaller numerical quantities when compared to the number of at–risk behaviors. Heinrich suggested that to eliminate accidents that occur infrequently, organizations must make effort to eliminate the root causes which occur very frequently. This makes sense because imagine a member of personnel coming to work intoxicated every day. Binging intoxicated at work is an at–risk behavior. The employee is very likely to be involved in an accident at some time as a result of his drinking habit. The number of times he is intoxicated if counted will be huge when compared to the impact of the accident when it does occur. The iceberg theory is supported by work from Bird (1980) and Ludwig (1980) who both attempted to establish the correct ratio of accidents to root causes in different industries. Heinrich suggested a ratio of three hundred incidents to twenty nine minor injuries to one major injury. This researcher chose to use the number of at–risk behavior exhibited by the turnaround maintenance teams to rate the safety performance of tasks despite criticism from individuals like Robotham (2004) who said that from his experience minor incidents do not have the potential to become major accidents and Wright et al (2004). Leading indicators are convenient to analysis because of their relative large quantity. In a turnaround environment, the numbers of accidents that occur are relatively few unlike the number of near misses (Bird, 1980). It is easy to statistically analyze thirty at–risk behaviors than four accidents. In addition Fleming et al (2001) noted that data from industry show much success by companies in the reduction of accidents by efforts at reducing the number of at–risk behaviors, increase the number of safety audits, and reduce the number of closed items from audits etc. Phimister et al made similar claims when they said Near miss programs improve corporate environmental, health and safety performance through the identification of near misses. Existing literature also reveals many theories about management styles and their possible impact on performance. The theories are grouped into trait theories, situational theories and behavioral theories. The trait theories tries to explain management styles by traits of the managers like initiative, wisdom, compassion and ambitious. Situational theories suggest that there is no best management style and managers will need to determine which management style best suit the situation. Behavioral theories explain management success by what successful managers do. Behavioral theorists identify autocratic, benevolent, consultative and participatory management styles. Vroom and Yetton (1973) identified variables that will determine the best management style for any given situation. The variables are; 1. Nature of the problem. Is it simple, hard, complex or clear? 2. Requirements for accuracy. What is the consequence of mistakes? 3. Acceptance of an initiative. Do you want people to use their initiative or not? 4. Time–constraints. How much time do we have to finish the task? 5. Cost constraints. Do we have enough or excess to achieve the objective? A decision model was developed by Vroom and Yago (1988)to help managers determine the best management style for different situations based on the variables listed above (See figure six). They also defined five management style could adopt, namely the; 1. Autocratic I style 2. Autocratic II style. 3. Consultative I style 4. Consultative II style 5. Group II style The autocratic I management style is a management style where the leader solves the problem alone using information that is readily available to him/her, is the normal management style of the Escravos gas plant management in all turnarounds prior to 2009. However the Vroom and Yago model recommends the Consultative II management style for the type of work done during the Escravos gas plant turnaround maintenance. According to Coye et al (1995), participatory management or consultative style II creates a sense of ownership in organization. In this management style the leader shares problem with group members individually, and asks for information and evaluation. Group members do not meet collectively, and leader makes decision alone (Vroom and Yago, 1988). Coye et al believe that this management styles instills a sense of pride and motivate employees to increase productivity. In addition they stated that employees who participate in the decisions of the organization feel like they are a part of a team with a common goal, and find their sense of self–esteem and creative fulfillment heightened. According to Filley et al (1961), Spector and Suttle did not find any significant difference in the output of employees under autocratic and participatory management style. This research studies if and how the Escravos gas plant turnaround maintenance can be improved by changing the management style from autocratic I style to consultative II style. Two tasks in the turnaround were studied; namely the change out of the molecular sieve catalyst beds and the servicing of the turbine engines. The turnaround contractor Techint Nigeria Limited divides the work group into teams responsible for specific tasks. Six teams (team A, B, C, D, E and F) were studied. EGP management will not allow the researcher to study more than these six teams for fear of the research disrupting the work. The tasks completed by these teams are amongst those not on the projects critical path so delays caused by the research will not impact the entire turnaround project provided the float on these activities were not exceeded. They also had the fewest number of personnel, so cost impact of the research work could be easier to manager. Teams A, B and C are different maintenance teams comprising of eight personnel each. They were responsible for changing the EGP molecular sieve beds A, B and C respectively in the 2007 and 2009 turnaround. Their tasks are identical because the molecular sieve beds are identical. Teams E, D and F are also maintenance teams comprising of six personnel each. They were responsible for servicing the EGP turbine engines A, B and C during the 2007 and 2009 turnaround maintenance. Their tasks are also identical because the turbine engines are identical. Consultative management style II is exercised by involving team A and team D in the development of the procedures, processes and job safety analysis of all tasks that they were assigned to complete during the 2009 turnaround maintenance. They were also permitted to participate in the turnaround maintenance meetings and to make contributions in the meetings. In the 2007 turnaround maintenance team A and team D only carried out their tasks. They did not participate in the development of procedures and job safety analysis neither did they participate in the turnaround maintenance meetings. The other four teams; team B, team C, team E and team F are used as experimental controls for the research. They did not participate in the development of the procedures, processes nor the job safety analysis for the tasks in either of the turnaround maintenance. They were also not permitted to attend the daily turnaround meetings. They only completed their tasks based on instructions given to them during the 2007 and 2009 turnaround maintenance. It was necessary to study the experimental control teams as the researcher was not sure whether task repetition, increased knowledge or improved team cohesion would lead to a reduced time or a reduced numbers of at–risk behavior. ix The research tested the hypothesis 1H0 and 1H1 and 2H0and 2H1 at the 0.025 and 0.05 level of significance as follows; Null hypothesis, 1H0: There is no significant difference in the time spent by team A and team Din 2007 when they did not participate in the development of the procedures and processes with the time in 2009 when they did(u1-u2=0). Alternate hypothesis, 1H1: There is a significant difference in the time spent by the team A and Din 2007 when they did not participate in the development of the procedures and processes with the time in 2009 when they did (u1-u2!=0). Null hypothesis, 2H0: There is no significant difference in the number of at–risk behaviors observed to have been exhibited by the team A and team D in 2007 when they did not participate in the development of the procedures and processes with the number in 2009 when they did (u1-u2=0). Alternate hypothesis, 2H1: There is a significant difference in the number of at–risk behaviors observed to have been exhibited by the team A and team D in 2007 when they did not participate in the development of the procedures and processes with the number in 2009 when they did (u1-u2!=0). The student t test was used to analyze these times and number of at–risk behavior. At the 0.025 and the 0.05 level of significance, the data show that there is no difference in the times all the teams used to complete their task in 2007 and in 2009. The researcher concludes that a change in the management style from autocratic I style to consultative II style did not lead to a reduction in the time used by any team to complete their task. However at the 0.025 and the 0.05 level of significance, there is a significant difference in the number of at–risk behaviors of the research team A and team D. There is however no significant difference in the number of at–risk behavior of the control team B, team C, team E and team F at the same level of significance. The researcher concludes that a change in the management style from autocratic I style to consultative II style lead to a reduction in the number of at–risk behavior of team A and team D. In addition the reduction in the number of at–risk behavior of team A and team D could not have been because of task repetition, increased knowledge or improved team cohesion since there is no significant difference in the number of at–risk behavior exhibited by team B, team C, team E and team F. The research can be used by the Escravos gas plant management and the management of any similar process plant to fashion out more cost effective, time effective and safer methods for carrying out their turnaround maintenance. A change in management styles may just be a better approach to improving productivity than giving financial incentives to contractors and personnel. Changes in management style will have to be managed. The change must be gradual because sudden change can be detrimental as people may just need to understand and adapt to the change. The turnaround personnel must also understand the intent so as to prevent conflicts. / Thesis (M.Ing. (Development and Management Engineering))--North-West University, Potchefstroom Campus, 2012.

According to Oliver (2002) the success of turnaround maintenances is measured in terms of the cost of completion, time, safety performance and the performance of the plant afterwards. The Escravos gas plant (EGP) is a gas processing plant that converts associated gas from Chevron owned crude oil wells to liquefied petroleum gas, natural gas and gas condensate (Chevron intranet. Website assessed on September 14, 2007). According to the EGP plant operations coordinator (See interview Appendix A), the plant undergoes a turnaround maintenance exercise once every two years. The major tasks done during these turnaround maintenances are 1. Change–out of three molecular sieve beds. 2. Servicing of three compressor turbines. 3. Servicing of expander turbo–machinery. 4. Clean–out of fired gas heater tubes and burners. 5. Tie–ins for major upgrades. The EGP management does not involve the contractor personnel that carry out the tasks in the management of the turnaround maintenance. The contractor’s personnel simply follow the work plans and instructions developed by the EGP management. The EGP turnaround management team consists of the coordinator who is the head of the turnaround maintenance team, shift supervisors, maintenance supervisors (rotating equipment maintenance supervisor, instrumentation and electrical maintenance supervisor, and static equipment maintenance supervisors), safety supervisors, maintenance planners, process engineers and construction supervisors. All these listed personnel in the preceding paragraph and the supervisors of the contractor teams participate in the pre–turnaround meetings which happen once a month for the first 10 months of the 12 months leading to the turnaround. The meeting frequency increases to once every two weeks during the last two months leading to the turnaround maintenance. The meeting is held daily during the turnaround maintenance and once every two weeks for the first month after the turnaround maintenance. During the preceding months to the turnaround maintenance, the work scope is defined, the job sequence outlined and schedules are developed. Resources requirements are detailed and procured. During the turnaround maintenance the focus of the turnaround meeting is to discuss potential deviations, observe at–risk behaviors and likely challenges. Plans are then made to address these deviations, challenges and at–risk behaviors. After the turnaround maintenance, “lessons learnt” are captured and the turnaround maintenance is closed out. According to the EGP coordinator (see interview in appendix A), the success of its turnaround maintenance is measured by the time used to complete the turnaround maintenance, the total recordable incident rate during the turnaround maintenance, the days away from work, the lost time injury(LTI) and the cost incurred. Poling et al noted that it is difficult to rate turnaround maintenance projects because no two turnaround maintenances strategies are exactly the same. They iterated that the most common tactics used is benchmarking and that benchmarking enables a company to measure and compare its performance against peer companies in a constructive and confidential manner. They pointed out that the quantitative differences computed between a plant and other similar plants using detailed data taxonomy can provide invaluable information regarding improvement opportunities. This is a way of effectively extending a “lessons learned” exercise across multiple companies. According to then however a critical attribute of effective reliability and maintenance benchmarking is the ability to compare disparate assets; but even small differences for similar plants can alter the value of the comparison. Existing literature indicate that the parameters the gas plant management use to rate the safety of its turnaround maintenance (i.e. the total recordable incident rate, the days away from work and the lost time injury)are reactive in nature. They are otherwise called lagging indicators. Lagging indicators are safety performance metrics that are recorded after the accident or incidents has occurred. For example lost time injury is any work related injury or illness which prevents that person from doing any work day after accident (E&P Consultancy Associates. Website assessed on June 15, 2009). In contrast the other group of metrics called pro–active metrics or leading indicators such as at–risk behaviors, near misses and preventive maintenance not completed are parameters that measure safety performance before accident occurs. Leading indicators gained popularity in the 1930’s after Heinrich postulate his iceberg theory (Wright, 2004). Heinrich’s used the iceberg analogy to explain reactive (lagging) and proactive (leading) indicators. Heinrich likened accident and at–risk behaviors to two parts of an Iceberg; the part you see above water and the part hidden under the water. The size of the iceberg above water is relatively small compared to that under water. The iceberg starts to grow under the water and only after they reach a certain size does part of the ice begin to appear above water. Heinrich believed that accidents are the result of root causes such as at–risk behaviors, inconsistencies, wrong policies, lack of training and lack of information. When the number of accidents that occur in an endeavor is measured you get relatively smaller numerical quantities when compared to the number of at–risk behaviors. Heinrich suggested that to eliminate accidents that occur infrequently, organizations must make effort to eliminate the root causes which occur very frequently. This makes sense because imagine a member of personnel coming to work intoxicated every day. Binging intoxicated at work is an at–risk behavior. The employee is very likely to be involved in an accident at some time as a result of his drinking habit. The number of times he is intoxicated if counted will be huge when compared to the impact of the accident when it does occur. The iceberg theory is supported by work from Bird (1980) and Ludwig (1980) who both attempted to establish the correct ratio of accidents to root causes in different industries. Heinrich suggested a ratio of three hundred incidents to twenty nine minor injuries to one major injury. This researcher chose to use the number of at–risk behavior exhibited by the turnaround maintenance teams to rate the safety performance of tasks despite criticism from individuals like Robotham (2004) who said that from his experience minor incidents do not have the potential to become major accidents and Wright et al (2004). Leading indicators are convenient to analysis because of their relative large quantity. In a turnaround environment, the numbers of accidents that occur are relatively few unlike the number of near misses (Bird, 1980). It is easy to statistically analyze thirty at–risk behaviors than four accidents. In addition Fleming et al (2001) noted that data from industry show much success by companies in the reduction of accidents by efforts at reducing the number of at–risk behaviors, increase the number of safety audits, and reduce the number of closed items from audits etc. Phimister et al made similar claims when they said Near miss programs improve corporate environmental, health and safety performance through the identification of near misses. Existing literature also reveals many theories about management styles and their possible impact on performance. The theories are grouped into trait theories, situational theories and behavioral theories. The trait theories tries to explain management styles by traits of the managers like initiative, wisdom, compassion and ambitious. Situational theories suggest that there is no best management style and managers will need to determine which management style best suit the situation. Behavioral theories explain management success by what successful managers do. Behavioral theorists identify autocratic, benevolent, consultative and participatory management styles. Vroom and Yetton (1973) identified variables that will determine the best management style for any given situation. The variables are; 1. Nature of the problem. Is it simple, hard, complex or clear? 2. Requirements for accuracy. What is the consequence of mistakes? 3. Acceptance of an initiative. Do you want people to use their initiative or not? 4. Time–constraints. How much time do we have to finish the task? 5. Cost constraints. Do we have enough or excess to achieve the objective? A decision model was developed by Vroom and Yago (1988)to help managers determine the best management style for different situations based on the variables listed above (See figure six). They also defined five management style could adopt, namely the; 1. Autocratic I style 2. Autocratic II style. 3. Consultative I style 4. Consultative II style 5. Group II style The autocratic I management style is a management style where the leader solves the problem alone using information that is readily available to him/her, is the normal management style of the Escravos gas plant management in all turnarounds prior to 2009. However the Vroom and Yago model recommends the Consultative II management style for the type of work done during the Escravos gas plant turnaround maintenance. According to Coye et al (1995), participatory management or consultative style II creates a sense of ownership in organization. In this management style the leader shares problem with group members individually, and asks for information and evaluation. Group members do not meet collectively, and leader makes decision alone (Vroom and Yago, 1988). Coye et al believe that this management styles instills a sense of pride and motivate employees to increase productivity. In addition they stated that employees who participate in the decisions of the organization feel like they are a part of a team with a common goal, and find their sense of self–esteem and creative fulfillment heightened. According to Filley et al (1961), Spector and Suttle did not find any significant difference in the output of employees under autocratic and participatory management style. This research studies if and how the Escravos gas plant turnaround maintenance can be improved by changing the management style from autocratic I style to consultative II style. Two tasks in the turnaround were studied; namely the change out of the molecular sieve catalyst beds and the servicing of the turbine engines. The turnaround contractor Techint Nigeria Limited divides the work group into teams responsible for specific tasks. Six teams (team A, B, C, D, E and F) were studied. EGP management will not allow the researcher to study more than these six teams for fear of the research disrupting the work. The tasks completed by these teams are amongst those not on the projects critical path so delays caused by the research will not impact the entire turnaround project provided the float on these activities were not exceeded. They also had the fewest number of personnel, so cost impact of the research work could be easier to manager. Teams A, B and C are different maintenance teams comprising of eight personnel each. They were responsible for changing the EGP molecular sieve beds A, B and C respectively in the 2007 and 2009 turnaround. Their tasks are identical because the molecular sieve beds are identical. Teams E, D and F are also maintenance teams comprising of six personnel each. They were responsible for servicing the EGP turbine engines A, B and C during the 2007 and 2009 turnaround maintenance. Their tasks are also identical because the turbine engines are identical. Consultative management style II is exercised by involving team A and team D in the development of the procedures, processes and job safety analysis of all tasks that they were assigned to complete during the 2009 turnaround maintenance. They were also permitted to participate in the turnaround maintenance meetings and to make contributions in the meetings. In the 2007 turnaround maintenance team A and team D only carried out their tasks. They did not participate in the development of procedures and job safety analysis neither did they participate in the turnaround maintenance meetings. The other four teams; team B, team C, team E and team F are used as experimental controls for the research. They did not participate in the development of the procedures, processes nor the job safety analysis for the tasks in either of the turnaround maintenance. They were also not permitted to attend the daily turnaround meetings. They only completed their tasks based on instructions given to them during the 2007 and 2009 turnaround maintenance. It was necessary to study the experimental control teams as the researcher was not sure whether task repetition, increased knowledge or improved team cohesion would lead to a reduced time or a reduced numbers of at–risk behavior. ix The research tested the hypothesis 1H0 and 1H1 and 2H0and 2H1 at the 0.025 and 0.05 level of significance as follows; Null hypothesis, 1H0: There is no significant difference in the time spent by team A and team Din 2007 when they did not participate in the development of the procedures and processes with the time in 2009 when they did(u1-u2=0). Alternate hypothesis, 1H1: There is a significant difference in the time spent by the team A and Din 2007 when they did not participate in the development of the procedures and processes with the time in 2009 when they did (u1-u2!=0). Null hypothesis, 2H0: There is no significant difference in the number of at–risk behaviors observed to have been exhibited by the team A and team D in 2007 when they did not participate in the development of the procedures and processes with the number in 2009 when they did (u1-u2=0). Alternate hypothesis, 2H1: There is a significant difference in the number of at–risk behaviors observed to have been exhibited by the team A and team D in 2007 when they did not participate in the development of the procedures and processes with the number in 2009 when they did (u1-u2!=0). The student t test was used to analyze these times and number of at–risk behavior. At the 0.025 and the 0.05 level of significance, the data show that there is no difference in the times all the teams used to complete their task in 2007 and in 2009. The researcher concludes that a change in the management style from autocratic I style to consultative II style did not lead to a reduction in the time used by any team to complete their task. However at the 0.025 and the 0.05 level of significance, there is a significant difference in the number of at–risk behaviors of the research team A and team D. There is however no significant difference in the number of at–risk behavior of the control team B, team C, team E and team F at the same level of significance. The researcher concludes that a change in the management style from autocratic I style to consultative II style lead to a reduction in the number of at–risk behavior of team A and team D. In addition the reduction in the number of at–risk behavior of team A and team D could not have been because of task repetition, increased knowledge or improved team cohesion since there is no significant difference in the number of at–risk behavior exhibited by team B, team C, team E and team F. The research can be used by the Escravos gas plant management and the management of any similar process plant to fashion out more cost effective, time effective and safer methods for carrying out their turnaround maintenance. A change in management styles may just be a better approach to improving productivity than giving financial incentives to contractors and personnel. Changes in management style will have to be managed. The change must be gradual because sudden change can be detrimental as people may just need to understand and adapt to the change. The turnaround personnel must also understand the intent so as to prevent conflicts. / Thesis (M.Ing. (Development and Management Engineering))--North-West University, Potchefstroom Campus, 2012.

This diploma thesis deals with design, realization and analysis of security and surveillance systems for buildings and spaces containing advanced components. One of the main design's parts is dedicated to intruder alarm system, access system, attendance and CCTV systems with the possibility of automatic motion tracking. Controlling and monitoring of particular subsystems is possible both locally and remotely from a computer via a web interface or by means of a software. The access to camera system from a mobile phone is also possible. IAS/ACS systems also enable controlling and transferring information about their state via SMS. The designed system was realized completely and its operating was demonstrated. The realization is described in detail including illustration of configuration of particular components. A security analysis and a possible future development of the project is summarized in the conclusion.