Academic literature on the topic 'Plant Maintenance and Operation'

Operation and maintenance costs have been compiled for 20 wastewater treatment plants in the range of 7 000 to 650 000 population equivalents. Great effort has been made to exclude the effects of local conditions on the costs. Data on energy and chemical consumption and manpower are given as well as the total operating costs and the distribution of manpower, energy, chemical and other costs. The results show that costs for manpower and electricity as well as total costs on a per capita basis decrease with increasing plant size. The variation between individual plants is, however, large even when differences in local conditions are accounted for.

The Kashima petrochemical complex and the Fukashiba industrial wastewater treatment plant are described. The complex consists of 19 core factories (petroleum, petrochemicals, and thermal power generation) and 39 other factories (including organic chemicals, foods, metals, machinery, etc.). The total amount of industrial wastewater produced is 59,800 m3/day. The treatment plant also accepts municipal wastewater from the surrounding area, totalling 1,100 m3/d. A system for charging for the industrial wastewater has been introduced. The water quality standards for the industrial wastewater discharged to the sewerage system and the effluent of the treatment plant are described. The main treatment process is activated sludge with operational conditions of high dissolved oxygen and long solids retention time (SRT). These operational conditions solved the problems of high ammonia and refractory substances in the influent. Complete nitrification occurred under the low alkalinity conditions and the effluent COD was low due to the long SRT. Successful operation and maintenance were achieved by good co-operation between the factories and the treatment plant.

Many oil and gas companies have suffered major production losses, and higher cost of maintenance due to the total shutdown of their plants to conduct TAM event during a certain period and according to scope of work. Therefore, TAM is considered the biggest maintenance activity in oil and gas plant in terms of manpower, material, time and cost. These plants usually undergo other maintenance strategies during normal operation of plants such as preventive, corrective and predictive maintenance. However, some components or units cannot be inspected or maintained during normal operation of plant unless plant facilities are a totally shut downed due to operating risks. These risks differ from a company to another due to many factors such as fluctuated temperatures and pressures, corrosion, erosion, cracks and fatigue caused by operating conditions, geographical conditions and economic aspects. The aim of this paper is to develop a TAM model to optimize the TAM scheduling associated with decreasing duration and increasing interval of the TAM of the gas plant. The methodology that this paper presents has three stages based on the critical and non-critical pieces of equipment. At the first stage, identifying and removing Non-critical Equipment pieces (NEs) from TAM activity to proactive maintenance types. During the second stage, the higher risk of each selected equipment is assessed in order to prioritize critical pieces of equipment based on Risk Based Inspection (RBI). At the third stage, failure probability and reliability function for those selected critical pieces of equipment are assessed. The results of development of the TAM model is led to the real optimization of TAM scheduling of gas plants that operated continuously around the clock in order to achieve a desired performance of reliability and availability of the gas plant, and reduce cost of TAM resulting from the production shutdown and cost of inspection and maintenance.

An evaluation was conducted at the County Sanitation Districts of Orange County (CSDOC) which led to the purchase and installation of the belt filter presses currently in use. A selection process was made including pre-qualification of bidders after an exhaustive nationwide search and study of all known existing belt filter press facilities. Subsequent methods were employed for purchasing belt filter presses of the same make and manufacturer. Operating experiences and maintenance costs as well as minor modifications which were found to be desirable were documented. The paper will discuss in some detail the design criteria, capacity, polymer addition system, performance at CSDOC Plant No. 1 and Plant No. 2, sludge characteristics and the effect of chemical conditioning. Discussion regarding operation and maintenance criteria, such as staffing, operating and maintenance modes, operational checks, belt life and belt specification, safety ventilation required for the removal of odorous materials and hydrogen sulfide, data recording, and polymer dosing is included. Cost considerations, including capital costs, as well as operating and maintenance costs for the past five years are covered.

In this study, an analysis is made of facility maintenance process and its modeling for economic analysis. Especially, we are looking after the modeling method for estimating its cost through input data based on facility information. This allows biding for some plant operating and maintenance orders through results of cost estimation and economic analysis. Thus, we can make proper cost sheet of plant operation and maintenance through systematic cost assessment, reliable operation and maintenance related projects in the bid through management. Furthermore, we are going to conduct a case study to apply the above mentioned model.

In recent years the electric power industry has been challenged by a high level of uncertainty and volatility brought on by deregulation and globalization. A power producer must minimize the life cycle cost while meeting stringent safety and regulatory requirements and fulfilling customer demand for high reliability. Therefore, to achieve true system excellence, a more sophisticated system-level decision-making process with a more accurate forecasting support system to manage diverse and often widely dispersed generation units as a single, easily scaled and deployed fleet system in order to fully utilize the critical assets of a power producer has been created as a response. The process takes into account the time horizon for each of the major decision actions taken in a power plant and develops methods for information sharing between them. These decisions are highly interrelated and no optimal operation can be achieved without sharing information in the overall process. The process includes a forecasting system to provide information for planning for uncertainty. A new forecasting method is proposed, which utilizes a synergy of several modeling techniques properly combined at different time-scales of the forecasting objects. It can not only take advantages of the abundant historical data but also take into account the impact of pertinent driving forces from the external business environment to achieve more accurate forecasting results. Then block bootstrap is utilized to measure the bias in the estimate of the expected life cycle cost which will actually be needed to drive the business for a power plant in the long run. Finally, scenario analysis is used to provide a composite picture of future developments for decision making or strategic planning. The decision-making process is applied to a typical power producer chosen to represent challenging customer demand during high-demand periods. The process enhances system excellence by providing more accurate market information, evaluating the impact of external business environment, and considering cross-scale interactions between decision actions. Along with this process, system operation strategies, maintenance schedules, and capacity expansion plans that guide the operation of the power plant are optimally identified, and the total life cycle costs are estimated.

The deregulation of the electric power market introduced a strong element of competition. Power plant operators strive to develop advanced operational strategies to maximize the profitability in the dynamic electric power market. New methodologies for gas turbine power plant operational modeling and optimization are needed for power plant operation to enhance operational decision making, and therefore to maximize power plant profitability by reducing operations and maintenance cost and increasing revenue. In this study, a profit based, lifecycle oriented, and unit specific methodology for gas turbine based power plant operational modeling was developed, with the power plant performance, reliability, maintenance, and market dynamics considered simultaneously. The generic methodology is applicable for a variety of optimization problems, and several applications for operational optimization were implemented using this method. A multiple time-scale method was developed for gas turbine power plants long term generation scheduling. This multiple time-scale approach allows combining the detailed granularity of the day-to-day operations with global (seasonal) trends, while keeping the resulting optimization model relatively compact. Using the multiple timescale optimization method, a profit based outage departure planning method was developed, and the key factors for this profit based approach include power plant aging, performance degradation, reliability deterioration, and the energy market dynamics. A novel approach for gas turbine based power plant sequential preventive maintenance scheduling was also introduced. Finally, methods to evaluate the impact of upgrade packages on gas turbine power plant performance, reliability, and economics were developed, and TIES methodology was applied for effective evaluation and selection of gas turbine power plant upgrade packages.

Management system for enhancing transfer of knowledge in wind power industry has not received sufficient research attention in recent times. In some cases, the wind power plant owner does not control the management system for operation and maintenance activities. Most of these wind power plants are under contract and rely upon the turbine vendor to perform most of the maintenance works and subsequently share their experience at the initial stage of operation. This research investigates the management system for the operations and maintenance activities of the offshore wind plant in Lillgrund. The research also explores the type of learning method that was adopted by the wind turbine vendor (Siemens) to transfer the operation and maintenance knowledge to the operator and owner (Vattenfall) within the speculated period. It was realized that in the next one year, the Vattenfall would be in full control of the operations and maintenance activities of the offshore wind power plant in Lillgrund. The co-management arrangement will give Siemens a good reputation and gainful experience in the wind power industry. The arrangement is achievable due to Siemens strategy to strive for constructive and long-standing relationships with their customer, based on trust, respect, and honesty. Vattenfall on the other hand, is aiming to be the partner of choice for their suppliers at the same time as best serving their internal customers. The provision for the training during the co-management period enables Siemens to strengthen their relationship with Vattenfall in this industry. In addition, Siemens also maintain close relationship with their customers and develop a large part of their portfolio, frequently on site. Vattenfall improves profitability and value creation, as a fundamental prerequisite for continued growth. The management systems of Vattenfall can be related to professional bureaucracy, this is due to the fact that it was organized to accommodate Siemens experts. Vattenfall benefits from the co-management activities of the operation and maintenance of the Lillgrund wind power plant for a specific period of time. The outcome of the research work has proven that there is an effective time-dependent proportionality for a gradual transfer of the technical knowledge of operation and maintenance from Siemens Wind AB to the Vattenfall personnel. The research started from the perspective of the maintenance method by Swedish standard for wind power, and the way things are being carried out in a more practical way in Lillgrund plant.

Els Sistemes d'Aiguamolls Construïts (SAC) de Flux Subsuperficial Horitzontal (FSH) és una tecnologia apropiada pel sanejament d'aigües residuals procedents de nuclis de població petits. No obstant els SAC de FSH són considerats una tecnologia natural, l'operació i manteniment d'aquestes depuradores és crucial per a garantir el seu correcte funcionament. Aquestes necessitats d'operació i manteniment varien entre depuradores segons (1) les característiques de la comunitat, (2) la configuració de la depuradora i el disseny del SAC de FSH i (3) les característiques del medi receptor. En aquest sentit, en aquesta tesi es presenta el desenvolupament d'un Sistema d'Ajuda a la Decisió (SAD) per a la definició de protocols d'operació i manteniment per a SAC de FSH tenint en compte els factors que causen variabilitat entre aquest tipus de depuradores (1, 2 i 3).
Horizontal Subsurface Constructed Wetlands (HSCW) is an appropriate technology to treat wastewater coming from small communities. Despite HSCW is considered a natural technology, operation and maintenance are crucial to guarantee their performance. These necessities vary according to (1) the characteristics of the community, (2) the wastewater treatment plant configuration and the HSCW design and (3) the characteristics of the receiving media. In this sense, the this thesis presents the development of an Environmental Decision Support System (EDSS) to asses the definition of operation and maintenance protocols for HSCW taking into account the aspects that cause variability among these facilities (1, 2 and 3).

Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Nuclear Engineering, 1999.
Includes bibliographical references (leaves 167-168).
Investigations of unplanned shutdowns at the Seabrook and the Pilgrim Nuclear Power Stations were carried out to improve the understanding of the cause of those events, which had been reported in Boston newspapers. Failures of turbine-generator systems and nuclear steam supply systems reduced plant reliability, while failures of safety-related systems did not. Risk analysis with fault tree modeling was carried out to quantify risk of major components in turbine-generator systems, and in nuclear steam supply systems. The risk was evaluated in terms of the frequency of unplanned shutdowns in order to identify which components are important to plant reliability, As a result, feedwater pumps, major valves installed on main steam lines, the chemical and volume control system, and switchyards are identified as risk significant components, Other equipment was also ranked according to their respective risk significance, Uncertainty analysis for failure rates of components was carried out using Monte Carlo approach to compare the result of fault tree analyses with historical data. Taking uncertainty into consideration, the analytical data and the historical data showed good agreement in regard to reliability over different time spans of operation, Maintenance practices for major components at the Seabrook Nuclear Power Station was investigated in order to correlate this practice and the components I risk significance. Some components, such as Feedwater Pumps and Main Steam Isolation Valves, are maintained by the condition-based methods; however, because they have high risk significance in terms of plant shutdowns, preventive maintenance is preferable for these components.
by Kenichi Tezuka.
S.M.

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.

Thesis (MScEng)--Stellenbosch University, 2012.
ENGLISH ABSTRACT: The aim of this thesis is to compare the aviation derived reliability metric known as the Maintenance Free Operating Period (MFOP), with the traditionally used, and commonly found, reliability metric Mean Time Between Failure (MTBF), which has over the years shown some innate disadvantages in the field of maintenance. It will be shown that this is mainly due to MTBF’s inherent acceptance of failure and the unscheduled maintenance therewith directly connected. Moreover, MFOP is successfully applied to a mining specific case study, as to date, no other application of the MFOP concept to the mining sector is known. An extensive literature study is presented, which covers concepts relevant to the overall study and which helps to contextualise the problem, revealing the major shortcomings of the commonly accepted MTBF metric. A methodology to analyse systems MFOP performance, making use of failure statistics to analyse both repairable and non-repairable systems, is presented. Validation makes use of a case study which applies the MFOP methodology to a system, specifically in the mining sector. It was shown that MFOP could be applied to the data obtained from the mining sector, producing estimates which were accurate representations of reality. These findings provide an exciting basis on which to begin to facilitate a paradigm shift in the mind set of maintenance personnel, setting reliability targets and dealing with unscheduled maintenance stops. KEYWORDS: Maintenance Free Operating Period, Mean Time Between Failure, Maintenance, Mining
AFRIKAANSE OPSOMMING: Die doel van hierdie tesis is om die Onderhoudvrye Bedryf Tydperk (OBT), ’n betroubaarheidsmaatstaf afkomstig van die lugvaart industrie, te vergelyk met die Gemiddelde Tyd Tussen Falings (GTTF) maatstaf wat tradisioneel in algemene gebruik is, maar wat oor die jare inherente nadele met betrekking tot instandhouding geopenbaar het. Dit sal bewys word dat hierdie nadele hoofsaaklik ontstaan as gevolg van die GTTF se inherente aanvaarding van failure en die ongeskeduleerde instandhouding wat daarmee gepaard gaan. OBT word ook suksesvol aangewend in ’n mynwese-spesifieke gevallestudie, wat aaangegaan is aangesien geen ander sooortgelyke aanwending in die mynwese sektor tot datum bekend is nie. ’n Breedvoerige literatuurstudie word voorgelê wat relevante konsepte dek en die probleem binne konteks plaas, en daardeur die hoof tekortkominge van die algemeen aanvaarde GTTF metriek ontbloot. ’n Metodologie waardeur analise van die stelsel werkverrigting van die OBT uitgevoer kan word met gebruik van onderbrekings statistiek om herstelbaar sowel as onherstelbare stelsels te analiseer, word voorgestel. Geldigheid word getoets deur ’n gevallestudie wat die OBT metodologie aangewend word spesifiek vir ’n stelsel in die mynwese Dit is bewys dat OBT toegepas kan word op data afkomstig van die mynwese sector, en skattings lewer wat akkurate voorstellings is van die werklikheid. Hierdie bevindinge is opwindend, en dit dien as die basis vir ’n die aanwending van ’n paradigmaskuif in die benadering van instandhoudingspersoneel tot die daarstelling van teikens vir betroubaarheid en ook in hul hantering van ongeskeduleerde instandhoudingsophoud. SLEUTELWOORDE: Onderhoudvrye Bedryf Tydperk, Gemiddelde Tyd Tussen Falings, Onderhoud, Mynbou

AbstractIn this final chapter, we summarize the DataBio learnings about how to exploit big data and AI in bioeconomy. The development platform for the software used in the 27 pilots was a central tool. The Enterprise Architecture model Archimate laid a solid basis for the complex software in the pilots. Handling data from sensors and earth observation were shown in numerous pilots. Genomic data from crop species allows us to significantly speed up plant breeding by predicting plant properties in-silico. Data integration is crucial and we show how linked data enables searches over multiple datasets. Real-time processing of events provides insights for fast decision-making, for example about ship engine conditions. We show how sensitive bioeconomy data can be analysed in a privacy-preserving way. The agriculture pilots show with clear numbers the impact of big data and AI on precision agriculture, insurance and subsidies control. In forestry, DataBio developed several big data tools for forest monitoring. In fishery, we demonstrate how to reduce maintenance cost and time as well as fuel consumption in the operation of fishing vessels as well as how to accurately predict fish catches. The chapter ends with perspectives on earth observation, machine learning, data sharing and crowdsourcing.

Petlin (Malaysia) Sdn Bhd was incorporated in March 1999 and has a Low Density Polyethylene plant that was commissioned in February 2002. The plant has a capacity of 255,000 tons per annum. The aim of the plant is to generate a reasonable return by manufacturing top quality products. To realize this aim, it’s important for the operators of the plant to operate the machines in accordance to the parameters set by the original equipment manufacturer. This will also ensure the availability and reliability of the plant. It is also important to regularly monitor the performance of the plant in relation to the operation and maintenance activities in order to prepare a better plan for continuous improvement. The Hyper-Compressors are the most fragile component in the system as they’re running under fatigue conditions and high operating pressures. It is essential to have the right processes and procedures in place to ensure that safety is not compromise in meeting the production target.

This paper describes a method that optimizes the commercial benefit by modifying gas turbine control parameters like turbine inlet temperature and variable inlet guide vane position for any dispatched power plant load. The method is a trade-off between best efficiency in the component characteristic together with higher efficiency due to increased turbine inlet temperature and lifetime. With commercial data, both effects are transferred into costs and an optimization routine identifies controller settings for minimum power plant operation cost. Test cases demonstrate the advantage of the operational cost optimization. Costs are calculated based on historic plant data with the original and the optimized operation concept. Although savings per operating hour are small, the accumulated savings over years or major inspection intervals are significant. It could be demonstrated that in regions with high fuel prices the commercial benefit of the optimized gas turbine operating concept sums up to “several million dollars” of savings. Parametric and sensitivity studies show the effect of the main parameters. Dispatch power optimization is not subject of the presented model, but can be implemented on top of the proposed concept. All in all, this work demonstrates and quantifies the commercial benefits when todays and future digital industrial capabilities are applied to gas turbine operation concepts and strategies. The proposed digital approach has the advantage of minimum investment and is attractive for gas turbine operators to generate electricity at lower costs and fuel consumption, increasing revenues and minimizing environmental impact.

This paper describes a methodology to quantify scheduled and unscheduled maintenance costs and a software framework for estimating operations and maintenance (O&M) costs of combined-cycle power plants over their operating life. Scheduled maintenance costs consist primarily of replacement and repair of hot section components of the combustion turbine that occur during planned inspections and overhaul events. Scheduled maintenance costs can be estimated based on anticipated parts life, operating conditions and parts costs. Some degree of uncertainty exists, but the range of costs is fairly well understood. Unscheduled maintenance costs are not as readily defined. Experiential data of unplanned events from a large sampling of plants over time can be used to estimate unscheduled costs. Because of the wide variation in experience from unit to unit, a range of costs are anticipated. This paper includes a description of a study of F-class combined-cycle plant data that provides the basis for defining a cost distribution of unscheduled maintenance costs. In addition, the reliability and availability statistics of these plants are used to estimate lost generation revenue due to unplanned outages, which can be significantly higher than the cost of performing the repairs to return the unit to service.

Abstract It is nowadays a common understanding that, due to the uneven availability of renewable energy sources, the operation of traditional power generation plants and especially of combined cycles has to be more flexible and subject to more frequent and, most probably, colder starts than in the past. This phenomenon translates into a negative impact on maintenance intervals and operating costs as resulting by a higher increase rate of equivalent operating hours. In addition, the optimization of start-up time, largely driven by initial components temperature, has become a key performance indicator for the profitability of such plants. The case study presented in this paper deals with a steam turbine in a combined cycle power plant, commissioned on the early 2000s. The turbine is currently operating daily for half of the year and occasionally for the other half, collecting about 150 warm and 30 cold starts per year. The application to the steam turbine of a Thermal Warming System (TWS) is analyzed in detail by assessing casing and rotor temperature distribution, in transient operation. The control algorithms, that allows maximizing the system effectiveness while safeguarding against possible issues due to uneven temperature distributions, are also discussed. The resulting increase in average starting temperature, as evidenced by online rotor temperature calculation, is then considered with respect to its benefits for maintenance optimization and plant profitability.

Diesel generator sets are installed at nuclear power plants to provide emergency power to ensure safe shut down of the reactor in the event of an accident. In the United States, all nuclear power plants belong to one of six different Diesel Generator Owner’s Groups. Some groups have been in existence for over 17 years and the members have all benefited from their participation. In the past three years, the Diesel Generator Owner’s Group concept has spread and two new groups have been formed among a number of independent diesel generator power plant owners and operators in Latin America and the Caribbean area. This paper describes: (1) how electric power plants, large and small, have formed Diesel Generator Owner’s Groups, (2) how better working relationships between the power plants and the engine manufacturer have been established, and (3) how involvement in a strong owner’s group provides significant benefits to the members. The primary goal of the groups is to increase reliability and improve performance of the diesel engines at the respective power plants. Typical objectives of effective Diesel Generator Owner’s Groups include: • Provide a mechanism for rapid resolution of specific problems with the diesel engine, generator and auxiliary systems, • Provide improved communications among the owners and the diesel generator manufacturer, • Develop a group of “technical experts” and expand that knowledge base to other plant personnel, and • Identify methods to improve diesel engine generator and overall power plant performance, reliability, availability and safety. Active participation in Diesel Generator Owner’s Group has resulted in real payback for the owners and manufacturers alike. To illustrate this fact, several unique diesel engine problems are described along with the approach the Diesel Generator Owner’s Groups used to resolve the problems. Finally, overall diesel generator reliability and availability have improved. These groups have worked to develop the best possible technical environment to continue improving diesel generator power plant performance, operation and maintenance.

This paper describes the major machinery used in a 108 megawatt combined cycle Cogeneration Plant at the Union Carbide’s Seadrift petrochemical complex. Philosophy of design, erection, start-up, and the first year of operation is discussed. Specific machinery problems and their remedies are described.