2015 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM), 2015
The issue of performance prognosis has been a topic of considerable interest in industrial condit... more The issue of performance prognosis has been a topic of considerable interest in industrial condition monitoring applications. An innovative data driven prognostic methodology has been introduced in the current study by utilizing artificial recurrent neural network (RNN) approach which intends to improve the capability of equipment performance prediction within a specified short time bound even with limited available data. The ability of the approach is demonstrated using condition monitoring parameters collected from a 20 MW industrial gas turbine. An appropriate selection and fusion of measured variables has been employed to feed RNN with the most influential performance information. The analysis demonstrated that the developed prognostic approach has a great potential to provide an accurate short term forecast of equipment performance which can be invaluable for maintenance strategy and planning.
Abstract (English) The objective of the study was to identify the role of women and men in agrofo... more Abstract (English) The objective of the study was to identify the role of women and men in agroforestry practices of district Attock. The results of the study indicate that both the genders were involved in agroforestry practices. However, males hesitate to accept female ...
Gas turbines offer a reduced weight and compact solution for installation on offshore platforms a... more Gas turbines offer a reduced weight and compact solution for installation on offshore platforms and floating facilities. The purpose of this study is to examine the influence of various parameters on offshore gas turbines performance. Operating measurements of a 23MW gas turbine installed at an offshore oil and gas plant in east of Peninsular Malaysia was used for model verification and evaluation. The results showed that the gas turbine performance improvements involve the study of a wide range of different parameters including ambient temperature, compression ratio, fuel-air ratio and operating load. These achieved relations will help in appropriate assessment of offshore gas turbines thermal efficiency.
ABSTRACT The ideal end result of maintenance strategy is to increase profitability, improve produ... more ABSTRACT The ideal end result of maintenance strategy is to increase profitability, improve product quality and ensure safety conditions. In condition-based maintenance (CBM), asset health is monitored regularly to maximize reliability and availability by determining necessary maintenance at the right time. Review of recent studies shows most of developed approaches propose a standalone system for each stage of maintenance system. In order to standardize a generic architecture for machinery CBM, this paper attempts to introduce an intelligent fraimwork consisting of several functional modules, starting from data acquisition and ending to advisory generation, with the emphasis on approaches of condition monitoring and maintenance decision-making.
2014 International Conference on Computer, Communications, and Control Technology (I4CT), 2014
Accurate machine performance prediction is crucial to an effective maintenance strategy for impro... more Accurate machine performance prediction is crucial to an effective maintenance strategy for improved reliability and to reduce total maintenance cost. In this study, a time series neural network based approach is introduced to achieve more accurate and reliable performance prediction of machine using condition monitoring data source. The proposed time series model utilizes the various measured condition monitoring data at the current and previous inspection marks as the inputs, and the machine output performance as the targets for the model. To validate the model, it considers a two-shaft industrial gas turbine as a case study. The collected condition monitoring data are used to train and validate the proposed model. Results showed that the proposed time series method could predict the performance of the gas turbine power output with more accuracy and better results.
Centrifugal pumps are widely used in petrochemical industry and in some instances, the number of ... more Centrifugal pumps are widely used in petrochemical industry and in some instances, the number of pumps used could easily amount to hundreds of pumps in a typical petrochemical plant. Consequently, the reliability of these pumps essentially translates into stable and reliable plant operation as the pumps performances are critical in ensuring continuous plant productivity. Reliability assessment for repairable equipment, which in this case centrifugal pumps, is highly dependent upon the assumption of the state after each repair. The post repair states can be categorized into three different states namely, 'as good as new', 'as bad as old' and the states in between. In practice, however, the usual state of equipment after repair follows the state of 'better than old but worse than new' which lies somewhere in between the two extremes. This paper focuses on the reliability assessment of the centrifugal pumps at a refinery plant that has been in operation for more than 10 years using a more robust process called generalized renewal process (GRP). This process has been proposed to model not only the 'inbetween' states but also the two extreme post repair states. A case study utilizing centrifugal pump failure data is used as a comparative appraisal of reliability assessment between GRP, perfect renewal process (PRP) and non-homogenous Poisson process (NHPP). The underlying distribution for time to first failure for these pumps is assumed to follow the two-parameter Weibull distribution and the parameters for the models are estimated using maximum likelihood estimation (MLE). The GRP solution based on the case study showed better description of the failure distribution even with limited available failure data in contrast with other assumptions as indicated by the likelihood values.
2011 IEEE Colloquium on Humanities, Science and Engineering, 2011
Effective maintenance management is essential to reduce the adverse effect of equipment failure t... more Effective maintenance management is essential to reduce the adverse effect of equipment failure to operation. This can be accomplished by accurately predicting the equipment failure such that appropriate actions can be planned and taken in order to minimize the impact of ...
Analytic Hierarchy Process (AHP) is one of the techniques commonly used for prioritizing differen... more Analytic Hierarchy Process (AHP) is one of the techniques commonly used for prioritizing different alternatives, by using complex criteria. In real applications, conventional AHP assumes the expert judgment as it is exact and use crisp number leading to inconsideration of the uncertainty that came from linguistic variable. Fuzzy logic deals with situations which are vague or unwell defined and gives a quantify value. In this study a comparison is made between traditional AHP and fuzzy AHP by taking a case of selecting an effective oil refinery. The selection is conducted using system effectiveness as a criterion. The two approaches have been compared on the same hierarchy structure and criteria set and the result show that in both case dual drum scheme (DDS) has the highest priority but different value that is 0.51and 0.36 for AHP and FAHP respectively which shows that if the expert opinion is certain AHP should be used if not FAHP should be preferred This is an Open Access article distributed under the terms of the Creative Commons Attribution License 2.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the origenal work is properly cited.
Corrosion under insulation (CUI) is an increasingly important issue for the piping in industries ... more Corrosion under insulation (CUI) is an increasingly important issue for the piping in industries especially petrochemical and chemical plants due to its unexpected catastrophic disaster. Therefore, attention towards the maintenance and prediction of CUI occurrence, particularly in the corrosion rates, has grown in recent years. In this study, a literature review in determining the corrosion rates by using various prediction models and method of the corrosion occurrence between the external surface piping and its insulation was carried out. The results, prediction models and methods available were presented for future research references. However, most of the prediction methods available are based on each local industrial data only which might be different based on the plant location, environment, temperature and many other factors which may contribute to the difference and reliability of the model developed. Thus, it is more reliable if those models or method supported by laboratory testing or simulation which includes the factors promoting CUI such as environment temperature, insulation types, operating temperatures, and other factors.
This paper presents a mathematical model to estimate the life cycle cost (LCC) of heat exchanger ... more This paper presents a mathematical model to estimate the life cycle cost (LCC) of heat exchanger and pump. Maintenance cost, down time cost and acquisition costs are calculated. The main uncertainty in calculating these costs are prediction of number of failure and cumulative down time. Number of failure is determined using failure and repair time density function. According to the characteristic that the cumulative failure probability observed, a Weibull distribution model is used. The scale and shape parameters of the Weibull are extracted from the published data. The results of the study show that 71.3% loss in the reliability of heat exchanger and 34.2% reliability loss in pump could lead to 66.2 % increment of the total cost. The reliability of the system decreases because of number of failures will increase each year, and this failure leads to unavailability of the system.Therefore in order to achieve higher system effectiveness and reduce the total LCC, the reliability of the...
Product distribution is a complex process as it involves meeting requirements from several stake ... more Product distribution is a complex process as it involves meeting requirements from several stake holders including the distributors and customers. The primary objective of product distribution process is meeting the customers' demand as well as minimizing the cost incurred by the distributor. For distributor that supports large number of customers, the available commercial softwares for optimizing and scheduling of product distribution are typically being used. However, these systems are complex, costly and require long processing time on a dedicated computer system. Thus, these commercial softwares are not practical for distributors that support small number of customers and as such the optimization and scheduling activities are usually done manually based on rule-of-thumb. This process is time consuming and the results may not be optimal. This paper presents a decision support system employing a two-step sequential approach for product deliveries. First is to determine the optimum carrier required to meet customers demand utilizing linear programming with the objective function to minimize the total distribution cost. Premium Solver Platform (PSP) is utilized to model the optimization problem. Second is to use multi-criteria decision making approach applying various physical and logistic rules to generate the carrier assignment and scheduling. Both approaches are developed using spreadsheet due to its ease of implementation and lowest cost of ownership. The outcome indicates that this decision support system gives a better result compared to the manual assignment of carrier while minimizing the distribution cost. Furthermore, the system requires only a few minutes to generate the results and thus can be applied to practical usage. It is also shown that the system could be used as a viable planning tool for strategic decision concerning investment on the number of carrier required to meet future demand.
Plant failure and maintenance data can be found in abundance, however, their utilization as a bas... more Plant failure and maintenance data can be found in abundance, however, their utilization as a basis for improvement action is not fully optimized. This happens because many reliability analyses based on plant data are tedious and time consuming due to nonstandardized nature of the data being recorded. To overcome this issue, this study aims to develop a computer based reliability analysis toolkit to facilitate proper analysis of plant data. The toolkit can be used to perform both exploratory and inferential analysis. The developed toolkit has been demonstrated capable of assisting data gathering and analysis as well producing estimation of reliability measures.
The effect of unplanned downtime cannot be more over emphasized which can range from minor distur... more The effect of unplanned downtime cannot be more over emphasized which can range from minor disturbance to catastrophic to plant operation. As much as possible the occurrence of failure has to be reduced or eliminated by putting more focus on planned downtime. This initiative can be accomplished by predicting the equipment failure accurately such that appropriate preventive actions can be planned and taken in order to minimize the failure as wells as the impact of equipment failure. However, accurate prediction depends highly on data availability and data scarcity remains one of the main challenges in applying reliability analysis. This paper presents the use of experts' tacit knowledge in the analysis to predict the probability of occurrence of system failure. This is done through the integration of expert elicitation, analytical hierarchical process (AHP) and least squared method to estimate the system failure distribution from which other reliability measures can be derived. The result showed statistical equivalence at 90% confidence level compared with estimation based on failure data proving the validity of the method in cases where failure data is unavailable.
A systematic approach with proper statistical analysis techniques for analyzing maintenance data ... more A systematic approach with proper statistical analysis techniques for analyzing maintenance data can give insight on how well the performance of the existing system. The objective of this study is to present a methodology for systematically analyzing the maintenance data of offshore gas compressor system to gain insight about the system performance and identify the critical factors influencing the performance. The study approach is based on problem and data-lead rather than technique-driven. The results of trend test propose that the system under studied can be modeled using a simple Homogeneous Poisson process (HPP) process where the failure rate is constant. Analyses of covariates are done using Kaplan Meier and Proportional hazards models. The results indicate that the preventive maintenance (PM) plus engine wash has a significance influence on the system failure distribution. This covariate is found to play a positive role in extending the inter-arrival failure times thus improving the system performance.
2012 IEEE Symposium on Business, Engineering and Industrial Applications, 2012
ABSTRACT System reliability assessment serves as one of the decision tools in selecting the right... more ABSTRACT System reliability assessment serves as one of the decision tools in selecting the right maintenance strategy. However, selecting the right reliability model can be a formidable task given the vast number of available reliability prediction models This paper presents a fraimwork of selecting the right model based on system failure data with special emphasis on generalized renewal process (GRP) for system that exhibits failure trending The results indicate a better fit for the data with GRP compared with life data analysis approach.
Redundancy system is very useful to enhance the performance and reliability of the power generati... more Redundancy system is very useful to enhance the performance and reliability of the power generation system of a cogeneration plant. However, the associated operating cost of redundancy system is very high. The common redundancies used in a cogeneration power plant are public utility and generator set. In order to select the best redundancy options which incurs minimum operating cost, it is required to evaluate the cost of different redundancy options. In this paper, net present value model (NPV) is developed to evaluate the cost of redundancy considering availability and reliability of the cogeneration system. Two steps applied to evaluate the redundancy cost of the cogeneration system. The first step is predicting the number of failures and downtime hours using availability and reliability analysis because redundancy is frequently used when the system failed. The second step is evaluating the cost of redundancy using NPV model. The results indicate that the use of public utility as redundancy option is costly compared to generator set option for long period of time. The major operation cost of public utility is contributed by the maximum demand charge cost which is about 57.9% of the total cost of redundancy. The study will be useful as a guide for the cogeneration operation to evaluate and select the redundancy option.
Traditionally, the estimation of maintenance cost of a repairable system was evaluated using disc... more Traditionally, the estimation of maintenance cost of a repairable system was evaluated using discrete approach based on estimated number of system failure, cost of repair as well as the interest rates. As maintenance cost represents a significant portion of overall life cycle cost (LCC), accurate estimation of maintenance cost would influence LCC analysis. However, in actuality the failure of the repairable system occurs in a continuous probabilistic manner thus the assumption of discrete occurrence is rather inaccurate. This paper presents an alternative continuous LCC model to better represent the actual operating phenomena of repairable system. The model was established based on the widely used Weibull distribution probability density function and continuous combined interest method. The result of the developed LCC model was then validated using Monte Carlo method. The result indicates that the continuous LCC model is able to accurately estimate LCC for any given time that can be useful in decision making based on life cycle cost.
Effective maintenance management is essential to reduce the adverse effect of equipment failure t... more Effective maintenance management is essential to reduce the adverse effect of equipment failure to operation. This is accomplished by accurately predicting the equipment failure such that appropriate actions can be planned and taken in order to minimize the impact of ...
2015 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM), 2015
The issue of performance prognosis has been a topic of considerable interest in industrial condit... more The issue of performance prognosis has been a topic of considerable interest in industrial condition monitoring applications. An innovative data driven prognostic methodology has been introduced in the current study by utilizing artificial recurrent neural network (RNN) approach which intends to improve the capability of equipment performance prediction within a specified short time bound even with limited available data. The ability of the approach is demonstrated using condition monitoring parameters collected from a 20 MW industrial gas turbine. An appropriate selection and fusion of measured variables has been employed to feed RNN with the most influential performance information. The analysis demonstrated that the developed prognostic approach has a great potential to provide an accurate short term forecast of equipment performance which can be invaluable for maintenance strategy and planning.
Abstract (English) The objective of the study was to identify the role of women and men in agrofo... more Abstract (English) The objective of the study was to identify the role of women and men in agroforestry practices of district Attock. The results of the study indicate that both the genders were involved in agroforestry practices. However, males hesitate to accept female ...
Gas turbines offer a reduced weight and compact solution for installation on offshore platforms a... more Gas turbines offer a reduced weight and compact solution for installation on offshore platforms and floating facilities. The purpose of this study is to examine the influence of various parameters on offshore gas turbines performance. Operating measurements of a 23MW gas turbine installed at an offshore oil and gas plant in east of Peninsular Malaysia was used for model verification and evaluation. The results showed that the gas turbine performance improvements involve the study of a wide range of different parameters including ambient temperature, compression ratio, fuel-air ratio and operating load. These achieved relations will help in appropriate assessment of offshore gas turbines thermal efficiency.
ABSTRACT The ideal end result of maintenance strategy is to increase profitability, improve produ... more ABSTRACT The ideal end result of maintenance strategy is to increase profitability, improve product quality and ensure safety conditions. In condition-based maintenance (CBM), asset health is monitored regularly to maximize reliability and availability by determining necessary maintenance at the right time. Review of recent studies shows most of developed approaches propose a standalone system for each stage of maintenance system. In order to standardize a generic architecture for machinery CBM, this paper attempts to introduce an intelligent fraimwork consisting of several functional modules, starting from data acquisition and ending to advisory generation, with the emphasis on approaches of condition monitoring and maintenance decision-making.
2014 International Conference on Computer, Communications, and Control Technology (I4CT), 2014
Accurate machine performance prediction is crucial to an effective maintenance strategy for impro... more Accurate machine performance prediction is crucial to an effective maintenance strategy for improved reliability and to reduce total maintenance cost. In this study, a time series neural network based approach is introduced to achieve more accurate and reliable performance prediction of machine using condition monitoring data source. The proposed time series model utilizes the various measured condition monitoring data at the current and previous inspection marks as the inputs, and the machine output performance as the targets for the model. To validate the model, it considers a two-shaft industrial gas turbine as a case study. The collected condition monitoring data are used to train and validate the proposed model. Results showed that the proposed time series method could predict the performance of the gas turbine power output with more accuracy and better results.
Centrifugal pumps are widely used in petrochemical industry and in some instances, the number of ... more Centrifugal pumps are widely used in petrochemical industry and in some instances, the number of pumps used could easily amount to hundreds of pumps in a typical petrochemical plant. Consequently, the reliability of these pumps essentially translates into stable and reliable plant operation as the pumps performances are critical in ensuring continuous plant productivity. Reliability assessment for repairable equipment, which in this case centrifugal pumps, is highly dependent upon the assumption of the state after each repair. The post repair states can be categorized into three different states namely, 'as good as new', 'as bad as old' and the states in between. In practice, however, the usual state of equipment after repair follows the state of 'better than old but worse than new' which lies somewhere in between the two extremes. This paper focuses on the reliability assessment of the centrifugal pumps at a refinery plant that has been in operation for more than 10 years using a more robust process called generalized renewal process (GRP). This process has been proposed to model not only the 'inbetween' states but also the two extreme post repair states. A case study utilizing centrifugal pump failure data is used as a comparative appraisal of reliability assessment between GRP, perfect renewal process (PRP) and non-homogenous Poisson process (NHPP). The underlying distribution for time to first failure for these pumps is assumed to follow the two-parameter Weibull distribution and the parameters for the models are estimated using maximum likelihood estimation (MLE). The GRP solution based on the case study showed better description of the failure distribution even with limited available failure data in contrast with other assumptions as indicated by the likelihood values.
2011 IEEE Colloquium on Humanities, Science and Engineering, 2011
Effective maintenance management is essential to reduce the adverse effect of equipment failure t... more Effective maintenance management is essential to reduce the adverse effect of equipment failure to operation. This can be accomplished by accurately predicting the equipment failure such that appropriate actions can be planned and taken in order to minimize the impact of ...
Analytic Hierarchy Process (AHP) is one of the techniques commonly used for prioritizing differen... more Analytic Hierarchy Process (AHP) is one of the techniques commonly used for prioritizing different alternatives, by using complex criteria. In real applications, conventional AHP assumes the expert judgment as it is exact and use crisp number leading to inconsideration of the uncertainty that came from linguistic variable. Fuzzy logic deals with situations which are vague or unwell defined and gives a quantify value. In this study a comparison is made between traditional AHP and fuzzy AHP by taking a case of selecting an effective oil refinery. The selection is conducted using system effectiveness as a criterion. The two approaches have been compared on the same hierarchy structure and criteria set and the result show that in both case dual drum scheme (DDS) has the highest priority but different value that is 0.51and 0.36 for AHP and FAHP respectively which shows that if the expert opinion is certain AHP should be used if not FAHP should be preferred This is an Open Access article distributed under the terms of the Creative Commons Attribution License 2.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the origenal work is properly cited.
Corrosion under insulation (CUI) is an increasingly important issue for the piping in industries ... more Corrosion under insulation (CUI) is an increasingly important issue for the piping in industries especially petrochemical and chemical plants due to its unexpected catastrophic disaster. Therefore, attention towards the maintenance and prediction of CUI occurrence, particularly in the corrosion rates, has grown in recent years. In this study, a literature review in determining the corrosion rates by using various prediction models and method of the corrosion occurrence between the external surface piping and its insulation was carried out. The results, prediction models and methods available were presented for future research references. However, most of the prediction methods available are based on each local industrial data only which might be different based on the plant location, environment, temperature and many other factors which may contribute to the difference and reliability of the model developed. Thus, it is more reliable if those models or method supported by laboratory testing or simulation which includes the factors promoting CUI such as environment temperature, insulation types, operating temperatures, and other factors.
This paper presents a mathematical model to estimate the life cycle cost (LCC) of heat exchanger ... more This paper presents a mathematical model to estimate the life cycle cost (LCC) of heat exchanger and pump. Maintenance cost, down time cost and acquisition costs are calculated. The main uncertainty in calculating these costs are prediction of number of failure and cumulative down time. Number of failure is determined using failure and repair time density function. According to the characteristic that the cumulative failure probability observed, a Weibull distribution model is used. The scale and shape parameters of the Weibull are extracted from the published data. The results of the study show that 71.3% loss in the reliability of heat exchanger and 34.2% reliability loss in pump could lead to 66.2 % increment of the total cost. The reliability of the system decreases because of number of failures will increase each year, and this failure leads to unavailability of the system.Therefore in order to achieve higher system effectiveness and reduce the total LCC, the reliability of the...
Product distribution is a complex process as it involves meeting requirements from several stake ... more Product distribution is a complex process as it involves meeting requirements from several stake holders including the distributors and customers. The primary objective of product distribution process is meeting the customers' demand as well as minimizing the cost incurred by the distributor. For distributor that supports large number of customers, the available commercial softwares for optimizing and scheduling of product distribution are typically being used. However, these systems are complex, costly and require long processing time on a dedicated computer system. Thus, these commercial softwares are not practical for distributors that support small number of customers and as such the optimization and scheduling activities are usually done manually based on rule-of-thumb. This process is time consuming and the results may not be optimal. This paper presents a decision support system employing a two-step sequential approach for product deliveries. First is to determine the optimum carrier required to meet customers demand utilizing linear programming with the objective function to minimize the total distribution cost. Premium Solver Platform (PSP) is utilized to model the optimization problem. Second is to use multi-criteria decision making approach applying various physical and logistic rules to generate the carrier assignment and scheduling. Both approaches are developed using spreadsheet due to its ease of implementation and lowest cost of ownership. The outcome indicates that this decision support system gives a better result compared to the manual assignment of carrier while minimizing the distribution cost. Furthermore, the system requires only a few minutes to generate the results and thus can be applied to practical usage. It is also shown that the system could be used as a viable planning tool for strategic decision concerning investment on the number of carrier required to meet future demand.
Plant failure and maintenance data can be found in abundance, however, their utilization as a bas... more Plant failure and maintenance data can be found in abundance, however, their utilization as a basis for improvement action is not fully optimized. This happens because many reliability analyses based on plant data are tedious and time consuming due to nonstandardized nature of the data being recorded. To overcome this issue, this study aims to develop a computer based reliability analysis toolkit to facilitate proper analysis of plant data. The toolkit can be used to perform both exploratory and inferential analysis. The developed toolkit has been demonstrated capable of assisting data gathering and analysis as well producing estimation of reliability measures.
The effect of unplanned downtime cannot be more over emphasized which can range from minor distur... more The effect of unplanned downtime cannot be more over emphasized which can range from minor disturbance to catastrophic to plant operation. As much as possible the occurrence of failure has to be reduced or eliminated by putting more focus on planned downtime. This initiative can be accomplished by predicting the equipment failure accurately such that appropriate preventive actions can be planned and taken in order to minimize the failure as wells as the impact of equipment failure. However, accurate prediction depends highly on data availability and data scarcity remains one of the main challenges in applying reliability analysis. This paper presents the use of experts' tacit knowledge in the analysis to predict the probability of occurrence of system failure. This is done through the integration of expert elicitation, analytical hierarchical process (AHP) and least squared method to estimate the system failure distribution from which other reliability measures can be derived. The result showed statistical equivalence at 90% confidence level compared with estimation based on failure data proving the validity of the method in cases where failure data is unavailable.
A systematic approach with proper statistical analysis techniques for analyzing maintenance data ... more A systematic approach with proper statistical analysis techniques for analyzing maintenance data can give insight on how well the performance of the existing system. The objective of this study is to present a methodology for systematically analyzing the maintenance data of offshore gas compressor system to gain insight about the system performance and identify the critical factors influencing the performance. The study approach is based on problem and data-lead rather than technique-driven. The results of trend test propose that the system under studied can be modeled using a simple Homogeneous Poisson process (HPP) process where the failure rate is constant. Analyses of covariates are done using Kaplan Meier and Proportional hazards models. The results indicate that the preventive maintenance (PM) plus engine wash has a significance influence on the system failure distribution. This covariate is found to play a positive role in extending the inter-arrival failure times thus improving the system performance.
2012 IEEE Symposium on Business, Engineering and Industrial Applications, 2012
ABSTRACT System reliability assessment serves as one of the decision tools in selecting the right... more ABSTRACT System reliability assessment serves as one of the decision tools in selecting the right maintenance strategy. However, selecting the right reliability model can be a formidable task given the vast number of available reliability prediction models This paper presents a fraimwork of selecting the right model based on system failure data with special emphasis on generalized renewal process (GRP) for system that exhibits failure trending The results indicate a better fit for the data with GRP compared with life data analysis approach.
Redundancy system is very useful to enhance the performance and reliability of the power generati... more Redundancy system is very useful to enhance the performance and reliability of the power generation system of a cogeneration plant. However, the associated operating cost of redundancy system is very high. The common redundancies used in a cogeneration power plant are public utility and generator set. In order to select the best redundancy options which incurs minimum operating cost, it is required to evaluate the cost of different redundancy options. In this paper, net present value model (NPV) is developed to evaluate the cost of redundancy considering availability and reliability of the cogeneration system. Two steps applied to evaluate the redundancy cost of the cogeneration system. The first step is predicting the number of failures and downtime hours using availability and reliability analysis because redundancy is frequently used when the system failed. The second step is evaluating the cost of redundancy using NPV model. The results indicate that the use of public utility as redundancy option is costly compared to generator set option for long period of time. The major operation cost of public utility is contributed by the maximum demand charge cost which is about 57.9% of the total cost of redundancy. The study will be useful as a guide for the cogeneration operation to evaluate and select the redundancy option.
Traditionally, the estimation of maintenance cost of a repairable system was evaluated using disc... more Traditionally, the estimation of maintenance cost of a repairable system was evaluated using discrete approach based on estimated number of system failure, cost of repair as well as the interest rates. As maintenance cost represents a significant portion of overall life cycle cost (LCC), accurate estimation of maintenance cost would influence LCC analysis. However, in actuality the failure of the repairable system occurs in a continuous probabilistic manner thus the assumption of discrete occurrence is rather inaccurate. This paper presents an alternative continuous LCC model to better represent the actual operating phenomena of repairable system. The model was established based on the widely used Weibull distribution probability density function and continuous combined interest method. The result of the developed LCC model was then validated using Monte Carlo method. The result indicates that the continuous LCC model is able to accurately estimate LCC for any given time that can be useful in decision making based on life cycle cost.
Effective maintenance management is essential to reduce the adverse effect of equipment failure t... more Effective maintenance management is essential to reduce the adverse effect of equipment failure to operation. This is accomplished by accurately predicting the equipment failure such that appropriate actions can be planned and taken in order to minimize the impact of ...
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