RELIABILITY BASED PERFORMANCE ASSESSMENT ON MECHANICAL MAIN SYSTEM USING RELIABILITY AVAILABILITY MAINTAINABILITY (RAM) ANALYSIS METHOD AND BLOCKSIM 9.0 AT PT. PERTAMINA GEOTHERMAL ENERGY KAMOJANG

ABSTRAKSI: In the daily life, electricity is a vital thing and something that never released from human activity. Pertamina Geothermal Energy (PGE) is a subsidiary company of PT. Pertamina (Persero) established since 2006 which utilize geothermal resources to generate electricity in Indonesia. PT. PGE Kamojang is the first geothermal field which was inaugurated on January 29th 1983. Total generating capacity of Kamojang Power Plant is 200MW consist of Unit 1, 2, 3 with total of 140MW and 60MW from Unit 4. In Power Plant, there are seven Mechanical Main System which is have important role. The seven system are, Steam Separating System (LBJ), Steam Supply and Venting System (LB), Steam Turbine and Lube Oil System (MA), Steam Return System (MAG), Gas Removal System (MAJ), Circualtiong Cooling Water System (PA), and Raw Water System (GA). When the seven system is being operated and there is a system fail, then Power Plant cannot be operated. The failure that can occur in the system can be avoided by doing research using RAM Analysis Method and Blocksim 9.0 software. Because with RAM Analysis Method and simulation through Blocksim 9.0 software, the Availability, Reliability, and Maaintainability of a system will be known. The last results of this research is also to determine the Critical Equipment in Mechanical Main System. From this research which is use the RAM Analysis Method and Blocksim 9.0 software, can be seen the Availability of Power Plant is 73,8675% and the Reliability is 68,7% for one month interval and 0,8% for one year (12 months) interval. For the critical equipment if it is based on RS FCI then the critical equipment are PA-BF207 with RS FCI 13,08%, PA-BF109 with RS FCI 12,99%, PA-BF110 with RS FCI 12,21%, MA-STRB with RS FCI 10,26%, MAG-CND with RS FCI 6,51%, MA-GEN with RS FCI 5,03%, and LBJ-SCR with RS FCI 4,04%. For the critical equipment when it is based on RS DTCI then the critical equipmetn are MA-STRB with RS DTCI 21,16%, MA-GEN with RS DTCI 11,98%, MA-BRX with RS DTCI 6,48%, MA-TRG with RS DTCI 5,55%, MA- GBR02 with RS DTCI 5,23%, MA-MTG with RS DTCI 5,05%, and MA-TBR02 with RS DTCI 5,05%. KATA KUNCI: Reliability, Availability, Maintainability, Reliability Block Diagram (RBD), Failure Mode and Effect Analysis (FMEA), Equipment Configuration, Power PlantABSTRACT: In the daily life, electricity is a vital thing and something that never released from human activity. Pertamina Geothermal Energy (PGE) is a subsidiary company of PT. Pertamina (Persero) established since 2006 which utilize geothermal resources to generate electricity in Indonesia. PT. PGE Kamojang is the first geothermal field which was inaugurated on January 29th 1983. Total generating capacity of Kamojang Power Plant is 200MW consist of Unit 1, 2, 3 with total of 140MW and 60MW from Unit 4. In Power Plant, there are seven Mechanical Main System which is have important role. The seven system are, Steam Separating System (LBJ), Steam Supply and Venting System (LB), Steam Turbine and Lube Oil System (MA), Steam Return System (MAG), Gas Removal System (MAJ), Circualtiong Cooling Water System (PA), and Raw Water System (GA). When the seven system is being operated and there is a system fail, then Power Plant cannot be operated. The failure that can occur in the system can be avoided by doing research using RAM Analysis Method and Blocksim 9.0 software. Because with RAM Analysis Method and simulation through Blocksim 9.0 software, the Availability, Reliability, and Maaintainability of a system will be known. The last results of this research is also to determine the Critical Equipment in Mechanical Main System. From this research which is use the RAM Analysis Method and Blocksim 9.0 software, can be seen the Availability of Power Plant is 73,8675% and the Reliability is 68,7% for one month interval and 0,8% for one year (12 months) interval. For the critical equipment if it is based on RS FCI then the critical equipment are PA-BF207 with RS FCI 13,08%, PA-BF109 with RS FCI 12,99%, PA-BF110 with RS FCI 12,21%, MA-STRB with RS FCI 10,26%, MAG-CND with RS FCI 6,51%, MA-GEN with RS FCI 5,03%, and LBJ-SCR with RS FCI 4,04%. For the critical equipment when it is based on RS DTCI then the critical equipmetn are MA-STRB with RS DTCI 21,16%, MA-GEN with RS DTCI 11,98%, MA-BRX with RS DTCI 6,48%, MA-TRG with RS DTCI 5,55%, MA- GBR02 with RS DTCI 5,23%, MA-MTG with RS DTCI 5,05%, and MA-TBR02 with RS DTCI 5,05%. KEYWORD: Reliability, Availability, Maintainability, Reliability Block Diagram (RBD), Failure Mode and Effect Analysis (FMEA), Equipment Configuration, Power Plan

Reliability, Availability and Maintainability Analysis for Main Oil Line Pump by Dominant Failure Modes

A good maintenance strategy requires a good reliability, availability and maintainability (RAM) analysis in order to cater the real problem to specific equipment or a system. Resolving the real problem will improve the equipment reliability to ensure higher availability of the system to operate. In this project, 2 units of main oil line (MOL) pumps of a crude oil transfer system were selected for RAM analysis. The analysis was carried out based on individual dominant failure modes that contributed to failures of the pumps which involve data of time-to-failure and time-to-repair. Reliability and maintainability analysis was carried out with the aid of Reliasoft Weibull++ software to obtain the required parameters. ReliaSoft BlockSim software was used for reliability block diagram (RBD) construction and simulation to obtain the availability of the whole system by assessing individual failure modes. External leakage – process medium was found to be the most critical failure mode which was a failure contributed by mechanical seal malfunction

Predictive Modeling for Navy Readiness Based on Resource Investment in Supply Support and Maintenance

NPS NRP Technical ReportThe Navy invests substantial resources to fleet maintenance in terms of part supply, corrective maintenance, maintenance availabilities, and overhauls. In order to measure and prioritize weapon systems investment decisions, an endurance supply metric (Es)is being developed to ensure these systems are ready for tasking across the full spectrum of operations. This research project will attempt to extend the endurance supply concept beyond a single ship by determining what would be the endurance supply for a given group of ships within line of sight of each other and assuming they could transfer parts from one ship to another. The effort will also determine the endurance supply for a single ship assuming resupply from the wholesale system is allowed. The research will provide guidance to what data should the Navy capture to make better decisions using the Es metric.N4 - Fleet Readiness & LogisticsThis research is supported by funding from the Naval Postgraduate School, Naval Research Program (PE 0605853N/2098). https://nps.edu/nrpChief of Naval Operations (CNO)Approved for public release. Distribution is unlimited.

Multiuser Communication through Power Talk in DC MicroGrids

Power talk is a novel concept for communication among control units in MicroGrids (MGs), carried out without a dedicated modem, but by using power electronics that interface the common bus. The information is transmitted by modulating the parameters of the primary control, incurring subtle power deviations that can be detected by other units. In this paper, we develop power talk communication strategies for DC MG systems with arbitrary number of control units that carry out all-to-all communication. We investigate two multiple access strategies: 1) TDMA, where only one unit transmits at a time, and 2) full duplex, where all units transmit and receive simultaneously. We introduce the notions of signaling space, where the power talk symbol constellations are constructed, and detection space, where the demodulation of the symbols is performed. The proposed communication technique is challenged by the random changes of the bus parameters due to load variations in the system. To this end, we employ a solution based on training sequences, which re-establishes the signaling and detection spaces and thus enables reliable information exchange. The presented results show that power talk is an effective solution for reliable communication among units in DC MG systems.Comment: Multiuser extension of the power talk concept. Submitted to IEEE JSA

Uncertainty Aware Mapping of Embedded Systems for Reliability, Performance, and Energy

Due to technology downscaling, embedded systems have increased in complexity and heterogeneity. The increasingly large process, voltage, and temperature variations negatively affect the design and optimization process of these systems. These factors contribute to increased uncertainties that in turn undermine the accuracy and effectiveness of traditional design approaches. In this thesis, we formulate the problem of uncertainty aware mapping for multicore embedded system platforms as a multi-objective optimization problem. We present a solution to this problem that integrates uncertainty models as a new design methodology constructed with Monte Carlo and evolutionary algorithms. The solution is uncertainty aware because it is able to model uncertainties in design parameters and to identify robust design points that limit the influence of these uncertainties onto the objective functions. The proposed design methodology is implemented as a tool that can generate the robust Pareto frontier in the objective space formed by reliability, performance, and energy consumption

Total Cost of Ownership Driven Methodology for Predictive Maintenance Implementation in Industrial Plants

Part 4: Product and Asset Life Cycle Management in Smart Factories of Industry 4.0International audienceThis paper proposes a methodology to drive from a strategic point of view the implementation of a predictive maintenance policy within an industrial plant. The methodology integrates the evaluation of system performances, used to identify the critical components, with simulation and cost analysis. The goal is to evaluate predictive maintenance implementation scenarios based on alternative condition monitoring (CM) solutions, under the lenses of Total Cost of Ownership (TCO). This allows guiding the decision on where in the industrial system to install diagnostic solutions for monitoring of asset health, by keeping a systemic and life cycle-oriented perspective. Technical systemic performances are evaluated through Monte Carlo simulation based on the Reliability Block Diagram (RBD) model of the system. To validate the methodology, an application case study focused on a production line of a relevant Italian company in the food sector is presented

Grey GERT Network Model of Equipment Lifetime Evaluation Based on Small Samples

The reliability evaluation of high reliability and long life equipment is widely concerned in recent decades. Enough failure samples of these kinds of equipment are not easy or economic to obtain in reliability test, in addition, experience information is sometimes inaccurate or uncertainty. To overcome the deficiency in traditional method which requires large numbers of samples, a quantitative analysis model of equipment reliability evaluation is proposed in this paper in view of the few failure data of equipment life tests. GERT network is introduced to describe the kinds of working states of the equipment system and random process of equipment state transition choice after stress impact of single component. Considering the uncertainty and inaccuracy of the statistical data and experience information, the parameters of GERT network are represented by interval grey number. The system equivalent transfer function could be obtained by GERT matrix solving algorithm, and the reliability evaluation of equipment system can be realized. The case study results show that the equipment reliability evaluation Grey-GERT model based on small samples would save much time with little accuracy losing. Besides, the study provides a new thinking for reliability accelerated life test

FRAMEWORK FOR RELIABILITY, MAINTAINABILITY AND AVAILABILITY ANALYSIS OF GAS PROCESSING SYSTEM DURING OPERATION PHASE

In facing many operation challenges such as increased expectation in bottom line performances and escalating overhead costs, petrochemical plants nowadays need to continually strive for higher reliability and availability by means of effective improvement tools. Reliability, maintainability and availability (RAM) analysis has been recognised as one of the strategic tools to improve plant's reliability at operation phase. Nevertheless, the application of RAM among industrial practitioners is still limited generally due to the impracticality and complexity of existing approaches. Hence, it is important to enhance the approaches so that they can be practically applied by companies to assist them in achieving their operational goals. The objectives of this research are to develop frameworks for applying reliability, maintainability and availability analysis of gas processing system at operation phase to improve system operational and maintenance performances. In addition, the study focuses on ways to apply existing statistical approach and incorporate inputs from field experts for prediction of reliability related measures. Furthermore, it explores and highlights major issues involved in implementing RAM analysis in oil and gas industry and offers viable solutions. In this study, systematic analysis on each RAM components are proposed and their roles as strategic improvement and decision making tools are discussed and demonstrated using case studies of two plant systems. In reliability and maintainability (R&M) analysis, two main steps; exploratory and inferential are proposed. Tools such as Pareto, trend plot and hazard functions; Kaplan Meier (KM) and proportional hazard model (PHM), are used in exploratory phase to identify critical elements to system's R&M performances. In inferential analysis, a systematic methodology is presented to assess R&M related measures