Reliability and availability analysis of a hybrid cooling system with water-side economizer in data center

Wang, Jiaqiang; Zhang, Quan; Yoon, Sung‐Min; Yu, Yuebin

doi:10.1016/j.buildenv.2018.11.021

Cited by 40 publications

(14 citation statements)

References 11 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…A reliability block diagram (RBD) is a diagramming method for showing how components of reliability contribute to the success or failure of a complex system. An RBD can be converted into a success tree by replacing the series path with AND gates and parallel paths with OR gates [17]- [23].…”

Section: Reliability Block Diagrammentioning

confidence: 99%

Sterilizer Reliability Analysis Using Reliability Block Diagram Based on Failure Identification Through Fault Tree Analysis

Bahri

Fatimah

Jalil

et al. 2021

Int. J. Eng. Scie. and Inform. Technology.

View full text Add to dashboard Cite

A sterilizer is a pressurized steam vessel used to boil palm oil. The condition of the sterilizer at PT .X often emits steam at the door and body of the stew. Throughout 2020, there were 12 critical components that were frequently damaged, such as ball valve, actuator, exhaust valve, packing door, elbow, condensate nozzle, liner, pipe, condensate valve, strainer valve, pipe flange, and packing flange. Fault Tree Analysis is an analysis tool that graphically translates the combinations of errors that cause system failures. Reliability Block Diagram is a diagramming method for showing how reliability components contribute to the success or failure of a complex system. Based on the results of the failure calculation using fault tree analysis, the probability of failure of the horizontal sterilizer component is the ball valve 12.2%, exhaust valve 10.9% actuator 6%, door packing 0.24%, elbow 0.24%, condensate nozzle 4.8%, liner 8.61%, 0.25% pipe, 0.21% condensate valve, 4.4% filter valve, 0.22% pipe flange and 0.27% packing flange. The reliability value of the horizontal sterilizer from the calculation using the reliability block diagram is 85.69% if it operates for 8 hours, 62.93% if it operates for 27 hours, 39.6% if it operates for 54 hours, 13.34% if it operates for 117 hours. o'clock. o'clock. o'clock. hours and 1.81% when operating for 234 hours. To maintain reliability above 60%, the preventive maintenance schedule is: Every 80 hours of operation a door packing inspection is carried out. Every 234 hours of operation, elbow tubing and flanges are checked. Every 300 hours of operation, a pipe inspection is carried out. Every 450 operational hours an inspection is carried out on the ball valve, condensate nozzle, liner, actuator, and exhaust valve. Every 30 hours of operation, valve condensate, filter valves and packing flanges are checked.

show abstract

Section: Reliability Block Diagrammentioning

confidence: 99%

Sterilizer Reliability Analysis Using Reliability Block Diagram Based on Failure Identification Through Fault Tree Analysis

Bahri

Fatimah

Jalil

et al. 2021

Int. J. Eng. Scie. and Inform. Technology.

View full text Add to dashboard Cite

show abstract

“…On the other hand, in the design of a DCP-IES, the reliability of the energy supply is very important [32], as any equipment failure may cause instability or even failure of the entire energy system. To improve the reliability of the DCP-IES, standby devices are typically provided [33]. However, this involves increasing the initial investment.…”

Section: Literature Reviewmentioning

confidence: 99%

Configuration Optimization Model for Data-Center-Park-Integrated Energy Systems under Economic, Reliability, and Environmental Considerations

Liu

et al. 2020

Energies

View full text Add to dashboard Cite

The analysis of energy configuration in the planning of data-center-park-integrated energy systems (DCP-IESs) has become an enormous challenge, owing to multi-energy complementarity, energy cascade use, and energy security. In this study, a configuration model of DCP-IESs was established to obtain the economic and low-carbon energy uses of the data centers, based on mixed integer linear programming. In the model, carbon emissions were converted to economic indicators through carbon pricing. Then, the configuration model was modified according to the security of the proposed device switching logic, and the Markov-based reliability estimation method was used to ensure the redundant design of the configuration. Using the new energy configuration method, the DCP-IES configuration scheme could be obtained under economical, low-carbon, and high reliability conditions. A data center park in Shanghai was selected as a case study, and the results are as follows: it will only take 2.88 years for the economics of DCP-IES to reach those of traditional data center energy systems. Additionally, the use of configuration model in DCP-IES would result in a reduction in annual carbon emissions of 39,323 tons, with a power usage effectiveness of 1.388, whereas an increase in reliability results in an increasingly faster increase in the initial investment cost.

show abstract

“…Analisis RAM dapat dilakukan dengan menentukan komponen kritis yang memiliki availabilitas terendah dalam sistem Klasifikasi ABC dan pemodelan simulasi dapat dilakukan dalam analisis kuantitatif. Setelah menentukan komponen kritis, dilakukan analisis skenario dengan menerapkan strategi maintenance persediaan spare part pada komponen kritis tersebut (Wang, Zhang, Yoon, & Yu, 2019 , dilakukan analisis availabilitas dengan mempertimbangkan persediaan spare part. Dari penelitian ini telah diuji bahwa peningkatan persediaan spare part dapat meningkatkan availabilitas secara signifikan.…”

Section: Pendahuluanunclassified

Analisis Availabilitas Perusahaan Pythalic Anhydride Berdasarkan Persediaan Spare Part dan Penyangga

Siswanto

Salsabila

Rochmadhan

et al. 2020

Teknoin

View full text Add to dashboard Cite

Penelitian ini akan membahas perusahaan kimia yang memproduksi Pythalic Anhydride (PA) di Indonesia. Perusahaan ini memiliki kapasitas 70.000 Metric Ton Per Year (MTPY). Selama 2017, total waktu produksi adalah 6.699,8 jam atau rata-rata 23 hari. Namun, dibandingkan dengan kapasitas produksi, perusahaan hanya dapat memenuhi permintaan dalam waktu 20 hari tiap bulannya. Waktu produksi minimum diperlukan untuk mencapai layanan pelanggan yang optimal dan biaya minimum. Perbedaan antara kapasitas dan kondisi yang ada disebabkan oleh penutupan pabrik. Penutupan pabrik disebabkan oleh kehabisan persediaan material dan kerusakan mesin. Frekuensi penutupan pabrik relatif tinggi. Selama 2014 hingga 2017, pabrik ditutup 48 kali dengan MTTF 3,1 hari dan MTTR 23 jam. Analisis reliability, availability, dan maintainability (RAM analysis) dilakukan untuk mengatasi masalah ini. Secara khusus, penelitian ini akan fokus pada pengembangan skenario dengan melakukan percobaan pada persediaan penyangga suku cadang untuk mengurangi waktu produksi dan meningkatkan availabilitas. Pendekatan simulasi digunakan dalam penelitian ini untuk memodelkan perilaku stokastik. Berdasarkan hasil percobaan, waktu produksi berkurang 232,7 jam dan availabilitas menjadi 0,8996. Analisis keuntungan dan biaya dapat dilakukan pada penelitian selanjutnya untuk mendapatkan solusi optimal.

show abstract

Reliability and availability analysis of a hybrid cooling system with water-side economizer in data center

Cited by 40 publications

References 11 publications

Sterilizer Reliability Analysis Using Reliability Block Diagram Based on Failure Identification Through Fault Tree Analysis

Sterilizer Reliability Analysis Using Reliability Block Diagram Based on Failure Identification Through Fault Tree Analysis

Configuration Optimization Model for Data-Center-Park-Integrated Energy Systems under Economic, Reliability, and Environmental Considerations

Analisis Availabilitas Perusahaan Pythalic Anhydride Berdasarkan Persediaan Spare Part dan Penyangga

Contact Info

Product

Resources

About