scholarly journals OPTIMASI PREVENTIF MAINTENANCE MENGGUNAKAN METODE RELIABILITY CENTERED MAINTENNACE

2020 ◽  
Vol 2 (2) ◽  
pp. 112
Author(s):  
Adi Candra
Keyword(s):  
Failure Mode ◽  
Condition Monitoring

Persaingan industri saat ini semakin ketat, setiap perusahaan dituntut untuk selalu meningkatkan produktfitas  agar bisa bersaing dalam industri. Produktifitas dalam memanfaatkan mesin produksi menjadi salah satu target untuk mendukung terpenuinya kebutuhan dan keinginkan pelanggan. Agar produktifitas mesin tercapai maka salah satu yang perlu dipertimbangkan ialah adanya strategi penerencanaan perawatan pada setiap mesin / peralatan produksi, diantara teknik atau cara merencanakan optimasi pada mesin atau peralatan metode Reliability Centered Maintennace (RCM) bisa diaplikasikan. RCM ialah suatu teknik  maintenance yang  memanfaatkan  informasi   berkenan dengan  keandalan  suatu  komponen,  untuk mendapatkan  strategi  perawatan  yang  efektif, efisien dan  mudah  untuk  dilakukan.  PT. XYZ merupakan perusahaan yang bergerak dalam bidang garmen. Selama ini untuk perawatan mesin di perusahaan tersebut dijadwalkan pada satu tahun sekali, jika melihat dari histori kerusakan kondisi tersebut belum cukup baik untuk menjaga mesin agar tetap beroprasi. Untuk kelancaran proses produksi, perusahaan bergantung pada tingkat ketersediaan meisn atau peralatan penunjang produksi, dikarenakan ketika mesin terjadi kerusakan atau kegagalan pada saat beroperasi maka proses produksi akan terhenti dan tidak tercapainya target produksi yang diinginkan. Adapun tujuan dari penelitian ini, peneliti bermaksud untuk merencanakan strategi perawatan yang optimal dengan menggunakan cara mengidentifikasi penyebab kerusakan mesin dengan metode Failure Mode and Effect Analisis (FMEA) dan dengan  metode RCM untuk dapat mengetahui interval waktu penggantian suatu part atau komponen. Berdasarakan hasil pengumpulan data dilapangan maka peneliti melakukan anlisisi pengolahan data didapatkan hasil penyebab kerusakan dengan metode FMEA yaitu, Jarum patah, Benang putus, Spul putus benang , Sekoci kusut benang, Rotari macet tidak berputar, Faktor kegagalan ataupun kerusakan disebabkan karna belum adanya tindakan perawatan pada mesin yang disebabkan karna belum adanya jadwal perawatan dan pengecekan pada mesin. Kemudian usulan Interval waktu perawatan berdasarkan hasil dengan metode RCM yaitu, jarum interval 1 hari, benang 5 hari, spul interval 12 hari, sekoci interval 10 hari. Untuk kegagalan yang tidak dapat diprediksi maka dilakukan upaya tindakan Condition Monitoring yaitu seperti melakukan pemberian pelumas pada bagian tiang jarum, guna mengurangi terjadi gangguan-gangguan yang menghambat proses produksi.

Development of Reliable Condition Monitoring Technology for Maritime Using FMECA and Bayesian Network Modeling

2018 ◽  
Author(s):  
Shan Guan ◽  
Knut Erik Knutsen ◽  
Øystein Åsheim Alnes
Keyword(s):  
Bayesian Network ◽  
Failure Mode ◽  
Condition Monitoring ◽  
Failure Modes ◽  
Vibration Monitoring ◽  
Mode Effects ◽  
Monitoring Technique ◽  
Oil Monitoring ◽  
Criticality Analysis ◽  
Over Time

Condition monitoring technique has been widely applied in Maritime to ensure safe operation and minimise unscheduled downtime. However, in practice, ship operators need to assure that a failure mode is indeed monitored by the sensor intended for it, and the sensor has sufficient accuracy and precision for its purpose. Additionally, for a reliable condition monitoring technique, issues such as sensors degradation or drift that will reduce the data quality over time must be addressed. All these require that ship owners to select a monitoring system with the best suitable sensors technology while is economically viable. In this paper, tunnel thruster was used as a case study to demonstrate the basic approach to develop a reliable condition monitoring technique through Failure Mode, Effects and Criticality Analysis (FMECA). Based on failure modes, four types of condition monitoring techniques were identified including Vibration Monitoring, Acoustic Emission Monitoring, Wear Debris /Water in Oil Monitoring, and Thermal Monitoring, where vibration monitoring is discussed in detail as an example for defining the sensor specification. For a reliable condition monitoring technique, prediction of sensor reliability will be especially useful in the situation where sensors systems can degrade over time in service. Using temperature sensors as an example, a Bayesian network (BN) modeling approach has been carried out for assessing sensor reliability affected by aging.

scholarly journals Practicality of Tricone Bit Wear Condition Assessment

2020 ◽  
Vol 1 ◽  
Author(s):  
Hamed Rafezi ◽  
Ferri Hassani
Keyword(s):  
Failure Mode ◽  
Condition Monitoring ◽  
Research Work ◽  
Monitoring Techniques ◽  
Rolling Elements ◽  
Mcgill University ◽  
Condition Monitoring System ◽  
And Performance ◽  
Critical Components ◽  
Prediction Approach

AbstractA practical bit condition monitoring system is a necessary component of autonomous drilling. Tricone bits are widely used in blasthole drilling in mining. Bits experience a variety of wear mechanisms during the operation and rolling element failure is the dominant catastrophic failure mode of tricone bits. Bit lifetime and performance significantly vary based on the working condition and the critical components of the bit i.e. rolling elements, are invisible to the direct condition monitoring systems. At McGill University, extensive research work is conducted to develop an indirect bit condition monitoring and failure prediction approach relying on the vibration signals and the technology is currently patent pending. This article presents real-world experimental evidence to show the unreliability of conservative bit changing strategy based on the bit operation life or drop in the rate of penetration (ROP) and ineffectiveness of direct wear monitoring techniques to cover the dominant failure mode.ObjectiveTo demonstrate the unreliability of tricone bit replacement relying on bit operation life or ROP measurement and ineffectiveness of vision-based monitoring techniques for autonomous drilling.

scholarly journals Addressing the Accuracy Concerns of Measuring MOV Stem Nut Wear From Diagnostic Testing

2014 ◽  
Author(s):  
Carter (Chuck) Reames
Keyword(s):  
Failure Mode ◽  
Condition Monitoring ◽  
Diagnostic Testing ◽  
White Paper ◽  
Nuclear Industry ◽  
Transition Time ◽  
Common Cause ◽  
Common Cause Failure ◽  
Nuclear Plants ◽  
Maintenance Practice

Excessive stem nut thread wear represents a potential common-cause failure mode that could impact all rising-stem valves. The consequence of unexpected failure of stem nuts emphasizes the importance of improving condition monitoring and maintenance practice activities by identifying, quantifying and minimizing stem nut thread wear. In the nuclear industry, motor-operated valve (MOV) diagnostics estimate stem nut thread wear on safety-related valves using the stem-to-stem nut transition time (zero plateau). But the stem-to-stem nut transition time could also be affected by other variables that would lead to an inaccurate calculation of wear. Using stem-to-stem nut transition time to estimate wear, coupled with generally erring on the conservative side, usually indicates wear that is more severe than actual. This method, combined with all of the unknown variables, results in nuclear plants using valuable outage resources and dose to pull good stem nuts unnecessarily. This white paper identifies some of the variables that can be mistakenly construed as wear and offers a method that more accurately and efficiently validates this wear. Paper published with permission.

Analytical electron microscopy of grain boundaries in Al-Cu metallizations

1992 ◽  
Vol 50 (2) ◽  
pp. 1684-1685
Author(s):  
J. R. Michael ◽  
A. D. Romig ◽  
D. R. Frear
Keyword(s):  
Electron Microscopy ◽  
Integrated Circuits ◽  
Failure Mode ◽  
Current Density ◽  
Thermal History ◽  
Analytical Electron Microscopy ◽  
Cu Metallization ◽  
Analytical Electron ◽  
Interconnect Lines

Al with additions of Cu is commonly used as the conductor metallizations for integrated circuits, the Cu being added since it improves resistance to electromigration failure. As linewidths decrease to submicrometer dimensions, the current density carried by the interconnect increases dramatically and the probability of electromigration failure increases. To increase the robustness of the interconnect lines to this failure mode, an understanding of the mechanism by which Cu improves resistance to electromigration is needed. A number of theories have been proposed to account for role of Cu on electromigration behavior and many of the theories are dependent of the elemental Cu distribution in the interconnect line. However, there is an incomplete understanding of the distribution of Cu within the Al interconnect as a function of thermal history. In order to understand the role of Cu in reducing electromigration failures better, it is important to characterize the Cu distribution within the microstructure of the Al-Cu metallization.

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