شماره ركورد كنفرانس :
2333
عنوان مقاله :
Off-On line Pump Dependability study for Increasing Stability and Effectiveness of Automated Controlled Systems in Offshore Industry
عنوان به زبان ديگر :
Off-On line Pump Dependability study for Increasing Stability and Effectiveness of Automated Controlled Systems in Offshore Industry
پديدآورندگان :
Ebrahimipo V نويسنده University of Tehran - 1Department of Industrial Engineering and Institute of Energy Management and Planning Faculty of Engineering , Azadeh A نويسنده Okayama University - Department of Systems Engineering - System Analysis Laboratory , Suzuki K نويسنده Okayama University - Department of Systems Engineering - System Analysis Laboratory
تعداد صفحه :
9
كليدواژه :
maintainability , principle component analysis , Importance analysis , dependability , Reliability
سال انتشار :
1387
عنوان كنفرانس :
پنجمين كنفرانس بين المللي نگهداري و تعميرات
زبان مدرك :
فارسی
چكيده لاتين :
Automated controlled systems are vulnerable to faults. Faults can be amplified by the closed loop control systems and they candevelop into malfunction of the loop. A control loop failure will easily cause production stop or malfunction at a petrochemical plant. A way to achieve a stable and effective automated system is to enhance equipment dependability. This paper presents a standardmethodology for the analysis and improvement of pump performance to enhance total operational effectiveness and stability in offshoreindustry based on dependability. Furthermore, it is shown how a reliability–safety analysis can be conducted through equipment dependability indicators to facilitate the mitigation of hazard frequency in a plant. The main idea is to employ principle component analysis (PCA) and importance analysis (IA) to provide insight on the pumps performance. The pumps of offshore industries areconsidered according to OREDA classification. The approach identifies the critical pump and their fault through which the majorhazards could initiate in the process. At first PCA is used for assessing the performance of the pumps and ranking them. IA is thenperformed for the worst pump which could have most impact on the overall system effectiveness to classify their components based onthe component criticality measures (CCM). The analysis of the classified components can ferret out the leading causes and common-cause events to pave a way toward improving pump performance through design optimization and online fault detection whichultimately enhance overall operational effectiveness.
شماره مدرك كنفرانس :
4490271
سال انتشار :
1387
از صفحه :
1
تا صفحه :
9
سال انتشار :
1387
لينک به اين مدرک :
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