خرید و دانلود نسخه کامل کتاب زبان اصلی Gas and Oil Reliability Engineering: Modeling and Analysis PDF | دانلود کتاب خارجی

آنتونی رابینز میگه : من در 40 سالگی به جایی رسیدم که برای رسیدن بهش 82 سال زمان لازمه و این رو مدیون کتاب خواندن زیاد هستم.

 
The advent of reliability engineering tools coupled with the cost of oil and gas operations has changed the paradigm of maintenance technology. A simple strategy of efficient replacement of failed equipment/component has been transformed into a more complex but proactive approach for keeping equipment running at peak efficiency concept of “total process” reliability engineering and maintenance. Applied Oil and Gas Reliability Engineering: Modeling and Analysis is the first book to apply reliability value improvement practices and process enterprises lifecycle analysis to the Oil and gas Industry. With this book in hand, engineers also gain a powerful guide to the most commonly used software modeling tools which aid in the planning and execution of an effective maintenance program.Easy to understand, the book identifies equipment and procedural problems inherent to oil and gas operations then applied a systematic approach for solving them. In this book, the author combines qualitative and quantitative methods with powerful software modeling tools to assist engineers in formulating a custom maintenance policy which will ensure process efficiency, reduce projects cost, reduce redundancies and optimum equipment replacement time.Mathematic methods for analyzing failure historical dataInstruction for utilizing modeling systems such as MAROS, TARO, and BLOCKSIM and interpret resultsStep by Step approach for formulating an cost effective maintenance programIdentifies equipment and procedural problems inherent to oil and gas operationsEasily understood methods and software tools that will save time and moneyProvides a tutorial for using the most used software programs such as: MAROS, TARO, and BLOCKSIMStep by step instruction to create a custom maintenance policyReduce project cost, reduce redundancies and optimize equipment life