Книга Guidelines for Improving Plant Reliability Through Data Collection and Analysis

Формат
Язык книги
Издательство
Год издания

Written by reliability data experts, the book gives plant managers and supervisors the guidance they need to collect, and use with confidence, process equipment reliability data for risk-based decisions. Focusing on the process industries, it provides the protocol and techniques to collect and organize high quality plant performance, maintenance, and repair data from your own operations, and includes methods and examples on how the data can be converted into useful information for engineering, maintenance, safety, and loss prevention. This data can be used for: facility reliability/availability assessments; making decisions on the need for redundant systems; improving equipment designs; selecting the best equipment for specific tasks; estimating required work force; benchmarking current efforts both frequency and time; integrating predictive and preventive maintenance effort; integrating shutdowns with production needs; quantifying risks; and minimizing human reliability issues.

Код товара
20006949
Характеристики
Тип обложки
Твердый
Язык
Английский
Описание книги

Written by reliability data experts, the book gives plant managers and supervisors the guidance they need to collect, and use with confidence, process equipment reliability data for risk-based decisions. Focusing on the process industries, it provides the protocol and techniques to collect and organize high quality plant performance, maintenance, and repair data from your own operations, and includes methods and examples on how the data can be converted into useful information for engineering, maintenance, safety, and loss prevention. This data can be used for: facility reliability/availability assessments; making decisions on the need for redundant systems; improving equipment designs; selecting the best equipment for specific tasks; estimating required work force; benchmarking current efforts both frequency and time; integrating predictive and preventive maintenance effort; integrating shutdowns with production needs; quantifying risks; and minimizing human reliability issues.

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