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 organ
Guidelines for Improving Plant Reliability Through Data Collection and Analysis
โ Scribed by Center for Chemical Process Safety (CCPS)
- Publisher
- Wiley-AIChE
- Year
- 1998
- Tongue
- English
- Leaves
- 215
- Edition
- 1
- Category
- Library
No coin nor oath required. For personal study only.
โฆ Synopsis
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.
๐ SIMILAR VOLUMES
<p>The ever increasing public demand and the setting-up of national and international legislation on safety assessment of potentially dangerous plants require that a correspondingly increased effort be devoted by regulatory bodies and industrial organisations to collect reliability data in order to
The book supplements Guidelines for Chemical Process Quantitative Risk Analysis by providing the failure rate data needed to perform a chemical process quantitative risk analysis.