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Publisher ‏ : ‎ Wiley-AIChE; 1st edition (February 15, 1989)
Language ‏ : ‎ English
Hardcover ‏ : ‎ 328 pages
ISBN-10 ‏ : ‎ 0816904227
ISBN-13 ‏ : ‎ 978-0816904228
Item Weight ‏ : ‎ 1.73 pounds
Dimensions ‏ : ‎ 7.24 x 0.9 x 10.28 inches

Process equipment reliability data is crucial for maintaining optimal performance and preventing unexpected downtime. To ensure accurate and consistent data collection, it is important to follow established guidelines. Below are some key guidelines to consider when collecting and analyzing process equipment reliability data, along with data tables to help organize and track this information:

1. Define Key Performance Indicators (KPIs): Before collecting data, identify the KPIs that are most relevant to your equipment reliability goals. This could include metrics such as mean time between failures (MTBF), mean time to repair (MTTR), and overall equipment effectiveness (OEE).

2. Establish a Data Collection Plan: Develop a plan for collecting data on a regular basis, including the frequency of data collection, the methods for recording data, and the personnel responsible for collecting and entering data.

3. Use Consistent Data Formats: Maintain consistency in how data is recorded and stored to ensure accuracy and ease of analysis. Utilize data tables to organize information in a clear and structured manner.

Below is an example of a data table for tracking equipment downtime:

| Equipment | Date | Time Down (hours) | Reason for Downtime | Actions Taken |
|———–|——|——————-|———————|————–|
| Pump | 1/15 | 3 | Motor failure | Replaced motor |
| Compressor| 1/20 | 5 | Leak in system | Repaired leak |
| Mixer | 1/25 | 2 | Control panel issue | Reset control panel |

4. Implement Root Cause Analysis: When equipment failures occur, conduct root cause analysis to identify the underlying reasons for the issue. This can help prevent similar failures in the future and improve overall equipment reliability.

5. Monitor and Analyze Data Trends: Regularly review and analyze the collected data to identify trends and patterns. This can help pinpoint areas for improvement and optimize maintenance strategies.

By following these guidelines and utilizing data tables to organize and track process equipment reliability data, organizations can improve equipment performance, reduce downtime, and enhance overall operational efficiency.
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