Delayed Maintenance Turnarounds a Major Source of Unplanned Downtime

According to conventional wisdom, most unplanned downtime occurs during certain operational procedures, most notably startup and shutdown.  Normal plant operations are not seen as a major source of unplanned downtime events, nor are regularly scheduled planned downtime activities such as maintenance turnarounds. 

Our survey responses indicate that this conventional wisdom may not be entirely correct.  ARC asked survey respondents to rank the most common times for unplanned shutdown.  Available options included: “during normal operations,” “startup”, “shutdowns”, “higher than normal load”, “extraordinary events” (like hurricanes and floods”, “shift changes”, “other plant transitional states” (grade changes, etc.), and “delays in regularly scheduled maintenance turnarounds.” 

On a weighted average basis, startup was tied with “other transitional changes” in the process (like grade changes) as the most common times during which unplanned downtime happens.  Maintenance turnarounds are a planned activity, but unexpected delays in these turnarounds were cited as a major source of unplanned downtime. This confirms other ARC research.    Maintenance turnarounds are typically planned well in advance -- in many cases as far as a year in advance.  Due to this extended planning window, turnarounds don’t always take advantage of the available real-time, dynamic asset and plant information to change the plan.  Many end users also do not take advantage of intelligent device diagnostic data to maximize turnaround efficiency. 

Surprisingly, “normal operation” was cited as one of the most common times for unplanned downtime, ranking higher than “during shutdown”, “operating at higher than normal loads”, or “shift changes.”  Extraordinary events like hurricanes and floods were ranked as the least prevalent time for an unplanned plant shutdown.  Many end users, particularly in the oil & gas and downstream industries, have become much more sophisticated when it comes to using real-time weather data to shut down plant operations when an impending weather-related, natural disaster is predicted.