Webinar Replay:

Making Operator Alarm Rationalization the Beginning of Better Process Performance

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Webinar Replay: Making Operator Alarm Rationalization the Beginning of Better Process Performance 2024-05-15

In a good, consistent alarm system, annunciations will be few and alarm limits will outline a Window of Best Operation, acting as a guide to the operator for achieving process objectives. The operator takes action to achieve business objectives and in response to changes in process capability due to abnormal equipment events resulting in regulatory control being unable to keep the process within the Operating Window. Alarms are integral for this function, being the definition of the operating window for operator action, but today, because of inconsistent alarm limits, alarms have become a substantial workload for the operator. We want consistent alarm limits that will result in fewer annunciations and give better target ranges for operation.

This sounds like a tall order if you have not previously seen our methods, because there has not been a method for finding this Window of Best Operation. This has resulted in alarm limits that are inconsistent with process objectives, leading to many annunciations which require no operator action, and thus are false, when process operation is within this window.

Once the new Alarm Limits are implemented you will discover that operation improves with fewer alarms. You will see increased performance of lagging KPIs. You will continue to track changing process capability as exchangers foul, catalyst degrades etc. But you won’t change individual alarm limits to compensate, instead you will use Consistentizer function that we provide to bring the entire Window back to a Consistent state. If an individual variable is actively alarming, you will have the tools to learn why the process capability has changed and address it rather than the symptoms.

This process will be demonstrated in this webinar using our entirely visual tool taking process data from a process historian and other time-series data (e.g., lab data, emissions history, additive usage etc.) from a variety of sources. It is based on geometry so is pictorial and easy to understand.

First presented on 15 & 16 May 2024.

Presenter: Alan Mahoney