June 2024
Environment and Safety
Alarm rationalization at Kuwait National Petroleum Company (KNPC) refineries
The national oil refining company of Kuwait has two state-of-the-art refineries: Mina Abdullah (MAB) and Mina Al-Ahmadi (MAA).
The national oil refining company of Kuwait has two state-of-the-art refineries: Mina Abdullah (MAB) and Mina Al-Ahmadi (MAA). Following the successful commissioning of the Clean Fuels Project (CFP) in March 2022, the energy production of both refineries increased to approximately 800,000 barrels per day (bpd).
The CFP at the MAB refinery incorporated 33 new units, resulting in the addition of 90,000 field instruments and 200,000 alarm points.
The issue
The commissioning phase of the MAB CFP refinery commenced in January 2021 and spanned about 15 mos. Before the final commissioning, each sub-facility underwent mechanical run, functional and pre-commissioning tests, during which many changes transpired.
Following the commissioning’s completion, operators experienced frequent alarm surges in specific sub-systems, exceeding the allowable engineering limit. FIG. 1 shows the alarm counts for a sub-system prior to the alarm rationalization activity.
Since this sub-system is handled by five operators, it can be inferred that the average alarm rate reached over 450 alarms/hr per operator, exceeding the company’s acceptable limits. The number of alarms that can be effectively handled by one operator per hour may differ from company to company, as these targets are governed by the company’s policy documents. The reasons identified for the alarm surges were:
- The implemented alarm configuration was different from the originally engineered alarm, according to the alarm objective analysis (alarm study report)
- The temporary changes to the alarm settings during site tests were not reinstated back to their original settings
- The lack of alarm suppression techniques for equipment that was idle or on stand-by mode.
These findings necessitated the implementation of an alarm rationalization process.
THE ALARM RATIONALIZATION PROCESS
Alarm management is a wide scoped topic of discussion which essentially deals with the work process and implementation of good engineering practices from a regulatory point of view. The standards most widely used for alarm management are mainly the International Society for Automation (ISA) 18.2 Standards and the Engineering Equipment and Materials Users Association (EEMUA)191 guidelines. Alarm rationalization is the process of reviewing, validating and justifying parameters that meet the criteria for an alarm. FIG. 2. illustrates the key steps involved in the entire alarm rationalization exercise.
Mitigation plan
During the engineering, procurement and construction (EPC) phase, contractors conducted an alarm objective analysis (AOA) and provided the company with a unit-wise alarm database table. It was observed that the spreadsheet provided by the various EPC contractors varied in format and style, resulting in inconsistent and non-standardized documentation across different units.
Further discrepancies were detected between the alarm database table provided by the contractors and its implementation in the control systems. Due to the absence of a consolidated alarm database for the entire facility, verifying the credentials of each engineered alarm against the implemented ones posed a significant challenge for the company as it required scanning through multiple documents and systems. With over 200,000 process related alarms in the MAB refinery, the task of carrying out alarm verification for all units was humungous.
SOLUTION
To address the above concerns, the company's project department developed an in-house toola (FIG. 3). This tool facilitated the import of data from diverse Excel sources and the consolidation of information from different spreadsheets with varying formats, resulting in the creation of a comprehensive master alarm database (MAD). The MAD table serves as a single point of reference for all alarm-related information, listing 30–35 parameters for an alarm point. These parameters align with the essential data required according to the company's alarm management philosophy. This tool gathered data from project engineering sources such as the alarm database table, instrumentation databaseb and implemented sources, namely extracts from the control systems database.
The tool could run a comparison for each alarm point, pinpointing disparities between the engineered values and their implementation in the plant control system (FIGS. 4 and 5). This module significantly aided the company in consolidating information from various sources and establishing a comprehensive MAD. Ultimately, this will aid the company to conduct continuous assessments and audits to align with the alarm management lifecycle in accordance with ISA 18.2.
Once the MAD was ready, a taskforce was formed comprising of process, operations, process safety, engineering and maintenance groups to conduct alarm rationalization workshops to evaluate the alarms. The toola contained a module which included a tag view feature, enabling the review and commenting of each tag during the alarm rationalization workshop and generation of tag-wise reports (FIG. 6). These reports were subsequently utilized as approved attachments to the management of change procedures. The comments and recommendations from the workshop were also logged onto the MAD to document the history of changes.
There were various general issues which were noted during this workshop. Some of the major recommendations that helped in reducing the high alarm counts were:
- Suppress alarms for certain plant states such as shutdown or maintenance, or for certain modes of operations when process units or spare equipment are not in use, but alarms are active (e.g., low-flow alarm for a pump when the pump is not running)
- The priority of the alarms was re-assessed based primarily on the severity and time to consequence between the initiation of the safety system by a failure and the moment the hazardous consequence occurred. Best efforts were taken to reach the alarm priority distribution as defined under the company’s alarm philosophy (TABLE 1).
The above distribution may differ among companies as this is managed as a key performance indicator under the company’s policy document. Additional issues included:
- Several cases were found where multiple alarms were being used for the same process conditions. These cases were meticulously evaluated, and the alarms were optimized:
- In cases where instrumented protective function (IPF) pre-alarms were available in distributed control systems (DCSs), the redundant alarms configured under the IPF transmitters were removed
- The IPF trip alarms are known to create alarm floods, so these were set to “Journal” priority (e.g., these were logged as an event without notification)
- For multiple voting trip inputs, a single voted alarm was used rather than multiple individual alarms.
- The deadband and signal filtering requirements for the bad-actor alarms were also reviewed to tackle the chattering and fleeting alarms.
Takeaway
The preparation of the MAD and the facilitation of the alarm rationalization workshops paved a clear path on how to administer the alarm management lifecycle in an efficient manner and reduce the staggering alarm counts within acceptable limits.
When comparing the alarm count to a more recent date, it can be inferred that the alarm counts have significantly reduced by over 30 folds after the implementation of the change recommendations proposed during this rationalization workshop (FIG. 7).
While commercially available software and consultant options were available for this purpose, the in-house toola has proven highly advantageous and cost-effective for the company. It not only allows customization to meet the company's specific needs but also promotes the development of expertise among the company's resources.
Following the toolsa success at the MAB refinery, a liquified natural gas import facility and main refinery of KIPIC Al-Zour have also adopted it for their in-house alarm rationalization exercise. HP
NOTES
- AlaR
- SmartPlant Instrumentation database
Comments