by Since 2016, the Global Liquified Natural Gas (LNG) imports industry has enjoyed a CAGR of more than 10%. Due to oversupply, unpredictable demand and varying price as a result of COVID-19, this CAGR came to a screeching halt in 2020. In an industry that was experiencing oversupply prior to the impact of COVID-19, the decrease in demand has lead to even greater excess and market volatility. Many LNG producers are looking to cut spending across the board and the rush to implement these measures has led to, in some instances, significant negligent maintenance practices.
These measures snowball into the real pressing issue for LNG producers, forcing them to ask the tough question:
“How can we maintain/ increase profitability in such a volatile environment?”
The answer lies in Artificial Intelligence, specifically Maestro.
Oversupply is a significant issue as it forces producers to reduce operational costs, often from critical areas in the production process, since they are unable to sell all their supply. Cost cutting measures, along with workforce disturbance caused by COVID-19, have led to prolonged maintenance backlogs for many of the world’s LNG plants.
By way of example, a look at the fire that occurred in the Hammerfest LNG plant in Norway in September 2020. This fire was a result of negligent maintenance due predominantly to poor planning and a backlog of cost-cutting measures that had to be implemented due to urgency. The plant narrowly missed destruction, but the event could have been prevented in its entirety while still maintaining cost reduction if an AI engine, like Maestro, been implemented.
The oil leak that caused the fire was foreseeable, it was determined to be one of many leaks that were called out by a safety audit issued by the PSA. However, due to the vulnerability of the market, the plant elected not to address it. On the day of the fire, the fire-alert system malfunctioned and even still, it threw out several faults which the plant, likely understaffed, decided not to address. The fire was ultimately discovered by staff as it occurred. What is known for certain is that the fire was preventable in many ways.
The president and founder of Bellona, an international environment agency, Frederic Hauge, noted of the fire that,
“Our information points to serious design and construction weakness at the plant, serious negligence in follow-up of maintenance issues, and an astounding lack of attention to safety by top management.”
Frederic Hauge, Bellona
In a survey conducted by Oil & Gas IQ in 2020 (illustrated below) and administered to over 200 O&G professionals, almost 75% of respondents believe that intelligent enterprise applications can save money on CAPEX/ OPEX.
Most respondents went on to say that the amount of which this could save was unquantifiable at the time.
Further, the respondents shared that the two most significant areas for impact with intelligent enterprise applications are predictive analytics & intelligent automation, both of which are not only wheelhouse benefits delivered by Maestro AI, but are also just the tip of the iceberg in transformational impacts that Maestro autonomously implements.
Instinctually, any business aims at reducing cost if it is experiencing an oversupply and is in a market that is vulnerable. However, cost-reduction must never come at the expense of safety, something that the Hammerfest LNG plant failed to prioritize and has now cost them an entire year of unplanned downtime. The question remains,
“How could this fire and shutdown, as well as future maintenance related disasters, be prevented while still maintaining and even increasing profitability?”
Maestro Artificial Intelligence and the team at Elutions have extensive experience in the LNG market, working with clients to increase profitability as well as preventative plant failure, an overall reduction in downtime and more whilst maintaining proper reporting and safety standards.
In the case of the fire at Hammerfest, had Maestro been deployed, the automated directives, as part of the Maestro Autonomous Value Chain, would have been able to address not only any potentially faulty alarms but also the entire maintenance backlog with ease and with priority assigned to those issues that impact profitability and safety the most. Unplanned and overdue maintenance is a serious issue in the LNG industry, one that has lead to a tighter market and an increase in prices, but it doesn’t have to be with the help of AI.
Unplanned maintenance is just one of many issues that Maestro can address in the LNG industry due to it’s unique end-end holistic approach to the value chain. The Maestro Autonomous Value Chain overcomes chaos theory in a measurable dynamic environment like a refinery, understanding the input characteristics in real time as they change, and accounting for cause and effect up and down the value chain automatically as a result. To learn more about the Maestro Autonomous Value Chain applied and how our team can help your business combat the volatile markets please contact us.
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