Whether it’s managing storage tanks for the oil and gas industry, airports, ports or governments, there are many levels of complexity when managing the bulk liquid supply chain at tank farms and terminals. The volatility in tank management across these fuel eco-systems continues to be intensified by the pandemic, war, weather, inflation, labour shortages, and decarbonisation initiatives, generating more uncertainty with regards to business planning and management.
As a counter, enterprises upstream and downstream continue to focus on automating predictive intelligence – processing petabytes of data from disparate sources to make better decisions about the future, faster. Beyond the prevention of operational failures, one of the most promising areas in digitalisation is the ability to leverage historical and recent data to reveal important trends and better project and plan for more profitable future outcomes. As many operators scramble to achieve some semblance of financial and operational stability, the goal is control, automation and, of course, profits through technological advancements that allow us to better predict, not just react to these changing headwinds.
DATA COLLECTION & DIGITALISATION
A novel approach lies in collecting more data – looking beyond your typical data sources and considering a new paradigm where first, second- and third-party data come together in a mosaic of visualised, enhanced analysis and understanding. Examples of this in fuel management systems are the integration of weather data and forecasts, maintenance system data for frequency of anomalies, personnel metrics, pipeline schedules, and the emerging vault of IIOT sensors relaying key attributes such as vibration, pressure, temperature, or run time.
In the era of data, a semblance of innovative technologies combining cellular, satellite, wireless, mobile and cloud connectivity allow us to take advantage of cloud-computing speed to prop up and upgrade systems and make accessible and valuable, a constant flow of real-time data for decision making and prognosis. Data-as-a-service allows data to be accessible outside of the terminal, consolidated across multiple locations, and positioned in front of the right people analysing operations across those sites in the enterprise.
With more data than ever and not enough data scientists, the automation of measurement and control has been extended to the area of data analytics where artificial intelligence (AI) and machine learning (ML) facilitate and automate the process of all forms of analysis. There is so much data now that it is impossible to manually collect and analyse it the way we have in the past. For efficiency, it’s time to master the flow of data through the enterprise, leveraging algorithms and tools created by the world’s smartest data scientists to automate data analysis, which would have taken much longer before with just a human.
IMPROVING PROCESSES
Making better decisions does not mean replacing people with computers, but it does necessitate a vast improvement in our approach to analysis and insights through more automation. With better and faster decisions, the business can scale to support faster growth and better outcomes, while using talent for more strategic improvements driven towards a more profitable enterprise.
Additional power has also emerged from AI and ML with dashboards where the visualisation of mass amounts of information can be manipulated and filtered, automatically providing critical calculations. It becomes much easier to track key performance indicators (KPIs) within acceptable thresholds, in an easy-to-read graphical interface, while automated notifications and alarms trigger action before rather than after forecasted events. With the power to prevent expensive, even catastrophic stock shortage, equipment or supply chain failure, the opportunity cost and value of digitalisation initiatives has an almost immediate payback.
Derek Blagg, director of products and delivery at Varec, will be speaking at StocExpo in Rotterdam on 14-16 March. Register now and get your conference pass.
