Chemical plants and oil refineries help keep the world safe and moving forward. The industry, as a whole, is conservative and has not been an early adopter of digitalisation but there is a maintenance revolution looming and it is about to change the game of how equipment and operations are maintained, and data is collected to protect assets.
Chemical plants produce life-critical materials for water treatment, pharmaceuticals, plastics, hand sanitisers, disinfectants, antibacterial wipes, soaps, and personal protective equipment (PPE), as well as other vital products. Oil refineries produce gasoline, diesel fuel, asphalt base, heating oil, kerosene, LPG, jet fuel, and other fuels.
The downstream sector is having to adapt to a new world order, demanding higher levels of uptime, from reduced maintenance budgets on ageing facilities, so requiring new rules of engagement. With asset integrity optimisation as a primary goal, owners and operators of plants and refineries are looking to revamp ageing facilities with digitalisation and new business models.
These times demand that plant and refinery maintenance and interventions be smarter, more strategic, and proactive. That translates to operational efficiencies and optimisation that extend the intervals between turnarounds, whilst ensuring plants continue to run safely, profitably, and reliably at peak performance. This can only be achieved through the introduction of digital solutions, allowing for optimisation at the plant level, not equipment level.
What does it mean to extend turnaround intervals?
Some will say interval extension means cost savings, others will say time savings, and others may say improved performance. And all those answers would be correct. But asset integrity optimisation at the plant level is so much more than that. Long-term asset integrity and performance optimisation takes vision, a holistic and dynamic view of plant condition and how it will change with time, and the ability to look into the future and work back from there.
The oil refining and chemicals industries have proven to be a challenge because digital adaptation has been slow to uptake necessary changes as technology evolves. Ultimately, this costs owners and operators far more in the long run. Plants and refineries must strategically design peak performance models for asset protection and operational optimisation.
By integrating expert thinking, digital technologies, and automation solutions, plants and refineries must strategically implement peak performance models for asset protection and operational optimisation. The key to successfully increasing efficiency is changing the maintenance approach from reactive to proactive, from time based to condition based. That means helping customers get more out of assets with predictive modelling and data analysis, which ultimately can save up to 20% of overall maintenance costs. This is achieved by eliminating low value maintenance, catching failures before they occur, reducing the risk of downtime or unplanned shutdowns, and increasing the reliability, availability, and efficiency of assets.
The big picture vantage point
The majority of a refinery’s asset cost is operational, and maintenance related. To meet the new rules of engagement, asset management, optimisation, and integrity in operations are moving away from task-focused disciplines to long-term, multidisciplinary processes. The goal is to encapsulate the full operational impact of asset integrity, seeing the full scope of activities, with the big picture in mind. Short-term solutions or silo thinking may appear to reduce expenditures, but they often lead to longer-term expenses.
Operational successes come from binding together every facet of the organisation. Implementing solutions that move away from traditional time-based models to newer, safer, more efficient condition-based outcomes is the goal. This conceptual approach applies not only to the plant assets and equipment but to data, people, and plant infrastructure.
Asset integrity transformation requires breakthrough solutions
There are five main areas where vision breakdowns occur and adaptation is needed:
- An ageing workforce, without the right data transference, means a loss of workplace experience and knowledge. Lack of data transference ultimately means less onsite know-how within the operation, maintenance, and engineering teams assigned to performance success.
- Market pressures command higher performance. Competitive challenges mean a continuous improvement model must be part of the solution. Without dynamic plant wide models, they are confined to functional optimisation.
- Profitability is always a concern. Short-term cost challenges force producers to increase production while reducing maintenance spend, often leading to long-term reduced performance.
- Maintenance of ageing assets. Reliability gets more challenging as assets age and can be mitigated with a full understanding of asset functionality, durability, and performance.
- Asset complexity and adaptation. As digitalisation becomes a part of the performance equation, digital competence is required. A higher level of knowledge and expertise to adapt to an ever-changing digital world must be factored in.
With the right asset performance management system in place, efficiencies will offset cost pressures, intervene at the right time and in the right way. Asset management avoids unnecessary servicing or replacing equipment, can extend the lifecycle of assets, and it identifies issues before they disrupt production.
Asset management increases returns on assets and ensures intervention only happens at the point-of-need. A point-of-need intervention solution establishes an operational protocol that is non-intrusive and operationally effective.
Six critical steps to asset integrity optimisation
Asset integrity optimisation makes gains through operational readiness, operational excellence, performance improvements, analysis of root cause failures, reliability planning, lifecycle value realisation, and a peak performance model of constant improvement.
Figure 1. ABB asset management dashboard.
With new digital technology and automation solutions in play, an optimisation formula that brings the long-term vision into play is the right game. At ABB, a proven six-step process for optimal refining results has been developed:
- Gain full visibility of the operation with a holistic vantage point.
- Close any gaps where information could be missing from assets.
- Detect any anomalies through condition monitoring.
- Analyse and understand key trends towards results.
- Leverage trends to predict faults before they happen and optimise maintenance strategy.
- Develop an organisation reliability culture.
The digital world has advanced operations in previously unthinkable ways. The scope of optimisation is elevated when condition monitoring solutions are in place. Gathering real-time data from multiple systems into one unified dashboard will save time by ensuring that the operation is monitored from one location with the big picture in mind.
Information sharing and collaboration between instrumentation, mechanical and electrical departments allow for predictive maintenance efficiency. Data analytics and monitoring give the user decision-making power that ultimately reduces maintenance and operational costs.
Implementing performance improvements is not only smart, but it is also key to savings. Asset performance management models should promise at least a 10% improvement in production uptime, a 20% reduction in shutdown duration, a 30% increase in turnaround interval, and a corporate return on investment in less than one year.
Leveraging the power of predictive analytics to create scalable enterprise solutions is critical. As refineries and plants adapt to the information age, a cultural shift has to take place in individuals. Barriers to digital adaptation, particularly in the downstream sector, are evident and are one of the top priorities to rectify.
Effective change management is essential to implementing predictive maintenance and optimal performance, whereby modifications are made to processes, job roles, organisational structures, and technologies implemented. The method includes comparing plant performance with expected performance, uncovering potential failures, and implementing a system of monitoring and analysis that optimises critical plant equipment.
Shymkent: PKOP oil refinery case study
At the Kazakhstan Shymkent Oil Refinery, new capabilities were realised with ABB’s predictive maintenance modelling system. The refinery moved away from a time-based maintenance system to a predictive maintenance strategy based on the equipment condition. The goal was to increase the intervals between large maintenance outages from annually to every three years, without adversely impacting asset reliability or integrity.
Figure 2. Shymkent Oil Refinery (image supplied by PetroKazakhstan Oil Products [PKOP]).
The company helped the oil refinery navigate the digital journey to make a step-change in their process control and maintenance programmes to drive peak performance from and extend the lifecycle of its assets with plant simulation technology or digital twins. These simulations allow plant operators to run tests on machinery and act as health indicators of machinery and equipment.
ABB’s Asset Performance Management program was successful in implementing:
- Criticality analysis.
- Change management.
- More robust reliability management with interconnection to an enterprise asset management (EAM) system.
The goal at the Shymkent refinery was to take a long-term strategy, which led to a reduction in shutdown durations, increased turnaround intervals, decreased overall maintenance costs, improved production, and provided a healthy return investment. Through ABB’s consulting and analysis protocol, this is what was achieved.
Delivering what chemical plants and oil refineries need
The journey of implementing solutions for process control and maintenance programmes will drive peak performance and extend the operations cycle of assets. Digital technologies, coupled with asset management, are key to successfully increasing operational efficiency.
Changing the maintenance approach from reactive to proactive and predictive will support chemical plants and refineries in getting substantially more out of their assets. The ability to see failures before they occur is safer, more efficient, and promises a more profitable bottom line and a streamlined operation. Clients now have the opportunity to be forward-looking and digitally competent, which ultimately creates plant success at unprecedented levels.
Ultimately, the real benefit of intelligent asset integrity and optimisation solutions comes in creating a culture of clean, safe, reliable, and efficient operations. As the optimisation and asset management sector revolutionises, system integration will be seen in new and creative ways. It is going to be an exciting time for change and progress.
Written by Alan D’Ambrogio, ABB Energy Industries, USA.
Read the article online at: https://www.hydrocarbonengineering.com/special-reports/25012021/from-theory-to-practice/
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