Key points
Vladimir Nitu, European digital and connected services manager at Emerson explains how IIoT technologies can be leveraged to improve reliability through condition monitoring
The idea of collecting data to enable experts to perform condition monitoring is not a new concept within the process industry. Automation vendors have provided specific services, such as vibration monitoring on rotating equipment, for some time.
What’s different with the industrial internet of things (IIoT) is the introduction of a completely new suite of sensing technology, new cost-effective approaches for connectivity and better ways of connecting data with people, anywhere in the world.
In addition, the industry has recognised that machine learning, artificial intelligence and cloud technology can be applied within condition monitoring concepts to enable predictive maintenance practices that significantly reduce unplanned downtime.
Automation technologies are a great lever for connecting what is happening in operations with business performance KPIs. Automation systems are the nerve system for all the data and enable experts to see what’s happening inside the facility.
Real-time data is generated by new sensing technologies, then secure connectivity sends the data to analytical tools that can be embedded in edge computing devices or run in the cloud.
This enables expertise to be leveraged wherever it exists. Then mobile tools can provide access to that data anywhere inside the plant. The IIoT is about data connected through a network, feeding analytics to experts to enable more strategic decision-making.
Equipment condition monitoring
Equipment condition monitoring is an important use case for the IIoT. A condition-based maintenance programme can be stablished, with early detection of potential failures for a wider variety of critical assets to enable predictive maintenance.
It is not just about monitoring vibration data on rotating equipment anymore. Leveraging a wide variety of sensor technologies, the condition of all critical equipment can be monitored online between shutdowns, turnarounds and outages.
This allows better planning of parts and resource needs for when a planned outage takes place. This will eliminate unnecessary work and unplanned downtime, making it easier to stay within budget and increase plant availability.
Three step process for a successful condition monitoring programme
The first step in setting up a successful condition monitoring programme is to identify critical equipment and applications that could most benefit. In many cases, maintenance and operations management will be very familiar with bad actors and equipment that have caused the most headaches when they have failed in the past.
If required, a more formal criticality analysis can be performed, usually as part of a standardised reliability programme, leveraging industry best practices for risk management.
Another approach might be to review maintenance records to see which equipment has historically created the biggest negative impact to operations.
When establishing a business case, the key drivers will be lowering maintenance costs, improving plant performance, increasing process availability and improving maintenance efficiency. All of which can be tied back to avoiding unplanned downtime.
Monitor equipment while it is operating
The next step is to monitor the equipment while it is operating. This is where the IIoT provides real value. Traditionally, equipment has been inspected when it is offline and out of service.
Often the equipment is removed from service, and an internal inspection is performed to check the condition of parts. Sometimes parts are replaced whether they need to be or not.
With many facilities extending the period between planned outages to five years or more, equipment will now run for many years with there being little understanding of its condition.
Some preventative maintenance programmes have been established to periodically inspect equipment. This often involves skilled technicians visiting the equipment and collecting data manually on an infrequent basis. Due to the cost of labour this may only happen once a year.
Besides the challenge of trying to detect issues through a manual inspection at a single point in time, there is also the safety risk of sending people into hazardous areas while the process is in operation.
Optimise planned maintenance
The third and final step is perhaps the most important because it is where the real value can be achieved. It is not enough to simply monitor the condition of critical equipment.
There needs to be the ability to act on the monitoring results. There must be a focus on planned maintenance and success depends on the proper integration of predictive maintenance into work processes.
There are some key concepts to consider. The recommendations made by the domain experts need to be integrated into the maintenance planning systems and the work needs to be prioritised properly.
By gaining the ability to detect potential failures before they happen, the necessary replacements parts can be ordered well in advance of the maintenance work.
Condition monitoring results will help focus efforts on critical equipment that requires repair and avoid performing maintenance on equipment that doesn’t need it.
Finally, much more will be known about the condition of equipment going into a maintenance activity. A better plan will ensure maintenance work is finished on time, with a reduced risk of surprises.
IIoT offers the ability to continuously monitor the condition of equipment between planned maintenance events. Data is collected while the equipment is online, during normal operation.
Analytics software can then help experts to identify potential failures in the early stages of development, and their expert guidance can be used to plan for future maintenance events.
Connected Services
As a result of IIoT technology, a new business model has been created where external service providers can offer an outcome-based service. This is not unique to the process industry but is gaining in popularity as companies realise that they cannot meet their business objectives by only leveraging internal resources.
When attempting to achieve a desired outcome, it can make sense to turn to external service providers, such as Emerson, that offer a lot more domain expertise than is available in-house, especially for very specific equipment classes, such as control valves.
Connected Services leverages IIoT technology to securely connect on-premise data systems and sensing networks to cloud-hosted systems that enable experts to analyse the data in order to gain new actionable insights.
Using the example of control valve condition monitoring, valve experts located in service centres around the world, can use their extensive experience to interpret the data that is collected from digital valve controllers.
Time series data, events and diagnostic test results are made available, without having to send experts to the local site. Expertise can be shared across a wider base of critical control valves, without the added cost and complexity of travel.
Using this method, operators can achieve the outcome they are looking for without having to develop specialised in-house expertise. Companies can then focus on better planning of maintenance activities, preparing for shutdowns, turnarounds and outages, and respond to the more urgent daily priorities.
Justifying investment in control valve monitoring
A global oil and gas company was able to quantify the business case for monitoring control valves. This was based on a target of having zero unexpected shutdowns due to control valves over a two-year period. The business case was based on the impact to production when an unplanned outage occurs.
With a 24,000 bpd production rate and a product value of $50/barrel, there would be a loss of $1.2M in production value per day or $50,000/hour. The cost of one year of condition monitoring can be justified, if just one hour of unplanned downtime could be avoided.
More complex models can be applied, based on the probability of equipment failure and the broader impact on operations. In this case, this simple calculation was all that was needed to justify the cost of performing condition monitoring on control valves.
Efficient shutdowns, turnarounds and outages
When it comes to digital transformation and maintenance, applying digital technologies like IIoT to improve the efficiency of shutdowns, turnaround and outages can really amplify savings. Extending a shutdown due to poor planning can be just as bad as unplanned downtime.
The cost metric is the same – time spent not making products. The goal is to plan maintenance using actual equipment data, ordering parts early to avoid the high costs of rushed orders and execute work based on the condition monitoring results achieved in between outages.
Returning to the valves example once more, the average cost of pulling a control valve is $5000. Based on maintenance records, 30% of valves pulled don’t require a repair.
For a small 30 valve outage, condition monitoring using connected services could save $45,000. This means that the cost of the condition monitoring is covered just by the effective outage planning, and that’s before the bigger prize of avoiding unplanned shutdowns is considered.
