Asset Digital Twin

The process industries are asset intensive, safety and profitability are highly dependent on asset reliability and availability.

In this blog I will discuss Asset Digital Twin, and how it provides benefits to the process industry in crucial times such as now, the supply chain is in trouble, manpower is in short supply, rather I should say skilled manpower is in shortage, demand fluctuates and above all when technology improves every day.

Digital Transformation provides several opportunities to the industry to perform better today than yesterday. Before we move ahead with Asset Digital Twin which is a part of Digital Transformation, we need to understand where our business lies: -

• Vulnerable

• Operable

• Optimal

• Sustainable

Figure-1

After knowing the area in which your business lies, the next step is to move towards Sustainable business model, which is toward the right side of Figure-1.

To be sustainable, everyone wants to utilize the assets to their full capacity with minimum wear and tear, but conventionally it is quite difficult to achieve operational goals with minimum maintenance. Yokogawa and KBC have made it possible with the help of an Asset Digital Twin which not only helps in meeting operational goals, but also supports maintenance teams to reduce their workload and optimize their efficiency.

Figure-2

As we can see in Figure-2, as the equipment reliability increases: Safety increases, Mechanical availability increases, and Maintenance cost reduces. This chart explains the benefits of Reliability factor in the Asset Management. With Asset Digital Twin, we have seen that it ensures 2–8% higher availability of assets which reduces the maintenance cost by 20-35%.

Figure-3

Digital transformation only occurs when People, Assets, Practices and Systems are considered as an integrated set; aligned to the corporate vision or business model.

Figure-4

To achieve autonomous operation, Integrated operation centers are a step on the way.

Yokogawa automation and information technologies including IIoT and AI and KBC’s world class practices, change management and process simulation support these transformations, and achieve goals of autonomous operation. Combining cloud-based simulation, semantic web technologies and artificial intelligence to enable autonomous operations is the new generation technology which are already showing good results in our Oil and Gas Industry.

Figure-5

When we use Map services on our smartphones, we always try to find maximum information with one Application such as- searching the direction from source to destination, time requirement, options to commute, shops on the way, ATMs on the way etc. How all this information is presented to us in a convenient way is a very good example to understand the Knowledge Graph importance.

In a Manufacturing unit, there are several documents in different formats, a lot of information is present in them, but they are scattered, and it is difficult to connect that information. In such scenarios the Enterprise Knowledge Graph is very useful, it connects the dots and provides the information in most efficient way, so that a decision could be easily taken.

Figure-6

Yokogawa with more than 100 years of Industry knowledge and KBC with Process expertise work closely to develop a Best in Class Asset Digital Twin model. Process Simulation with First Principle of Engineering is the most effective form of developing Asset Digital Twin for Hydrocarbon Industry.

Figure-7

Having created a big vision, how do we start? Achieving a step change in value chain optimization is only possible with assets that are available in a reliable and predictable manner. Deep understanding of reliability and degradation patterns is therefore a source of competitive advantage. This requires an asset digital twin and is a natural starting point for digitalization of the value chain.  It moves the existing asset and value chain models to the cloud and extends then using machine learning to give models capable of predicting future performance and continuous managing the process.

Figure-8

Assets from different locations could be easily analyzed and managed well, when connected to experts not only from one location, but also at different locations. Cloud system makes it possible. No doubt security is the top priority and it can not be compromised, that’s why a renowned and trustable Digital Transformation partner – Yokogawa is needed.

Let’s see few examples that how Asset Digital Twin works: -

Figure-9

In Figure-9, we can see that black dotted line denotes usual equipment replacement time of the equipment from initial failure, even though the actual replacement time should be red dotted lines. It means customer has replaced equipment too early, through Asset Digital Twin, customer would be knowing that no need to replace the equipment at black dotted line, customer would plan equipment replacement at yellow dotted line, thus has utilized the equipment to its maximum potential.

Figure-10

Sushi Sensor is another example of Asset Digital Twin in the running plants, it detects the cavitation well in advance and saves the pump blades to get damaged. With the help of AI it detects the false peaks (considering acceleration, velocity and surface temperature) and avoids unnecessary pump changeover, thus saves man hours and pump maintenance cost.

Figure-11

In Figure-11, we can see that for Vibration measurement, operators must take field rounds, in above example the cost on maintenance is approximately 48,000 USD per annum. On the other hand, with the help of IIoT, Cloud, and Dashboard, an operator can visualize that when a field round is necessary, and a detailed inspection could be done to save equipment as well as to save time.

Now let’s see that how Yokogawa and KBC are making Asset Digital Twin work.

Figure-12

Once operating and maintenance records are in a digital format, we can apply knowledge graphs to structure the information and combine it with process data in a data lake. The structured data can then be fed to machine learning algorithms to provide new insights, automate procedures and support natural language search.

Figure-13

Knowledge and information are useless unless you are going to do something with it. Whilst swathes of data present many opportunities it can also paralyze an organization and hinder speed of decision-making. Data can also cost a lot to gather and maintain.

Data must be collected and reconciled, creating a data framework giving a single source. This single source means that there is no replication between tools and no multiple versions of the truth. A value chain optimization data model should be created that addresses all aspects from front to back of the value chain and then overlays the continuous technology advancements to take advantage of a true sustainable value chain digital twin. Semantic web technology, knowledge graphs and industry standards should be used to support knowledge management.

Figure-14

Any data-driven approach for continuous improvement requires definition, ongoing tracking and reporting of KPIs against targets. Value chain optimization must have goals and targets to achieve, constraints and limits to respect, and tasks to be done. Some are explicit and some are implicit; some are simple to measure, and some are derived from complex chemistry, physics and math; some are static, and some are dynamic; some are constant, and some are conditional.

Figure-15

Most well-run businesses in our industry will have a simulation model of their facilities – maybe it was created during the design stage, or maybe it has been created in the initial stages of design. To make it practical to use the model for continuous performance monitoring, adjustment and optimization, the model needs to be non-linear in nature and extended to cover the entire asset and thereafter, be operationalized with real-time data as a digital twin.

Figure-16

These asset models can then be used to process real-time structured and unstructured data and present the results to the right people at the right time in the right way to support real-time decision making. Using agile implementation to create quick wins and demonstrate the value created is critical. 

*This blog is based on webinar presented by Simon Rogers, Vice President, Digital Solutions at Yokogawa