We hear the term “Digital Twin” often in the context of the Industrial Internet of Things, Digital Transformation, or just going digital. What should we be doing to prepare for and to leverage the digital twin for machine failure prevention? Can the Digital Twin help us beyond machinery failure prevention? How about process optimization, lowering the cost of production? How about lowering the carbon footprint of the enterprise as part of process optimization? These are indeed some of the benefits of a contextualized holistic view of our plants that the Digital Twins offer.
So where do we start? We first need to define our critical manufacturing processes. From a business perspective, what drives our profits? By understanding our profit drivers, we can focus any digital efforts on those that impact business profits (or risk or costs).
Next, we need to identify the critical assets and components in the plant. What data is available from these assets? We are typically interested in engineering data including performance specifications, process and instrumentation diagrams (P&ID), repair and maintenance manuals, operational manuals, and drawings (both two-dimensional and three-dimensional). We are also interested in machinery and equipment data. Can we pull data from the equipment controllers in real-time? What network infrastructure is in place or can be added to connect the data to our digital twin? Do we need to add sensors and instrumentation to obtain the data we need to make decisions that will drive our business Key Performance Indicators (KPIs)?
What performance metrics are valuable? How about Overall Equipment Effectiveness (Availability * Performance * Quality)? What Operator tools are available that allow the operator to see a holistic picture of the equipment they operate and manage?
As you can see there are many questions, we should review on our digital twin journey.
In the end, our individual equipment assets, the subsystems they form, the systems, the plant units or lines, and the plant all have a digital twin. Each layer in the digital twin builds upon lower elements in an asset hierarchy-oriented twin network. An individual asset is connected to a wide range of data about itself, both real-time data, and static document data.
As noted in the following diagram, the asset (equipment or system) is at the core of the digital twin. There is a range of real-time data including time series, maintenance and operation events, and worker operator activity associated with the event. There is static data including engineering documentation, manuals, and three-dimensional drawings.
As an example, a feed pump may be part of a distillation column and is listed on the P&ID. A digital operator notes his production schedule event and starts the feed pump. The feed pump automatically executes a series of start-up steps and checks. This is the start-up sequence. Motor current and vibration data from the pump are logged along with temperatures, pressures, and flows. These are time-series data. The operations manuals provide limits on any of the data, sequence timing, etc. Our three (or two) dimensional models provide any visualization that is helpful to the operator or to management.
It may seem obvious, yet our digital twin needs access to core data. Data resides in our control system and data historian. Data resides in our maintenance management and operator management systems. Data resides in our engineering archives. It is likely, that the data and systems are provided by multiple vendors, each with its own application programming interface. We need to identify where the data is, that will empower our digital twin.
We will also need to address our networking and security parameters as well. For example, we can use OPC UA to pull data from the control systems. OPC UA gives us security layers and can work across firewalls. OPC UA will allow us to see time-series data, some sequence-related data, and data that maps to events.
In other cases, we will need to access or implement digital versions of our management processes. These are business and process sequences we may wish to automate. We will need to access and manipulate our engineering data, those manuals, and P&IDs. It is likely we will need some help from natural language processing or similar tools to interpret the engineering data. In the case of multi-dimensional drawings and models, we may need augmented reality resources that can bring the drawings to life. Lastly, we will want to bring our plant field personnel into the digital twin by adding smart devices for digital workflow, and access to digital twin information.
Participating in the new digital industrial environment requires digital thinking, that is digitizing and automating many of our manual processes. However, these are often a two-to-three-year journey. For this journey, we will need support at the top of our organization, which may include cultural and change management efforts.
Of course, we start with our business justification. What areas of the business should we improve to solidify or increase our competitiveness in the market? This list gives us low-hanging fruit and smaller bite-size projects we can work with initially, as we build out our digital roadmap.
The process is a team sport, requiring representation from leadership, information technology, operations, maintenance, and of course a team to perform the integration. With the right team in place, it is possible to prioritize the business opportunities, with a focus on impactful and measurable initiatives that can be implemented quickly. A technology roadmap should be implemented to address all or most of the business objectives.
To keep the effort moving, it is recommended that companies partner with integration teams with expertise in operational technology (OT) and information technology (IT) and that have expertise in the company’s manufacturing process. Experience yields the ability to anticipate and overcome challenges that are likely to arise.
As the journey continues, communication is paramount. Newsletters and other status updates should be shared with all stakeholders, so everyone is included. Always ask for feedback to help refine the journey.
With these implementation elements in place, the team is ready to scale and ultimately transform the organization into a new digital entity. Machines will be more reliable, processes more efficient, energy consumption lower, and ultimately a more profitable and competitive enterprise.
Schedule a meeting with our IIoT Innovation Team to learn more.