If you are looking at ways to handle transforming workflows with digital twins in aviation, then you have come to the right place. We have eight reasons for doing just that. Let's start at the root of the concept.
What are digital twins? We can think of digital twins as a kind of simulation - a technologically advanced simulation. The digital twins are charted so thoroughly that they mirror the real-life thing or organization that they were created to mimic. This mirror image allows a business to simulate the life cycle of a particular thing or organization or a workflow process for the purpose of predicting and solving potential problems.
Digital twins rely heavily on Internet of Things (IoT) technology to gain business insights based on a variety of locations and sensor data. Digital twins provide the ultimate real-time visibility into the simulation process. Digital twins leverage artificial intelligence (AI) and the power of cloud technology to bring IoT to life.
How digital twins work in aviation. In the aviation industry, digital twins can take the form of virtual, three-dimensional, working models of a real airplane or any parts of the airplane e.g. an engine. Several aviation manufacturers, like Boeing, have incorporated digital twins into their avionics processes. Digital twins of a particular airplane model permit engineers to conduct various experiments using the virtual version of the airplane to predict good and bad outcomes. Using IoT location and sensor data, engineers can subject the digital twin aircraft to the same weather conditions and environments that they anticipate the model will experience in the real world.
Quality and safety are critical elements in the aviation industry. Aviation manufacturers strive to produce quality products. The failure to do so can result in fatal consequences for their consumers and spell financial disaster for the company.
Maintaining quality and determining where a flaw occurred requires the ability to trace orders and material all the way from the original source to delivery of the final product. That's no small task in the aviation industry where manufacturers rely on an extensive labyrinth of parts and raw material suppliers and vendors.
To keep on top of the monumental task, today's aviation manufacturers need an automated tracking system that concentrates on regulatory compliance. They need a system that provides visibility into the process of tracking materials and parts, as well as one that follows completed orders while in the supply chain to the point of delivery.
In addition, during the manufacturing stage, the aviation workflow process demands that managers have the ability to quickly search and find particular components among the thousands of small parts hidden in its huge inventory.
For system efficiency experts, the good news is that digital twins do not just refer to virtual airplane models. The airplane manufacturer can create a digital twin of its workflow process to help managers discover ways to improve staff productivity. An automated management system can point out ways to minimize nonproductive time and avoid those budget-busting interruptions in production.
One example of nonproductive time is the staff hours spent coordinating and searching for assets using a manual system that depends solely upon human intervention. An automated system based on AI and enhanced by the interconnectivity of IoT can always find the appropriate materials and do it quicker than a manual approach. In the final analysis, digital twin technology can help improve a business's return on net assets.
Simon AI (Simon) is a location IoT analytics platform that helps businesses analyze processes, monitor inventory, and predict outcomes. Simon applies its masterful analytics to business processes with the same success that it handles locating assets and materials.
Simon has two applications most pertinent to the aviation industry. They are its Search & Find capability and its Order & Material Traceability.
Simon's search and find application builds on IoT location and sensor data to provide management with insights in real-time. The resident technology is its Bluetooth real-time location system (RTLS) which makes it possible for manufacturers to detect the indoor location of movable assets and workers. This is an application of machine learning to the Radio Frequency Identified (RFID) asset tags used for inventory tracking. The RFID tags share information through wireless transmissions throughout the manufacturing facility. RTLS gives a digital representation of how a company's assets move within its four walls. RTLS makes it possible to see everything that happens as it happens within the four walls. If GPS is the outdoor positioning technology, then RTLS is indoor positioning that helps businesses track workers and assets. These abilities are made possible by Bluetooth RTLS devices that can see those signals. The Bluetooth device passes the information it gathers to Simon in the cloud.
Simon translates all the signals it receives so the managers know where the equipment, assets, and people are at any given point in time. Simon locates essential unprocessed materials faster than it is possible for staff working unaided by IoT. Simon's search function posts live notification of asset locations on heat maps and floorplans. The system sets off blinking lights on asset tags for easier discovery. The remarkable results mean that staff spends less nonproductive time searching for the assets that the business requires for the next phase of production.
Notably, Simon is "technology-agnostic" which means it works uniformly and efficiently over multiple platforms. It does not matter whether Simon needs to communicate using:
Such flexibility is critical to the aviation industry where thousands of small parts require tracking.
Simon AI can integrate easily via Application Programming Interfaces (APIs) with other third-party management tools, such as:
This remarkable technology also integrates effortlessly with:
New devices added to an existing framework experience immediate onboarding and positioning through Simon's straightforward plug and play feature, leaving more time for IT professionals to focus on finding the keys to problem-solving.
In sum, the use of IoT in asset location raises staff productivity levels, which results in improved staff morale and increases the number of units processed by the factory in any given period of time.
Aviation manufacturers have something in common with all other manufacturing entities: the need to boost capital in the most efficient way possible. That means reducing the business's level of scrappage and shrinkage while making the most out of its works-in-progress. Simon's order and material traceability functions help businesses manage all three business-critical tasks by placing a priority on analyzing, evaluating and improving the aviation business's manufacturing process.
Simon can help revamp an aviation manufacturer's production process to ensure that the products deliver on-time and within budget. The order and material traceability functions help uncover the traffic jams that threaten each production phase. Manufacturers can track pallets, parcels, forklifts and other moveable equipment. Simon alerts managers whenever an asset moves out of its permitted location. This feature helps cut down on missing and stolen assets. Simon's analytics and report graphics improve the business's understanding of how its assets occupy available space as well as the ebb and flow of inventory.
Simon speeds up issue reporting and slashes manager reaction time to potential problems. This feature is an example of how Simon's analytics based on the collection of real-time data yield valuable insights. Real-time data enables management to discover the seeds of production line obstacles that prevent the end product from arriving in a timely fashion.
Simon's analysis can help managers assess problem areas and:
Simon also promotes visibility into a business's Overall Equipment Efficiency (OEE) by automatically tracking the time a machine is in use. Such information documents the cost-effectiveness of each machine involved in the production line at each stage of production. This information helps eliminate inefficiencies and identify the assets causing congestion and obstruction in the product pipeline.
Assets held in storage areas often require monitoring to ensure that the conditions remain conducive to maintaining their production quality. All of Simon's system monitoring devices plug directly into the existing IT network. Simon uses real-time location technology to monitor temperature, light, and the humidity of storage areas. If the parameters drop below the set conditions, the system notifies managers. It also alerts managers to impending equipment shutdowns through its sensor-based failure predictions.
All monitoring data and infrastructure management features are easily accessed anywhere from mobile devices using the web. Data downloads effortlessly into comma-separated values (CSV) files or to external databases using APIs.
When it comes to documentation and reporting Simon provides a complete overview of the raw materials, labor, and other overhead costs of products during the various production stages. The system can show how much of their day employees spend actively working at their posts and how much is passive downtime. Managers have the advantage of reports showing workflows that are 100% transparent. Simon provides access to all shipment logs, which means less guesswork and more improved production planning.
In addition, Simon automatically reports the production history of each work order which provides management with the documents it needs to prepare for audits. Since the production history of every product is open to visual inspection, Simon makes it easy to respond to questions from a client about a product's work order status.
If you would like to discuss digital twins, tracking, and location analytics further, please contact us. We will be happy to schedule a demo so you can discover how Simon AI can help you tame your production process.