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A large defense and technologies company with more than 15,000 employees worldwide. They are a leading manufacturer of unmanned aerial vehicles (UAVs). These UAVs can be remotely piloted from anywhere in the world and are capable of very long duration, high altitude flights while carrying significant payloads. They are widely used by world militaries for intelligence, surveillance and offensive operations as well as by civilian organizations for border enforcement, firefighting and scientific Applicationsapplications.
The Need: UAVs are crafted from composite materials in an exacting process that demands high degrees of precision. If any step is executed under improper conditions, the entire aircraft may need to be reworked or even scrapped. The client wants to instrument every aspect of thethe manufacturing process to ensure that it is performed correctly and efficiently. By doing this, they expect to increase quality while reducing expenses from rework and scrappage. To completely monitor the production process, the client expects to deploy hundreds of sensors across multiple manufacturing stages. Data from these sensors must be available to personnel on the production floor, to supervisory personnel and for historic review.
The Solution: The key requirement for the project was a data management solution that could collect readings from hundreds of heterogeneous sensors and reliably transmit information to the multiple information systems that require it. To accomplish this, the client selected Fledgesoftware Fledge supported by Dianomic Systems. Fledge is an LF Edge Open Source project for industrial IoT IoT that collects data from sensors, processes it at the edge, alerts and delivers it to data systems or the cloud. The client integrated Fledge with their existing operational operational systems to provide central monitoring and historical archiving. The initial stage of the project was to monitor the UAV painting process. UAVs are painted with multiple layers of primer and topcoat. These must be applied within strict ranges of temperaturetemperature and humidity to ensure proper drying and curing. The client instrumented each paint booth with 4 temperature and humidity sensors—one sensors one set in each corner. These sensors are attached to A/D converters and then to Fledge software running on Advantech Embedded IoT Gateways.
Fledge software converts the sensor readings to JSON format and reliably delivers the data to OSIsoft PI. In addition, Fledge connects with local displays at each paint booth to display temperature and humidity information on the factory floor. The display is green/red color color coded to alert production personnel when environmental conditions are appropriate to begin the painting process.
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The next stage is to monitor autoclaves as they press and cure composite materials into UAV components. The client wants to review autoclave operations to ensure they have precisely executed the series of temperature/pressure/time stages necessary to eliminate bubbles and create structurally sound components. With the Fledge and PI infrastructures already in place, deploying monitoring for this process will be as simple as attaching additional pressure and temperature sensors to the Fledge Fledge gateways.
Jacksonville Energy Authority - A Leading Electrical Utility
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The electrical utility spends millions of dollars on transformer maintenance each year. Much of this expense results from emergency responses to restore service due to failures in the field. They wanted to reduce these reactionary expenses and move to a proactive model where they could forecast systems requiring maintenance before failures actually occur. This will allow them to decrease outages while saving money by using their maintenance crews more effectively. Proactive maintenance requires a great deal of instrumentation and trend data on each transformer. This information needs to be available to multiple organizations across the enterprise for planning, analytics, monitoring and scheduling.
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