When it comes to aerospace manufacturing, the data conundrum is one that many underestimate.
A single flight component goes through numerous steps in its creation and integration into an aircraft – from fabrication and inspection to environmental testing and storage – and information about the component, equipment, process, inspection, environment, and more can be generated during each.
The issue is not that this information should be captured, but rather, how to connect this data into a reliable digital thread.
What is a digital thread?
A digital thread is a connected information chain about a given physical asset.
By linking information related to production, quality, inventory, and equipment into a shared set of records (rather than having this data siloed in various systems), engineers and operations managers can have a greater degree of situational awareness about what has occurred to a component, when, and which process or system may be involved.
For example, component genealogy – linking a given part to manufacturing, inspection, material, equipment, and other production records – can provide this much-needed situational awareness when questions about a particular component arise months or years after its initial production.
But what role does AIoT play in all of this?
Industrial IoT provides a means of capturing information about the physical environment, while analytics and AI offer a means of deriving operational intelligence.
Depending on the given manufacturing environment, this can take a variety of forms, such as:
• RFID to identify components or assets
• BLE and UWB to determine location
• Environmental sensors to capture conditions in controlled environments
• Telemetry from equipment to derive information about its operation
• WIP tracking to observe production
• PLM, ERP, or MES data for linking manufacturing records
The point is not to create yet another dashboard, but to think at the level of the enterprise: can information derived from physical manufacturing processes be tied to the digital records about them?
For instance, WIP tracking can indicate the progress of a sub-assembly through a production process, while component genealogy can store information about that component’s history. By linking these data sets, operations managers can obtain a greater degree of situational awareness about their production process.
The importance of traceability
Aerospace manufacturing is a complicated affair that requires significant engineering know-how to configure a product correctly and ensure that it meets quality standards. As such, the ability to capture information about a component as it goes through the production process and store that information digitally can be extremely beneficial to situational awareness: if questions arise about a particular aspect of a component (e.g., a non-conformance), connected production records can help identify the root cause much faster by pointing to the relevant process, inspection, equipment or other factors involved.
That is why the digital thread is so interesting: it represents a way to connect the life-cycle of a component digitally.
For a more in-depth look at how aerospace and space manufacturing can employ AIoT technologies, see this manufacturing resource.
The engineering challenge
The challenge that engineers face when trying to implement a digital thread is similar to many other aspects of industrial IoT: there is a need to connect disparate systems, capture relevant data in a standardized manner, and establish a shared understanding of things like component identity or temporal metadata. For instance, when it comes to component genealogy, some pertinent questions include: What information needs to be captured at each stage of the production process? How should component identity be standardized across systems? Where should processing of sensor data occur? How can legacy manufacturing systems be connected to more modern IoT-enabled ones? How can the integrity of data be maintained without creating unnecessary data entry and processing overhead? What information needs to be available in real-time, and what can be processed periodically?
As such, an appropriate architecture for this kind of application would need to address the needs of the physical manufacturing process as well as the digital thread linking these processes.
After all, from the perspective of an aerospace manufacturer, the ability to connect component information from various stages of the production process is not likely to be determined by any one particular sensor, tracking technology or analytics model, but rather the whole.
It makes one wonder what engineers working on manufacturing systems would identify as the most challenging part of building a digital thread: data collection, system integration, ensuring data quality, or maintaining temporal and asset integrity throughout the component’s life-cycle?
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