Global A&D industry revenues are expected to start recovering this year after a difficult 2020, according to Deloitte. Although the commercial sector has been disproportionately more affected than the defense sector, strengthening and sustaining innovation across the industry depends on its continued willingness to adapt to smart manufacturing technologies.
Embracing digital transformation is key to breaking out of volatility during this period of recovery, and the defense industry’s success with Quality 4.0 technology proves how well they support resilience in the face of uncertainty.
Recent events have boosted global digital transformation efforts. However, as the period of global recovery approaches, these digital mechanisms are not only a necessity but also a norm. One of the main drivers of this change is the demonstrated value of data. For A&D, it’s helpful to create a digital thread to embed into the digital fabric of the supply chain that connects every step of the manufacturing process. Developing this strategy through digitization unleashes assets that ensure stability in the face of disruption.
Quality 4.0 strategies use a data driven approach to quality processes. But these methods require high-quality, precision data to be effective. A metrology grade blue light 3D scanner enables the collection of such data, functioning as a digitizer for critical aerospace components.
The resulting digital twin offers opportunities to update archaic inspection processes.
For example, traditional methods of thickness measurement often involve expensive destructive techniques such as cutting high value parts, such as turbine blades. Digitizing this inspection process saves time and money, and the resulting data creates a digital record of the part validation that accompanies it for life.
Successful A&D manufacturers are currently accelerating in-line production inspection using batch processing systems that enable automatic robotic transfer of parts from an automated 3D scanner integrated into a controller interface station programmable logic. The machine uses advanced calculations to quickly determine if critical parts will pass inspection.
Improving the inspection process through this form of automation reduces the time required to inspect small components.
However, for larger parts and assemblies, A&D manufacturers get the same improvement with larger automated 3D scanning and inspection solutions or autonomous guided vehicles equipped with blue light 3D scanning systems.
Automation helps manufacturers manage the quality process by reducing repetitions, creating a repeatable process, and eliminating human errors.
A&D companies that adopt automation strategies are gaining advantages and strengthening the industry’s rebound while protecting its future, using technology to stay ahead of foreign competition.
Quality 4.0 initiatives use data to measure quality and analyze, predict and solve business challenges. For example, performing trend analysis using 3D measurement data reveals patterns that provide information to accurately predict trends for planning and remediation of manufacturing processes. After identifying trends, machining issues, surface defects and geometric anomalies, this data becomes digital documentation that follows the part for life. The information presented prompts successful business decisions.
By tracking minor deviations in production processes and addressing the root cause before creating out-of-specification parts, manufacturers predict and fix problems before they arise.
Industry can move forward smarter, with better information derived from better technology. As advancements in quality processes continue to reshape the relationship between technology and humans, they will also continue to drive down costs. By automating tedious processes, Quality 4.0 technology gives humans more ability to focus on advancing engineering, quality and safety.
Adopting advanced data collection methods and strategies will make a relevant contribution to the recovery, persistence and resilience of the aerospace industry.