Axon Case Study

Axon accelerates issue detection and resolution and avoids launch delays

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Axon accelerates issue detection and resolution, and gains engineering efficiency from EVT to MP using AI.


Founded in 1993, Axon’s mission is to protect life by creating technology and services that promote safety, efficiency, and transparency. They offer a full tech suite of critical devices, software, and training for use by law enforcement, military, corrections, private security personnel, and by private individuals for personal defense. In addition to hardware such as in-camera systems, body-worn cameras, and less-lethal devices like TASERs, Axon has developed technology to handle data to capture, securely store, and manage video/audio evidence. Headquartered in Scottsdale, Arizona, Axon operates and conducts business in over 75 countries with more than 5,000 suppliers worldwide. As Axon continues to grow and conduct business in many countries, its supply chain is becoming more vast and diverse.

For Bill Maginn, NPI Engineering leader at Axon, the development and production of hardware has a direct connection to Axon’s value of accelerating justice by providing the infrastructure and systems that make the preservation of truth possible. Both the hardware and the resulting recorded evidence are treated as mission-critical assets, impacting front-line officers as well as an array of stakeholders across the judicial system and the community at large.

The widespread benefits of Axon’s products and services are immediate. For example, during the early builds of Axon’s latest in-car camera system, Fleet 3 (now available), the Automated License Plate Recognition (ALPR) enables agencies to capture 8 times the plate reads for the cost as traditional systems. Furthermore, Fleet 3 includes mobile ALPR as part of every system, making mobile ALPR capabilities more available to agencies without requiring separate hardware. By accelerating the efficiency of license plate scanning, coupled with mobile ALPR technology, law enforcement can identify stolen vehicles or find people with warrants much more effectively. For Axon, upholding social justice through product development starts with understanding the impact on the community. Axon established a first-of-its-kind AI Ethics Board to ensure that they operate within ethical guardrails.


The following is an abridged version of our case study. Download the PDF to see the full story.

The Challenge

In 2019, Maginn, senior NPI manager Alex Lee, and the Axon team completed the prototype build for Fleet 3 towards the end of 2019. Development of Fleet 3 coincided with bringing up new overseas factories, which meant starting relationships with new contract manufacturers. This situation can be challenging as a high degree of trust in the upcoming build is needed. To compound matters further, travel came to a halt for the team as of January of 2020 due to the spread of COVID-19. This posed further challenges for the team spread across the U.S., Finland, and Vietnam with contract manufacturers located in Taiwan and China.

Additionally, while the NPI team made use of standardized funtional tests for many elements of Fleet 3, not all possible issues are detectable through such tests. It can be impractical to inspect elements like screws or sensitive sealing gaskets in every unit.

For Maginn and Lee, having remote quality oversight at the contract manufacturers in Taiwan and China was essential, especially for a mission-critical product like Fleet 3 that must work reliably in a moving police car, withstanding vibrations, altering temperatures, shocks, and other forces that occur in the course of an officer’s daily work. With the global travel restrictions inhibiting the teams traditional on-site support strategy, Maginn reached out to Caitlin Kalinowski, Axon board member and Head of Hardware at Oculus. Kalinowski recommended Instrumental to help build out a strategy for remote management of teams and quality. After researching traditional AOI solutions that require programming, Maginn and Lee found that Instrumental’s AI-powered anomaly detection operated akin to a product design engineer, providing insights you would normally get looking over someone’s shoulder, inspecting each unit.

Maginn reached out to Caitlin Kalinowski, Axon board member and Head of Hardware at Oculus. Kalinowski recommended Instrumental to help build out a strategy for remote management of teams and quality.

Axon Fleet 3

The Results

The value of using Instrumental could be seen from the early stages through to MP. Download our full case study below to see exclusive details about how the Axon team achieved the following:

  • After the first day, the team automatically detected unknown issues, gained a full data record and instant, remote failure analysis.
  • More than 20 different types of unknown issues were discovered, some of which would have resulted in escapes.
  • Defect rates dropped 6% from EVT1 to DVT, improving design and processes early on, avoiding rework on dozens of units
  • Traceability increased between builds, which enabled teams to rapidly respond with historically accurate information.
  • Team efficiency increased. In EVT2, the team saved 35 hours of engineering time by prioritizing efforts on the most important issues.

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