Calibration is essential for maintaining quality and safety in industries like pharmaceuticals, food and beverage, and chemicals. The future looks to digital certificates and AI technology to make calibration processes faster and more efficient. This article discusses how AI is set to transform calibration.
I have worked in regulatory and quality teams for surgical eye implants, virtual reality based devices and wearables for remote patient monitoring, along with providing thought leadership on artificial intelligence regulation.
How did I end up working with medical devices? Reflecting on my career, it's been diverse. Three years ago, I was working on protein structure in research labs. I never thought I'd be in the world of quality later on!
By establishing precise parameters for success from the outset and implementing proven strategies, manufacturers can proactively mitigate risks, streamline operations, and foster a culture of excellence.
Ensuring high quality in medical device manufacturing requires operational excellence, which optimizes efficiency and enhances product quality and compliance. Let’s explore some of the key elements and best practices.
In the medical device industry, reliability is critical. Manufacturers conduct extensive testing to ensure devices meet required standards, such as 95/95 or 95/99 confidence and reliability, assessed using Minitab Statistical Software.
In a world where AI vision technology is setting new quality control standards across industries, machines can now detect even the smallest defects in car parts and ensure that every packaged product meets health standards.
Here are a handful of example quality control processes that focus on the measurement of torque, with emphasis on sectors where testing is highly regulated, FDA 21CFR Part 11 being a prime consideration.
The official document is titled ISO/IEC 17025: 2017, General requirements for the competence of testing and calibration laboratories. It is the international reference for laboratories performing calibration and testing activities.
Traditional machine vision used rule-based programming for controlled environments but struggled in less controlled settings. Edge learning AI, operating directly on vision systems, enhances machine vision's power and usability, revolutionizing quality assurance and manufacturing processes.
Enable a manufacturing quality-driven collaboration between suppliers and buyers to eliminate interpretation, reduce costs, risks, and expedited delivery time.
A leading aircraft manufacturer faces $27B in losses due to slow supply chain fixes, aggravated by escalating quality standards like AS9102 Rev C. The solution lies in seamless communication of requirements from buyers to suppliers, streamlining operations for all parties involved.
As the industry continues to trend toward a more patient-centric approach, we see an increasing buzz around the development and utilization of wearable injectors, also known as on-body delivery systems (OBDS)—the next evolution in needle-based drug delivery products.