Unlocking the Promise of AI in Electronic Manufacturing
Manufacturing is getting smarter, with most processes and equipment generating vast volumes of data. Dynamic electronics manufacturers are adopting innovative solutions to increase output while reducing expenses and improving product quality. This research details a robust AI-based system targeting some of the most common issues in the electronics test and measurement industry.
Testing and measurement have multiple phases, each highly complex and requiring significant debugging time. Smarter, robust, and efficient processes are achieved using Artificial Intelligence/Machine Learning (referred as AI/ML) solutions. Additionally, AI/ML can help unearth previously unknown relationships in the data.
The proposed AI and ML approach leverages test logs, systems logs and sensor data. The models process real-time streaming test log data to identify patterns, outliers, anomalies, and problems based on historical data learnings. Companies adopting AI can quickly identify the root cause of various issues, solve them, and integrate those learnings to optimize processes.
AI transformation is a critical element of Industry 4.0 and is still in its early stages of development. It is expected to rapidly grow and disrupt traditional problem-solving methods currently followed in manufacturing. AI use cases currently implemented by the industry have demonstrated tangible value and the ability to be executed at scale. This paper will discuss some of the actual industrial implementations and showcase real benefits achieved.
This paper also provides insights into AI implementation design and the common practical challenges faced by organizations in making such initiatives successful.