Driving continuous process improvement: Do it right the first time, every time

In automotive electronics manufacturing, few challenges are greater than producing ADAS cameras that are high performing and reliable, while being cost-efficient. The key to overcoming this challenge is collecting parametric data from the production and test equipment as well as from the suppliers of material and consumables and applying powerful analytics to extract actionable insights in real time. This is the only way manufacturers can react fast and avoid costly scraps, as they improve product performance.

Connect value chain silos

OptimalPlus collects, harmonizes, analyzes, and connects data from across all the relevant ADAS camera processes in the value chain. Alerts on outliers and anomalies are sent for real-time prevention, while in-field and process data is fed back to design for continuous improvement.

Ensure product performance

Incoming and in-line lens performance is improved by utilizing powerful machine learning algorithms to identify potential camera failures and alerting on these outliers as early in the process as possible, reducing the scrap rate at final test.

Optimize materials, equipment, processes

Real-time performance monitoring and feedback on key process indicators improves equipment and tooling health. When issues are detected, alerts are sent for early intervention, enabling immediate adjustments or adaptations as needed. Moreover, predictive maintenance is enabled, for reducing downtime and increasing line efficiencies.

See the other solutions

Electrification:
improve EV powertrain
quality, efficiency, & scrap rate

Utilize machine learning and big data analytics, to perform large scale multi-variate analyses for determining the factors that have the biggest impact on scrap rates.
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