Artificial Intelligence

Analytics solution to decrease costs of ADAS manufacturing

25th July 2019
Lanna Deamer

Optimal Plus has announced the launch of its new Lifecycle Analytics Solution for ADAS cameras. The new offering provides the manufacturers of ADAS with real time data insights based on big data and machine learning to optimise production and increase product quality. A cornerstone of the technologies being developed for autonomous and semi-autonomous vehicles, ADAS cameras are electro-optical systems that aid a vehicle driver and are intended to increase car and road safety.

The manufacturing of ADAS cameras is a highly complicated and costly process. Assembling ADAS cameras involves the integration of multiple specialised and sensitive sensors in a series of irreversible processes to create a high performance system. This has made it difficult for manufacturers to detect defective products during the assembly process, resulting in unpredictable performance that remains undetermined until the camera system is fully assembled and tested.

As a result, new designs of ADAS camera manufacturers struggle with extremely high scrap rates of around 25% on already expensive systems, leading to a high cost per unit and impeding the rate automakers can integrate the systems into their cars.

“Automakers need a holistic solution that can provide the big picture about the health of a vehicle,” said Dan Glotter, CEO of OptimalPlus.

“OptimalPlus is enabling automakers to take full advantage of the potential offered by new technologies while removing concerns about manufacturing quality products cost efficiently. The next two waves facing the automotive industry are autonomy and electrification, and both are going to bring enormous manufacturing complexities, requiring new analytics methods for faster product ramp, reduced scrap rates, and improved quality and reliability.”

Assembling ADAS cameras relies on a complicated supply chain to provide electronic and optical components from different geographical locations, all with different methods of ensuring and monitoring reliability, and with manufacturers relying on separate silos of product data and information, it is exceedingly difficult to ensure that these components will perform up to the required standards.

OptimalPlus addresses these issues by providing unprecedented visibility throughout the supply chain, connecting supplier data to field performance, enabling a full overview of production, increasing efficiency and enabling preemptive actions to find problematic products earlier in the manufacturing cycle and preventing unreliable products from being deployed or removing them in real time from the factory floor, reducing scrap rates and avoiding costly recalls.

“As systems such as ADAS cameras, that are the backbone of autonomous vehicles, become critical for safe driving, guaranteeing system quality is only going to become more important. As such OEMs are going to demand accountability from their technology providers on all supply chain tiers. With Optimal Plus’s solution, ADAS manufacturers can employ a proactive, prescriptive approach to improve production efficiency, cost, and quality rather than scrambling to react when a flawed product reaches the end of the production line,” continued Glotter.

OptimalPlus is able to accomplish this level of insight by combining big data with machine-learning algorithms on a global data infrastructure to drive real time product analytics that extracts hidden insights across data silos throughout the supply chain, enhancing all measurable production metrics.

The ADAS camera solution is part of OptimalPlus’s growing role in the automotive industry, where the company is working with OEMs and Tier-1s to optimise their production methods for both mechanical and electronic systems.

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