Automation & IIoT software
Machine data analytics (AI/ML)
Digital platforms (smart factory)
Based on machine sensor, hardware components and available system data (streamed in real-time), ADAPDIX integrates machine learning and artificial intelligence (AI/ML) in order to promote the use of predictive data analytics 1) in advanced manufacturing environments.
The Company’s in-house developed EdgeOps™ platform technology enables industrial clients from the semiconductor, electronics manufacturing and automotive industry to transition from forecasting and planning of events to the real-time monitoring and management of equipment and process failures (i.e. AI powered anomaly detection) in order to optimize system uptimes, production yields and total costs of ownership (OEM equipment) on a factory level. As the industry progresses towards “Industry 4.0”, it requires competitive and scalable industrial IoT technology at the Edge 2) that becomes a competitive force in modern manufacturing.
Adapdix’ EdgeOps™ software platform combines big data, machine learning and artificial intelligence, enabling machinery equipment OEM’s and industrial manufacturers to deploy Autonomous Edge solutions to implement predictive analytics and Adaptive Control of operational technology (OT). In this regard, the EdgeOps™ platform enables unlimited real-time access to large data stores of previously unreachable critical OT data, and creates a digital core for new and legacy industrial equipment deployed in large-volume manufacturing environments.
Fortune 500 companies and leading advanced technology system providers (OEM’s) are piloting and implementing ADAPDIX’ integrated machine learning and AI capabilities in high-volume production environments in order to manage, maintain and gain deeper insights to their manufacturing ecosystem. Current OEM equipment applications include semiconductor process, robotic stations and other yield critical assembly equipment.
X2 partnered with Adapdix in 2019, provided growth financing and supports the company during its international roll-out further providing operational platform support in Germany and China.
1) Predictive analytics encompasses a variety of statistical techniques from data mining, predictive modelling, and machine learning, that analyze current and historical facts to make predictions about future or otherwise unknown events.
2) Edge Analytics is an approach to data collection and analysis in which an automated analytical computation is performed on data at a sensor, network switch, IoT Gateway or other machinery hardware device instead of waiting for the data to be sent back to a centralized data store.