Industry 4.0 AI Solutions for the Manufacturing Industry
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Manufacturing

Your Pathway to Predictive Manufacturing​

Edge Intelligence

Deploy Industrial 4.0 Solutions – Powered by AI​

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What We Do

We Provide Smart Device & Machine OEM’s with Industry 4.0 Capabilities:​

  • Endpoint Intelligence – AI at the MCU Level
  • Edge Intelligence – Process Critical Data Locally
  • Intelligent Insights – Real-time Monitoring of Asset Performance
  • Self-Learning Algorithms – Machine Learning that Continuously Evolves
  • Endpoint Security – AI-Enabled Security Right at the Asset ​

Optimize Factory Floors with the
Intelligent Edge


  • Deploy Industrial 4.0 Solutions – Powered by AI​


  • Collect Raw Data, Train & Process on the Endpoint


  • MicroAI™ provides Privacy & Security​

Industry Challenges

Costly Machine Downtime

Increased automation makes machinery downtime more costly

Lack of Visibility into Machines

Output is not being optimized due to not understanding the “why” behind critical machinery and operator efficiency

Expensive/Inefficient Data Collection

Complex machines are producing enormous amounts of data making it very expensive to collect and process actionable intelligence.

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Business KPIs

Improve your OEE to 80% or better

  • Reduction in asset downtimes equates to improved output and greater ROI
  • Optimized maintenance schedules reduce the frequency of asset stoppages
  • More efficient utilization of asset maintenance staff
  • Faster identification and remediation of asset performance issues improves asset uptime and health
  • AI-enabled security protocols protect critical assets from malicious cyber attack
  • All the above result in increased production capacity, better resource utilization, reduced waste, increased asset lifespans, reduced COGS, and higher margins.

Benefits to Machines and Processes

Edge-based AI and ML for asset and process optimization

  • Visibility
  • Performance
  • Assessment
  • Operational Excellence
  • Business Excellence

Predictive Maintenance

MicroAI™ Atom eliminates the problem of poor visibility into real-time asset performance

  • Transition from reactive to predictive maintenance
  • Reduce expensive downtime of critical assets
  • Maximize the efficiency of operator and maintenance staffs

Predictive Process

MicroAI™ monitors the health and performance of manufacturing processes

  • Intelligent workflows that learn and evolve
  • Processes optimized to improve reliability and repeatability
  • Intelligent Workflows to reduce the reliance on human intervention

Predictive Security

MicroAI™ Atom provides AI-enabled security protocols

  • Self-learning security algorithms that evolve with changing threats
  • Proactive vs reactive cyber-threat mitigation
  • Reduction in security-induced downtimes and data integrity risks

Silicon & Hardware Manufacturers

  • Differentiated Offerings​
  • Deploy on Low Cost MCUs​​
  • Intelligence at the Source​
  • By providing AI as an integral part of the hardware architecture, Silicon and Hardware Manufacturers are able to offer differentiated product solutions.

Smart Equipment Manufacturers

  • Expanded Product Capabilities
  • Improved Customer Experience and Satisfaction
  • Integrated Cyber-Security Protocols
  • Performance and security of IIoT assets are continuously improved by self-learning algorithms that learn and train within their actual working environments.

Asset Owners

  • Reduction in Unexpected Asset Downtime
  • Deeper Insights into Asset Performance
  • Lower Cost of Ownership and Improved ROI
  • MicroAI™ can be deployed onto new or existing IoT devices or machines. MicroAI™ provides edge-based AI that enables predictive performance modeling and workflow-based alerts that improve asset performance and reduce downtimes.

Want to know more about how to optimize your specific industry?

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Case Studies

Problem

  • Unexpected downtimes and static maintenance schedules result in inefficient service routines, unnecessary service hours, and increased costs.
  • Lack of intimate, real-time, visibility into the performance of IoT assets. Assets not fully optimized.
  • Assets and their data under increasing threat from cyber-attack.

Use Case

  • Robotic welding arms across automotive assembly line were performing at a lower than expected overall equipment effectiveness (OEE~50%)
  • Non-optimized asset performance and security vulnerabilities were creating unacceptable yield loss and non-competitive manufacturing costs

Deployment Model

Fast deployment for fast and quantifiable results

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