nControl

nControl

nControl

nControl fueled by AIPC™ integrates advanced electronics, hardware and software with its DLC Edge™ computing to revolutionize manufacturing.

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AIPC

Using signal splitters to connect to sensors in your facility (such as PLCs, cameras, or wireless devices), AIPC™ aggregates real-time data about your manufacturing process, and uses deep learning to build models that provide KPI predictions, anomalous activity alerts, and autonomous control so the factory automatically adapts to increase yields and avoid malfunctions.

Most process control systems have some degree of automated monitoring, alerting, and diagnostic abilities, involving fixed formulas or statistical rules. If a sensor measurement is outside allowable bounds, alerts will be sent and mitigation measures will be put in place.

nControl

Inspect. Correct. Protect.

  • What if environmental conditions change, or the process elsewhere in the facility changes? A more flexible, contextually aware, nonparametric model can adapt, when a fixed formula would break down.
  • AIPC™ can catch subtle anomalies that traditional process control would miss and it can enable the facility to operate closer to its performance envelope without sacrificing quality or safety.
  • AIPC™ generates its models by directly copying analog signals from sensors in the facility, or by even including addition sensors where relevant such as microscopes and cameras. These models can generate instructions that connect directly to control actuators to directly prevent process failures and improve productivity.

AIPC Ensures:

Prediction:

AIPC™’s models track and predict KPIs such as yield, waste, energy use, and uptime.

Alerting:

If AIPC™ observes anomalous patterns indicative of process failure, or if it predicts a drop in KPIs, operators will be alerted so they can take corrective action.

Autonomous Control:

AIPC™ models directly feed back into process control automation, so the factory automatically adapts to increase yields and avoid malfunctions.

AIPC™ enables a variety of useful capabilities for manufacturers. Our capabilities in prediction, alerting, and autonomous control assist in our customers’ future success and longevity.

Scaling Production to Multiple Facilities: 

AIPC™ can track the output of each facility and allow you to identify root causes of underperformance.

Predictive Maintenance: 

AIPC™ can predict process failures before they occur, and localize impending failures to pieces of equipment that need repair.

Increase Productivity:

AIPC™s reinforcement learning models can optimize processes to increase manufacturing yields and facility uptime, making factories more efficient.

Greener Factories: 

AIPC™ can track metrics like energy use, resource consumption, emissions and optimize manufacturing processes to be more efficient and cleaner.

Security: 

Cyberattacks can sabotage the function of industrial facilities. AIPC™ can identify process anomalies that indicate possible malicious attack, and send alerts or directly modify processes, to prevent dangerous accidents or performance degradation.

 

nControl Live

nControl Live™ is an integrated hardware and software solution for improving manual assembly processes through AI video analysis.

 

 

The nControl Live platform enables three categories of applications:

 

Monitoring & Analytics, such as:

  • Automatic recording of the cycle time of each assembly step.
  • Predicted time to completion of each step and the entire process.
  • Detection of bottlenecks in the production process.
  • Trends in productivity and throughput over time, broken down by process step, assembler, time of day, or other predictive variables.
  • Correlation of quality KPIs with patterns in assembly technique to identify possible improvements.

 

Monitoring & Analytics, such as:

  • Logging missed steps.
  • Logging misoriented parts.
  • Alerting the assembler when an error is made, to prompt corrective action.
  • Alerting the assembler when an injury risk is detected (such as poor ergonomics or proximity to a dangerous piece of equipment).
  • Enabling root cause analysis for defects by calling up relevant error logs.

 

Monitoring & Analytics, such as:

  • An interactive video manual for training new employees or teaching a new assembly process.
  • Checklists prompting the assembler to move on to the next step as each step is completed.
  • Extracting nuances of good technique from expert assemblers.