Our team analyses each requirement using our unique methodology that combines the principles of physics and data diagnostics using in-house algorithms. Our persistence on good quality data collection and high-resolution analyse has made us stand out from the conventional; the methodology has allowed us to define individually the signature of each machine. The data is analyzed real-time to maximize machine performance. The system ingeniously looks for correlations across multiple parameters and compares the results against predefined goals or data from a base-line run.
Our solution has been successfully implemented in the below department:
* The above images are from just one set of the real-time data captured with our system. Please contact us should you need detailed case studies. Robotic stability issues are broad and this was just one scenario. Approach us for a free consultation to identify our solutions applied to your issues
ROBOTICS STABILITY MONITORING
Sigenic’s Robotics Stability Solution provides comprehensive, high accuracy and real-time monitoring
of the condition of targeted robots throughout the integrated circuit manufacturing process. This ensures successful automated silicon wafer transfer and logistics. The solution prevents unwanted excursions, identifies
(via real-time analysis) and then predicts unexpected
wear and damage. This reduces error rates, boosts quality, increases reliability and optimizes throughput.
Some proven error conditions and causes already identified bn the system include:
• Robot position drift causing wafer collision against flange.
• Wafer on lower arm bounced, causing wafer scratch.
• Robot blade scratched wafer underside.
• FFU fan motor irregularities caused undesirable cantilever effects
• Plunger condition monitoring.
• Vacuum induced bouncing prediction.
POLISHING CONDITION MONITORING
Sigenic provides reliable health monitoring solutions for wafer polishing machines. These services provide precision results. The condition monitoring technologies improve process reliability and are designed to ease machine operation. The analysis provides insight of the polishing conditions, reducing chances of excursions from the optimal result.
Proven error conditions and causes already identified by the system include:
• PC arm collision against polishing head prediction
• Broken Flexure Plate prediction
• Pad surface condition/properties monitoring
• Platen bearing condition monitoring
* The above images are from just one set of the real-time data captured with our system. Please contact us should you need detailed case studies. Polishing Condition Monitoring issues are broad and this was just one scenario. Approach us for a free consultation to identify our solutions applied to your issues.
PREDICTIVE MAINTENANCE SOLUTIONS
Our predictive maintenance approach is determined by the actual condition of equipment rather than average or expected statistics. Essentially, the system predicts failure prior to any related excursion by closely monitoring the machine during operations. When this approach is applied to maintenance, it immediately delivers cost savings over routine or time-based preventive maintenance. The maintenance tasks are performed only when warranted, increasing up-time and reducing maintenance costs.
Proven case in point:
• Manual periodic checks on cleaning sponge & brush.