‣Product Improvements:-

Design changes for

• Product cost reduction

• Part count reduction

• Proper fit and function

‣ Problem Solving:-

• Solve design problems to optimize function, reliability and robustness

• Solve engineering problems through analysis and computation

• Bring the best of both worlds – design feasibility and design requirement

‣ Part Handling Solutions:-

Design changes for

• Optimum handling solution for the given problem

• Make or buy decision for handling accessories like grippers

• Combining parameters like speed, capacity, safety and cost to arrive at the right solution

‣ Manufacturing Automation:-

• Sophisticated automation with PLCs, sensors and actuators

• Choosing the right actuator/sensors

• System design considering impact of control on the accuracy and reliability of the automation system

‣Industrial Application:-

Industrial Robots for :-

• Pick and Place / Handling for precise handling

‣ Commercial Application :-

Robots for needs like

• Service robots

• Friendly robots

‣ Defence / Nuclear Application:-

Robots for needs like

• Surveillance robots

• Swarm robots

‣ Sensor Application:-

• Sensor selection based on the application

• Building circuitry to enable sensor data capture

• Saving sensor data into a proper data structure

‣ Data Analytics:-

• Data transformation / Data normalization

• First level statistical analysis

• Using Machine Learning algorithms for finding patterns and doing prediction

• Partitioning data into training, cross validation and test data

• Inferencing insights from predictions and patterns

‣Manufacturing / Assembly Risk:-

• Evaluate manufacturing & assembly risk based on manufacturing & assembly parameters

• Combine process capability, DFMEA & manufacturing/assembly risk to predict quality cost

‣ Engineering de-skilling:-

• To reduce human error

• To make skill free decision making

• System dependent solutions

‣ Anomaly Detection:-

• Find anomalies from process data

• Provide actionable information like early warning for failures

‣Gesture Recognition:-

• For intuitive user interfaces in industry and consumer applications

‣ Visual Inspection:-

• Using camera / laser/ IR sensor

• Defect recognition / Defect classification

‣ Artificial Intelligence:-

• Custom “learning” algorithms

• Combine sensors, data and AI to design intelligent adaptive systems