InControl Engineering
A technology company delivering turn key automation and control solutions
Specializing in equipment health monitoring, real-time embedded control systems and run-to-run process control. Our products will improve process capability, reduce product scrap and minimize equipment downtime.
Smart Sensors
A True Predictive Maintenance Solution
Our smart sensors monitor your equipment health and quickly alert you when maintenance is required
Heating Elements
Resistance monitoring to prevent wafer scrap and reduce equipment downtime
Vacuum Pumps
Vibration monitoring to prevent wafer scrap and reduce rebuild costs
Turbo Pumps
Vibration monitoring to prevent wafer scrap and process tool damage as well as reduce rebuild costs
Boat Rotation Units
Vibration monitoring of ferrofluid seal, motor and mechanical linkage to prevent particle contamination and wafer scrap
DC Power Supplies
Voltage monitoring of power supplies to reduce wafer scrap and equipment downtime
Chemical Mechanical Planarization
Vibration monitoring of polishing heads, tables, conditioning arms, spin rinse dryers and brush boxes to prevent wafer breakage and unscheduled downtime
Wafer Scratch and Impact
Vibration monitoring to detect misalignment of the automation resulting in wafer scratching or breakage
Wafer Transfer Robots
Vibration monitoring to detect component degradation and calibraton drift of the robot to prevent wafer scrap and equipment downtime
Mass Flow Controllers
Gas flow monitoring to ensure MFC integrity to reduce wafer scrap and process drift
Boat Loaders and Elevators
Current and vibration monitoring of step motors to prevent particles and equipment downtime
Exhaust Line Obstructions
Pressure monitoring of exhaust draw to detect clogging in the lines or abatement system to prevent wafer scrap and equipment downtime
Cabinet Exhausts
Vibration monitoring of bearings and motors of the exhaust to prevent cabinet overheating, process drift and wafer scrap
Halogen Lamps
Resistance and light intensity monitoring to process uniformity variation and wafer scrap
Heater Blocks
Resistance monitoring to prevent wafer scrap and reduce equipment downtime
Spin Rinse Dryers
Vibration monitoring to detect rotational imbalance due to ferrofluid seal, bearing, motor, missing cassettes or rotor degradation
Widespread sensor integration in consumer products is changing the face of industrial manufacturing
Today we expect to have real-time information at our finger tips to make informed decisions about our manufacturing equipment and processes. The exponential growth in conjunction with new innovations in this market provides us with more sensing element options than ever before.
- Current: hall effect, rogowski coil, transformer coil
- Distance and Proximity: capacitive, eddy-current, hall effect, inductive, laser, LED, magnetic
- Flow: magnetic, mechanical, optical, pressure, thermal mass, ultrasonic
- Force: resistive strain, piezoelectric
- Gas: composition, mass flow, pressure, leak
- Light and Color: LED, photodiode, photoelectric, photoresistor
- Motion: doppler, infrared, optical, radar, ultrasonic
- Orientation: accelerometer
- Pressure: gas, barometric, vacuum
- Radiation: nuclear, RF, photovoltaic, pyroelectric
- Resistance: current, voltage, temperature
- Seismic: accelerometer
- Sound: microphone
- Temperature: thermocouple, PRT, RTD, laser
- Vibration: accelerometer
- Voltage: resistive, transformer
Equipment Control Systems
Our solutions improve process uniformity, yield, throughput and reliability
Whether you are upgrading a single control component or completely replacing an obsolete/unsupported equipment control system, our state of the art control system systems will breath new life into your manufacturing equipment
Model Based Temperature Control (MBTC)
Diffusion furnace controller retrofit to improve process capability and eliminate profiling
Heating Element Life Optimization Controller
Optimization of the existing temperature control system power application to improve heater life
Technologies
Equipment Modeling
Differential equations developed using first principles or empirical modeling techniques to mathematically describe the equipment to optimize the equipment control system
Virtual Sensors
Offline process modeling using sensors embedded in the product being produced to improve process control and uniformity during normal operation
MIMO Control
Advanced control of equipment with multiple inputs (control adjustments) and multiple outputs (sensors measurements) that have interactions or dependencies between each other
Nonlinear Control
Control of complex equipment with either significant variation across operating conditions or over time
Run to Run Process Control
Model Based Temperature Control (MBTC)
Diffusion furnace controller retrofit to improve process capability and eliminate profiling
FeedBack Process Control
Adjust control variables using process measurements from the previous run
Compensate for process drift
FeedForward Process Control
Adjustment of the process objective in the current manufacturing step based on the results of previous steps
Compensate for past process variability in multi step processes
