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DEVELOPMENT AND IMPLEMENTATION
This is a partial list of
systems designed and developed by Sergio Sedas. Each one of these systems has
been operating in their intended industrial environment.
 photos
video
video
INDEX
(for
details click on each link)
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Vision
& Robot Inspection System for GM Chasis - Line1, Line2, Line3. (FORMEX/MAGNA)
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Vision
& Robot. Automated Sorting System for GM3.4L, GM3.5L and GM China Engine
Heads. (NEMAK)
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Final
Packaging Station
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Pre-Machinning
Station
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Post-Machinning
Station
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Vision
Sorting ID System FORD Duratec 3.0/2.5 Right and Left Engine Heads.
(VALIANT/NEMAK)
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Vision
System for Engine Liner Model Verification 5.7L/5.3L/6.1L. (VALIANT/NEMAK)
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Vision
System to Detect Chassis Model through Differential Hole Locations (FORMEX/MAGNA)
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Vision
System to Detect Bumper Presence in Chassis (FORMEX/MAGNA)
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Vision
System to detect obstructions in Engine Block Pallets (NEMAK)
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Vision
System to Detect Proper Model and Orientation of Catalytic Converter
Substrate Line1 and Line2 (VISTEON)
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Detect
presence of GIMB, Components, Part Model and Screw Alignment in Automotive
Lamps - three models (VISTEON)
A DVT Smart Image Sensor is used to inspect 13
points of a truck frame. The sensor is mounted on a FANUC robot arm.
Different illumination techniques are used to highlight the features for
inspection. Backlighting is used to detect pin and bolt presence, baklighting at
an angle is used to detect the presence of threads. Finally, dark field
illumination is used to high-hight a pin stamped data matrix that contains
traceability information. Cycle time is
13 points in 21 seconds.The result of each inspection is displayed in a
Panelview 1400. The control is generated by an Allen Bradley PLC5 with Remote
I/O. Synchronization with the robot is done through Control Net.
Click
for Video
in a reduntant system, A DVT Smart Image Sensor and a High Accuracy SMAC
Smart Actuator are used to identify three different part models. Each sensor
concentrates on seeing or touching a primary geometric feature of the part. A
motorized conveyor with Clutched Rollers conveys the part to an unload station.
A robot takes the part from the unload station and deposits it in one of four
gravity conveyors – one for each model plus the parts that are
“unidentified”. The system is controlled by an Allen Bradley SLC5/04 PLC.
Results are graphically presented on a Panelview 600C. Cycle time one part every
9.5 seconds.
Click
for Video
A DVT Smart Image Sensor and a High Accuracy SMAC
Smart Actuator are configured in a reduntant inspection system to identify three different part models. Each sensor
concentrates on seeing or touching a primary geometric
feature of the part. Only one is accepted through the line, the other two
are rejected through a gravity conveyor. A motorized conveyor with Clutched
Rollers conveys the part. A pneumatic lift and reject cylinder push rejected
parts over the reject conveyor. The system is controlled by an Allen Bradley
SLC5/04 PLC. Results are graphically presented on a Panelview 600C. Cycle time
9.5 seconds.
Two DVT Smart Image Sensors are used to identify four different part models. Each sensor
concentrates on seeing a primary geometric feature of the part from where the
part model is determined. Only one part model is accepted through the line, the
other three are rejected through a passive rail conveyor. The good parts are fed
onto a two station unload shuttle. A robot, takes the part from the shuttle and
loads them into a sand-decoring machine to initiate process of the parts. The
system includes the identification system, a pneumatic “walking beam”
conveyor, an output rail, a download shuttle, the inspection station and two
pushing mechanisms. The system is controlled by an Allen Bradley SLC5/04 PLC.
Results are graphically presented on a Panelview 600C. Cycle time 1 part every
12 seconds.
Click
for Video
Two DVT Smart Image Sensors are used to identify
four different part models. Each sensor concentrates on seeing a primary
geometric feature of the part from where the part model is detemined. Inspection
is performed on moving parts. Infrared illumination and specific lamp locations
are used to generate good illumination without specular reflections. The part model is communicated to a gantry robot
that stacks the parts into a particular bin. The system is controlled by an
Allen Bradley Micrologix PLC. Cycle time 1 part every 10 seconds.
A DVT Smart Image Sensor with a high accuracy tele-centric
lens is used to identify the model and orientation of engine liners. These are
identified by measuring the wall thickness of the liner. A telecentric lens is
used to minimize distortion, and lighting at an angle is used to minimize
reflections that could mislead the identification algorithsm. The system is controlled by an Allen Bradley PLC. Cycle time
1 part every 0.5 seconds.
A DVT Smart Image Sensor with a high accuracy tele-centric
lens is used to measure the location of two holes on a Cadillac Frame. The
distance determines the part model. The part is inspected in motion and only a
single camera is used. Information
is communicated to an Allen Bradley PLC.
A DVT Smart Image Sensor with a long distance zoom
lens is used to locate and identify a plastic bumper on a Cadillac Frame. The
diameter of a hole determines the part model. The DVT Sensor is located at over
6 meter distance from the part. Information is communicated to an Allen Bradley
PLC.
A DVT Smart Image Sensor with a long distance zoom lens
is used to verify that three holes on a solid conveyor pallet are clear of
aluminum. The part is presented to the Smart Image Sensor by an articulated ABB
Robot Arm. Mounted on the robot grippra is a large high-power red LED lamp to
provide high-contrast imaging. Communication is direct between the robot and the DVT Smart Image
Sensor.
A DVT Smart Image Sensor is used to verify that
orifices are clear of aluminum which would have resulted from a broken sand
core. The part is conveyed on a motorized conveyor and the inspection is done with the
part in motion. Multiple infrared strobe lamps provide the required shadowless
illumination. Communication is direct between the robot and the DVT Smart
Image Sensor.
A DVT Smart Image Sensor is used to read an ID
label on a catalytic converter substrate to verify the model is correct and
properly oriented. Infrared lighting and white balance are used to improve the
image acquisition. The ID system is part of a manual inspection and assembly
station in which the operator simply places the part into shell and passes the hand over optical
sensor to trigger the inspection. If the part is bad, it is blocked from
removal until the fault is acknowledged by the operator.
Four DVT Smart Image Sensors are used to fully
inspect an automotive lamp assembly. The angle and depth penetration of two
screws and presence of gimb and waterjet are inspected. The part model is read
from an engraving on the plastic surface of the lens. Different lighting
conditions are set up for each of the cameras. Back-lighting is used to measure
part presence and image the screw. Dark field illumination is used to high-light
the embossing over clear plastic. Differnt vision operators are used. The station includes a
manual load station, pneumatic shuttle and four DVT smart Image Sensors. Control
is through an Allen Bradley SLC5/04 PLC. Feedback in visual graphics through a
panelview Display. Currently nine models have been programmed.
Three DVT Smart Image Sensors are used to fully
inspect an automotive lamp assembly. The angle and depth penetration of two
screws and presence of gimb and waterjet are inspected. The part model is read
from an engraving on the plastic surface of the lens. The station includes a
manual load station, pneumatic shuttle and three DVT Smart Image Sensors.
Different lighting conditions are set up for each of the cameras. Back-lighting
is used to measure part presence and image the screw. Dark field illumination is
used to high-light the embossing over clear plastic. Differnt vision operators
are used. Control is through an Allen Bradley SLC5/04 PLC. Feedback in visual graphics
through a Panelview Display. Currently nine models have been programmed.
A DVT Smart Image Sensor is mounted in a
pressurized enclosure inside a paint booth to detect the presence and model of
transparent automotive lens covers. Specular reflection is used to detect the
presence of the transparent cover. Regular lighting is used to determine the
part model. The information is relayed to a robot which
will paint according to this information. The parts are inspected while in
motion. Communication is through an Allen Bradley SLC5/04 PLC.
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