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As industrial automation advances toward flexibility and intelligence, the gap between what robotic systems can see and what they can understand remains the single greatest barrier to true autonomy. ifm, a global leader in sensing technology, bridges this gap by delivering three core values for robotic systems: high-precision perception, real-time data fusion, and virtual commissioning support. Through these pillars, ifm empowers partners like momac GmbH to achieve reliable, repeatable automation in the most complex and demanding scenarios – from mixed-model automotive assembly to high-mix logistics picking.
This is not sensing for sensing's sake. This is perception as an enabler – turning robotic arms from blind, pre-programned movers into adaptive, intelligent systems that respond to their environment with human-like precision.
ifm's competitive edge rests on three differentiated technology platforms, each addressing a critical gap in modern robotics applications.
Beyond 2D Limitations: Conventional 2D cameras cannot determine depth, orientation, or surface curvature – limitations that fail in bin-picking, depalletizing, and assembly applications where parts are randomly positioned. ifm's 3D industrial cameras leverage either Time-of-Flight (ToF) or stereoscopic vision technologies to generate millimeter-precision point clouds, even under challenging lighting conditions, reflective surfaces, or cluttered backgrounds.
Dynamic Grasping Capability: The 3D vision system outputs real-time data on:
3D position (X, Y, Z coordinates)
Orientation (roll, pitch, yaw angles)
Surface features (curvature, flatness, hole locations)
This enables robots to perform random bin picking – extracting irregularly shaped parts from unstructured containers without human intervention – and dynamic grasping where the robot adjusts its grip in real-time based on the part's actual orientation.
Typical Applications:
Hole alignment in automotive assembly – the 3D camera guides the robot arm to within 0.5mm of the target hole, enabling precision insertion of fasteners and bushings.
Six-sided inspection of logistics cartons – the system captures the full 3D geometry of each package, verifying dimensions, label placement, and damage before automated sorting.
The 3D vision system provides the "eyes" of the robotic cell; the IO-Link sensor network provides the "sensory nervous system."
Pallet Positioning System – A Deployed Solution:
8 x ifm photoelectric distance sensors form a distributed detection array around the palletizing station.
An IO-Link master transmits contour data from all sensors in real-time, automatically generating palletizing coordinates for the robot.
The system achieves ±1mm accuracy with adaptive algorithms that compensate for material color, surface reflectivity, and ambient light variations – no manual calibration required.
Predictive Maintenance Enablement: Beyond positional sensing, ifm's IO-Link portfolio includes:
Vibration sensors – monitor motor bearing health; detect imbalance or wear before failure.
Temperature sensors – track thermal drift in critical actuators.
All condition data is transmitted via the same IO-Link infrastructure, eliminating the need for separate monitoring wiring and enabling centralized asset health management without additional hardware investment.
Digital Twin Ready: ifm sensors provide standardized data interfaces (including OPC UA, Profinet, and ROS-compatible formats) for direct integration with simulation tools such as TIA Portal, ROS, and Siemens NX Mechatronics Concept Designer. This allows system integrators to build complete digital twins of the robotic cell – including sensor behavior, environmental interference, and lighting variations.
Pre-Validation Benefits:
Optimize vision thresholds – determine optimal exposure, confidence levels, and recognition parameters in simulation, eliminating trial-and-error on the physical line.
Validate robot trajectories – simulate pick-and-place paths to avoid collisions before the robot is even mounted.
Reduce on-site debugging time by 50% – the physical commissioning phase becomes verification, not discovery.
The partnership between ifm and momac GmbH exemplifies how technology and system integration combine to deliver measurable value across the entire project lifecycle.
| Phase | ifm Contribution | Customer Benefit |
|---|---|---|
| Design | 3D vision selection guidance + scenario-specific test data – match the right camera model, resolution, and field-of-view to the application | 15% cost savings by avoiding overspec'd sensors; confidence that the chosen hardware will perform before purchase |
| Integration | IIoT platform support (e.g., moneo software suite) – cloud-based equipment monitoring, dashboarding, and alerting | Real-time visibility into sensor health and performance; reduced maintenance overhead |
| Optimization | Data-driven algorithm improvement recommendations – ifm analyzes field data and suggests tuning parameters | 12% recognition rate increase within 3 months (validated in a live production case) |
Why This Model Works: ifm does not just sell sensors. The company provides continuous performance improvement – treating each installation as a living system that evolves with production demands.
The Challenge: A leading automotive manufacturer needed to implement mixed-line assembly of 12 engine block variants on a single production line. Each variant had different mounting hole patterns, weights, and surface geometries – yet the robot needed to pick, position, and insert fasteners with absolute precision regardless of which variant arrived.
ifm Solution Deployed:
| Component | Function |
|---|---|
| 3D camera | Part identification and positioning with 0.5mm accuracy – instant recognition of which engine block variant is present and its exact spatial orientation |
| Force-torque sensors | Shaft-hole alignment during insertion – the robot senses resistance and adjusts in real-time, preventing jamming or damage |
Measurable Results:
| Metric | Before | After | Improvement |
|---|---|---|---|
| Changeover time | 45 minutes (manual re-tooling) | 90 seconds (fully automated) | ↓ 96% |
| First-pick success rate | ~85% (with previous vision system) | ≥ 99.7% | ↓ defect rate by factor of 30 |
| Line flexibility | Single variant per shift | Mixed variants per minute | Unprecedented agility |
ifm is redefining industrial automation reliability – shifting the paradigm from reactive response (fixing failures after they occur) to active perception (anticipating, adapting, and optimizing in real-time). Through millimeter-accurate 3D vision, intelligent IO-Link sensor networks, and virtual commissioning capabilities, ifm delivers the foundational certainty that smart manufacturing demands.
Technology Extension: ifm's latest CR-series 3D cameras now feature on-edge AI classification – enabling direct feature learning without PC processing. This allows the camera to distinguish between part variants, detect surface defects, and classify objects at the edge, in real-time, reducing system latency and eliminating the need for external inference hardware.
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