Stage - Flexible Assembly Demonstration

VIVENTRIS – Smart production solutions for the industry of tomorrow

Viventris develops smart and flexible production solutions that help companies improve their processes and make them future-proof. We specialize in visual inspection and assembly, with applications in consumer products, high-tech systems, and healthcare, among others.

Our strength lies in combining generic building blocks with customer-specific customization. This allows us to realize efficient and reliable solutions for the production of compact and often complex products. We work pragmatically and closely with our clients to achieve results quickly and make a real impact on the shop floor.

Within our focus area of assembly, we automate manual processes and complex operations, leading to increased product quality and improved efficiency. Within our inspection expertise, we develop advanced vision systems utilizing both rule-based algorithms and AI. This enables accurate product inspection and reliable defect detection.

With our solutions, we contribute to smarter production processes and consistent product quality.

Demonstration of flexible assembly

Modern production systems are moving towards flexible, reconfigurable modules that can be quickly deployed in various machines and processes. Instead of fixed production lines, an ecosystem of modules (robotics, tooling, transport, and inspection) is emerging, which work together via standard interfaces.

In this internship, you will work on a physical demonstrator of such a plug-and-play production module where mechanics, control, and sensor technology come together.

Goal

Develop and demonstrate a flexible production module (robotic assembly or pick-and-place station) with standardized mechanical, electrical, and sensory interfaces that are reusable and expandable.

What are you going to do?

Depending on your interests, background, and internship duration:

• You are working on designing and building a modular production module that can function independently and be easily linked to other systems. This results in a robotic assembly or pick-and-place station based on a cobot or industrial robot.
• An important part of the internship is investigating flexibility in two layers.
  • On the one hand, you look at handling product variation within a set variant, where the challenge lies in reliably holding, positioning, and assembling parts with variations in shape, tolerance, or orientation. For this, you investigate the interplay between the robot, gripper, camera, and any additional sensors, and how feedback (such as vision, force, or position information) can be used to react adaptively during the process.
  • On the other hand, you investigate how the system can be quickly learned for new products, i.e., beyond existing product variations. This is about reducing engineering and setup time: how can a new product configuration be added without complete reprogramming of the robot, gripper, and vision system? You will look at modular configuration, reusable motion and gripping logic, simulations, and possibly (semi-)automatic calibration or teaching strategies.
• Based on these insights, you will design a working demonstrator in which mechanics, robotics, and sensors work together to handle both variations and new product introductions. The focus will not be on a single component, but precisely on the integration between all subsystems.
• In addition, you ensure that the module can be linked to other modules within a broader system concept via standardized interfaces, so that combinations with, for example, inspection or transport modules also become possible.

Result

A working plug-and-play production module (prototype) that performs a realistic assembly or handling process and can demonstrably be integrated into a modular production system.

Required skills

• A mechatronics education or similar
• Basic programming experience
• Affinity for industrial automation
• Interest in robot programming and system integration
• Experience with cobots or industrial robotics
• Experience with computer vision or force-torque sensing