As a first proof of concept of the potential of RTDMP in agile production, the DynaMo joint effort will implement RTDMP as part of a bin picking application in Kuka R&D lab in Augsburg, Germany. RTDMP will become an essential part of solving the need for flexibility, agility and low lead times for flexible multipurpose robotic picking systems. The project aims to demonstrate the increased flexibility, adaptability and efficiency enabled with RTDMP in bin picking applications.

Project SALSA2d intends to develop a real-time online-offline robotic programming interface specific to AM: Essentially a digital teaching, commissioning and monitoring platform, aka ‘Digital Twin’. We are combining this custom software with a sensor-rich layer and low-cost off-the-shelf robots, tools and vision systems. The result will present a new type of automation, one that is flexible, agile, low CapEx, easy to scale and empowers users.

ARGRIND robotic system features: Scalable industrial robot and compliant grinding tools. Embedded tool wear control for homogeneous material removal along the part. Companion ground surface simulation software for fast programming of new parts. Single grinding strategy management and control human-machine interface. Increased productivity with automatic collision-free tool changing and calibration. Continuous robot and process monitoring for production traceability. Validation on real aerospace parts.

Showcase advanced robotics solutions that increase the agility of the automotive cable production industry by using TRINITY robotics solutions like HRC, projected user interfaces and AI based machine vision.

Snipe developed a Sensor Network for Intelligent Predictive Enterprise. IoT / Cybersecurity.  The main objective of was to to create a Smart Monitoring infrastructure for revamping 4.0 of non-digitalized Foundry process, predicting machine down-time collecting and analysing process data.

As optimization of internal production logistics is crucial to become more agile, we are still struggling with the fact that integrating a task driven AMR solution is very complex, the loading and unloading is still too slow (docking) and it is difficult to combine systems of different brands. This demonstrator will show a solution for these challenges, that can be reproduced in your own facility.

The demonstrator provides a complete robotized sorting solution for logistics. The system localizes and picks each parcel post from a large bin, weighs it, measures its volume, and sorts it into different outgoing containers according to their destination. The implemented solution is designed for easy integration into existing production lines.

The MYWAI-4-ROBOTICS project aims to develop a novel CBM solution for robotic arms integrating Natural Language Processing (NLP) for voice driven control, Artificial Neural Networks (ANNs) for preventive anomaly detection, and an innovative Distributed Ledger Technology (DLT) for pre- and post-sale supply chain certification. All these features are necessary for a CBM solution to be easy to interact with, effective and trustworthy.

LMD-AUTO automates the process of laser cladding on two fronts: Automate material handling with robot-assisted bin-picking and robot-welding. Enable turn-key operation by means of Industry 4.0 operation. The core of the LMD auto module is the combination between specific sensor solutions and active process control

This project demonstrate a single, low infrastructure cost system for manufacturing that enables track&tracing, the creation of worker safety zones and/or collision detection. The solutions will be made available for experimentation through the IMEC industrial IoT testbeds.

The objective of the project was to demonstrate a smart factory concept, for robotics-based manufacturing of complex photonic products, with in-line operator stress detection for safety and optimized production. The demonstration is based on a modular machine platform having in-line monitoring and quality control functionalities for in-line adaption of production steps.  The demonstration includes an appealing showcase in which human factors are successfully included in the execution of a manufacturing process for optimized production, eventually opening the gateway for affective cobots.

Fully autonomous and highly interactive inventory taking robot for agile production, Libraries, Archives, Warehouses, Offices etc. Higher Level of Intralogistics Automation, Near Real Time and Accurate Information on Inventory with Online Availability, Fast Product Access Enabled by Precisely Known Product Location, Direct Information Provision for Users (right content at right place and right time), Smart Warehouse, Internet of Things, Gain of Efficency and Enhanced Environmental Protection by Eliminated Excess Inventory and Associated Goods Movement, Future Proof High System Flexibility.

Robotic Wire Arc Additive Manufacturing (WAAM), a large-scale metal 3D print technology that uses an arc welding process to produce metal parts additively, has the potential to shorten the lead time of producing pipeline clamps as the production can be fully automatic with less material waste, enables new/optimal geometries and can be done on-site. The consortium aims to facilitate post-processing and inspection acceptance by integrating standard connections and 3D printing to create a customized industrial pipeline clamp.

AkkuSer Oy receives and sorts all the recycled portable batteries in Finland (1.500 tons per year). After the sorting it is possible to re-use the metals used in the batteries as well as re-locate the dangerous materials safely after the use. This project aims to automatise the slowest part of the process (identifying and sorting the cylindrical cells (AAA to D size) and the consumer batteries).

Although the use of industrial robotics in the automotive industry is mainstream, there are still parts of the production process which need human intervention - demand for increased dexterity. These manual tasks increase the production time and reduce the flexibility of the production line, as well as the quality of the end product. TRAINMAN-MAGOS aims on tackling this Challenge.

Main objective of ROBOBEND is to provide the world’s first standard bending robot with an easy to manage hardware and unique control solution, enabling it to be used at any of the existing press brakes. The solution is an integrated intelligent system that operate bending machine fully replacing the operator.

The objective of the current proposal is the development of a complete automated system for robotized welding through the combination of advanced (collision free) offline programming, with advanced sensing for part localization and robot calibration. A successful project will allow the broad adoption of robotic welding, through the removal of the current major barriers.

Digi-SAAP demonstrator showcased how to increase the flexibility and lower programming time for assembly task with collaborative robots running screwdriving task. The focus was on fast and easy teach-in while ensuring high screw insertion process quality. A monitoring system logs all screw insertion data.

The main objective of the demonstrator was to make the manufacturing process of electric motors more agile, by deploying three TRINITY-originated modules in a production line. This may lead to increased HRC level and productivity in the coils winding step, waste material saving, economic and social benefits.