THOMAS | Mobile dual arm robotic workers with embedded cognition for hybrid and dynamically reconfigurable manufacturing systems
01-10-2016
-31-03-2021
01-10-2016
-31-03-2021
01-10-2016
-31-03-2020
01-11-2019
-30-04-2023
01-10-2016
-30-09-2019
Through oinline monitoring an immediate reaction to quality problems is possible and the autonomy of the production line is increased.
01-10-2018
-31-03-2022
ROSSINI provides several advances beyond the state of the art, developing a Safety Aware Control Architecture for robot cognitive perception and optimal task planning and execution.
In order to enable actual perception, ROSSINI leverages on a data processing technique for real-time image recognition, to obtain a semantic scene map that adapts to dynamic working conditions.
ROSSINI adopts also algorithms for motion prediction of humans and moving entities, and embeds their stochastic information in the dynamic semantic scene map. This allows the robot to further refine its planning in order to maximize performance while preserving safety.
In this way, ROSSINI introduces a novel perception and control architecture blending safety and performance oriented planning/control that wants to reach the goal of optimising the trade-off between human operator safety and manufacturing productivity.
The ROSSINI platform implementation of a Safety Aware Control Architecture makes it possible for robots to optimally schedule the tasks reacting to a changing environment. in fact, each action to be execute is sent to a dynamic planner that dynamically optimizes its execution in terms of trajectory to follow and/or interactive behaviour to reproduce while considering the variable safety conditions in the working area.
01-12-2019
-30-11-2022
ATS Bus - Enabled a single, common service bus for data exchange between the PLCs and other high level components of the system, including a SCADA system. Used a broker-based publish-subscribe approach to decouple the physical sources and destinations of the data to facilitate reconfigurability.
ATS Bus - Enabled a single, common service bus for data exchange between the PLCs and other high level components of the system, including a SCADA system. Used a broker-based publish-subscribe approach to decouple the physical sources and destinations of the data to facilitate reconfigurability.
01-07-2010
-30-06-2013
01-10-2016
-31-03-2020
01-09-2016
-30-11-2019
01-05-2017
-31-10-2020
01-11-2015
-31-10-2017
01-10-2017
-31-03-2021
01-09-2022
-31-08-2025
01-04-2015
-31-03-2019
11-01-2015
-31-12-2018
11-01-2015
-31-07-2020
11-01-2015
-31-10-2018
01-10-2017
-31-03-2021
Z-Bre4k will provide a complete monitoring solution at component, machine and system level by combining the high capabilities and effectiveness in sensors and actuation, networking and computational power, utilisation of better and smarter technologies (e.g. material and tools). The latest technologies and algorithms will be utilized for adaptive systems while surpassing the fact that they are disjointed, overwhelmed by complexity, vulnerable to external influence and poor Predictive Capabilities.
A real-time adaptive simulator with high fidelity will be a demonstrator (remote or local) of the machine’s state, in which a fast-forward simulation mechanism (prognostic models) predicts the potential events of breakdown of components and machines. What-if capabilities will allow the maintenance planners to find the most effective and cost-efficient schedules for component replacement and maintenance plans.
Strategies to improve maintainability and increase operating life of production will be applied to update the existing and to develop a set of new strategies based on real data in order to improve maintainability and operating life of production systems. This approach will use a method to translate optimization objectives defined at production and factory levels, into optimized maintenance policies at asset/production process levels.
At the asset and machine level, the Z-BR3AK solution will perform a condition monitoring and generate health status reports. Attention will be given to the faults detection through FMEA analysis (FMECA) to allow remedial actions and synchronise the manufacturing process. The proposed engine will perform monitoring, inspection and control at component, machine, system and product level to issue warnings, alerts (e.g. about deviations from production and quality requirements), reports on (potential) failures or failure prone situations and pass related information to a higher-level Z-Bre4k DSS (for decision support at manufacturing and enterprise level).
01-01-2020
-31-12-2023
01-11-2018
-30-04-2022
01-02-2015
-31-01-2018
01-10-2016
-30-09-2019
11-01-2015
-31-10-2018
01-10-2016
-30-09-2019
01-10-2020
-30-09-2023
01-11-2020
-31-10-2024
Siemens PLM XML - Data standard used to define process data from Teamcenter and send to the SCADA and to PLCs.
Siemens Mindsphere will be used to collect and analyse data from the shop floor; cloud-based.
Amazon Web Services – Currently used to host cloud data and machine learning algorithms.
Z-Fact0r is expected to support the transition to the so-called smart factories of the future. Smart factory is one equipped with technology that enables machine-to-machine and machine-to-human communication in tandem with analytical and cognitive technologies so that decisions are made correctly and on time. Factory automation, inparticular, implies a set of technologies and automatic control devices to enhance the productivity and quality of products and simultaneously decrease the production cost. It also entails the minimization of human intervention in the industry and ensures a superior performance as compared to humans. It comprises the use of computers, robots, control systems, and information technologies to handle industrial processes. Given the above definition, it is clear that the Z-Fact0r solution can be viewed as a factory automation tool, as it can significantly contribute to the integration and convergence of technologies for measurement and quality control, for data collection, storage and analysis at the factory level, aiming to guarantee high-quality of products without interfering, actually improving the production efficiency of the entire system. Since the concept of smart factories is under development and in practice a lot of changes are anticipated in this field in the near future, new markets may emerge or existing ones may shift to accommodate integrated and state of the art solutions, such as Z-Fact0r.