USE-IT-WISELY | Innovative continuous upgrades of high investment product-services
01-09-2013
-30-11-2016
01-09-2013
-30-11-2016
01-12-2014
-01-12-2018
01-01-2015
-01-01-2018
01-01-2015
-31-12-2017
Autonomy in factories is achieved by security systems that produce alerts and warnings, by training courses that does not require a trainer and by applications that signs daily jobs automatically to the most appropriate employees based on specific criteria.
This kind of spreadsheets are used for presenting the scheduled daily jobs, assigned to employees.
This software has been implemented for scheduling the daily jobs in an industrial premises. Implemented at both central pilots.
Implemented at both central pilots.
IoT enabled connection between the factory's applications.
Optimization on security level and safety monitoring
Optimization on the assembly line
Applicable, 24/7 safety monitoring
Applicable, real time analysis in received data from the production line.
11-01-2015
-31-10-2018
01-04-2015
-01-04-2019
01-07-2010
-30-06-2013
01-09-2012
-31-08-2016
Next future development and application is the automatic and intelligent retrofit excluding the current communication limits.
The data-driven digital twin is between SCADA and MOM
The GUI open the interaction with data-driven digital twin to data entry and KPI analytics
The data-driven digital twin enables the real-time process optimization contorlling the process deviation affceting the quality and efficiency
01-10-2012
-30-09-2015
Simulation of Robot and human processes at station level.
Dual arm robot simulation developed.
Integration of Robot and human processes at station level.
Dual arm robot planning and contorl developed.
11-01-2015
-31-10-2018
11-01-2015
-28-02-2019
10-01-2015
-30-09-2018
01-09-2016
-31-08-2019
01-09-2016
-31-08-2019
The concept of the autonomous factories is approached in the intrafactory part of the project with connections between different links of the value chain. Agent marketplace and automated bidding process which enable automated negotiation and transaction.
A part of information at shopfloor level may be fed to a MOM via a texteditor for the final user.
IoT enabled connectivity with intrafactory systems.
01-10-2016
-30-09-2019
01-10-2016
-30-10-2019
The Analytics domain of the FAR-EDGE Platform is addressing data acquisition and analysis at the lowest level: optimizing the use of network and computing resources by applying Edge Computing patterns.
The Automation domain of the FAR-EDGE Platform introduced the concept of a Distibuted Ledger as an decentralized aggregation/coordination layer positioned between legacy ERP/MOM/MES systems (centralized control) and Edge Gateways (distributed analysis and execution), which in turn are aggregators of IoT-enabled field devices.
The Virtualization domain of the FAR-EDGE Platform supports digital simulation, by means of which cyber-physical systems can be optimized following a what-if approach.
01-09-2016
-31-08-2019
CloudBoard: offers multiple views and access rights to different human actors Decision Support Toolkit: supports decisions authorised by humans, especially in the shop floor Enterprise and Factory models: accessible and re-configurable through user interaction
01-10-2016
-30-09-2019
01-10-2016
-30-09-2019
01-10-2016
-31-03-2020
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.
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.
Part flow simulation provides real-time feedback about the state of the production line and enables the evaluation of different strategies to optimize performance.
01-11-2015
-31-10-2017
01-09-2017
-31-08-2020
UPTIME will provide a unified predictive maintenance management framework and a smart predictive maintenance information system covering the whole prognostic lifecycle. It will contribute to improve smart predictive maintenance systems capable to integrate information from many different sources and of various types, in order to more accurately estimate the process performances and the remaining useful life.
In UPTIME Whirlpool Business Case, each sensor is directly connected to the respective PLC (Programmable Logic Controller), which is on board of the specific equipment. The internal SCADA system is then gathering the data from each PLC and send them to Whirlpool MOM software, which in turn stores them into the database (SQL Server).
01-11-2017
-31-10-2020
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).
Data connectors provided to connect any kind of ERP-MOM data sources