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.
The SERENA cloud-based platfrom will provide insight towards the optimisation of the production process considering the maintenance operations that ensuring a non-interrupted production.
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.
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.
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
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.
Part flow simulation provides real-time feedback about the state of the production line and enables the evaluation of different strategies to optimize performance.
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).
Simulation of Robot and human processes at station level.