Despite the proclaimed benefits (i.e. scalability, reliability, cost-effectiveness) of Future Internet (FI) technologies (i.e. edge & cloud computing, IoT/CPS) for factory automation, their adoption from manufacturers remains low for various reasons, including technology issues (e.g., poor situation awareness, limited deployments, no standards-based reference implementations) and the lack of a smooth migration path from legacy systems.
FAR-EDGE is a joint effort of leading experts in manufacturing, industrial automation and FI technologies towards the smooth and wider adoption of virtualized factory automation solutions based on FI technologies. It will research a novel factory automation platform based on edge computing architectures and IoT/CPS technologies. FAR-EDGE will provide a reference implementation of emerging standards-based solutions for industrial automation, along with simulation services for validating automation architectures and production scheduling scenarios.
FAR-EDGE will lower the barriers for manufacturers to move towards Industrie 4.0, as a means of facilitating mass-customization and reshoring. Emphasis will be paid in the study of migration options from legacy centralized architectures, to emerging FAR-EDGE based ones.
FAR-EDGE will be validated in real-life plants (VOLVO, WHIRLPOOL) in the scope of user-driven scenarios (business-cases) for mass-customization and reshoring, where tangible improvements relating to reliability, productivity increase, quality cost, reduction in adaptation effort/costs will be measured and evaluated. Also, a wide range of migration scenarios will be evaluated in the scope of a CPS manufacturing testbed. FAR-EDGE will also establish a unique ecosystem for FI factory automation solutions, which will bring together the FoF and FI communities and will ensure sustainability of FAR-EDGE results.
For being positively affected by the use of the FAR-EDGE Platform, use cases must have one or more of the following high-level requirements:
- Distributed Automation: multiple (semi-)autonomous systems on the shopfloor having local resposibilities but global accountability.
- Distributed Analytics: multiple local sources of raw data having high volume / velocity / variety characteristics (big data scenario).
| Web resources: |
https://cordis.europa.eu/project/id/723094
https://www.edge4industry.eu/ |
| Start date: | 01-10-2016 |
| End date: | 31-10-2019 |
| Total budget - Public funding: | 4 490 194,00 Euro - 3 992 631,00 Euro |
Original description
Despite the proclaimed benefits (i.e. scalability, reliability, cost-effectiveness) of Future Internet (FI) technologies (i.e. edge & cloud computing, IoT/CPS) for factory automation, their adoption from manufacturers remains low for various reasons, including technology issues (e.g., poor situation awareness, limited deployments, no standards-based reference implementations) and the lack of a smooth migration path from legacy systems.FAR-EDGE is a joint effort of leading experts in manufacturing, industrial automation and FI technologies towards the smooth and wider adoption of virtualized factory automation solutions based on FI technologies. It will research a novel factory automation platform based on edge computing architectures and IoT/CPS technologies. FAR-EDGE will provide a reference implementation of emerging standards-based solutions for industrial automation (RAMI 4.0, Industrial Internet Consortium reference architecture), along with simulation services for validating automation architectures and production scheduling scenarios. FAR-EDGE will lower the barriers for manufacturers to move towards Industrie 4.0, as a means of facilitating mass-customization and reshoring. Emphasis will be paid in the study of migration options from legacy centralized architectures, to emerging FAR-EDGE based ones.
FAR-EDGE will be validated in real-life plants (VOLVO, WHIRLPOOL) in the scope of user-driven scenarios (business-cases) for mass-customization and reshoring, where tangible improvements relating to reliability, productivity increase, quality cost, reduction in adaptation effort/costs will be measured and evaluated. Also, a wide range of migration scenarios will be evaluated in the scope of a CPS manufacturing testbed.
FAR-EDGE will also establish a unique ecosystem for FI factory automation solutions, which will bring together the FoF and FI communities (e.g., EFFRA, Industrie 4.0, AIOTI, ARTEMIS JU) and will ensure sustainability of FAR-EDGE results.
Status
CLOSEDCall topic
FOF-11-2016Update Date
27-10-2022For being positively affected by the use of the FAR-EDGE Platform, use cases must have one or more of the following high-level requirements:
- Distributed Automation: multiple (semi-)autonomous systems on the shopfloor having local resposibilities but global accountability.
- Distributed Analytics: multiple local sources of raw data having high volume / velocity / variety characteristics (big data scenario).
FAR-EDGE demostrates the feasibility and business value of Edge Computing (EC) applied to manufacturing, using Distributing Ledger Technology (DLT) as the key enabler. DLT allows several autonomous local processes to cooperate as peers in the scope of the same global process, the required state synchronization and common business loging being implemented by Smart Contracts. This approach, if applied correctly, results in totally decentralized and fail-safe CPS that are still easily monitored, controlled and managed centrally.
Adoption of new and disruptive technology is not an easy task for SME, due to lack of budget and of internal skills. To mitigate this problem, FAR-EDGE defines speficic migration strategies that may help SMEs plan their Industry 4.0 journey, with the support of FAR-EDGE assets.
In FAR-EDGE, the value of DLT is in distributed consensus: enabling the intelligent edge nodes of a system to agree - or disagree - on state transitions, to the effect that any change in global state (e.g., the assignment of a task to a specific node) must be approved collectively; moreover, individual nodes may fail or go offline without compromising the system as a whole. However, standard DLT platforms also maintain an immutable log of transactions (the Blockchain) that is replicated on all nodes, which may represent a significant performance bottleneck in many real-world applications. What we learned from the FAR-EDGE experimentation is that, in most factory automation scenarios, the historical memory of any transaction may be cleared once consensus is safely reached on it - something that is not supported by any current DLT implementation. This form of short-lived state persistency is something that is probably worth experimenting with in the future.
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 system blueprint is the FAR-EDGE RA. After having defined the requirements and the constraints for each block of the RA, a thorough analysis of the SotA has been done, which led to the identification of some existing software components meeting the specs. We then identified the gaps that the project will need to fill-in: not surprisingly, these where all the key enabling technologies, like the distributed ledger. However, hardly anything is going to be built totally from scratch in FAR-EDGE. The distributed ledger, for example, will be a customization of a generic, open source Blockchain platform (Hyperledger Fabric).
We are considering some core GEs from FIWARE as candidate building blocks of our Edge Computing architecture. In particular, the Publish/Subscribe GE (Orion Context Broker implementation) is a good candidate as the northbound interface exposed by Edge Gateways – i.e., computing nodes aggregating a number of local edge nodes (field devices, smart factory equipment) and running local automation and/or analytics processes. We are considering to significantly extend the Publish/Subscribe GE by adding distributed computing capabilities: a data context that is replicated and kept in-sync across a number of GE instances (running anywhere on the network), using a Blockchain and smart contracts as the backing technology. FAR-EDGE will contribute its results, as open source software, to the FIWARE for Industry community.
In the scope of FAR-EDGE, the value of FIWARE is in the OMA NGSI standard: a RESTful Web API implementing the publish/subscribe pattern on context information – i.e., a set of attributes representing the current state of some device or process. NGSI is the common language that FIWARE applications use to integrate themselves with the IoT world. For this reason, supporting NGSI in FAR-EDGE means opening up the Platform to the FIWARE community. The FIWARE asset that is crucial for the support of NGSI is Orion Context Broker (OCB), which as for all FIWARE Generic Enablers is open source software. In FAR-EDGE, we envision the use of OCB to implement the generic publish/subscribe interface of the Distributed Data Analytics subsystem
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| Engineering Ingegneria Informatica S.p.A. (Coördinator)
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| AIT
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| LULEA TEKNISKA UNIVERSITET
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| Politecnico di Milano
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| SENSAP MICROSYSTEMS ANONIMI ETAIRIA ILEKTRONIKON SYSTIMATON KAI EFARMOGON LOGISMIKOU
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| Siemens AG
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| TECHNOLOGIE INITIATIVE SMARTFACTORY KL E.V.
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| The Open Group Limited
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| UNPARALLEL INNOVATION LDA
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| University of applied sciences and arts of southern switzerland (SUPSI)
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| VOLVO Group - VOLVO LASTVAGNAR AB
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| WHIRLPOOL EMEA SPA
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| Whirlpool Europe srl