SECTORAL ANALYSIS OF MANUFACTURING (NACE SECTION C), EU-28, 2016
4.3.3. Major challenge 3: Generalising condition monitoring, to pre-damage warning on-line decision-making support and standardisation of communication scenarii to enable decision-making support and standardisation of communication scenarii to enable
big data collection across huge (remote) sites
The role of IoT is becoming more prominent in enabling access to devices and machines, which used to be hidden in well-designed silos in manufacturing and farming systems. This evolution will allow IT and IoT to penetrate digitised manufacturing and precise agriculture systems further.
Industrial IoT applications are using the gathered data, data analytics, cloud services, management information systems, enterprise mobility and many others to improve the industrial processes. The future IoT developments integrated into the digital economy will address highly distributed IoT applications involving a high degree of distribution and processing at the edge of the network by using platforms that provide computing, storage and networking services between edge devices and computing data centres (at the edge and/or at the cloud levels) with AI capabilities.
Most companies are now experiencing difficult times justifying risky, expensive and uncertain investments for smart manufacturing across company borders and factory levels. Changes in the structure, organisation and culture of manufacturing occur slowly, which hinders technology integration. Similar issues are also experienced in the digital farming sector.
There are many initiatives around Digital Manufacturing, Digital Farming, and IoT Platforms, thanks to the widespread research and innovation in the EU (C2Net, CREMA, FIWARE, FITMAN, ARROWHEAD, sensiNact, etc.). However, those IoT driven platforms have not yet led to a successful and effective digitisation of all the aspects and resources of manufacturing and farming industries. This is mainly due to the heterogeneity of the IT supply side and of the heterogeneity of the domains to be addressed and transformed in the industry demand side.
Questions to be solved:
Are the digital platforms meant for manufacturing business processes also suitable for real time execution?
Have performance and security issues been solved?
Are the proposed platforms reasonable for low tech SMEs?
Can we define a Meta-Platform that acts as the translator between the different digital platforms?
Can we define something similar to AUTOSAR, a standard way to communicate between the different parts and platforms for the Intelligent Manufacturing/Farming ecosystem or something to solve the interoperability problem? Each of the actors in an Intelligent Manufacturing/
Farming ecosystem is using their own solution. Having a standard way to connect and have interoperability of those different digital platforms and different devices located at different levels of the factory/farm will provide a competitive position to the European intelligent manufacturing/farming ecosystem.
IoT devices will have significant environmental impacts (e.g. waste management); therefore, development and use of recyclable and, ideally, biodegradable systems is needed. Can new material concepts provide electronic hardware meeting these requirements?
To resolve this last question, the Industrial Internet Consortium (IIC) has defined the so-called Connectivity Framework (IICF). The IICF defines the role of a connectivity framework as providing syntactic interoperability for communicating between disparate Industrial Internet of Things (IIoT) systems and components developed by different parties at different times. The IICF is a comprehensive resource for understanding connectivity considerations in IIoT. It builds on the foundation established by the Industrial Internet Reference Architecture and Industrial Internet Security Framework by explaining how connectivity fits within the business of industrial operations, and its foundational role in providing system and component interoperability when building IIoT systems.
EFFRA (European Factories of the Future Research Association): The diversity of approaches and implementations of Digital Manufacturing or Digital Farming platforms prompt the need for the creation of Meta-Platforms to connect existing platforms, including abstraction layers for interface, protocol and data mapping to provide interoperability as a service. There is a need for holistic interoperability solutions spanning all communication channels and interfaces (M2M, HMI, machine to service) in the factories/farms and supply chains. Moreover, Meta-platforms will need interoperability for security, semantic, data-bases, user interfaces, etc.
In addition, new players are arriving from the IT sector:
Hadoop
Kafka
Apache STORM
IBM (Bluemix)
Microsoft Azure
Digital Enterprise Suite (SIEMENS), MindSphere (Siemens, open IoT operating system, turn data into knowledge, and knowledge into measured business success).
How can they be considered in the intelligent manufacturing/farming ecosystem? How can these tools be integrated into the digital platforms? How can the IPR issues of the data and knowledge created by those tools be solved?
4.3.3.1.
Scope and ambition For Digital Manufacturing: Study for meta-platform that can communicate and provide services between different platforms and their integrated tools.
Managing complexities with AI-based design, self-configuration, life-management and with many kinds of autonomous adaptation. “How to connect intelligence!”.
ECS-SRA 2020 — Strategic Research Agenda for Electronic Components and Systems
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For Digital Farming:
Continuous monitoring of crops and livestock, as well as environmental/nutrient parameters (in soil, water, air) influencing the growing cycles of plants and animals in farm environments.
Operation, update and maintenance of large numbers of distributed devices in rural/remote areas, with scarce battery resources and lack of connectivity
Combination of advanced models and artificial intelligence tools applied on collected data to support decision making (e.g. to optimise farm operations, predict diseases, etc.)
Ensuring high security levels in the management of data.
4.3.3.2.
Competitive situation and game changersThere are actually several benchmarking studies about digital platforms, either in progress or very recently completed. In the same way, companies are carrying out their own respective surveys. A general remark is that there are several digital platforms emerging, as research project outcomes, or actually as the result of several consecutive projects, both national and EU. Certain standardisation is under way, most notably by RAMI 4.0 (Reference Architectural Model 4.0) and IIC. Since the realms of respective applications are huge and, therefore, technologies as well, the standard actually consists of many standards that have been known and used for some time already; though there are needs to create new (sub)standards. The commercial digital platforms are also emerging, most notably Siemens MindSphere and GE Predix. At the time of writing, it is not clear which platform perhaps will win, or how the market positions will evolve. The situation very much resembles with the early stages of evolving operating systems of personal computers or mobile phones, or rather the early situation of industrial fieldbuses. As we well know, in some domains there have been clear global winners, but for instance with fieldbuses, several strong players seem to prevail. Due to the emergence of Industry 4.0, rectification of initiatives is apparently taking place.
The research origin platforms may be more versatile than the current commercial offerings. At the end of the day, application industries may start choosing more and more commercially supported platforms but, as we have seen in recent history of ICT, open source platforms may keep their strong position.
Digital platforms are clearly becoming ever more state-of-the-art technologies, i.e., they are pushed somewhat in the background as we have operating systems of PCs today. The applications have been dominating engineering, in the past and in the future. As is clearly recognised in industry, applications in all life-cycle stages and on all system levels, both in digital and physical realms, are most valuable. The digital assets themselves are important, as well as, the connectivity of ever more elaborate and diverse applications.
A similar situation exists in digital farming. Moreover, there are strong signals in favour of an increasingly deeper digitisation of the EU’s agricultural sector. On the one hand, from a policy perspective, the upcoming EU’s Common Agricultural Policy (CAP) 2021–2027 will have a special focus on digitisation.
Additional stimuli are expected to happen at national or regional levels in those regions where agriculture is a key contributor to the local GDP.
On the other hand, in the private sector, the agriculture sector itself (the end users or demand side) has embarked on an increasing digital take-up that seems to be only in its beginnings. Therefore, the supply side of digital farming faces quite promising market opportunities on a vertical market that is expected to attract heavy investments in the upcoming years. Interestingly, the supply side of digital farming embraces a rich value chain of actors that ranges from component manufacturers to digital platform providers, application developers or agricultural machinery manufacturers.
The digitisation of food production will open the door to unprecedented productivity levels in the agriculture sector, while reducing the environmental footprint of the agriculture activity, thus becoming a real game changer.
4.3.3.3.
High priority R&D&I areas Move focus on the industrial or engineering applications. It is important to win the global platform game on various application sectors (which are strong today) and in building effectively and on high-level outperforming applications and systems, for the actual industrial and business needs.
Prepare for the era of 5G in communication technology, and especially its manufacturing and engineering dimension.
Long-range communication technologies optimised for M2M communication, large numbers of devices, low bit rates are key elements in smart farming.
Solve the IoT cyber-security and safety problems, attestation, security-by-design. Only safe, secure, and trusted platforms survive in industry.
Next-generation IoT devices with higher levels of integration, low power consumption, more embedded functionalities (including artificial intelligence capabilities) and lower cost.
Interoperability-by-design at component, semantic and application levels.
IoT configuration and orchestration management allowing for (semi)autonomous deployment and operation of large numbers of devices.
Decision support: artificial intelligence, modeling and analytics, in Cloud but also in Edge/Fog settings.
4.3.3.4.
Expected achievements Meta-platform could be used with other platforms, systems and tools.
Easier, more comprehensive and tools supported integration of compound applications, on top of digital platforms.
Automated design features.
Technologies to connect intelligence.
Availability of a new generation of smart farming-ready intelligent IoT components, devices, platforms and applications offering a high degree of interoperability, configurability, orchestration manager and security, that allows Europe to stand out as global leading supplier of smart-farming technology during 2020–2030.