Showing 1 to 30 of 36 entries
CFG has enabled workflow automation in the manufacturing engineering domain. Human-centred design of all tools being virtual or physical ones is vital to implement innovation in manufacturing.
Creativity support was not in the focus of CFG.
New manufacturing capabilities, materials and processes open up new possibilities for integrated functional designs. This capabilities come with potential complexity that can only be mastered by innovative design and engineering tools fostering creativity and increasing productivity along the product and manufacturing development. Tools such as advanced modelling tools for 3D and 4D objects, functional integration, multi and mixed material parts and complex organic shapes, alongside with the corresponding simulation tools and optimization methods that integrate human creativity into rapid automated computing in an augmented intelligence way.
AR and VR was not in the focus of CFG.
AR and VR has traditionally been focusing on experiencing and interacting with real and virtual 3D scenes, however their potential to exploid the capability of digital twins has yet to be unlocked. One field of future activities shall be the integration of interactive simulation technology for digital twins into AR and VR user experiences.
Not in the focus of CFG.
As introduced in objective 4.1 the concept of augmented intelligence shall be further developed and exploited in the context of manufacturing excellence to synergistically benefit both humans and technology.
CFG has run 21 application experiments with SMEs to advance both the CFG technology and the manufacturing processes of SMEs and validate them against the experiments' requirements.
The feedback from SMEs on the concept of Open Calls for allowing them to participate in European projects following a lean preparation phase has been overly positive and thus it is recommended to have similar instruments in Made In Europe.
DIHIWARE is the MIDIH Innovation and Collaboration Platform that will act as a facility intended to support knowledge sharing and technology transfer, based on human to human interaction, communication and technology informationbetween CCs and DIHs.
The MIDIH Open Source Reference Architecture (MIDIH RA) is a functional and modular architecture that supports IoT, Big Data and Artificial Intelligence technologies, which are expected to drive the change in Manufacturing Industry by enabling smart products (digital inside), smart processes and smart business models.
The MIDIH RA is composed by 39 components (34 as background open source assets, 5 as foreground assets) and was instanciated in three Industrial Experiments with specific needs. The DIHIWARE was experimented by 16 DIHs/CCs part of the MIDIH Consortium (plus three external experiments)
MIDIH is using in its project the 6Ps Approach for the validation of the digital transformation journey of an SME: Product, People, Production, Partners, Platform, Performance.
The need for migration of products, platforms and processes is not a novelty indeed, while very innovative and in some cases disruptive aspects emerge when migrating performance (business models and their kPIs), people (skills and roles) and partners (new collaboration models and open innovation ecosystems also with competitors).
Digital platform and engineering tools supporting productivity in a manufacturing environment, in the form of an ecosystem.
Digital platform and engineering tools supporting excellence in manufactuirng, using decision support systems.
Virtual tool to design innovative robotic cells
Virtual tool to design innovative robotic cells
Job quality evaluation and optimal task allocation betweek humans and robots (WP6).
Use cases for different set-ups and needs
More flexible production and industrial processes reorganisation
Definition of guidelines and proof of concept validation for both large enterprises and SMEs (see WP9)
Improving human understanding by means of (3D-)visualization and digital twins. Z-Bre4k will automatically adapt and update the physics-based simulation models.
Z-Bre4k considers the concept of human operators and their immense cognitive capabilities (e.g. high reactivity, agility and adaptability) that can support autonomy in the planning processes and control systems of maintenance operations of production systems
Besides basic supervisory control and data acquisition, Z-Bre4k will also comprise a complete monitoring solution at component, machine and system level
The Technology Validation is executed at the industrial environment of 3 pilots and going towards the TRL7
SHOP4CF is an EU-funded project within the eighth framework programme Horizon 2020 aiming to create a unique infrastructure that allows the easy deployment of human-centric industrial applications. In this context, twenty partners work on a comprehensive software platform allowing to conveniently obtain and deploy a wide range of components selected to cover a broad spectrum of industrial requirements especially in the context of modern, flexible and data-rich manufacturing. The overall vision of SHOP4CF is that tomorrow's production will require both machine capabilities like high accuracy, precision, or endurance and human assets such as creativity, adaptability, or tactile sense. All components considered in SHOP4CF aim at the mutual complementarity of human workers and machines.
In order to facilitate rapid adoption, great emphasis is placed on user-friendliness, reusability, interconnectivity and accessibility, which is achieved mainly through two key elements: (1) Digital marketplace: components can be conveniently obtained by a web-based interface, (2) unified platform: all components are developed using a single point of integration to ensure a high degree of interconnectivity and compatibility.
The basic idea behind the digital platform developed in SHOP4CF is that a high degree of simplicity in setting up automating processes allows humans to focus more on the problem-solving task where their creativity comes into play. To this end, a unique infrastructure is developed that serves as a single point of integration to easily deploy, orchestrate, and develop components that cover a wide range of different tasks in modern manufacturing environments. The idea of achieving a high degree of reusability is similar to the open source software movement and can lead to high cost efficiency and low access barriers to solutions from competitors. This modern approach is an appealing alternative to the classical approach of rebuilding solutions to specific problems from scratch. To make this vision work, a highly modular approach is envisaged, from which people can creatively select and combine modules until the problem is addressed without being overwhelmed by technical issues. We believe that this approach can significantly accelerate human-driven innovation in manufacturing process design.
SHOP4CF strives to build a holistic ecosystem that facilitates communication, collaboration, knowledge and technology transfer in a community that includes SMEs, universities, research institutes and system integrators.
It is worth noting that non-classical approaches (an example for an classical approaches is the rigid programming of industrial robots), which involve humans as an essential part, usually require advanced, interdisciplinary methods. Hence, knowledge transfer takes place not only between component developers, but also between disciplines within universities and research institutes to develop techniques based on other disciplines:
Biology (e.g., employing (spiking) neural networks),
Psychology (e.g., reinforcement learning)
Physics (e.g., advanced models for digital twins to simulate real world dynamics)
The concept behind SHOP4CF can have a strong positive impact on the labour market as people in manufacturing are not simply replaced by automated processes but gain new importance as a complement to machines. However, another implication is that new rules are being developed within SHOP4CF to address novel issues related to privacy, security, safety, legal aspects, or data ownership. It is worth noting that a successful digital platform that meets the described requirements can significantly increase the level of automation and maintain the competitive edge of European companies in the manufacturing sector.
Utilisation of human capabilities like abstract reasoning and the optimization of human-machine collaboration are the most important targets of SHOP4CF. In many industrial applications, human labour keeps playing an important role even in repeatable and non-creative tasks. Many of these tasks require monotonous motions leading to increased fatigue and a lack of attention. This in turn leads to more accidents, ultimately resulting in increased stress of the worker.
To mitigate such challenges, a set of augmented / virtual reality tools were developed in various projects by different partners associated in the SHOP4CF project. Those components include, for example, virtual planning of safety behaviour, augmented reality projection of assembly instructions or digital twins of production lines to monitor the condition. The relevance of those tools has been already validated in different research projects and verified in various research scenarios.
In SHOP4CF, the results of different research initiatives focused on the investigation of augmented / virtual reality methods in manufacturing environments will be combined into a unified platform (c.f. point R&I Objective 4.5).
One of the main ambitions of SHOP4CF is to develop a human-oriented technological platform in order to support human workers in the production activities of the manufacturing industry. This platform will provide technological solutions that will improve the well-being and working conditions of human workers, automatizing monotonous and exhaustive tasks and increasing their productivity due to technological support.
In order to contribute to the human-robot collaboration on the shop floor, SHOP4CF develops and integrates components and supporting tools to the platform that lead to a great support in the different stages of the manufacturing process. The set of components will provide functionalities related to IoT, robotics, AI, Big Data and HMI. Moreover, the supporting tools will facilitate the design and deployment of the human-centric manufacturing processes.
The components and supporting tools are highly designed to best complement the collaboration between human & technology. SHOP4CF fosters the ability to swiftly adapt the manufacturing capacities and will ensure the safety of the human operators while working in a highly robotic and digitized environment.
Utilisation of research outputs is usually problematic as the transition of investigation results to industry is typically not straightforward. In many cases, the research is performed under isolated conditions with specific technological solutions (non-industrial hardware and software platforms). An industrial partner to be able to use the technology would first need to reimplement the results of research into industry-ready platform before he could actually validate the results.
Such challenge in many cases deters potential interested SMEs from validating new, advanced technologies. In many industries the companies do not possess enough resources to introduce aforementioned technologies and therefore find the transition to robotisation and digitalisation troublesome. Removing the entry barriers to introduce and validate new technologies would significantly improve the accessibility of state-of-the-art inventions and would simplify the path to the migration.
SHOP4CF aims for overcoming these challenges by bringing together the results of different research projects into a unified, human-oriented platform which is easily deployable and user-friendly. The ultimate goal is to allow robotic, automation and AI technologies to be deployed by SMEs with minimal effort. The SHOP4CF platform will be started with a set of components validated by big industrial players with the intention to evolve into a community-based platform where everyone can develop its components and share them with the others. The unification of interfaces that SHOP4CF aims for will allow easy integration and cross-industry applicability.
Development of Manufacturing Demonstration Facilities (MDF) and DIY4U Training: After analyzing user demands and needs, initial small-scale manufacturing trials of the early personalized/customized formulations designed on the platform will be produced and characterized at MDFs (STEF and CPI) using existing high-throughput and other complex liquid/particle processing equipment. Learning from these trial runs will feed into the requirements specification and design of fablab machines for automated production of powdered and liquid FMCG. Subsequently, we will demonstrate the feasibility of DIY4U manufacturing by building 2 fablab prototypes (1 powdered and 1 liquid) and using them to provide open access collaborative production. These prototypes will be transitioned to commercial design and replicated after the project’s completion. To ensure smooth adoption by consumers, SME users and wider industry, DIY4U platform and fablab training will be developed and delivered to stakeholders including future EU industry workforce via dedicated workshops and apprenticeships at MDFs.
Empowering different actors to be more involved in the DIY growth and increasing the DIY product acceptance: DIY4U will increase involvement of makers, customers and stakeholders by:
a) Enhancing public and end-user awareness on the DIY creativity aspects by providing modern tools, such as serious games and interactive tools on both the digital platform and fablabs.
b) Identifying and understanding the needs, behaviors and demands of consumers, makers and manufacturers through data collation via cloud-based tools.
c) Running open innovation competitions (OICs) to encourage non-consortium SMEs to build additional functionality atop the DIY4U platform or to develop new innovative/customized FMCG using the DIY4U platform and fablab MDFs.
d) Facilitating the Open Access of the interested stakeholders and widely communicating the positive impacts of creativity and DIY4U services and products.
Human-robot collaboration for flexible production.
Pilot cases applied to industrial SEMs. Business model for applying to SMEs analysed.
Contribution: VR and AR in on-the-job training and AR in contextual guidance
Future: User experience, user acceptance, safety and ergonomics with AR/VR solutions. Personalized and contextual access to diigital twins. Combining user generated and measured information in digital twins.
KPIs: user acceptance
Contribution: Operator 4.0 solutions to empower and engage factory workers, so that they can influence the work environment and their own work.
Future: Collaboration in teams that include both human and technology actors (AI and robots), getting the best out of both. Extending the view in human-technology interaction from individual users to teams of human operators and several technical actors. Support for continuous learning and competence development at worker's own pace.
KPI: productivity and work well-being
Contribution: Tools for participatory design with operators and other factory stakeholders. Factory workers are very motivated in participating designing the manufacturiong processes, and their contribution to the design is important.
Future: Innovative tools are needed to support all factory actors in contributing to the design of manufacturing, and sharing their knowledge.
KPI: percentage of workers participating in design
faster and more efficient robotic process planner enables superior reconfigurability for mass customized products
digital twin-driven human device interaction
AI and advanced simulation support operators and process engineers to improve both overall sustainability and manufacturing performance
Novel robotic plants focused on extreme reconfigurability, energy efficiency and manifacturing quality
reduced robotic plants Life Cycle Cost to ease the massive adoption of Industry 4.0 technologies also by SME
Implement advanced mechanisms for realizing safe and efficient collaboration with humans; AR-based human-machine communication.
KPI: enhance worker perceived collaboration efficiency & safety by at least 25%
Calltopic: National - regional
Future developments necessary
KPIs for impact: Flexibility, Adaptability, Productivity, Error rate, Quality, Training time
Future developments necessary
KPIs for impact: Quality rate, Training time, Trust, Technology acceptance, Worker satisfaction
Future developments necessary
KPIs for impact: Trust, Technology acceptance, Worker satisfaction, Safety
Intelligent and autonomous handling and robotics, assembly and logistic technologies (including Assistive technologies) would be considered.