Humans are at the center of knowledge-intensive manufacturing processes. They must be skilled and flexible to meet the requirements of their work environment. The training of new workers in these processes is time consuming and costly for companies. Industries, such as the Italian textile sector suffer from the shortage of skilled workers caused, e.g. by the demographic change. A second challenge for the manufacturing sector is the continuous competition through high quality products. COALA will address both challenges through the innovative design and development of a voice-first Digital Intelligent Assistant for the manufacturing sector. The COALA solution will base on the privacy-focused open assistant Mycroft. It integrates prescriptive quality analytics, AI system to support on-the-job training of new workers, and a novel explanation engine - the WHY engine. COALA will address AI ethics during design, deployment, and use of the new solution. Critical components for the adoption of the solution are a new didactic concept to reach workers about opportunities, challenges, and risks in human-AI collaboration, and a concurrent change management process. Three use cases (textile, white goods, liquid packaging) will evaluate the results in common manufacturing processes with significant economic relevance. COALA will contribute its results to the European AI community, e.g. via the AI4EU platform, and it will involve Digital Innovation Hubs to replicate its demonstrators for Europes first trustworthy digital assistant for the manufacturing industry. We expect to reduce the failure cost in manufacturing by 30-60% with the prescriptive quality analytics feature and the assisted worker training. For the change over time we expect a reduction of 15% to 30% by shortening the worker training time.

WASABI aims at providing SMEs with the tools and knowledge to improve workers capacities and performance, providing advanced user interfaces for continuous augmented hybrid-decision-making. Such interfaces assist employees in interacting with complex software, effectively reducing its skill floor. In consequence, humans will find using software easier and be more open to applying it effectively at work. WASABI’s advanced interfaces will cover, for instance, situation analysis, intervention identification, action planning and execution, and impact monitoring and mitigation. One of the key technologies in WASABI’s solution portfolio is the digital intelligent assistant (DIA) - an anthropomorphic, task-oriented AI with a conversational interface. A network of DIHs that will help boosting impact by guiding SMEs in this new path will be created and integrated within other existing DIH networks. Our customized, federated, white-label shop will include such DIAs and skill-packages to help organizations reach their sustainability goals. Blue-collar and white-collar workers will be capable of using it for hands-free or eyes-free computer-interaction, AI-based advice and guidance, and augmented analytics.

UPTIME will seek to reframe predictive maintenance strategy by proposing a unified framework and to create an associated unified information system in alignment to the aforementioned framework. Therefore, UPTIME will extend and unify new digital, e-maintenance services and tools in order to exploit the full potential of a predictive maintenance strategy with the UPTIME solution, will deploy and validate the UPTIME solution in the manufacturing companies participating in the UPTIME consortium and will diffuse the UPTIME solution in the manufacturing community. UPTIME will enable manufacturing companies having installed sensors to fully exploit the availability of huge amounts of data with respect to the implementation of a predictive maintenance strategy. Moreover, production, quality and logistics operations driven by predictive maintenance will benefit from UPTIME. UPTIME will enable manufacturing companies to reach Gartner’s level 4 of data analytics maturity (“optimized decision-making”) in order to improve physically-based models and to synchronise maintenance with quality management, production planning and logistics options. In this way, it will optimize in-service efficiency through reduced failure rates and downtime due to repair, unplanned plant/production system outages and extension of component life. Moreover, it will contribute to increased accident mitigation capability since it will be able to avoid crucial breakdown with significant consequences. Consequently, UPTIME will exploit the full potential of predictive maintenance management and its interactions with other industrial operations by investigating a unified methodology and by implementing a unified information system addressing the predictive maintenance strategy.

The initiative for Fostering DIHs for Embedding Interoperability in Cyber-Physical Systems of European SMEs (DIH4CPS) will help European enterprises overcome these innovation hurdles and establish Europe as a world leading innovator of the Fourth Industrial Revolution. DIH4CPS will create an embracing, interdisciplinary network of DIHs and solution providers, focussed on cyber-physical and embedded systems, interweaving knowledge and technologies from different domains, and connecting regional clusters with the pan-European expert pool of DIHs. Backed by the IVLab, an experienced and well-established network organisation focussed on Interoperability, DIH4CPS can innately build on an extensive existing network, add value to its existing knowledge transfer capabilities and guarantee the sustainability of the growing DIH network. DIH4CPS expands the already existing network and aims for creating an integrated platform for DIHs from different, especially digitally underdeveloped sectors and regions. A selection of eleven initially starting application experiments guarantees an outstanding funding for European SMEs and Mid-Caps right from the start and demonstrates the high dedication of the consortium to reduce the digital divide. At least ten additional experiments will take up that torch during the project and allow external companies from sectors in need to further exploit the DIH4CPS network and uplift their portfolio, especially by including (semi)-autonomy into their products and systems. DIH4CPS will not only benefit the application experiments but also the individual DIHs by significantly complementing the regional investments made. Implemented in the IVLab structure, the DIH4CPS Network will leverage and sustain its impact far beyond the project duration, creating a vibrant, overarching and cross sector one-stop-shop for collaboration between SMEs, DIHs and Tech providers.

The undergoing transformation in our current socio-economic models, led by the advent of emerging technologies, has changed the relation of customers to products and services. Customers play no longer a passive role in the product and service development process as they express their product and service experiences and opinions through several channels such as discussion forums, blogs, chat, idea voting, and more. In addition, sensor systems in combination with products incorporated in the Internet of Things (IoT), are becoming increasingly common. The potential endless amounts of available information offer a rich ground for value creation in the product-service innovation chain. In this context FALCON envisions to provide a framework to enable the realization of new products and value-adding services, resulting from user-experiences and product and related services usage; undertaken with the principles of sustainability and social responsibility. FALCON will create impact through the following objectives: First the project will address product-service information collection through collaborative intelligence and Product Embedded Information Devices. Second, it will enable new mechanisms for product-service knowledge representation, exploitation, openness and diffusion. Third, it will strengthen collaboration and new product-service development through new feedback and feed forward mechanisms in the product life-cycle. Fourth, FALCON will explore manufacturing intelligence to support innovative product-services design and finally FALCON will improve product-service lifecycle assessment approaches through the real-time collection of product-service usage information and related experiences. The project is driven by a consortium of highly recognized researchers (BIBA, EPFL, TU Delft ), experienced solution providers (UBITECH, Holonix, Softeco, i-Deal) and industrial companies (Arcelik, Philipps, Dena Cashmere, DATAPIXEL, Vinci Consulting).