The main objective of MultiFAL project is to design, develop and construct an automated plant system for joining thermoplastic fuselage shells considering three different design use-cases, taking into account the existing assembly plant system at the topic managers’ facility. MultiFAL will consider automation and virtual commissioning technologies in order to bring both an increase in the assembly process performance and a deep understanding of the relevant factors implementing a full size automated plant following a brownfield approach. Different assembly approaches and joining process for different use-cases will be considered, taking into account the currently existing double-sided and limited accessibility for full fuselage sections. As a result, MultiFAL will also facilitate the adaptability of both the robotic machinery and the central control system. Objectives include reducing the commissioning time of automated plant systems up to 20% by the use of virtual commissioning tools, increasing the level of detail for production steps around 25% by implementing interfaces between plant system and production control. Additionally usability and re-utilization of automation systems by development and implementation of standardized interfaces will be enhanced. In the MultiFAL project, lean development approaches will be combined with agile methodologies to develop not only software modules for the simulation but also for the virtual commissioning of the plant system. Moreover, following results will be achieved: • End-to-End design approach exploiting model based system-engineering methodologies • Flexible automated plant system enabling multi use-case coverage

Digital servitisation of manufacturing allows to produce on-demand customised products, with high quality, flexibility and short lead time. Although this is a win-to-win situation, there is a lack of methodologies. To reverse this trend, the project Lasers4MaaS will spearhead innovations in manufacturing technologies and digital platforms with associated services. The ultimate goal is to enable a 6-point strategy (reconfigure, connect, control, predict, improve, comply) to operationalise the smart, decentralised and sustainable factories of the future. Lasers4MaaS is set to deliver breakthroughs that merge manufacturing technologies with cutting-edge digital innovations. It marks significant scientific and technical advancements in several areas: the latest advances in dynamic beam shaping and modular production schemes to maximise flexibility and reconfigurability; harmonized protocols and distributed/centralised ledgers for data interoperability across factory boundaries; IIoT solutions for remote monitoring/predictive maintenance; real-time AI-based decision support for improved product quality; advanced physics-based digital twins; life cycle-based tools for environmental impact and costing assessment. The Lasers4MaaS digital platform, with its comprehensive range of services and breakthroughs, will be demonstrated in automotive, fusion, food packaging, aerospace and hydrogen sectors, which are considered strategic sectors for reaching the Green Deal objectives. This consortium comprising 4 academic partners, 8 industrial partners and an industry advisory board, ensures a seamless progression from TRL 4 to 6 with well-defined exploitation routes, while supporting standardisation initiatives, such as digital product passport, and facilitating training initiatives and knowledge transfer.

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.

MODAPTO envisions flexible industrial systems composed of modules enhanced by distributed intelligence via interoperable Digital Twins (DTs) based on industrial standards. Moreover, it materializes enables collective intelligence within modular production schemes for effective module and production line design, reconfiguration and decision support. Motivated by the six principles of Reconfigurable Manufacturing Systems, MODAPTO aims at materializing reconfigurability through the joint use of all principles and not by considering it as an isolated vision of each one. To that end, MODAPTO focuses on two technological pillars: 1. Distributed Intelligence & Control via Interoperable Digital Twins 2. Modular Production Framework & Toolkit Within MODAPTO, each production module is augmented by a DT offering additional distributed intelligence functionalities. MODAPTO standardizes the module’s interface via AAS to enable coordination with other modules and systems. MODAPTO also proposes a framework for production design and reconfiguration supported by collective intelligence tools. MODAPTO will be implemented in 3 industrial UCs involving 4 manufacturers at 3 different levels to showcase its versatility and applicability. UC1 targets the development of production modules (robots) with novel sustainability capabilities, while UC2 production reconfiguration and optimization even for single lots. UC3 targets the timely set up of press shop lines and coordination with robots and AGVs to handle supply chain disruptions in collaboration with the producer of semi-finished product kits. MODAPTO aims at substantial KPI improvements related to efficiency, cost, quality, energy and sustainability. Moreover, MODAPTO will develop business models facilitating its transferability to other sectors and the adoption of its industrial strategies, especially by SMEs, while supporting knowledge transfer via workforce and trainers’ training activities.

EU manufacturing is constantly becoming “more productive with less”, both in terms of material usage and energy consumption. The dynamics of global markets demand shorter product lifecycles and higher product variety, impacted by an increased volatility in demand. Traditional manufacturing systems are unsuitable to meet the new “think small” paradigm. They enable flexibility but at high operational complexity and for high volume operations to get lower cost production. To realise resilient factories and supply chains, it is mandatory to reduce complexity and cost of plug & produce modular manufacturing. MODUL4R envisions reliable, maintainable, affordable, (re)usable, and changeable SME-friendly autonomous modular factories and supply chains, able to manufacture new product in low-volumes and rapidly respond to unexpected events as well as the overall supply chain. MODUL4R proposes a holistic framework applicable both to new and existing manufacturing lines to achieve flexibility, rapid responsiveness, and sustainability. MODUL4R will be demonstrated in specialized mould manufacturing for the automotive sector, CPPS for flexible & modular assembly of PCBs, and tools manufacturing for the aerospace. MODUL4R focuses on 4 pillars, offering HW and SW components: Pillar 1: Resilience against changes in customer and societal demands and disruption on the supply chain Pillar 2: Modular technologies for flexible manufacturing operations Pillar 3: Simulation and interfaces to the Industrial Metaverse Pillar 4: Human centred technologies and upskilling The impact of MODUL4R for the EU Manufacturing industry, but also the society itself, can be summarised as follows: (i) Process ramp-up time (>20%), (ii) Speed in product shifting (>29%), (iii) Yield & CpK (>12% & >21%), (iv) OEE (>21%), (v) Part cost reduction (>15%) with over 41 MEUR ROI for the consortium, (vi) 408 new jobs, and (viii) help industry to reduce Energy consumption (>30%) through Automation of processes (>25%).