PIONEER will develop
an open innovation platform and interoperable digital pipeline
to address a design-by-simulation optimisation framework allowing a seamless dataflow along the material value chain, from product design to manufacturing and quality control.
The project connects materials modelling and characterisation, simulation-based digital twins, and data-driven models, updated through production data from embedded IoT edge devices and product quality. Based on data aggregation and Artificial Intelligence (AI), this model provides advanced strategies for online adaptation to evolving environments. To that extent, PIONEER implements inline feedforward control strategies to enhance the industrial systems' efficiency in high-mix/low-volume production schemes.
PIONEER integrates product development, process, and material characterisation data to improve design efficiency by using data standards for data exchange and aggregation between virtual engineering and production/quality data.
This will allow virtual multidisciplinary optimisation, reducing physical testing and improving product quality.
The project is built around 5 pillars.
PILLAR 1
Open Innovation Platform integrating materials, products, and processes to enhance the efficiency of the manufacturing processes.
Product specifications, all information related to material properties and materials modelling, as well as information collected from manufacturing processes and product quality criteria, must be accessible and ensured along the product lifecycle from the initial design and conceptualisation. This digital pipeline is built on a hybrid cloud and edge computing infrastructure,
combining distributed manufacturing monitoring and product quality data through edge computing devices with distributed modelling and simulation as a service boosted by HPC infrastructures, allowing multidisciplinary and multi-scale optimisation in multi-stage manufacturing processes. Furthermore, interoperability, adaptability, connectivity and modularity along the material value chain and virtual engineering workflows are based on neutral and open standards for cross-company connectivity.
PILLAR 2
Interoperable virtual engineering workflows for integrating multi-scale/ multi-disciplinary and multi-software simulation processes.
PIONEER relies on a vendor-neutral and open data exchange format capable of importing/exporting numerical simulation data between different vendor-specific modelling tools. The goal is to ensure the connection between different modelling suites in the material value chain
to ensure simulation data exchange and integrate them at HPC environments to execute the simulation workflow seamlessly. This ensures data consistency as well as the distributed and multidisciplinary modelling needed to cover multi-stage manufacturing processes.
PILLAR 3
Advanced material modelling and hybrid modelling for improving product quality and optimising responsiveness to market changes.
The hybrid modelling captures the complete process chain and directly describes the anisotropy and nonlinear properties of materials, drawing from physics models and manufacturing/characterisation data. Therefore, PIONEER implements a framework that integrates data-driven models and digital twins, enhancing product quality by linking simulation models with the process and material data
to obtain a model that is continuously updated. In addition, data-driven and AI-based pattern recognition solutions are developed to provide feedback to the engineering, improving decision-making efficiency, quality and understanding while assisting in the design optimisation of new components and thereby reducing physical testing.
PILLAR 4
Multi-dimensional visualisation tool for an end-to-end representation of the material value chain.
The multi-disciplinary and holistic product-service engineering environments require collaborative knowledge management and its multi-directional exchange between material characterisation, product design, advanced modelling and simulation, manufacturing, and quality control. PIONEER enhances data interoperability by developing innovative and intuitive user-centred visualisation tools for each stage of the material value chain
to understand patterns, outliers, and trends in data to support the analysis of large quantities of data and for creating data-driven decision support systems/methodologies. PIONEER also addresses multidimensional structure/property relationships visualisation for materials characterisation and modelling by enhancing data extraction and structuration through exploiting natural language processing (NLP) tools.
PILLAR 5
Semantic layer for common knowledge representation.
Defining a common terminological framework with interpretable references is vital when it comes to enhancing the interoperability between materials, product and process design, and industrial production lines. As far as possible, PIONEER follows publicly available definitions, industry standards and well-accepted standard literature for the significant taxonomies and classifications and relations for helping data integrators to adopt PIONEER concepts and digital tools to existing data platforms.
PIONEER also uses existing specific domain ontologies –i.e., production equipment, materials, monitoring and control devices– that are present in the material and manufacturing value chain. Based on industry norms, PIONEER builds a network of existing/emerging ontologies from the following already-existing initiatives.