{"id":65090,"date":"2025-07-21T09:04:48","date_gmt":"2025-07-21T07:04:48","guid":{"rendered":"https:\/\/grupoalava.rearmachine.com\/industrial-innovation-ecosystem-for-the-manufacturing-of-electric-and-connected-vehicles-in-spain\/"},"modified":"2026-06-22T12:36:28","modified_gmt":"2026-06-22T10:36:28","slug":"industrial-innovation-ecosystem-for-the-manufacturing-of-electric-and-connected-vehicles-in-spain","status":"publish","type":"post","link":"https:\/\/grupoalava.rearmachine.com\/en\/industrial-innovation-ecosystem-for-the-manufacturing-of-electric-and-connected-vehicles-in-spain\/","title":{"rendered":"Industrial Innovation Ecosystem for the Manufacturing of Electric and Connected Vehicles in Spain"},"content":{"rendered":"

PERTE for Electric and Connected Vehicles<\/b><\/p>\n

Beneficiary’s business name: T\u00e9cnicas <\/b>Predictivas e Instrumentaci\u00f3n S.L.<\/p>\n

Case No.: VEC-010000-2022-223 <\/b><\/p>\n

Primary Project Title: <\/b>Data Platform <\/b>for Predictive Maintenance of Industrial Assets in the Automotive Sector<\/p>\n

Implementation period: <\/b>June 1 <\/b>, 2022 \u2013 December 31, 2024<\/p>\n

Overall objective:<\/b><\/p>\n

The project, \u201cData Platform for Predictive Maintenance of Industrial Assets in the Automotive Sector,\u201d aims to create a data platform and a digital twin for the automotive industry. This initiative represents a significant effort to provide an advanced tool that simplifies the management of the lifecycle of industrial assets, enabling users to make more informed and agile decisions. <\/span><\/p>\n

The project is part of PREDITEC’s vision to be a leader in the digital transformation of the industrial sector, using state-of-the-art technologies to provide value and enhance competitiveness for its clients.<\/p>\n

Specific objectives: <\/b><\/p>\n

    \n
  • Basic System Architecture<\/li>\n
  • Demonstration of a digital twin and its data analytics interfaces\n
      \n
    • Expanding the capabilities of the digital twin from production assets to the assets produced, enabling more comprehensive tracking of each part or batch.<\/li>\n
    • Implementation on the visualization platform for business models related to connected products and products in manufacturing<\/li>\n
    • Implementation of a Role-Based Visualization System<\/li>\n
    • Implementation of a visualization system for produced assets<\/li>\n<\/ul>\n<\/li>\n
    • Demonstration of the Data Tagging and Reporting Tool<\/li>\n
    • Demonstration of the Artificial Intelligence Model for Predictive Maintenance<\/li>\n
    • Test Development and Platform Validation<\/li>\n<\/ul>\n

      This project aligns with the Original Equipment Manufacturing and Assembly (OEM) cluster, as its process innovations will be directly applicable to all industrial players in the electric vehicle manufacturing ecosystem.<\/p>\n

      In addition, the project falls under the cross-cutting component of the Digitalization Plan, as the project\u2019s outcome will enable the real-time transmission of all information generated by factory assets and\/or the production line and\/or products in production and finished products, as well as the ability to take action regarding them in the event of quality or maintenance issues.<\/p>\n

      Description of activities:<\/b><\/p>\n

        \n
      1. 1. Definition of functional requirements: Analysis of project requirements at various levels:\n
          \n
        1. Definition of key inventory elements and relevant indicators.<\/li>\n
        2. Specification of case studies and use cases.<\/li>\n
        3. Study and Implementation Specifications for Low-Cost Mobile Mapping Technology.<\/li>\n
        4. Study and specification of the processing architecture for point clouds and images.<\/span><\/li>\n
        5. Study and specification of the processing architecture for point clouds and images.<\/li>\n<\/ol>\n<\/li>\n
        6. Basic System Architecture: Representation of the system and determination of the relationship between functions and hardware and software components, the relationship between the software architecture and the hardware architecture, and human interaction with these components.<\/li>\n
        7. Visual Interfaces in New Business Models: Implementation on the Visualization Platform for Connected Product and Product-in-Manufacturing Business Models.<\/li>\n
        8. Integrated and Holistic Digital Twin in Industry: Equipping the platform with the ability to share assets across organizations.<\/li>\n
        9. Information Tagging and Reportability: Developing a data tagging system is essential so that both domain experts and operators can accurately reflect what actually happened in the data. This is necessary so that, in the future, similar situations can be automatically identified and recommendations can be issued. <\/li>\n
        10. Scalable Artificial Intelligence Models for Prescriptive Maintenance: Automating Diagnostics and Recommendations for the Most Frequent Failure Modes in Each Asset.<\/li>\n
        11. Testing and validation of the platform under the “connected product” and “product in manufacturing” models: Applying the developments to a real-world case and validating the proposed and developed functionality together with the client. Validating the effectiveness of the digital twin and ensuring that the new interfaces are suited to the new business models. <\/li>\n
        12. Testing and validation of the labeling and reporting system: Functional tests, such as usability validations with end users and domain analysts.<\/li>\n
        13. Testing and validation of artificial intelligence models applied to predictive maintenance: Validation of the proposed algorithms, with a particular focus on accuracy and completeness.<\/li>\n
        14. Qualitative and quantitative impact analysis of innovations implemented within the organization or in its processes.<\/li>\n<\/ol>\n

          Conclusions from the Project Implementation<\/b><\/p>\n

          The innovations implemented have had a significant impact on efficiency, operating costs, and staff motivation, driving organizational change toward digitalization and predictive maintenance in the pilot organizations thanks to the data platform designed for the predictive maintenance of industrial assets. However, areas such as usability, training, and support need to be strengthened to maximize the impact and ensure the sustainability of the results achieved. <\/p>\n

          For PREDITEC, the implementation of the project has established the company as a strategic leader in predictive maintenance solutions within the highly competitive automotive industry. The ability to adapt the platform to the specific needs of the automotive sector opens up new business opportunities with Tier 1 and Tier 2 manufacturers and suppliers. <\/p>\n

          Furthermore, the incorporation of advanced technologies, such as IoT and predictive analytics, positions PREDITEC as an innovative provider, aligned with the sector\u2019s digital transformation and creating capabilities that can be applied to other industrial sectors. The experience gained fosters a culture of innovation and continuous improvement within the organization, adapting processes to the demands of Industry 4.0. <\/p>\n

          Finally, it has led to the creation of a new business model, as the platform paves the way for models based on recurring predictive services, expanding revenue streams and fostering more lasting relationships with customers.<\/p>\n<\/div><\/div><\/div><\/div><\/div>

          <\/span><\/div><\/div><\/div>
          <\/span><\/div><\/div><\/div>
          <\/div><\/div><\/div><\/div><\/p>\n","protected":false},"excerpt":{"rendered":"","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"footnotes":""},"categories":[8497],"tags":[],"class_list":["post-65090","post","type-post","status-publish","format-standard","hentry","category-news"],"acf":[],"yoast_head":"\nIndustrial Innovation Ecosystem for the Manufacturing of Electric and Connected Vehicles in Spain - Grupo \u00c1lava<\/title>\n<meta name=\"description\" content=\"The project, "Data Platform for Predictive Maintenance of Industrial Assets in the Automotive Sector," aims to...\" \/>\n<meta name=\"robots\" content=\"noindex, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Industrial Innovation Ecosystem for the Manufacturing of Electric and Connected Vehicles in Spain - 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