EAVE - Company and Team

EAVE as an innovative SME operating in the Renewable Energy industry is completely aligned with WASABI, particularly in its focus on enhancing energy efficiency, sustainability, and technological innovation.

For our WALLABI project, here are the colleagues involved:
  • Antonio Sánchez Miranda, CRO
  • Rubén González Lorenzo, PM & Cloud Architect
  • Jorge Gutiérrez Cejudo, Electronic Engineer & Renewable Energy expert
Antonio Sánchez Miranda

Antonio Sánchez Miranda

CRO

Rubén González Lorenzo

Rubén González Lorenzo

PM & Cloud Architect

Jorge Gutiérrez Cejudo

Jorge Gutiérrez Cejudo

Electronic Engineer & Renewable Energy expert

EXPERIMENT OVERVIEW

OVERVIEW

The experiment focuses on the application of COALA-OVOS during the quality control process of Wall-AI batteries manufacturing. These batteries are designed with a strong focus on circular economy principles, being constructed from recycled electric vehicle (EV) batteries. The Wall-AI is an advanced electronic device designed for better management of solar energy within photovoltaic systems. The OVOS implementation will be carried out:

  • As part of the QA manufacturing process, the OVOS solution will support technicians by automatically collecting and storing data, recording performance data under various operational and environmental conditions.

CHALLENGES

Several challenges for EAVE are presented during QA process:

    • Lack of digital traceability throughout disassembly and assembly stages.
    • Dependence on manual data entry and subjective evaluations, which can lead to inconsistencies.
    • Limited real-time visibility of quality data and test results.
    • Difficulty in identifying early trends or deviations that could affect product reliability.

OBJECTIVES

  • Integrate the COALA-OVOS digital assistant to enhance the existing QA process in Wall-AI battery manufacturing.
  • Improve efficiency by automating data management, reducing testing time and optimizing energy use.
  • Implement strategies for a greener approach in Wall-AI battery assembly, promoting more sustainable production.

EXPERIMENT IMPACT

EXPECTED RESULTS (KPIs)

  • Number of queries resolved by OVOS (per month)
  • Decrease in product testing time (measured in minutes)
  • Reduction in production costs
  • Growth in the number of successfully validated batteries (QA-approved battery units per day)
  • Decrease energy consumption per unit produced (measured in kWh/unit)
  • Increase in battery units sold in new markets, especially in Europe