IKHU

IKHU

Digital Product Passport Solution For sustainability

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We Are

IKHU

  • Transparency
    and Trust
  • Sustainability
    and Environmental Responsibility
  • Community
    and Collaboration

  • Transparency and Trust

    Transparency and Trust

    We believe in building trust through transparency.
    Our Digital Product Passport provides consumers with a comprehensive,
    verifiable history of the products they purchase,
    from origin to disposal. This ensures that every purchase is informed,
    responsible, and aligned with personal values.

  • Sustainability and Environmental Responsibility

    Sustainability and Environmental Responsibility

    We believe in building trust through transparency.
    Our Digital Product Passport provides consumers with a comprehensive,
    verifiable history of the products they purchase,
    from origin to disposal. This ensures that every purchase is informed,
    responsible, and aligned with personal values.

  • Community and Collaboration

    Community and Collaboration

    We believe in building trust through transparency.
    Our Digital Product Passport provides consumers with a comprehensive,
    verifiable history of the products they purchase,
    from origin to disposal. This ensures that every purchase is informed,
    responsible, and aligned with personal values.

Digital Product Passport

DIGITAL PRODUCT PASSPORT Solution

Each company has different objectives and methods for conducting product life cycle assessments. Therefore, the information included
in the Digital Product Passport (DPP) will also vary. We systematize the information that will be included in the DPP based on
ISO 14040:2006, ISO 14044:2006, and ISO 14955 standards. Once the necessary information is prepared, we create the DPP and provide it to our customers
Republic of Korea exports approximately around 500 million USD to the EU. To continue exporting to the EU, all products must comply with
the digital product passport (DPP) requirements for carbon neutrality by 2030.

Publications

[ PUBLICATIONS ]

Choi, M., Cho, Y., & Um, J. (2024). Real-Time Detection of Waste Battery Defect using Synthetic Image Datasets based on Deep Learning. Korean Journal of Computational Design and Engineering(KCI, ISSN 2508-4003), 29(1), 1-10.  

2024-10-02

[ PUBLICATIONS ]

Park, T. B., Min Park, J., Murdivien, S. A., & Um, J. (2024). Variational Autoencoder Model Based on 3D Convolutional Neural Network for generative design framework of 3D chair. International Journal of Industrial Engineering and Management(SCI, IF 2.9, ISSN 2271-2661), in-press.  

2024-10-02

[ PUBLICATIONS ]

Choi, M., Cho, Y., & Um, J. (2024). Real-Time Detection of Waste Battery Defect using Synthetic Image Datasets based on Deep Learning. Korean Journal of Computational Design and Engineering(KCI, ISSN 2508-4003), 29(1), 1-10.  

2024-10-02

[ PUBLICATIONS ]

Park, J. M., Choi, M., & Um, J. (2024). Convolutional LSTM based melt-pool prediction from images of laser tool path strategy in laser powder bed fusion for additive manufacturing. The International Journal of Advanced Manufacturing Technology(SCI, IF 3.4, ISSN 1433-3015), 130(3), 1871-1886.  

2024-10-02

[ PUBLICATIONS ]

Park, T. B., Min Park, J., Murdivien, S. A., & Um, J. (2024). Variational Autoencoder Model Based on 3D Convolutional Neural Network for generative design framework of 3D chair. International Journal of Industrial Engineering and Management(SCI, IF 2.9, ISSN 2271-2661), in-press.

2024-10-02