SDG-related Activities in Fujitsu


SDG-related Activities in Fujitsu

The Sustainable Development Goals (SDGs) adopted by the United Nations in 2015 are a set of common goals to be achieved worldwide by 2030. Fujitsu’s purpose is “to make the world more sustainable by building trust in society through innovation” and our company has made a commitment, both internally and externally, to contribute to achieving the SDGs. As a global enterprise that for decades has leveraged technology to create value for society, Fujitsu has a responsibility to proactively contribute to societal transformation. To help make the world more sustainable, we aim to generate larger and more beneficial impacts for society, which will also help to spur ongoing sustainable corporate growth. Fujitsu explained the Value Creation Concept for 2030 in the Medium-Term Management Plan which was released in May 2023. Our aim is to contributing SDGs by working on the Essential Contributions of Materiality : "Solving global environmental issues", "Developing a digital society", "Improving people's well-being".

Fujitsu believes the SDGs essentially define a system transformation that must be achieved by 2030 and that will act as the foundation for a world in which more than 9 billion people are able to live well, within planetary boundaries, by 2050. The issues highlighted in the SDGs involve a complex web of environmental, social, and economic elements. One key to solving these inherent problems is through digital transformation (DX). Fujitsu will harness the power of digital technology to create ecosystems that transcend industry boundaries and assist in the transformation of our customers and our own organizations, while playing a part in delivering fundamental changes to the way society interacts and contributes to the resolution of societal challenges.
The SDGs are an overarching framework of global social and environmental needs and form a common language for all stakeholders. Fujitsu will use its efforts to realize the SDGs as an opportunity for co-creation with a wide range of stakeholders, including international agencies, national and regional governments, private companies, non-governmental organizations (NGOs), and non-profit organizations (NPOs). By embracing a multifaceted approach to societal challenges, we can create and maximize positive impacts on an even larger scale.

Practical Application Within Fujitsu

We have built a framework that prompts all our employees to consider which of the 169 targets defined in the SDGs are relevant to our services and solutions when they are engaged in product planning and business discussions and when they issue press releases.
The objective is to make our employees routinely conscious of whether they are contributing to achieving the SDGs so that they approach their business activities from the standpoint of addressing social issues.

Using Digital Technology and Services to Contribute to the SDGs

Contributing to zero emissions by accelerating new catalyst discovery for clean ammonia production

Ammonia represents a promising carbon-neutral, next-generation energy source because it does not emit CO2 when burned and it is easier to transport than hydrogen. However, the current ammonia industrial production methods give rise to the emission of large amounts of CO2 in the manufacture of the hydrogen raw material, through the burning of fossil fuels such as natural gas and oil.
In April 2022, Fujitsu began joint research with Atmonia ehf.(*1) to accelerate the development of catalysts for the clean production of ammonia, which will contribute to a reduction in CO2 emissions. In February 2023, the two companies succeeded in reducing the search time for catalyst candidates by more than half by leveraging high-performance computing (HPC) and AI techniques to develop technology that improves the efficiency of materials discovery. Using Fujitsu’s HPC, a large number of quantum chemistry simulations were performed based on Atmonia’s ammonia synthesis simulation data. An AI simulation model was then developed by training the huge amounts of generated data from the simulations. The trained AI simulation model was used to rapidly generate much larger number of catalyst candidates than those generated by the simulations. Further, Fujitsu employed its proprietary AI causal discovery technology to narrow down suitable materials for alloy catalysts from more than 10,000 ammonia synthesis catalyst candidates .
The two companies aim to contribute to carbon neutrality by using HPC and AI-powered technology to improve the efficiency of materials search and by selecting catalyst candidates at an early stage and thereby making sustainable ammonia synthesis a practical reality.

Overview of the technologies developed and appliedOverview of the technologies developed and applied

  • (*1)
    Atmonia ehf is a start-up based in Reykjavík, Iceland, that uses computer simulations and experiments to develop catalysts for the efficient production of ammonia. The CEO is Guðbjörg Rist.

Key SDGs related to this project


Teijin and Fujitsu collaborate on initiatives to achieve sustainable lifecycles through recycled materials and environmentally conscious design(*1)

Working toward a common global goal of carbon neutrality, Teijin Limited and Fujitsu began a collaboration in July 2022 on an environmental value(*2) creation platform project. The aims are to achieve circular economies, starting from the material manufacturing origin, and to popularize reliable recycled materials.
Teijin and Fujitsu together plan to realize and commercialize this under the Fujitsu Uvance banner, as the first circular economy business.

Image of platform for enhancing the environmental value of recycled materialsImage of platform for enhancing the environmental value of recycled materials

In January 2023, Teijin and Fujitsu began a demonstration project using the Environmentally Valuable Recycled Materials platform for bicycle frames. There were a number of problems including energy consumption in the long-distance transportation of resources(*3) and the lack of established product recovery schemes, as well as the issue of how to recycle resources from bicycles without green-washing. Despite these, this initiative demonstrated the value of the platform for tracking resources used in bicycle frame materials and information on their environmental impact. It also provided visualization of the tracked data and an assessment of the feasibility of the data collection process.
The project demonstrated the environmental value created through recycling as a business model with guaranteed reliability, and created a path for environmental value creation in resource recycling for the bicycle industry. In the future, the aim is to create value through the disclosure of the traced data to bicycle users and its use in carbon management certification.
Moving forward, the two parties plan further discussions and field trials with partner companies and organizations, and will work toward the realization of a circular economy by supporting the growth of the recycling market not only for bicycle frames but in other industries as well.

  • (*1)
    Environmentally conscious design: Design that considers the whole product lifecycle and aims to reduce environmental impact.
  • (*2)
    Environmental value: Added value that contributes to the environment through a reduction in the carbon footprint of product manufacture and transport.
  • (*3)
    Resource transport-related energy consumption:
    CO2 emissions related to transportation: The issue arising from the global shipment of bicycle frames, more than 90% of which are manufactured in Asia (China).
    Environmental problems relating to waste disposal in landfill: The issue of the disposal in landfill of more than 90% of bicycle frames that return to Asia for disposal.

Key SDGs related to this project


Contributing to a sustainable society through demand forecasting

Fujitsu is continuing to progress its Digital Shifts initiative, one of the key focus areas under its global business brand Fujitsu Uvance, to realize data-driven management and an agile shift to the "new normal."
In November 2022, Fujitsu and TORIDOLL Holdings Corporation demonstrated the effectiveness of an AI demand forecasting service that uses a dynamic ensemble model, based on patented technology from Fujitsu Research, to predict the number of customers and sales of its Marugame Udon brand by shop, day, and time. The trial of the service had begun in a staged way in June 2021. With a corporate mission to “provide dining experiences that move its customers”, TORIDOLL Holdings had formulated a "DX Vision 2028" to leverage digital technologies in its transformation into a truly global food company.
Based on the results demonstrated, TORIDOLL Holdings then decided to deploy the service at all Marugame Udon noodle shops in Japan.
Incorporating AI and machine learning from data characteristics to imitate human thought processes, the dynamic ensemble model can optimally combine multiple demand forecasting models using automatic tuning.
Fujitsu’s demand forecasting technology provides stable and highly accurate demand forecasts by leveraging a learning model that accurately captures the characteristics of individual prediction objects that change according to various factors including periodicities, external factors and trends. It will also promote the use of forecast data in various planning operations including order placement, production planning, and work scheduling.

Overview of the AI Demand Forecasting ServiceOverview of the AI Demand Forecasting Service

Key SDGs related to this project


Supercomputer Fugaku and Discovery AI used in new technology for high-speed discovery of causes of cancer drug resistance

In a patient undergoing continued treatment with targeted cancer drugs (*1) , the spread and re-appearance of drug-resistant cancer cells represents an ongoing threat to full remission. To understand the mechanism behind the development of cancer resistance, detailed data and new analysis methods are essential. Fujitsu has further developed Explainable AI such as Wide Learning (*2), which explains the basis for decision making, and Discovery AI which enables the discovery of unknown causal relationships.
One development challenge was to accelerate the speed of processing calculations for a comprehensive search targeting all 20,000 human genes, which on a standard computer would take more than 4,000 years. Fujitsu implemented parallel conditional and causal algorithms on the supercomputer Fugaku to maximize computational performance so that all human genes could be analyzed in a reasonable timeframe. In addition, technology was developed that used Discovery AI to extract in one day promising genetic combinations causing conditions that might create drug resistance. This permitted high-speed calculation of conditional and causal relationship data for the entire human genome within a single day, successfully identifying the genes that caused resistance to lung cancer therapy drugs.
In future, Fujitsu will utilize the new technology to discover complex intersecting causes and resolve decision-making challenges in a variety of fields including marketing, system operations and manufacturing.

Overview of Discovery AIOverview of Discovery AI

  • (*1)
    Molecularly targeted drugs: Therapeutic drugs designed to act only on the molecule (protein, gene, etc.) causing the disease.
  • (*2)
    Official website for Hello, Wide Learning!

Key SDGs related to this project


Digital collaboration demonstrates possibilities for reducing CO2 emissions in EV charging

Digital collaboration demonstrates possibilities for reducing CO2 emissions in EV charging

The Electric Vehicle (EV) market has shown strong growth, mainly in Europe and China, with its aim of achieving the decarbonization of transportation. However, the increased demand for EVs, resulting in a greater load on the electricity network during charging, has posed a challenge for energy suppliers, and transport operators have struggled to control charging-related CO2 emissions. Unless charging uses green power, the impact of EVs on CO2 emissions reduction is decreased.
In a digital collaboration initiative with the World Business Council for Sustainable Development (WBCSD), Dutch consulting firm Arcadis NV and British electricity company National Grid plc, Fujitsu demonstrated its Fleet Management Optimization (FMO) solution for maximizing delivery efficiency. The goal was to reduce CO2 emissions from EV charging. Green power generation is subject to fluctuations due to weather conditions. In this demonstration, focusing on charging during periods with an ample supply of green power leads to reduced CO2 emissions and stability of the energy supply and demand balance. Simulation analysis was performed using FMO with delivery EV data from Arcadis as well as data on the greenness of electricity from National Grid. The results showed that by optimizing the charging schedule of delivery vehicles for transport operators, CO2 emissions from charging could be reduced by 15%. Based on this demonstration, Fujitsu is developing a Fleet CO2 Reduction solution, to support the use of green power for EV charging and reducing CO2 emissions.
Through cross-industry data sharing and collaboration with governments in various countries, Fujitsu will contribute to carbon neutrality by offering solutions that optimize the entire logistics and transportation service sector.

Key SDGs related to this project

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