グリッドは、「INFRASTRUCTURE＋LIFE＋INNOVATION」を企業理念として、テクノロジーを用いて社会インフラにイノベーションを起こし、インフラ全体の最適化を目指し、社会に貢献することをミッションに活動しております

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Grid co.

マルチモーダルウェビナー

マルチモーダルウェビナー

Announcing the expansion of "ReNom Power" functionality to enable optimization of power and energy-related planning operations.

Approval for Initial Listing on the Growth Market of the Tokyo Stock Exchange

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Notice of Completion of Development of "ReNom Apps for Industry SaaS," a SaaS Specializing in Social Infrastructure

Asahi Tanker and Grid Announce Development and Launch of AGREE, a Ship-to-shore Information Sharing Platform

Grid begins development of "ReNom Apps," SaaS specialized for social infrastructure.

Collaboration with Toyota Motor Corporation in the field of quantum machine learning research

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The company pioneered the development of an AI optimization system for vessel allocation planning in the petroleum wholesale industry. The system takes into account various constraints such as vessel operating efficiency, product loading balance, and vessel operating hours including voyage time and cargo handling time, enabling vessel allocation plans to be formulated in line with actual operations. The verification experiment has already confirmed that the time required for planning and transportation efficiency have already been improved, making it possible to improve the efficiency of the entire ship allocation operation.

idemitsu

Development of an optimization system for vessel allocation planning for domestic vessels of petroleum products

Started development of an AI optimization system to formulate ocean-going vessel allocation plans for approximately 120 car carriers, the largest number of car carriers in the world among shipping companies. The system also aims to reduce GHG emissions while taking into account various conditions such as ship schedule, ship type, and available space, etc. A system equipped with a ship allocation plan optimization AI engine will be developed for full-scale operation in 2024 to improve operational efficiency and reduce GHG emissions.

nihonyusen

Optimization of the world's largest fleet of approximately 120 car carriers

OMRON HEALTHCARE CORPORATION aims to promote digitalization by developing an "order quantity forecasting AI system that takes into account forecast swing" using Grid's AI technology "ReNom Plan" in order to cope with supply chain disruptions and supply constraints due to semiconductor shortages. This system is expected to improve the average error rate of order volume forecasts for key products and advance the planning process.

omron

Development and verification of an AI system for sales forecasting with forecast swing.

We have developed and introduced a system to develop an economical electricity supply and demand plan. The environment surrounding the electric power industry is becoming more and more complex every year due to soaring fuel prices, decarbonization/GX, introduction of renewable energy, and electricity deregulation. In addition to the complex business environment, there is a decrease in the number of skilled personnel with expertise, which led to the development of an AI-based electricity supply-demand planning system. This has enabled comparative analysis of multiple cases and high-speed planning work that could not be achieved manually until now. In the future, the system is also expected to contribute to the continuous effective use of energy resources and reduction of environmental burdens such as CO2 emissions.

yonden

Introduction of electricity supply-demand planning system using ReNom Power

Developed an air conditioning heat source control optimization system for large-scale commercial facilities that combines Digital Twin and AI optimization technologies, and confirmed that the system can reduce annual CO2 emissions by up to 16.3% and annual energy costs by up to 12.5% through demonstration tests at three commercial facilities.

kyuden

Joint development of air conditioning heat source control optimization system

An electric utility company with a combination of thermal and hydroelectric power plants faced the challenge of developing a generation plan that balanced market demand while using the most efficient output band. During technology validation, the drafted plan met all constraints while achieving an efficient operating plan that reduced daily operating costs by 3. This is expected to contribute to the reduction of C O2 as well as the reduction of thermal power generation costs.

hokuden

Development of an optimization system for thermal and hydroelectric power generation operation planning

Pre-implementation testing of 44 food products showed that sales volume forecasting accuracy improved by about 15%, and with a few exceptions, order planning was as good as actual order placement for all products. Currently, we are confirming the possibility of operational improvements such as reductions in lost sales opportunities, excess inventory, and order frequency in actual operations.

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Digital Twin & Optimization AI

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