DISTRIBUTED PLACEMENT SYSTEM FOR CARGO HANDLING MACHINE USING ARTIFICIAL INTELLIGENCE

Provided is a distributed placement system for cargo handling machines using artificial intelligence, whereby efficient placement of cargo handling machines is possible in advance. This management system for a container terminal 12 comprising a GC 26, a yard trailer 20, an external trailer 22, and a...

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Main Authors KAWAMATA Mitsuru, INOUE Shota, NISHIO Yasuyuki, KOJIMA Takahiro, HATTORI Masaki, UEHARA Shuji, YOSHIE Muneo, KIKUCHI Michio, MINO Tomohiko
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LanguageEnglish
French
Japanese
Published 20.06.2019
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Abstract Provided is a distributed placement system for cargo handling machines using artificial intelligence, whereby efficient placement of cargo handling machines is possible in advance. This management system for a container terminal 12 comprising a GC 26, a yard trailer 20, an external trailer 22, and a yard crane 24 comprises AI 32 and is characterized by: container information, container unloading information, cargo handling work information, and terminal external factors information being input to the AI 32; using deep learning and finding, as output data, the number of yard cranes 24 to be deployed and the arrangement of same, whereby the operation of the yard trailer 20 can be kept so as to maintain the maximum GC 26 operation rate, maximize the operation rate of the yard crane 24, and minimize the wait time for the external trailer 22 during cargo handling; and sending information specifying a storage location 14 for the external trailer 22 and the yard trailer 20 and information specifying arrangement of the yard crane 24. L'invention concerne un système de placement distribué pour des machines de manipulation de marchandises utilisant une intelligence artificielle, permettant un placement efficace de machines de manipulation de marchandises à l'avance. Ce système de gestion pour un terminal de conteneur (12) comprenant un GC (26), une remorque portuaire (20), une remorque externe (22), et un chariot-grue (24), comprend une IA (32) et est caractérisé en ce que : des informations de conteneur, des informations de déchargement de conteneur, des informations de travail de manipulation de marchandises, et des informations de facteurs externes de terminal sont entrées dans l'IA (32); un apprentissage profond est utilisé pour déterminer, en tant que données de sortie, le nombre de chariots-grue (24) à déployer et l'agencement de ceux-ci, l'utilisation de la remorque portuaire (20) pouvant être optimisée de façon à maintenir la vitesse de fonctionnement maximale du GC (26), maximiser le taux de fonctionnement du chariot-grue (24), et réduire au minimum le temps d'attente pour la remorque externe (22) pendant la manipulation des marchandises; et des informations spécifiant un emplacement de stockage (14) pour la remorque externe (22) et la remorque portuaires (20), ainsi que des informations spécifiant l'agencement du chariot-grue (24) sont envoyées. 効率的な荷役機械の配置を予め行う事を可能とする人工知能を活用した荷役機械の分散配置システムを提供する。 GC26と、構内トレーラ20と、外来トレーラ22、およびヤードクレーン24とを備えているコンテナターミナル12の管理システムにおいて、AI32を備え、AI32には、コンテナ関連情報と、コンテナ搬出関連情報、荷役作業関連情報、ターミナル外部要因情報を入力し、ディープラーニングの手法を用いて、GC26の稼働率が最大値に維持される構内トレーラ20の運行を保つと共に、ヤードクレーン24の稼働率が最大値となり、かつ外来トレーラ22の荷役時における待機時間が最少となるヤードクレーン24の配備数と、その配置状態を出力データとして求め、外来トレーラ22並びに構内トレーラ20に対する蔵置場所14の指定情報と、ヤードクレーン24に対する配置指示情報とを送信することを特徴とする。
AbstractList Provided is a distributed placement system for cargo handling machines using artificial intelligence, whereby efficient placement of cargo handling machines is possible in advance. This management system for a container terminal 12 comprising a GC 26, a yard trailer 20, an external trailer 22, and a yard crane 24 comprises AI 32 and is characterized by: container information, container unloading information, cargo handling work information, and terminal external factors information being input to the AI 32; using deep learning and finding, as output data, the number of yard cranes 24 to be deployed and the arrangement of same, whereby the operation of the yard trailer 20 can be kept so as to maintain the maximum GC 26 operation rate, maximize the operation rate of the yard crane 24, and minimize the wait time for the external trailer 22 during cargo handling; and sending information specifying a storage location 14 for the external trailer 22 and the yard trailer 20 and information specifying arrangement of the yard crane 24. L'invention concerne un système de placement distribué pour des machines de manipulation de marchandises utilisant une intelligence artificielle, permettant un placement efficace de machines de manipulation de marchandises à l'avance. Ce système de gestion pour un terminal de conteneur (12) comprenant un GC (26), une remorque portuaire (20), une remorque externe (22), et un chariot-grue (24), comprend une IA (32) et est caractérisé en ce que : des informations de conteneur, des informations de déchargement de conteneur, des informations de travail de manipulation de marchandises, et des informations de facteurs externes de terminal sont entrées dans l'IA (32); un apprentissage profond est utilisé pour déterminer, en tant que données de sortie, le nombre de chariots-grue (24) à déployer et l'agencement de ceux-ci, l'utilisation de la remorque portuaire (20) pouvant être optimisée de façon à maintenir la vitesse de fonctionnement maximale du GC (26), maximiser le taux de fonctionnement du chariot-grue (24), et réduire au minimum le temps d'attente pour la remorque externe (22) pendant la manipulation des marchandises; et des informations spécifiant un emplacement de stockage (14) pour la remorque externe (22) et la remorque portuaires (20), ainsi que des informations spécifiant l'agencement du chariot-grue (24) sont envoyées. 効率的な荷役機械の配置を予め行う事を可能とする人工知能を活用した荷役機械の分散配置システムを提供する。 GC26と、構内トレーラ20と、外来トレーラ22、およびヤードクレーン24とを備えているコンテナターミナル12の管理システムにおいて、AI32を備え、AI32には、コンテナ関連情報と、コンテナ搬出関連情報、荷役作業関連情報、ターミナル外部要因情報を入力し、ディープラーニングの手法を用いて、GC26の稼働率が最大値に維持される構内トレーラ20の運行を保つと共に、ヤードクレーン24の稼働率が最大値となり、かつ外来トレーラ22の荷役時における待機時間が最少となるヤードクレーン24の配備数と、その配置状態を出力データとして求め、外来トレーラ22並びに構内トレーラ20に対する蔵置場所14の指定情報と、ヤードクレーン24に対する配置指示情報とを送信することを特徴とする。
Author YOSHIE Muneo
KAWAMATA Mitsuru
INOUE Shota
KOJIMA Takahiro
KIKUCHI Michio
NISHIO Yasuyuki
UEHARA Shuji
HATTORI Masaki
MINO Tomohiko
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– fullname: YOSHIE Muneo
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– fullname: MINO Tomohiko
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DocumentTitleAlternate SYSTÈME DE PLACEMENT DISTRIBUÉ POUR UNE MACHINE DE MANIPULATION DE MARCHANDISES UTILISANT UNE INTELLIGENCE ARTIFICIELLE
人工知能を活用した荷役機械の分散配置システム
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RelatedCompanies JAPAN AS REPRESENTED BY DIRECTOR-GENERAL OF PORTS AND HARBOURS BUREAU, MINISTRY OF LAND, INFRASTRUCTURE, TRANSPORT AND TOURISM
NATIONAL RESEARCH AND DEVELOPMENT AGENCY NATIONAL INSTITUTE OF MARITIME, PORT AND AVIATION TECHNOLOGY
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Snippet Provided is a distributed placement system for cargo handling machines using artificial intelligence, whereby efficient placement of cargo handling machines is...
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SubjectTerms CALCULATING
COMPUTING
CONVEYING
COUNTING
DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FORADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORYOR FORECASTING PURPOSES
HANDLING THIN OR FILAMENTARY MATERIAL
PACKING
PERFORMING OPERATIONS
PHYSICS
PNEUMATIC TUBE CONVEYORS
SHOP CONVEYOR SYSTEMS
STORING
SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE,COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTINGPURPOSES, NOT OTHERWISE PROVIDED FOR
TRANSPORT OR STORAGE DEVICES, e.g. CONVEYORS FOR LOADING ORTIPPING
TRANSPORTING
Title DISTRIBUTED PLACEMENT SYSTEM FOR CARGO HANDLING MACHINE USING ARTIFICIAL INTELLIGENCE
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