MARITIME DIGITALISATION: AUTOMATED DOCUMENT · PDF file 2019-07-09 · According to...

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Transcript of MARITIME DIGITALISATION: AUTOMATED DOCUMENT · PDF file 2019-07-09 · According to...

  • Department of Mechanics & Maritime (M2) Department of Electrical Engineering (E2) CHALMERS UNIVERSITY OF TECHNOLOGY Gothenburg, Sweden 2018 Master’s Thesis EX082/2018

    MARITIME DIGITALISATION: AUTOMATED DOCUMENT CLASSIFICATION Interdisciplinary study on possible machine learning solutions for the container shipping industry

    Master of Science Thesis in the Master’s Degree Programme, Maritime Management

    CARL BLOMSTRÖM RODRIGO ASTORGA CASTILLO

  • MASTER’S THESIS EX082/2018

    MARITIME DIGITALISATION: AUTOMATED DOCUMENT CLASSIFICATION

    INTERDISCIPLINARY STUDY ON POSSIBLE MACHINE LEARNING SOLUTIONS FOR THE CONTAINER SHIPPING INDUSTRY

    CARL BLOMSTRÖM

    RODRIGO ASTORGA CASTILLO

    Department of Mechanics & Maritime (M2) Department of Electrical Engineering (E2)

    CHALMERS UNIVERSITY OF TECHNOLOGY Gothenburg, Sweden 2018

  • Maritime digitalisation: Automated document classification Interdisciplinary study on possible machine learning solutions for the container shipping industry CARL BLOMSTRÖM RODRIGO ASTORGA CASTILLO © Blomström, C. & Astorga Castillo, R. 2018 Supervisors: Henk Wymeersch, Department of Electrical Engineering (E2)

    Olle Lindmark, Department of Mechanics & Maritime Sciences (M2) Examiner: Henk Wymeersch, Department of Electrical Engineering (E2) Master’s Thesis EX082/2018 Department of Mechanics & Maritime Sciences (M2) Department of Electrical Engineering (E2) Chalmers University of Technology SE-412 96 Gothenburg Sweden Telephone: + 46 (0)31-772 1000 Printed by Chalmers University of Technology Gothenburg, Sweden 2018

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    Maritime digitalisation: Automated document classification Interdisciplinary study on possible machine learning solutions for the container shipping industry CARL BLOMSTRÖM RODRIGO ASTORGA CASTILLO Department of Mechanics & Maritime Sciences (M2) Department of Electrical Engineering (E2) Chalmers University of Technology

    Abstract

    Thesis report presents a conducted interdisciplinary study between the fields of Maritime Management and Electrical Engineering. The aim is to research how and to which degree machine learning algorithms can be applied within the area of maritime industry. The purpose is to find potential ways to innovate current burdensome administrative tasks, particularly within the freight forwarding and container shipping industry, through suggested methods of automated document classification. The study consisted of a mixed research method, with the double diamond approach as chosen design thinking model. The authors discuss possible issues identified in previous attempts to find similar solutions and research on the subject, in particular, related to organisational and cultural barriers, concluding that currently, available technology offers good improvement opportunities of many back-office activities. Keywords: Management, Shipping, Digitalisation, Machine learning, Strategy.

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    Acknowledgements

    The authors would like to take the opportunity in thanking everyone who has been involved in this thesis, whether through interviews or by providing guidance and motivation, without mentioning any names in particular.

    Also, the authors would like to thank Chalmers Ventures and Chalmers Innovationskontor for their great feedback concerning how to formulate the identified business case.

    A special thanks go out to current employers for being helpful and understanding regarding the need for time to focus on completing this master's thesis.

    Finally, but not least, the authors would like to thank the supervisors Henk Wymeersch and Olle Lindmark who have provided guidance, inspiration, feedback and support throughout the entire journey.

    Carl Blomström & Rodrigo Astorga Castillo, Gothenburg, June 2018

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    Contents

    List of Figures .................................................................................................................................................................. VIII

    Abbreviations ..................................................................................................................................................................... IX

    1. Introduction ..................................................................................................................................................................... 1

    1.1 Background ..................................................................................................................................................................................... 1

    1.2 Aim ...................................................................................................................................................................................................... 2

    1.3 Purpose ............................................................................................................................................................................................. 2

    1.4 Thesis statement ........................................................................................................................................................................... 2

    1.5 Research questions ...................................................................................................................................................................... 2

    1.6 Delimitations .................................................................................................................................................................................. 2

    1.7 Thesis outline ................................................................................................................................................................................. 2

    2. Theory ................................................................................................................................................................................ 4

    2.1 Industry ............................................................................................................................................................................................ 4

    2.1.1 Container shipping .............................................................................................................................................................. 4

    2.1.2 Container transport providers ...................................................................................................................................... 5

    2.1.3 Import process ...................................................................................................................................................................... 5

    2.1.4 Administrative work .......................................................................................................................................................... 7

    2.2 Technology ...................................................................................................................................................................................... 7

    2.2.1 Mathematical and statistical framework................................................................................................................... 8

    2.2.2 Machine learning .............................................................................................................................................................. 11

    2.2.3 Learning techniques ........................................................................................................................................................ 12

    2.2.4 Algorithms ........................................................................................................................................................................... 14

    2.2.5 Classification algorithms ............................................................................................................................................... 17

    2.2.6 Related topics ..................................................................................................................................................................... 20

    2.3 Business ......................................................................................................................................................................................... 21

    2.3.1 Diffusion of innovations ................................................................................................................................................. 21

    2.3.2 Automation of manual tasks ........................................................................................................................................ 22

    2.3.3 Labour costs ........................................................................................................................................................................ 23

    2.3.4 Projected future of administration ........................................................................................................................... 23

    2.3.5 Strategy ..............