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Abstract
Logistics has been the bottleneck in ecommerce, creating problems such as slow and/or wrong deliveries, lost packages, damaged goods and incorrect packing. Automation extends capacities and capabilities as justified by the vast volume of online orders. An automated storage and retrieval system (ASRS) can deliver high efficiency but may be limited in flexibility when it comes to dealing with order disparities in size, shape, weight, volume and mechanical properties. The ASRS may not offer adequate scalability to adapt to growth and cope with increased seasonal demands, or deal with facility breakdowns and carry out technical maintenance. Robotics promises to strike a balance between efficiency, scalability and flexibility. This paper addresses two broad questions: (1) How can robotics create a radical paradigm shift in ecommerce logistics automation systems? (2) Who should be responsible for investing in robotic ecommerce logistics facilities and how should the benefits be shared among key stakeholders? The first question is discussed through recent industrial developments in using mobile robots to achieve robotic picking methods including goods to picker/person (G2P), goods to robot (G2R), robot to goods (R2G), and through the bold concepts of robotic grid warehousing and cellular warehousing (CW). The second question is discussed by extending the emerging concept of the Product Service System (PSS) to propose a Logistics Automation Service System (LASS) business model where stakeholders focus on their own core competencies while complementing each other's expertise and sharing risks and benefits.
Acknowledgements
Throughout the process of writing this paper, a great amount of support and discussion have been offered by colleagues and researchers at the University of Hong Kong and other collaborating organisations. Prof Y H Hu at Shandong University, and Prof S P Lu and Dr H Luo at Shenzhen University have shown us how automation products and unmanned forklifts from BlueSword and BlueBird are used within ASRS, as implemented in tobacco warehouses and ecommerce distribution centres. They also explained the business model of implementing ASRS for a leading ecommerce operator as an industrial case of the proposed LASS model. We are extremely grateful to the editorial office for their great patience with and encouragement of us in the completion of this paper.
Additional information
Dr George Q Huang is a Professor and Head of Department in the Department of Industrial and Manufacturing Systems Engineering, the University of Hong Kong. He gained his BEng and Ph.D. degrees in Mechanical Engineering from Southeast University (the Mainland China) and Cardiff University (the UK), respectively. He has conducted research projects in the field of Physical Internet (Internet of Things) for Manufacturing and Logistics with substantial government and industrial grants. He has published extensively, including over three hundred refereed articles in journals and conferences in addition to ten monographs, edited reference books and conference proceedings. His research works have been widely cited in the relevant field. He serves as Associate Editors and Editorial Members for several international journals. He is a Chartered Engineer (CEng), a fellow member of the American Society of Mechanical Engineers (ASME), the Hong Kong Institution of Engineers (HKIE), the Institution of Engineering and Technology (IET) and the Chartered Institute of Logistics and Transport (CLIT), and a member of the Institute of International Education (IIE).
Dr Michael Z Q Chen received his BEng degree in Electrical and Electronic Engineering from Nanyang Technological University, Singapore, and his Ph.D. degree in Control Engineering from Cambridge University, the UK. He is currently an Assistant Professor at the Department of Mechanical Engineering, the University of Hong Kong. Dr Chen is a Fellow of the Cambridge Philosophical Society. He is now a Guest Associate Editor for the International Journal of Bifurcation and Chaos. His research interests include passive network synthesis, mechanical and robotic control, complex networks and smart grid.
Dr Jia Pan received his BEng degree in Control Theory and Engineering from Tsinghua University, the Mainland China, and his Ph.D. degree in Computer Science from the University of North Carolina at Chapel Hill. He is currently a Research Assistant Professor at the Department of Computer Science, the University of Hong Kong. His research interests include intelligent grasping and manipulation, motion planning, learning from demonstration and planning with uncertainty.