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An Augmented Reality Assisted Order Picking System using IoT
Author(s) -
Mayank Kumar Nagda*,
Sankalp Sinha,
E Poovammal
Publication year - 2019
Publication title -
international journal of recent technology and engineering
Language(s) - English
Resource type - Journals
ISSN - 2277-3878
DOI - 10.35940/ijrte.c3991.098319
Subject(s) - computer science , order picking , bottleneck , workflow , scalability , task (project management) , augmented reality , modular design , process (computing) , order (exchange) , database , human–computer interaction , warehouse , embedded system , engineering , systems engineering , operating system , finance , marketing , economics , business
It is widely recognized that order picking is the most complicated and time-consuming task in warehouse operations and often termed as the major bottleneck in warehouse workflow. Over the years the process of order picking has been extensively studied and many methods have been proposed to deal with its challenges. However, most of these solutions involve complex and expensive components with elaborate setups. In this paper, we propose RASPICK a modular, robust and cost-efficient order picking system that is scalable and can be used in warehouses of all sizes. The proposed system aims to reduce the cognitive load on the picker by providing crucial and relevant information for each item on the picking list. For a baseline, the proposed system is also compared to manual paper-based picking and shows significant improvements in average trip-time for lists of different sizes. The system combines the convenience of Augmented Reality with the power of the Internet of things to facilitate central control and management of pickers and attempts to address the low-level order picking bottlenecks.

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