Browsing by Author "Jahagirdar, Aniruddha"

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Open Access
Analysis and development of a digital picking system using IoT and Logistic 4.0
(2022) Jahagirdar, Aniruddha
Order picking is a crucial step in nearly all distribution networks and has a significant impact on how well warehouses run. Even though the majority of businesses still use manual order picking, development into diverse options for optimizing order picking operations or providing technological support for human order pickers is advancing quickly. A development in the logistics industry known as Logistics 4.0, or Industry 4.0 in logistics sector is taking place; it addresses new goals and the use of technology to handle impending issues in logistics and warehouse operations. More than half of a warehouse’s operational expenses are largely linked to order picking, which is the process of collecting material from the warehouse and delivering it to the packing station. Order picking procedures still primarily rely on manual labour, which notably contributes to the relatively high process costs, despite the prospect of digitising these procedures growing. In this study, a new way is proposed to optimise the manual operations of the paper-based order picking system by integrating the warehouse routing problem with an interactive webpage to give routes for pickers and order data in order to improve productivity and lower picking error rates. To evaluate the current level of knowledge in this area, a thorough literature study is conducted, and potential research areas in order picking are identified. Along with this, various Travelling Salesman Problem (TSP) heuristics are also examined, and thorough cost and performance analyses are done for various TSP heuristics. Additionally, an economic analysis is performed where several factors are taken into account for both the current paper-based system and the recently built digital system. In the end, this thesis work discovers that the digital picking method performs better in terms of worker ergonomics and efficiency than the traditional paper-based approach. Under the general conditions set, this is the only order picking solution that requires no modification of the warehouse’s environment and a minimum of initial investment in infrastructure.