Title: Warehouse optimisation using demand data analytics - a case study-based approach

Authors: P. Raghuram; Abhijeet Singh

Addresses: Department of Mechanical Engineering, Amrita School of Engineering, Coimbatore, Amrita Vishwa Vidyapeetham, India ' Department of Mechanical Engineering, Amrita School of Engineering, Coimbatore, Amrita Vishwa Vidyapeetham, India

Abstract: Pickup and delivery schedules in a warehouse depend on factors like order frequency, pick locations, manpower and layout of the warehouse. Warehouse data regarding demand, stock keeping units, layout and daily operations are collected. Data analytics can be used to process the demand data of the warehouse to find out SKU frequency, pick location, and daily demand. In this paper, the layout of an electronic warehouse handling a daily transaction of more than 10 million orders and anticipated expansion is analysed. The layout and pick locations are modified resulting in footprint optimisation and responsiveness. Modification of rack arrangements, redesign of the 'forward area' by changing conveyors in the forward area from a series to a parallel layout have reduced the travel distance by 79% and the workforce is reduced by 73%. The demand data can thus be analysed periodically leading to reduced lead times and reduced costs.

Keywords: warehouse optimisation; demand data analytics; footprint optimisation; layout modification; forward area; cost reduction.

DOI: 10.1504/IJBIS.2020.111643

International Journal of Business Information Systems, 2020 Vol.35 No.4, pp.519 - 538

Received: 22 Jul 2018
Accepted: 22 Oct 2018
Published online: 07 Dec 2020 *

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