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Artificial intelligence in materials handling : How machine learning tools boost warehouse safety, productivity and cost-effectiveness
Journal of Supply Chain Management, Logistics and Procurement,
4
(1),
6-16
(2021)
Abstract
This paper explores the growing potential of artificial intelligence (AI) and machine learning (ML) to bring about improvements in safety, which in turn can boost cost-effectiveness, productivity and operational efficiencies in a warehouse setting. While there is significant evidence in the literature on the impact AI is having in other areas of the supply chain, the authors believe the specific use of AI and ML in the warehouse has been underexplored. Companies that embrace machine-learning technologies and tools as a way to reduce incidents in their warehouses are improving worker safety, increasing productivity, and potentially yielding a competitive advantage for their businesses. This paper’s main purpose is to demonstrate, through a use-case approach, the clear benefits of these technologies and to promote further exploration of the potential of AI to drive improvements in the safety of materials handling in warehouse settings.
Keywords: case studies; materials management; technology management; transportation; distribution; logistics; warehousing
The full article is available to subscribers to the journal.
Author's Biography
Brien Downie is an experienced logistics professional with accomplishments in leading new business growth, operational efficiency and systems implementation. He has served as president of Holman Logistics since February 2019, leading the company with a focus on providing extraordinary service experiences for all customers. Prior to his current role, Brien served as vice president of Holman Logistics for five years. He holds a BA in media management from Biola University and an MBA in marketing and strategy from the Anderson School of Management at the University of California, Los Angeles.
Marc Gyöngyösi is founder and CEO of OneTrack, a company which provides an AI-powered warehouse operating system that leverages lift-mounted cameras to enhance safety and productivity. Since founding the company in 2017, Marc has led the business to deliver measurable increases in facility safety and productivity for leading logistics and manufacturing operations. He holds a degree in computer science and robotics from Northwestern University and was recently named to the Forbes 30 Under 30 list for the manufacturing sector.
Chris Kuehl is the chief economist for the Fabricators and Manufacturers Association, where he is responsible for interpreting and assessing the FFJSCR (Forming and Fabricating Job Shop Consumption Index) as well as writing their bi-weekly Fabrinomics. He is cofounder and managing director of Armada Corporate Intelligence, which provides services including economic forecasting, strategy development and competitive analysis for clients in a variety of industries. Chris is also a frequent keynote speaker for US and international conferences devoted to manufacturing, logistics, finance, credit, retail, accounting and other areas. He holds a PhD from the University of Kansas.
Citation
Downie, Brien, Gyöngyösi, Marc and Kuehl, Chris (2021, September 1). Artificial intelligence in materials handling : How machine learning tools boost warehouse safety, productivity and cost-effectiveness. In the Journal of Supply Chain Management, Logistics and Procurement, Volume 4, Issue 1. https://doi.org/10.69554/QRXL2129.
© Henry Stewart
Publications LLP
Publications LLP