Skip to main content
Mobile
  • Finance, Accounting & Economics
  • Global Business Management
  • Management, Leadership & Organisation
  • Marketing & Sales
  • Strategy
  • Technology & Operations
HS Talks HS Talks
Subjects  
Search
  • Notifications
    Notifications

    No current notifications.

  • User
    Welcome Guest
    You have Limited Access The Business & Management Collection
    Login
    Get Assistance
    Login
    Forgot your password?
    Login via your organisation
    Login via Organisation
    Get Assistance
Finance, Accounting & Economics
Global Business Management
Management, Leadership & Organisation
Marketing & Sales
Strategy
Technology & Operations
You currently don't have access to this journal. Request access now.
Practice paper

Artificial intelligence in materials handling : How machine learning tools boost warehouse safety, productivity and cost-effectiveness

Brien Downie, Marc Gyöngyösi and Chris Kuehl
Journal of Supply Chain Management, Logistics and Procurement, 4 (1), 6-16 (2021)
https://doi.org/10.69554/QRXL2129

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.

Already a subscriber? Login or review other options.

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.

Options

  • Download PDF
  • Share this page
    Share This Article
    Messaging
    • Outlook
    • Gmail
    • Yahoo!
    • WhatsApp
    Social
    • Facebook
    • X
    • LinkedIn
    • VKontakte
    Permalink
cover image, Journal of Supply Chain Management, Logistics and Procurement
Journal of Supply Chain Management, Logistics and Procurement
Volume 4 / Issue 1
© Henry Stewart
Publications LLP

The Business & Management Collection

  • ISSN: 2059-7177
  • Contact Us
  • Request Free Trial
  • Recommend to Your Librarian
  • Subscription Information
  • Match Content
  • Share This Collection
  • Embed Options
  • View Quick Start Guide
  • Accessibility

Categories

  • Finance, Accounting & Economics
  • Global Business Management
  • Management, Leadership & Organisation
  • Marketing & Sales
  • Strategy
  • Technology & Operations

Librarian Information

  • General Information
  • MARC Records
  • Discovery Services
  • Onsite & Offsite Access
  • Federated (Shibboleth) Access
  • Usage Statistics
  • Promotional Materials
  • Testimonials

About Us

  • About HSTalks
  • Editors
  • Contact Information
  • About the Journals

HSTalks Home

Follow Us On:

HS Talks
  • Site Requirements
  • Copyright & Permissions
  • Terms
  • Privacy
  • Sitemap
© Copyright Henry Stewart Talks Ltd

Personal Account Required

To use this function, you need to be signed in with a personal account.

If you already have a personal account, please login here.

Otherwise you may sign up now for a personal account.

HS Talks

Cookies and Privacy

We use cookies, and similar tools, to improve the way this site functions, to track browsing patterns and enable marketing. For more information read our cookie policy and privacy policy.

Cookie Settings

How Cookies Are Used

Cookies are of the following types:

  • Essential to make the site function.
  • Used to analyse and improve visitor experience.

For more information see our Cookie Policy.

Some types of cookies can be disabled by you but doing so may adversely affect functionality. Please see below:

(always on)

If you block these cookies or set alerts in your browser parts of the website will not work.

Cookies that provide enhanced functionality and personalisation. If not allowed functionality may be impaired.

Cookies that count and track visits and on website activity enabling us to organise the website to optimise the experience of users. They may be blocked without immediate adverse effect.