Orchestrating the Future: PepsiCo/FLNA's Warehouse Transformation with AutoScheduler.AI's AutoPilot

Free Online Webinar at 2:00 PM ET on Thursday, September 12, 2024

Austin, TX - (September 3, 2024) -AutoScheduler.AI, an innovative Warehouse Orchestration Platform and WMS accelerator, announces the company is sponsoring a webinar hosted by DC Velocity magazine to discuss PepsiCo/FLNA's (Frito Lay North America) warehouse transformation using AutoScheduler.AI's AutoPilot.


Keith Moore, CEO of AutoScheduler.AI, and Peter Hanna, a leader at PepsiCo, will share how AutoPilot is revolutionizing operations at PepsiCo/FLNA. Faced with rising demand, shrinking margins, and complex operations, PepsiCo turned to AutoScheduler.AI's cloud-based AutoPilot platform to optimize warehouse operations and improve efficiency, including a 30% increase in product picks per hour.
"PepsiCo has been focused on driving value for customers through innovative supply chain processes that improve fulfillment times, reduce operating costs, and maximize productivity," says Keith Moore, CEO of AutoScheduler.AI. "Our AI algorithms can prioritize customer orders based on predefined rules and criteria while considering warehouse constraints, which helps to improve customer satisfaction and overall profitability."
At the free webinar on September 12, 2024, at 2:00 PM ET, attendees will:

• Learn how AutoPilot unifies data across systems for better visibility.
• Discover how advanced algorithms maximize productivity and minimize costs.
• See how AutoPilot provides comprehensive, real-time insights for informed decision-making.
• Hear about the impressive gains at PepsiCo/FLNA, including a 30% increase in picks per hour.

AutoScheduler.AI AutoPilot smooths warehouse operations by orchestrating and planning all activities in real-time on top of an existing WMS. It considers space, time, labor, dock doors, and more constraints to ensure that orders are fulfilled on time and in full. Clients gain efficiencies and value in their supply chains through optimized labor, schedules, touches, and inventory.

To register for the free webinar, visit: https://event.on24.com/wcc/r/4676523/A2108DE2BC89DF1C73F2FCB1C1A5863F?partnerref=auto

About AutoScheduler.AI
AutoScheduler.AI orchestrates warehouse activities directly on top of your WMS, optimizing operations for peak performance. Developed alongside industry leaders like P&G and successfully deployed at prominent companies such as Pepsi, General Mills, and Unilever, our AI and Machine Learning platform seamlessly integrates with your existing systems. Focused on labor planning, inventory workflow, human-robotics interaction, and space utilization, we streamline operations, reducing travel and inventory handling while maximizing OTIF rates and labor efficiency. With prescriptive analytics driving insights, our clients harness the power to enhance efficiencies and generate value across their supply chains. Reach out to us at info@autoscheduler.ai for more information.

Featured Product

T.J. Davies' Retention Knobs

T.J. Davies' Retention Knobs

Our retention knobs are manufactured above international standards or to machine builder specifications. Retention knobs are manufactured utilizing AMS-6274/AISI-8620 alloy steel drawn in the United States. Threads are single-pointed on our lathes while manufacturing all other retention knob features to ensure high concentricity. Our process ensures that our threads are balanced (lead in/lead out at 180 degrees.) Each retention knob is carburized (hardened) to 58-62HRC, and case depth is .020-.030. Core hardness 40HRC. Each retention knob is coated utilizing a hot black oxide coating to military specifications. Our retention knobs are 100% covered in black oxide to prevent rust. All retention knob surfaces (not just mating surfaces) have a precision finish of 32 RMA micro or better: ISO grade 6N. Each retention knob is magnetic particle tested and tested at 2.5 times the pulling force of the drawbar. Certifications are maintained for each step in the manufacturing process for traceability.