Use Case
Using Simulations for Warehouse Optimization with Rebus Analytics and Cycle Labs
A leading provider of high-quality pet care and nutrition products sought solutions to optimize warehouse efficiency, specifically aiming to balance AGV (automated guided vehicles) and forklift workflows, reduce congestion in high-traffic areas, and test new workflows without disrupting live operations. They needed a way to simulate various configurations and peak demand scenarios with actionable data to better understand ideal setups for space utilization and workforce distribution and drive decision-making.
Challenges
Complex Workforce Optimization
Balancing the performance of AGV and standard workforce for tasks like picking and replenishment.
High Demand Scenarios
Handling peak volume demands efficiently and minimizing bottlenecks.
Space Utilization
Optimizing picking and replenishment zones to prevent congestion and honeycombing.
Data-Driven Decision Making
Achieving actionable data insights beyond visual simulation for accurate planning.
Solutions Implemented with Rebus and Cycle Labs
Warehouse Simulation for Workforce Optimization
Simulated both AGV (automated guided vehicles) and forklift workforce setups to compare performance and efficiency.
Dynamic Scenario Testing
Tested various configurations, including 50/50 AGV and human workforces, to optimize efficiency in picking, replenishment, and receiving tasks.
Workflow Simulation
Ran simulations on interleaving work and other workflows to identify optimal setups without disrupting live operations.
Real-Time Congestion Mapping
Leveraged Rebus warehouse maps functionality to identify high-traffic areas to improve space utilization and reduce congestion.
ROI and Benefits
Improved Efficiency
Provided visibility into AGV versus forklift workflows to support optimal workforce allocation.
Enhanced Decision-Making
Enabled comparison of simulated versus actual performance data to validate configuration effectiveness.
Reduced Congestion
Identified and addressed high-traffic areas to streamline warehouse flow and improve space utilization.
Scalable Testing Environment
Allowed the company to test configurations without the need for physical resources, reducing setup costs and enabling cost-effective experimentation.
This pet care company evaluated solutions that could simulate warehouse processes to test various configurations without implementing costly physical setups. Rebus Analytics, in partnership with Cycle Labs, stood out for its capabilities in creating data-driven warehouse simulations that align closely with actual warehouse operations, allowing for precise adjustments based on real-time needs. This approach ensured a pragmatic, scalable way to assess different scenarios efficiently.
Rebus was chosen for its robust data output capabilities that went beyond simple visuals to deliver metrics such as goal times and travel distances. This enabled the pet care company to simulate multiple workforce setups—such as AGVs versus forklifts—and optimize performance with measurable insights. Rebus’s flexibility in integrating with the company’s existing data and Cycle Labs’ automated workflow library ensured that simulations were realistic and tailored to their complex operational needs.
The company aims to continually optimize its logistics by leveraging Rebus and Cycle Labs for expanded simulations, including automated systems, peak volume scenarios, and more nuanced warehouse configurations. With data-driven insights, it is positioned to reduce operational costs further, enhance space utilization, and achieve a streamlined, adaptable warehouse environment.
