Exploring Five AI Warehouse Project Concepts
Artificial Intelligence (AI) will be transforming the landscape of future distribution centers and warehouses. These controlled environments offer the perfect setting to experiment with cutting-edge technologies like robots and AMRs.
The application of AI in these facilities is slowly gaining momentum, with a recent industry survey highlighting its growing adoption. Several large companies such as Amazon and Walmart have been using various AI tools for several years to optimize their supply chain.
However, challenges such as cost, complexity, and a lack of understanding regarding AI's potential are hindering further investments in this field. In reality, AI can significantly simplify and economize warehouse optimization without the need for massive investments in data science departments. Here are five compelling AI applications for your initial warehouse project.
1. Intelligent Automation for Enhanced Collaboration: Imagine orchestrating a seamless dance between humans and autonomous mobile robots (AMRs) in the order-picking process. AI-based execution systems can optimize the schedules of both robots and human pickers. These systems leverage machine learning algorithms to predict the locations of robots and pickers at any given time, ensuring efficient coordination and task sequencing. Moreover, they offer flexible communication tools for directing workers independently of the AMRs, using wearable mobile devices instead of robot-mounted tablets.
2. Streamlining Performance Management: Traditional labor management systems based on Engineered Labor Standards (ELS) have been a staple for years. AI can revolutionize performance management by automating data collection, eliminating labor-intensive processes. Learning algorithms predict task completion times based on real-world performance data, incorporating various variables such as work type, location, product, and quantity. This predictive accuracy allows for continuous adjustments when operational changes occur.
3. Optimizing In-Warehouse Travel: Warehouse employees often spend a significant portion of their day traveling within the facility. AI steps in where automation alone falls short, utilizing vast datasets to learn and reduce travel inefficiencies. It achieves this through intelligent order batching and pick sequencing, considering factors like congestion areas and slow-moving routes. AI-driven travel optimization has shown impressive productivity gains, even reaching up to 2x in piece-picking applications and 20-30% in case-pick to pallet operations.
4. Efficient Workforce Planning: Efficient labor allocation is crucial to meeting order deadlines while avoiding overstaffing or understaffing issues. Many DCs currently rely on supervisors' experience and skills to make real-time allocation decisions. AI-driven solutions offer predictive capabilities for labor requirements and task completion times. They can simulate different scenarios to determine the most efficient use of labor, preventing delays and ensuring optimal workforce utilization.
5. Dynamic Slotting Made Easy: Proper product slotting significantly impacts labor productivity, throughput, and accuracy in warehouses. However, this task is complex due to numerous factors and a multitude of products and locations to consider. Traditional slotting solutions demand extensive engineering, measurement, and data collection efforts. AI simplifies this process by learning spatial characteristics and travel time predictions based on real-time data captured within the DC. This adaptable model continually optimizes product placements as conditions change.
AI Breaks Down Barriers to Warehouse Optimization
The survey mentioned earlier pinpointed cost and a lack of AI understanding as major obstacles to adoption. However, AI solutions have the potential to reduce costs and minimize the manual engineering efforts required for various warehouse optimization tasks, from slotting to labor management. Importantly, these AI-based solutions do not necessitate the development of extensive in-house AI expertise. With AI's promising capabilities, the future of warehouse optimization looks brighter than ever.
