The Future of Inventory within Manufacturing

In the last decade the world of e-commerce has changed dramatically. This change has been accelerated with the pandemic, which resulted in a further increase in the use of online shopping. The time regarded ‘acceptable’ by shoppers has also plummeted, with an expectation of a 2-day turnaround from order to delivery, while the number of SKUs that must be managed, manufactured, stored, and distributed has massively increased.

Companies realize they need automation within their warehouse and manufacturing floor to successfully adapt to this increasingly unpredictable world. However, a phased, strategic approach to automation is often preferred to simplify the modernization process and accelerate the Return on Investment (ROI).

Phase 1: Improve Operations for Greater Individual Worker Productivity

The first phase is to gain control of basic business operations across all inventory processes from goods-in, through manufacturing and shipping. Firstly, it is important to identify inefficient processes by analyzing the internal supply chain. From here it is then possible to work on a simple increase in individual worker productivity to get a quick ROI.

This can be done by the introduction of mobile scanning. Cedar Bay Apps provides users with a familiar interface on devices rugged enough for warehousing environments. It is then possible to look at additional technology, such as wearable devices, tablets and mobile printers, to help improve visibility. This allows management to identify improvement areas and maximize productivity. Using IFS Transport and Warehouse tasks in conjunction with Cedar Bay Apps provides users with the ability to dynamically assign tasks. This can be extended based on real-time inventory data and contextual data from mobile devices, allowing employees to be directed to their best next action based on factors such as urgency.

Phase 2: Integrate for Greater Asset Visibility and Utilization

The second phase introduces sensor-based data collection. In earlier phases data capture is transactional and only provides a glimpse into warehouse operations. Automated data capture provides a more complete, real-time view. In the case of receiving, manual scans have missed entire cases of incoming goods. With an RFID system tagged goods are counted as soon as they pass through the dock doors with a portal style reader in the receiving areas. More readers can be placed at locations, including doorways within the facility. Thereby recording movements within the environment and to individual production lines. You now have sensor-based data; increasing accuracy and asset utilization, whilst decreasing time spent locating assets.

Phase 3: Be Responsive for Best Next-Move Guidance and Decision-Making

In the third phase, sensor-based, real-time data capture can be expanded more broadly across the entire facility. Real-time location services are fully integrated throughout the warehouse and manufacturing floor into IFS Applications. The result is more recording points, more accurate inventory data and minimal operator time recording transactions. This allows for better optimization of the flow of products from receiving through to shipping.

In the movement of goods, sensors associate forklifts, pallets and boxes to show goods on the forklift as it travels without the need for manual barcode scanning. Upon delivery at the destination the forklift and pallet are disassociated, the pallet shows as delivered or issued to a work center and the forklift shows it is ready for its next assignment. The same applies to autonomous mobile robots (AMR) with ready-to-ship materials, from picking to loading. Resources and assets are orchestrated, sequenced, and directed; meaning throughput volumes, costs and workflow speed are improved.

Phase 4: Predict and Adapt to Proactively Improve Performance

Finally, once data intelligence systems are deployed throughout the warehouse companies can begin data analytics and Artificial Intelligence (AI) to uncover ways to improve their processes even further. Whether that’s by updating their warehouse design, staffing levels, or perhaps changing workflows further. Companies can also use the data to quickly identify or predict changes in consumer buying habits and supplier shortages that could impact business profitability and use that data to rapidly adapt.