Supply Chains at the Edge of Manufacturing: The Benefits of Moving Beyond Data Centers

Some decision makers in the manufacturing sector have responded by moving to edge-based computing. Edge computing removes a portion of supply chain data from a central data center and repositions it closer to the source of the data itself – at the site of a farm, warehouse, processing plant, or manufacturing facility.

Santhosh Rao, Senior Research Director at Gartner, says “As the volume and velocity of data increases, so too does the inefficiency of streaming all this information to a cloud or data center for processing.”

Where only 10% of enterprise-generated data is currently processed outside a data center or cloud, Rao predicts that by 2025 that figure will reach 75%, positioning edge computing as the future of supply chain management.

Let’s look at how edge computing can benefit supply chains today.

Warehouse speed and efficiency

Warehousing solutions that rely on centralized data servers are hamstrung by technical performance issues. This causes delays collecting, transferring, processing, and storing information, slowing decision making and response time from supply chain managers. Edge computing solutions position servers and storage at the site where data is being generated, enabling devices to operate over smaller and leaner localized networks. This eases strain on resources by only sending essential data to a remote center. Edge computing also enables 5G connectivity, for unprecedented speed and efficiency.

Supply chain visibility

In today’s complex network of global supply chains, the need for visibility has never been greater. Edge computing can improve visibility by facilitating the adoption of a blockchain network—think of this as a shared ledger for recording and viewing transactions, orders, payments, accounts, and assets across a network of supply chain stakeholders. The result is complete, real-time visibility across entire supply chains, enabling managers to quickly and easily track down the location, quantity, or status of goods and components.

Machine learning & automation

Edge computing can be used to automate time-sensitive supply chain processes in warehouses, factories, or manufacturing facilities. These processes lessen the need for human management, creating optimal outcomes while eliminating the risk of error due to manual processes. Edge-based computing enables more to be done with less labor, increasing the efficiency and resiliency of supply chains. Reduced latency in the response time of automated processes saves money, prevents costly errors, and protects workers from accidents with real-time responses to automated alerts.

Gartner says: “75% of large enterprises will have adopted some form of intralogistics smart robots in their warehouse operations by 2026. Smart intralogistics robots are specialized forms of cyber-physical robotic automation primarily aimed at warehouse and distribution center environments. Edge computing and 5G is the ideal ecosystem to power this new era of supply chain AI and automation.”

Data autonomy & sovereignty

Edge computing is particularly effective in supply chain locations where connectivity is limited or restricted, such as transports on land, sea, or air, or remote farms and facilities. Since edge computing keeps data close to its source, the risk of bandwidth strain or outages resulting from environmental or location-based factors is reduced.

Edge-based computing is also a means of mitigating risk when it comes to protecting sensitive information. Data being sent across national borders is vulnerable to cyber-attacks and piracy, and subject to legal issues that can cause supply chain congestion. Because edge computing keeps data within the boundaries of its location, sensitive data can be processed locally and encrypted before being sent to a primary data center.

Smarter, faster warehousing

To improve efficiency and accuracy in warehouse processes, smart cameras can be deployed to scan individual pallet barcodes for full visibility into what stock is where. Employees (AI or otherwise) can lift boxes, holding them in view of the cameras, which in turn reads the barcode metadata to identify whether the box has been placed on the correct pallet. With the meta-data analyzed in real-time, fraudulent barcodes or misplaced pallets can be spotted in a timely manner. Data is streamed in real-time between edge devices, your leading warehouse management system (WMS), the cloud, ERP software, and employees. This can save significant time, and money, while allowing for agility in fluctuations of volume traded.

Manufacturing future-proofed

Edge computing is redefining industrial manufacturing supply chains as well, enabling analytics and machine learning to detect manufacturing errors, safety hazards, and ensuring quality control. In one example, edge computing for processing and storing data is positioned closer to the equipment, enabling loT sensors to monitor machine health with low latencies and generate analytics in real time. This allows manufacturers to analyze and detect changes in their production lines before a failure occurs.

Edge computing is enabling a new standard for warehousing performance and logistics in the manufacturing industry, helping supply chain managers tackle the challenges of the future. From AI and automation, to robotization. Download our Guide to the Warehouse of the Future.

Generix Group North America provides a series of solutions within our Supply Chain Hub product suite to create efficiencies across an entire supply chain. Our solutions are in use around the world and our experience is second-to-none. We invite you to contact us to learn more.