Quality Control Has Retail Distribution Centers Looking Like Automated Factories

 Emphasis on Quality Control Has Retail Distribution Centers Looking Like Automated Factories

Multiple forces are converging to propel this shift toward automating quality control in distribution centers. Retailers must untangle a wide assortment of issues to navigate this shift.

Emphasis on Quality Control Has Retail Distribution Centers Looking Like Automated Factories

 Cognex

Changing consumer habits are driving a wave of automation in the distribution centers (DC) that form the backbone of the logistics business. As retailers adapt to these realities, they are turning to the same kinds of technologies that automate modern production lines in factory automation: robotics, deep learning, and networked sensors.

Retailers are responding to increasingly demanding consumers who want to buy whatever they want, whenever they want it, on any device: smartphones, PCs, or tablets. If a store’s website tells them a product is in stock, it must be there when they are ready to buy — whether they’re in the car, sitting on their sofa, or strolling the aisles of a brick-and-mortar store.

Multiple forces are converging to propel this shift toward automating quality control in distribution centers. Retailers must untangle a wide assortment of issues to navigate this shift.

Key Challenges for Improving Quality Control in Distribution Centers

Distribution center operators face a raft of quality control challenges across four key areas: inbound, fulfillment, sortation, and outbound. Here is a quick look at some of their most common difficulties:

Tracing items throughout the facility. Extending traceability in the form of barcode reading, throughout a facility, ensures that the distribution center knows where every product is, all the time. With gaps in product tracking, at dock doors or at transfer points, it can be extremely difficult (and expensive) to satisfy customers who expect on-time delivery and accurate inventory levels while shopping online.

Managing barcode quality. Standard printed codes provide a unique signature for every product in the logistic chain, which makes accurate barcode scanning one of the most pressing challenges in the distribution center. Barcodes can be torn, scraped, and obscured by plastic wrappers, causing potential issues throughout the supply chain after they leave the facility. It’s important to read the barcode in any condition and have methods to identify when labels need to be replaced and ensure that what’s leaving the facility is going to be successful throughout its journey to the customer.

Dealing with returns. Failures in traceability and quality inspections often lead to customers not getting the items they ordered on time or at all or receiving damaged goods. These products may have to be replaced, repackaged, or reconditioned and sold at a lower price, squeezing profit margins. No longer can a company complete the quality inspection at the store, it must be done at the DC to ensure the customer is getting what they want, on time, and in an acceptable condition.

Improving runtimes. Speeding up throughput makes a facility more efficient and improves return on investment. But many production lines already run hundreds of products per minute, so finding even more efficiencies while maintaining quality control can be a tough balance.

Controlling maintenance and repair costs. Machines and conveyor lines with thousands of moving parts inevitably break down, forcing delays that pinch profit margins and expand delivery times.  

Understanding data signals. Distribution centers rely on a network of digital cameras to scan barcodes and inspect products, to ensure accuracy and quality. Each of these sensors produces massive volumes of data that must be carefully analyzed to root out inefficiencies and reduce the risk of reading errors.  

Implementing learning algorithms. The flood of sensor data contains insights on product defects and inefficient processes that are invisible to the human eye. Unearthing these insights requires advanced software that scans these data flow for consistent patterns and learns how to improve outcomes without human intervention.

How Cognex Helps Logistics Operators Elevate Quality Control

Efficient logistics operations rely on machine vision technology: cameras and software that interpret the data in digital images and provide insights that make distribution centers more efficient.

These tools are the heart of Cognex’s business. For example, Cognex machine vision technologies:

Here are some of the ways our technologies improve accuracy and quality in logistics:

Three-dimensional inspections. Cognex industrial 3D cameras use advanced 3D tools to quickly determine the shapes, dimensions, and other essential data on products and packages traveling on conveyor lines. One common inspection application is identifying damage detection on a box. Cognex vision systems identify issues that will cause problems conveying an item or lead to an unhappy customer getting a damaged package.

IoT and analytics. Industrial cameras are edge devices that feed data into Industry 4.0 networks. Data scientists can develop algorithms to scan for trends and inefficiencies that the human eye cannot see or leverage deep learning to determine the frequency in which errors happen for process improvement.  

Predictive maintenance. Real-time analytics data from Industry 4.0 networks give logistics operators vital clues on the lifespan of their equipment. Repairs can be scheduled during off-hours and worn parts can be replaced before they fail, preventing expensive delays during the busiest times of the year.         

Deep learning. Our premium deep learning vision software is trained to decipher OCR codes, perform assembly verification, detect defects, and classify scenes and objects... This software uses training images to establish the appearance of defect-free items and identify damaged goods automatically, reducing the reliance on human inspectors.

Robotics. Cognex machine vision systems, barcode readers, and deep learning software are laying the groundwork for advanced robotics in logistics operations. While the most complex picking jobs still require the eyes, fingers, and brains of humans, tech startups are working hard on automating these tasks. Cognex hardware and software will be central to implementing these advances as they arrive on the market.  

Recognizing the Imperative for Automation and Quality Control in Logistics

Retailers and logistics operators increasingly realize that “out-of-stock” messages are frustrating online buyers, while botched orders are driving them off for good. Meanwhile, demand spikes and external threats like the COVID-19 pandemic are making it difficult to hire enough people to satisfy these new demands.

These trends illustrate why retailers have no choice but to zero in on automation and quality control in their distribution centers. Cognex technologies make it all possible. 

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The content & opinions in this article are the author’s and do not necessarily represent the views of RoboticsTomorrow

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