Tag: warehouse automation

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Text Scanning Tire Sidewall

How scanflow helped automate tire handling, improve visibility, and reduce operational cost

When a global e-commerce supply chain team sought to improve the way they track and manage tire inventory across warehouses, their requirement was clear. They needed a solution that could eliminate manual SKU counting, track tire aging, and reduce turnaround time, all without relying on on-premises software. 

The challenges were deeply operational: 
  • Manual tire identification during unloading and storage introduced frequent errors in SKU matching and quantity counts 
  • There was no way to track tire aging, leading to SLOB (slow-moving and obsolete) stock buildup 
  • Retrieval workflows were slow, requiring repeated physical checks 
  • High man-hour consumption due to multiple verifications across touchpoints 
  • No real-time visibility into what was stored, where, or for how long 

The solution also had constraints. It had to be deployed in the cloud on the client’s AWS account with only hardware (if any) deployed on-site. The goal was a lightweight, scalable way to automate tire tracking using their existing infrastructure. 

Scanflow’s Approach: AI Data Capture for Asset Identification 

Scanflow deployed its enterprise-grade data capture system, using AI to enable real-time tire recognition through sidewall scanning. Operators used handheld smart devices and cameras positioned at loading and storage points to extract tire information directly from the physical asset, including TIN, size, and model codes. 

Each tire was instantly verified against the warehouse management system. The capture workflow did not rely on barcodes or printed tags. Instead, it read the markings directly from the tire’s sidewall using optical character recognition and computer vision. 

All scan data was processed in real time and transmitted to the client’s private AWS environment, aligning with internal data residency and compliance requirements. 

What Scanflow Enabled 
  1. SKU-Level Identification at Entry and Retrieval
    Tires were captured and validated on the spot, reducing mismatch errors and improving inbound accuracy. 
  2. Aging Visibility with Timestamped Tracking
    Each tire was logged with its arrival time, enabling rotation and active removal of aging stock before it became obsolete. 
  3. Live Warehouse Snapshot
    Warehouse managers could see a real-time view of stock levels, distribution by zone, and tire movement, improving space utilization. 
  4. Reduced Turnaround Time for Picking and Dispatch
    Because tire type and location were tied to live data, retrieval paths were optimized, cutting delays. 
  5. No On-Prem Software Required
    The solution ran securely in the client’s AWS cloud instance, with edge-only processing at the point of scan. 
  6. System Integration with Existing WMS
    Scan events and validations were passed directly into the warehouse platform using secure APIs. 

Results Delivered 

  • 80 percent reduction in SKU mismatch and manual entry errors 
  • 55 percent faster tire retrieval and dispatch turnaround time 
  • Reduction in SLOB inventory through proactive aging insights 
  • Lower man-hour usage through fewer touchpoints and fewer rechecks 
  • Full compatibility with cloud-first environments and edge data capture 

Final Note 

Scanflow enabled the client to move away from spreadsheets, barcode dependency, and repetitive checks into a structured, data-driven tire management model. By capturing data from the tire itself and syncing it directly to cloud systems, the warehouse team gained clarity, speed, and measurable control over tire operations. 

To learn how Scanflow can bring structured data capture to your tire or asset tracking workflows, connect with our solutions team.

Request a walkthrough by reaching out to us via [info@scanflow.ai]

or simply click – schedule a demo to start the discussion with us today. 
 
 
 

Categories
Text Scanning Tire Sidewall

How Tire Sidewall Scanning using AI is transforming tire warehousing in Automotive Manufacturing

In automotive manufacturing, precision in tire identification is non-negotiable. But inside warehouses, the way tires are received, stored, and retrieved still relies heavily on manual intervention, leading to mismatches, delays, and an inability to manage inventory effectively. Sidewall data capture introduces a system of record built directly from the tire, enabling smarter, faster, and more accurate warehouse operations.

 

In most tire warehouses, the process begins with unloading. Tires are manually counted and logged using either handheld scanners or visual checks. From this point forward, tracking relies on printed barcodes, handwritten logs, or product labels that are easy to misread or lose. The warehouse is left operating on estimates, assumptions, and static records.


  • Inaccurate SKU matching: Selecting the wrong tire model or size during retrieval is common when multiple similar variants are stored in close proximity.
  • Manual data entry errors: Serial numbers and model information are often typed in by hand, increasing the risk of mismatch or duplication.
  • Lack of visibility into tire aging: There is no reliable mechanism to track how long each unit has been stored, leading to slow-moving stock building up unnoticed.
  • No real-time inventory insight: Most systems only offer a point-in-time view, which becomes outdated as soon as stock is moved or reallocated.
  • Increased turnaround time: The time it takes to find, verify, and dispatch the correct tire grows, especially as SKU complexity increases.
  • High man-hour cost: Staff must spend time on low-value tasks like physical checks, double entry, and re-scanning due to initial inaccuracies.

In fast-moving production environments, these issues quickly become bottlenecks – not just for the warehouse, but for the entire supply chain that depends on it.

  • Every tire has essential data embedded in its sidewall. This includes:
  • The Tire Identification Number (TIN)
  • Size and load index
  • Manufacturer and model
  • Batch or production code

Instead of relying on external labels, barcodes, or manual logs, sidewall data capture uses computer vision and optical character recognition to extract this information directly from the tire. The system identifies each unit as it is received, moved, or retrieved without requiring any manual input.

This data is immediately matched to the expected SKU and stored in the warehouse management system in real time. As a result, the warehouse has a live, continuously updated inventory view based on what is actually in storage, not just what was scanned in at the door.

1. Asset-Level Identification at Entry

Tires are identified individually as they are unloaded, with precise data linked to each unit. This eliminates reliance on aggregated batch-level logging or barcode stickers that may detach or degrade.

2. Reduced SKU Mismatch During Retrieval

Operators retrieve tires based on validated data from the sidewall, not assumptions or packaging labels. The system flags any discrepancies between what is picked and what is expected.

3. Live Tracking of Tire Aging

Because each tire is scanned and time-stamped at arrival, its storage duration is tracked automatically. This enables FIFO or FEFO practices and prevents the creation of slow-moving or expired stock.

4. Real-Time Warehouse Snapshot

Management gets a complete picture of what is stored where, down to the model and age of each unit. This allows for better layout planning, stock rotation, and dispatch prioritization.

5. Space Utilization Optimization

With clear data on high-movement SKUs, warehouse teams can adjust placement zones and stacking logic to reduce time and effort spent on retrieval.

6. Reduction in Man-Hour Cost

Automated capture eliminates the need for repeated checks, re-scanning, and dual entry. Fewer errors mean fewer corrections, and fewer hands are needed to manage day-to-day tracking tasks.

Moving from Manual to Measurable

The shift from manual identification to structured AI sidewall capture is not just about saving time. It is about enabling tire warehousing operations to work with a level of data integrity and speed that matches the rest of the automotive manufacturing process.

Inaccurate or missing tire data delays dispatches, inflates inventory cost, and slows down assembly. When identification happens at the source; at the moment the tire is unloaded, these problems no longer accumulate. Warehouses become faster. Decisions become more informed. Stock becomes more visible and manageable.

Conclusion

Sidewall data capture transforms warehouse operations from manual and reactive to intelligent and data driven. By building traceability from the physical asset itself, it eliminates errors at the point of entry, improves selection accuracy during retrieval, and gives real-time visibility into every tire in the system.

For tire manufacturers, OEMs, and their warehousing partners, the message is simple: better data starts at the sidewall and the time to capture it is now.

If your teams are still spending time on manual tire checks, SKU revalidations, or inventory clean-ups, you’re losing more than just time – you’re losing traceability, efficiency, and cost control.

Scanflow lets you capture tire sidewall data directly from the tire; fast, accurate, and fully integrated into your existing workflows.

No guesswork. No double entry. Just clean data, from source to dispatch.

Book a walkthrough with our team to see how Scanflow fits into your warehousing environment.

Schedule a demo or Download SDK to start.

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