Efficiency and accuracy are indispensable in automotive manufacturing. The vehicle identification number (VIN) data capturing and entry must be very precise. However, the manual approach to VIN Data entry is prone to errors. This case study is based on an automobile manufacturer who transformed VIN Data Entry to more accurate and efficient.
The Challenge of Manual VIN Data Entry
This manual entry of VIN data was a big bottleneck in the manufacturer’s production workflow. Operators would read the VIN plate visually and type in the information: VIN, engine number, part number, and production date codes. The manual approach caused delays and was prone to human errors. These errors would then turn out to be costly mistakes. Eventually, they would have to recall couple of vehicles back to the factory.
The Innovative Solution: Automating VIN Capture with RS38 and Pic ‘n Fill™ OCR
With this problem at hand, the manufacturer then sought help from CipherLab, a world leader in mobile computing solutions. CipherLab deployed the RS38 touch mobile computer together with its Pic ‘n Fill OCR (Optical Character Recognition) technology. Even in the suboptimal lighting conditions or paint color variations, this customized solution was created to extract VIN data with extreme accuracy.
The 650 personnels who worked in the company were now equipped RS38 touch mobile computer equipped with the Pic ‘n Fill OCR solution to capture VIN data. The incorporation of this technology in the manufacturer’s Manufacturing Execution System (MES) was transformative.
Key Features of the RS38 and Pic ‘n Fill™ OCR:
- Accurate OCR engine trained specifically for the engraved VIN plate types
- Presetting camera adjustments to maintain consistent performance under diverse lighting conditions
- Integration of the solution into the manufacturer’s current shop floor control interface
- Conversion of extracted VIN data into a QR code that could be scanned by any workstation
Transforming Efficiency and Accuracy
After the implementation of the automated VIN data entry workflow, the manufacturer has seen a drastic transformation in their operations. The time taken to capture and enter the VIN data has been reduced by more than 90%, speeding up production considerably. Besides, the solution has also removed almost all human errors. It has helped in reducing the number of vehicles that had to be returned to the plant due to improper VIN entries.
Scaling for the Future
The RS38 touch mobile computer equipped with the Pic ‘n Fill OCR solution proved to be a game-changer for this particular client. Speed, precision, and easy manipulation all were on the list of praises by the operation team. Thus, the team considered for the deployment of the VIN recognition system on all applicable workstations. This scalable and economical innovation has restructured the current production process. It has also put the manufacturer in a favorable position for future success in the automotive industry.
Conclusion
The automation of VIN data entry has been a major transformation for the world’s leading automobile manufacturer. By collaborating with CipherLab, the company has changed a major facet of its manufacturing operations with efficiency, accuracy, and long-term competitiveness. This solution is a shining example of how technology can uplift the process from the past and usher in a more refined and responsive automotive industry.
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