Automotive Seats AI Quality Control EasyODM Case Study

Automotive Seats AI Quality Control: EasyODM Case Study

In the fiercely competitive automotive manufacturing industry, delivering top-quality automotive seats is critical for gaining a competitive edge.

However, detecting defects in car seat materials during production can be a daunting challenge.

Manual inspection processes are slow, error-prone, and inefficient, leading to increased defects and hindering overall productivity and profitability.

To address these challenges, EasyODM, a leading provider of AI quality control software, joined forces with EasyFlow’s MLOps consulting services.

Client Profile

EasyODM is an innovative company specializing in advanced AI solutions for quality control. Their AI-driven software leverages machine learning and computer vision to quickly and accurately detect defects in car seat materials.

Challenges Faced

The client, one of the world’s largest automotive seats producers, faced a significant hurdle in identifying and resolving wrinkles in car seat materials during the production process.

The traditional manual inspection methods were laborious, time-consuming, and lacked the precision required for detecting subtle defects.

Consequently, the client experienced a rise in defects, impacting the overall manufacturing efficiency and profitability.

The Solution: EasyFlow’s Tailored MLOps Consulting Services

To overcome the quality control challenges, EasyODM sought the expertise of EasyFlow’s MLOps consulting services.

The objective was to implement cutting-edge machine learning algorithms that would enable the AI-powered detection of seat material defects with exceptional accuracy and speed.

EasyFlow’s MLOps consulting team conducted an in-depth needs assessment to understand the client’s specific requirements and pain points thoroughly.

Leveraging their extensive expertise in machine learning and AI, the team devised a tailored solution using advanced deep learning algorithms for wrinkle detection across a wide range of seat materials.

Implementation Process

  1. Data Preparation: EasyFlow’s data scientists collaborated with EasyODM to gather and preprocess the training data. The dataset included annotated images of car seat materials, categorized into “with wrinkles” and “without wrinkles.”
  2. Model Training and Validation: EasyFlow’s machine learning engineers trained the deep learning model using the preprocessed data. Rigorous validation tests were conducted to ensure the model’s accuracy and reliability.
  3. Seamless Integration: Once the model was trained and validated, EasyFlow seamlessly integrated it into the EasyODM software. This allowed the client to incorporate the AI-powered defect detection seamlessly into their existing production line.

Results: A Leap Towards Automotive Seats Quality Excellence

The implementation of EasyODM, powered by EasyFlow’s MLOps consulting services, led to remarkable outcomes for our client, one of the world’s leading automotive seats producers:

  1. Time Reduction: The inspection time for wrinkles detection decreased from approximately 1 minute per part using the manual process to 2.2 seconds per part with AI.
  2. Cost Savings: EasyODM eliminated human bottlenecks, reduced tact time, and led to approximately 30x cost savings compared to manual inspection, positively impacting the bottom line.
  3. Enhanced Accuracy: The AI-powered EasyODM system achieved an impressive accuracy rate of 99% in wrinkle detection. This ensured consistent and reliable results, surpassing the capabilities of human inspection.
  4. Seamless Integration: EasyODM seamlessly integrated into the existing production line, empowering employees to focus on supervising and optimizing the platform. By automating repetitive and tedious inspection tasks, the workforce was freed up to concentrate on higher-value tasks, fostering a more efficient and engaged work environment.


The collaboration between EasyODM and EasyFlow’s MLOps consulting services exemplifies the potential of advanced AI technologies in revolutionizing traditional manufacturing processes.

By harnessing the power of machine learning, the client achieved substantial time reduction, improved accuracy, and significant cost savings, positioning themselves for operational excellence and improved profitability.

The successful implementation of AI quality control with EasyODM showcases the transformative power of AI and machine learning, empowering businesses to tackle complex challenges and achieve success in an ever-evolving industry.

With EasyFlow’s tailored MLOps consulting services, clients gain a competitive edge and pave the way for a visionary future in automotive seats manufacturing.

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Vėjūnė Krašinskienė
Chief Operating Officer

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