The 6 essential steps to a successful machine vision quality control project

Step 1: Creating specifications

Specifications are the cornerstone of any successful project. This initial stage aims to clearly define the project's objectives and constraints, in order to guide technical and strategic choices.

Key elements to include in specifications

• Quality control objectives: What defects or anomalies need to be detected? What precision is required? How is quality control currently carried out? What impact does quality control have on production?
• Production rate: Should the system be integrated into a high-speed line, or into a slower but complex process? Should inspection be carried out on 100% of products, or only by sampling?
• Types of defects to be treated: Are they scratches, deformations, dimensional deviations or other irregularities? Are they aesthetic or functional defects?

The importance of the defect library

A defect library is a collection of images and/or parts representing compliant and defective products. It plays a crucial role in this phase:

• It helps illustrate typical defects for service providers or technical teams.
• It serves as the basis for developing algorithms or training artificial intelligence models.
• It forms the basis for future validation of the automated quality control system. It avoids any disputes during final delivery.

CODA Systèmes supports its customers at this stage, helping to structure requirements and identify the specific constraints of each production environment.

Step 2: Feasibility study

The feasibility study validates that the project is technically feasible and economically viable. It's an essential step to avoid costly mistakes downstream.

What the feasibility study must include

1. Equipment testing: Identify the cameras, optics and lighting best suited to the specific features of the parts and the production environment.
2. Validation of AI algorithms or models: Traditional or AI-based vision software needs to be tested against the defect library to check its ability to detect expected defects.
3. Analysis of environmental constraints: Assess variations in lighting, temperature or speed of parts on the line. Part of the study can be carried out directly on the production line to anticipate these environmental problems.

A well-conducted study also enables us to compare different configurations, so that we can choose the best solution at the lowest cost. At CODA Systèmes, our methodology enables us to offer a commitment to results.

Stage 3: SOLUTION DEVELOPMENT

Once feasibility has been validated, the development phase can begin. This involves designing a technical solution that meets the objectives defined in the specifications.

Key elements of development

• Choice of equipment: high-resolution cameras, lenses, optimized lighting, sensors or PLCs for process integration.
• Algorithm programming: This can include traditional algorithms (edge detection, pattern recognition) or models based on deep learning.
• Creating the user interface: of crucial importance, it must be intuitive to facilitate its adoption by teams.

At CODA Systèmes, this stage is carried out by engineers specialized in machine vision, guaranteeing complete customization of programs to meet customer specifications.

Stage 4: Integration and commissioning

Integration involves installing the system in the production environment and connecting it to existing equipment (production lines, PLCs, MES systems).

Critical integration points

• System calibration: to ensure that cameras and optics are correctly positioned to cover the entire room.
• Real-life testing: Simulate production to identify any adjustments needed before official commissioning.
• Mechanical and automation integration: This stage can include the development of customized mechanical structures and the integration of automation modules.

With its expertise in mechanical engineering and automation, CODA Systèmes ensures smooth, efficient integration.

Step 5: User training

A high-performance system will only be effective if operators, technicians and quality managers know how to use it correctly. Training is therefore a crucial investment in long-term success.

Training objectives

• Learn to use the system: Set up inspections, analyze results and diagnose faults.
• Provide first-level maintenance: change settings or solve minor problems without relying entirely on technical support.
• Develop team autonomy: A well-trained team is more responsive to production variations or technological developments.

CODA Systèmes offers training courses tailored to the specific needs of each customer, covering both hardware and software aspects. Its QUALIOPI-certified training organization, CODA Formations, offers a wide range of training modules delivered by vision experts from the field.

Step 6: Technical support and maintenance

After commissioning, a machine vision system needs to be monitored to guarantee its performance over time.

Essential services after installation

• Reactive technical support: To solve problems quickly and minimize production downtime.
• Software updates: Integration of new functions or performance optimization.
• Preventive maintenance: Periodic inspection of equipment to prevent breakdowns.

With tailored maintenance contracts, CODA Systèmes ensures long-term support for its customers.

How to successfully implement a machine vision quality control project?

A machine vision quality control project is a structured process based on specific steps:

1. Creation of a complete specification, including the defect library.
2. Carry out a rigorous feasibility study.
3. Development of a suitable technical solution.
4. Integration and commissioning in production.
5. In-depth user training.
6. Post-installation follow-up with technical support and maintenance.

By following this methodology, you maximize your chances of success and get the most out of your investment. With its expertise and turnkey solutions, CODA Systèmes can support you every step of the way to ensure smooth implementation and optimum performance.