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Advantages of using artificial intelligence
Quality inspection covers the full manufacturing cycle, raw materials, components and parts in different stages of production to the final product. Inspections help identify defects at an early stage, thereby reducing production costs. Inspection can be done to compare existing raw materials, components or products with specified quality specifications. If an inspected item falls within the specified or permitted range, the item is accepted, otherwise it is rejected. Quality control helps improve product quality, automate production processes, and reduce manufacturing costs.
Machine vision technology uses digital cameras and image processing to replace or supplement manual inspections and measurements.
Quality Control
Quality control has always been an inherent concern of production and customer satisfaction, and accordingly, the issue of quality control with artificial intelligence becomes important. The main goal of production is to produce products that customers can buy and use. Therefore, it is necessary to produce the products needed by customers with the right quality and the right price.
Automation is a very important factor in the industry that leads to mass production. After the production of the product; To decide on rejection or acceptance, it is done by measuring quality parameters. In almost all industries, inspection is done manually to measure quality parameters such as dimensions and characteristics of the manufactured product. Manual inspection is time-consuming, expensive, sometimes error-prone, and such inspection is very difficult for complex shapes, and the method is also destructive in some cases. To overcome these problems, quality control for industrially sensitive products is possible using image processing techniques.
In many cases, human judgment depends on previous knowledge and experience. In many cases, the acceptance or rejection of products based on a wrong opinion from an expert may become a culture in the organization and change the structure of the inspection by mistake, or the inspector may notice some kind of non-conformity in the products but be able to classify the type. non-compliance.
Automation of quality control
Such manual processes take a lot of time with human interactions. In order to reduce or eliminate non-value-added time, effective quality inspection tools and process automation should be used. In recent efforts, an attempt has been made to automate this process by using machine vision cameras.
The image processing technique has the advantage of analyzing the captured image to measure multiple areas of the product. Therefore, quality control during production and the final product, even in very high production runs, every component of the product is guaranteed. The automation process includes moving components, capturing images, processing images, and making decisions using sensors, actuators, and microcontrollers.
Quality inspection of workpieces is intensive and may be prone to error. Also, 100% manual inspection of manufactured parts or products is expensive and time-consuming and may not be feasible. Machine vision provides a fast, economical, reliable and objective inspection technique. It is also an automated, non-destructive and cost-effective technique that can be used in industries for various applications. Some of the key benefits of using machine vision can be listed as follows:
Accuracy:
Machine vision systems provide greater accuracy in quality inspection compared to human operators. Even when humans rely on magnifiers or microscopes, machines are still more accurate because they can see and be sure of parts with different tolerances.
Speed:
Parts can be inspected at a higher speed than inspection by human operators. In addition, such high-speed inspections can be performed with greater efficiency and productivity.
Reproducibility:
Quality inspections can be repeated in exactly the same way by machine vision systems without fatigue, 24 hours a day, 365 days a year. In contrast, human inspectors may arrive at different actions at different times, even if all the pieces are exactly the same.
100% inspection:
Machine vision systems can be designed to inspect 100% of manufactured parts or products. Otherwise, it is often possible to inspect randomly sampled parts or products using statistical methods and tools.
Cost:
Since machine vision systems are faster than humans, such automated inspections can reduce costs. Improve process accuracy to reduce sending defective parts to customers. This in turn reduces external failure costs such as replacements, lost sales, and warranties or guarantees.
On-line management dashboard:
One of the main concerns of production organizations is the non-registration of non-conforming products and the type of non-conformity found. Because, in the first place, dealing with the occurrence of non-conforming products and their assignment can cause forgetting to register reports, and on the other hand, the high level of inspection concerns and the number of inspections of technical specifications in the production line may cause the loss of some data. Be related to non-conforming products.
By having a quality control system based on artificial intelligence, it is possible to identify all the information related to the occurrence of non-conformities, and in addition to storing the data in the databases defined in the organization, at the end of each day or on the management dashboard. Inconsistent products should be sent to the owners of the relevant processes.
Inspector safety:
One of the main advantages of the machine vision system is its non-contact inspection method. Contact inspections are the types of inspections where the inspector must be present in the process execution environment or have direct contact with the part to measure. Such an advantage is particularly useful in cases where contact measurements are difficult to perform. Machine vision systems can also be used in environments that are dangerous for human inspection.
The stages of establishing the machine vision system
The team of data-based consultants provides its services in 7 general phases in order to make the organization data-oriented and provide solutions for digital transformation in organizations. productions can be different and the database team offers its solutions tailored to your organization.
In the first step of implementing the quality control system with machine vision and artificial intelligence (AI sharp vision), the management team will hold a meeting with the experts in the fields of production, quality control and design in the organization to determine what parameters or technical characteristics should be To be considered for quality control. The main goal of this phase of the project is to determine the characteristics that:
- have special importance for the customer, or ctqs
- Have a high production circulation
- 100% inspection of such features is expensive
- Human power is not able to correctly diagnose such cases with a high percentage of accuracy and precision
The desired output from this stage is the important quantitative and qualitative parameter or parameters to perform quality inspection with the help of AI sharp vision in the desired station or stations.
At this stage, after locating the control points, the desired equipment of the AI sharp vision system, including cameras and accessories. Also, network equipment is estimated and provided.
This stage is related to the implementation of the network infrastructure and the design of the information transfer system, which includes considering the appropriate processors and how to transfer information for image processing and operator movement. According to the sensitivities of the product, the way the operators work can be different, and according to the production environment, wireless or cable data transmission methods can be used.
The initial stage of this phase is the preparation of a suitable data set of matching and non-matching product images for the selection, implementation and implementation of artificial intelligence algorithms in the development of a model specific to the product and the client.
The main goal of this stage is to design and develop a quality control model based on machine vision and artificial intelligence. This model is specially prepared and developed according to the product and production conditions of the employer's organization.
After designing the system model and integrating it with neural and mechanical systems, in order to calibrate the system with the production line; AI sharp vision should be tested on the line to ensure the correct operation of the system. Therefore, in order to carry out the test period, a certain period of time is determined with the esteemed customer.
After the final tests of the system, trainings and instructions for setting up the system are provided to those responsible for the implementation of the inspection process, and the perfect implementation of the system by the people of the organization is ensured.
It should be noted that in addition to creating an artificial intelligence system, the mentioned system is also capable of preparing daily reports and receiving dashboards of non-conforming products, which allows managers to have the statistics of non-conforming products of any kind at their disposal. Have
After determining the optimal algorithms for developing the model and defining new non-conformities in the product, final tests are performed on the product and the system is tested under high pressure production conditions. If necessary, the final revisions of the system are carried out and the intelligent quality control system is delivered to the organization. In the final step of this phase, the focus is on the owners of the process, who can make the most effective use of it during the training of the support team, and the prepared dashboards are in accordance with The needs of the beneficiaries of the process are designed and their service is approved by them.
After the delivery and operation of AI sharp vision in the employer's production line, the development of the artificial intelligence model and the maintenance of the AI sharp vision system, it is requested that the manager of AI Sharp Vision is ready to cooperate with the respected employers in case of any changes in the control parameters as well as more technical specifications. develop the model
Obviously, the more datasets are described for the nervous system, the more accurate it will be, and on the other hand, some other technical characteristics may be identified, and senior management may want to create checkpoints based on such technical characteristics. Based on this, the above should be applied to redefine the technical characteristics and improve the accuracy of the model
Implementation of quality control solutions, based on artificial intelligence
Obviously, providing a solution based on artificial intelligence requires technical and academic knowledge. The team of data-based consultants is proud to be with your organization by using the knowledge boundaries of artificial intelligence and data-oriented tools such as POWER BI, TABLUE, PYTHON, etc., so that you can effectively institutionalize digital transformation strategies in your organization in the shortest possible time. .
At the end of the 7 phases of establishing an intelligent quality control system, the following outputs are provided:
- Inspection of 100% of products and registration of inspection reports for each product
- The possibility of viewing non-conformities detected in the product using photos taken by the system
- Removal of non-conforming products in terms of appearance and dimensions
- Classification of non-conformities occurring in production
- Providing quantitative reports at the end of the day or online to stakeholders
- Management dashboards in platforms required by process owners
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