» TEST & QUALITY
» TEST & QUALITY ASSURANCE Potential for the use of AI-based methods in the domain of automatic inspection systems Source: Goepel electronic AI advisor Source: Goepel electronic The evolution of AI from assistant to decision-maker Artificial intelligence (AI) can increase production efficiency, save time and money, elevate quality and improve the robustness of industrial processes. But how exactly can AI be applied usefully in the area of automated inspection? Here, Goepel electronic introduces us to its newly-developed AI software module which can not only advise operators on defect classification but make decisions independently. Dr. Jörg Schambach & Philipp Drechsler, Goepel electronic With costs rising, the call for flexible and autonomous automation solutions will only get louder. This is especially true for inspection systems that are standard in modern production lines. AI is certainly an important element in this shift towards automation. AI innovation in the area of inspection systems is often focused on automating manual processes such as the creation of inspection programmes or the classification of defects at the verification station. With this in mind, the software used in Goepel electronic’s AOI systems was expanded at an early stage to include an AI-based expert system for automated test programme generation. With the software module ‘MagicClick’, test programmes can be created and optimised automatically. Without any library entry, a production-ready test programme, including component library, is generated in just a few minutes. The parameters are also automatically adjusted, taking into account real process fluctuations. Having succeeded in creating an AI solution in this area, Goepel electronic has now developed an AI-based solution to the classification of defects at the verification station. From assistant to decision-maker Automated optical inspection (AOI) or automated X-ray inspection (AXI) are an essential part of standard quality assurance processes in production lines for both SMD (Surface Mounted Devices) and THT (Through Hole Technology) assemblies. The systems 42 EPP Europe » 04 | 2023
AI advisor and the AI backend in the context of Goepel software applications Source: Goepel electronic inspect PCBs for correct component placement and soldering, and any defective assemblies are rejected. When an assembly is rejected, the defects detected by the inspection system are usually assessed and classified by human operators at a verification station. This visual evaluation is a monotonous task and is subject to human error because, for instance, the operator is tired. The risk of incorrect classification is increased when complex defect patterns need to be assessed with changing process parameters. These wrong decisions can be fatal when an AOI or AXI system has detected an actual defect, but this defect is subsequently classified by a human operator as a ‘pass’. In this case, we speak of a ‘falsepositive classification’, which can, in turn, lead to an escape. The defective PCB is processed further and, in the worst case scenario (if the subsequent electrical tests also do not detect a failure), ultimately delivered to the customer. This is where the AI advisor software module, newly developed by Goepel electronic and integrated into the PILOT Verify verification software, comes in. For each error detected by the AOI or AXI, the AI-based function forms its own opinion. In the first stage (level 1), the software provides the user with this additional information. This means that, analogous to the four-eye principle, there are two independent opinions for each error found: that of the operator and that of the AI. If the AI comes to a different conclusion than the operator, a message is displayed and the user is asked to review their decision again. Zusammenfassung Der Einsatz KI-basierter Methoden in der Inspektion ermöglicht die vollautomatische Erstellung und Optimierung von Prüfprogrammen. Auch geht es darum, die permanent gesammelten Daten der Inspektionssysteme mit Hilfe der KI effektiv zu nutzen, um Prozesse zu bewerten und Prozessanomalien frühzeitig zu erkennen. Résumé L’utilisation de méthodes basées sur l’IA dans l’inspection permet la création et l’optimisation entièrement automatisées de programmes de contrôle. Il s’agit également d’utiliser efficacement les données collectées en permanence par les systèmes d’inspection à l’aide de l’IA afin d’évaluer les processus et de détecter suffisamment tôt les anomalies de processus. Резюме Применение методов на основе искусственного интеллекта в области инспектирования дает возможность в полностью автоматическом режиме создавать и оптимизировать программы проверки. Речь также идет о том, чтобы эффективно использовать постоянно собираемые данные систем инспектирования при помощи искусственного интеллекта для оценки процессов и своевременного выявления технологических отклонений. EPP Europe » 04 | 2023 43
