SAN DIEGO – KIC, the leader in smart thermal process technologies for electronics manufacturing, is excited to announce its participation in the SMTA Tijuana Expo & Tech Forum on November 7, 2024 at the Quartz Hotel. Attendees are invited to explore KIC’s innovative solutions that are designed to empower businesses to drive continuous improvement and achieve their production goals with precision.

At the event, KIC will launch its revolutionary Thermal Analysis System™ software, featuring the new Overall Equipment Effectiveness (OEE) functionality and the Common Recipe Finder™.

These innovations are designed to provide manufacturers with actionable insights, helping them to not only improve their current production processes but also ensure continuous optimization based on past performance. KIC’s solutions aim to enhance efficiency, quality and sustainability for the electronics manufacturing industry.

One of the highlights of the KIC exhibit will be the Smart Profiler System (SPS). This system allows manufacturers to accelerate product launch cycles through rapid and precise profiling, ensuring high reliability and quality with optimized recipes. The OEE feature helps improve equipment performance, minimize downtime, and optimize production for maximum throughput. In addition, KIC’s solutions promote sustainability by reducing energy consumption and carbon footprints in the manufacturing process.

KIC also will demonstrate Automatic Profiling During Production, a value-added, cost-effective solution that streamlines profiling processes, enhances oven performance tracking, and ensures full traceability with detailed reporting. This system simplifies audit procedures with intuitive reporting tools and integrates seamlessly with Manufacturing Execution Systems (MES), CFX, and Hermes standards for superior process control.

Visit KIC at SMTA Tijuana to experience firsthand how their smart factory ecosystem helps customers achieve faster new product introductions (NPI), higher quality and reliability, increased productivity, reduced energy consumption, and improved OEE. For more information about KIC, visit https://kicthermal.com 

CLIFTON PARK, NY – Electronic Coating Technologies (ECT), specializing in electronics protection through turnkey subcontract services and material solutions, announces the grand opening of its newest facility in Orlando, FL, USA.

The new location, situated closely to the large aerospace market in the Southeast region of the United States, is expected to improve turnaround times and reduce lead times for customers in the area. This expansion supports ECT's focus on addressing customer challenges with an application engineering division dedicated to providing tailored solutions. Companies can leverage ECT's 30+ years of experience protecting critical electronics in-house or onsite at its facility.

The operation offers parylene and conformal coating application services to protect electronic assemblies via automated equipment and materials. ECT will collaborate with customers to select the appropriate products from its suppliers and create solutions that match each unique application.

Mike Charlton, the Global Brand Director at ECT, said, "Orlando represents more than a geographical expansion for us; it's about bringing our technical and customer-centric approach right to our client’s door. We're not just opening a facility; we're opening a gateway to collaboration and shared success."

Located at 6203 Chancellor Dr., Unit #3800, Orlando, FL 32809, the operation joins two existing ECT facilities in Clifton Park, NY, and Mississauga, Ontario, Canada. For service in the Southeast region of the U.S., direct your inquiries to electroniccoating.com/contact-us.

ECT remains committed to maintaining its record of quality standards, on-time delivery, and manufacturability in its operations.

NEUSS, GERMANY – Artificial Intelligence (AI) is renowned for image recognition and classification skills, suggesting a great fit with the objectives of AOI. How is the technology being applied and how is performance improving?

AI in AOI

Equipment suppliers are racing to integrate AI into their solutions. Equally, manufacturers are racing to integrate the technology into their processes. As surface-mount electronics assembly is already highly automated, AI brings the opportunity to extend machine-like speed and repeatability further into complex tasks that require learning, judgement, and adaptability. Automatic optical inspection (AOI) is a prime example.

AI’s skills in image classification, already widely used in applications such as disease diagnosis, automated driving, content moderation, and others, are a great fit with industrial quality control, and AOI in particular. Conventional approaches to AOI are heavily dependent upon the judgement of experts when setting up the system, introducing new products, and subsequently while production is ongoing to inspect images of suspected defect areas.

AI first became available in commercial AOI software to help with setting up and running the equipment. Automatic component library matching, which uses deep learning to identify component types from images and so enable the optimum library to be selected automatically. In addition, AI is used to assist 3D measurement of components to generate data for parts that are not found in any existing library.

Secondary Judgement

While AI has simplified and accelerated library management, the technology is now ready to offer greater value to manufacturers by applying its learning and classification skills to improve inspection accuracy on the production line. Here, relying on human judgement to classify defects as real defects, false positives, or false negatives can be time consuming and introduces variability into the manufacturing process. While some defects are easy to classify, such as missing or extremely poorly aligned components, or severe soldering problems, others are more difficult to see or to identify clearly as being below acceptable standards.

When judgement is left to human experts, individual operators can apply different criteria based on their experience level and opinions. Inspection can be slow as judgements take time. Some defects may be overlooked while, on the other hand, excessively strict assessments can produce false positives that demand unnecessary rework. Introducing AI to assist these secondary judgements offers the opportunity to relieve dependence on experts and eliminate inaccuracies thereby delivering a boost to productivity.

The AOI system shares images of detected defect areas with human operators as well as with the AI Judgement software application that hosts machine-learning models. The human experts assess the nature of the defects and their judgements are fed back to the AI software. By repeatedly adjusting as the experts judgements are logged, the model quickly acquires the experts’ best judgement skills and eliminate human errors. When trained, the model makes judgments allowing the operators to work confidently and more quickly as well as maintaining a consistently high level of accuracy. Thus, the operators can match the performance of skilled inspectors.

AI-assisted secondary judgement can enhance repeatability to prevent defective units escaping from the factory and can quickly identify false positives to prevent non-defective assemblies being sent for unnecessary rework. This stabilises the factory’s quality performance and increases productivity.

Confidence Index

Yamaha’s AI Judgement software for AOI provides comprehensive information for the operator that explains its own Good/NoGood decisions, including images, tables, and a confidence indicator (figure 2). In the case of soldering defects such as bridges or contamination, this index is shown as a graphical heatmap and calculated anomaly index. Judgements of other defects such as character recognition are expressed with a matching ratio. The software also reports its own performance with calculations of the anomaly detection rate and over-detection suppression. Through repeated data gathering and analysis including noise reduction, and with tools to build and optimise custom AI models, the AI Judgement software lets users control the machine-learning lifecycle and ultimately perform quality control without professional assistance.

From Assistance to Automation

Moving forward from AI-assisted secondary judgement by human operators, the next step is for fully autonomous AOI that performs consistently up to the standard of the best human experts in the company. Yamaha’s AI Judgement software is ready to connect seamlessly with the remote repair station and can share AI- judgement results directly with inline AOI systems, to continuously improve inspection accuracy. Leveraging AI to automate secondary judgement lets inline AOI systems operate continuously without intervention, at a high rate, with minimal false negatives or false positives to prevent defects escaping and avoid unnecessary rework.

Conclusion

Artificial intelligence can enhance multiple aspects of AOI, including accelerating library creation and automatically generating missing component data. With its image classification capabilities, AI is ready for deployment in the production line to assist and eventually automate secondary judgement. Historically, this task has demanded the attention of highly trained inspectors. AI now lets operators quickly reach a comparable level of proficiency. The roadmap is headed towards end-to- end automation from assembly to AOI, with learning, to continue improving quality assurance and raising productivity.

PHELPS, NY – Z-AXIS, an experienced provider of electronic design and manufacturing services, recently celebrated its 35th anniversary amid a major expansion at its Rochester-area facility. Employees, family, and friends enjoyed a lunch from Dinosaur BBQ, Molly V’s Homemade Ice Cream, and live music on a beautiful fall day in Western New York on October 1, 2024.

“Z-AXIS is very proud of the achievement we’re celebrating today,” said Michael Allen, company president and co-owner. “We’d like to thank everyone who helped make this possible. With the investments that we’re making, the best is yet to come.”

Founded on October 1, 1989, Z-AXIS started as a manufacturer of cathode ray tube (CRT) displays, a type of video monitor. As the market for CRTs declined and then largely disappeared, the company re-invented itself as an electronic contract manufacturer. Today, Z-AXIS provides printed circuit board assembly (PCBA), box builds, and cable and wire assembly services.

Michael Allen and co-owner Robin Allen purchased Z-AXIS on January 7, 2014. Michael Allen has held engineering and leadership roles at Z-AXIS since the company’s founding and served as Director of Engineering before becoming company president in 2006. He earned a Bachelor of Science from Rochester Institute of Technology (RIT) and is the holder of 26 U.S. patents.

Today, Z-AXIS is growing at approximately 20% a year and in the second phase of a $1.5 million expansion that is increasing capacity with new equipment. From startups to billion-dollar companies, Z-AXIS serves commercial and industrial customers but also has a strong and growing presence in aerospace, which now accounts for 30% of the company’s business.

Bear Power Supplies, a business unit of Z-AXIS, is also enjoying success in the design and manufacturing of power supplies for medical, industrial, and commercial customers. As a drone flew over the anniversary celebration and took pictures of the festivities, the feeling that the sky’s the limit was clear.