Evolving CEM technology

Electronic Manufacturing Solutions’ sales director, Rob Moore, explains how recent manufacturing innovations underpin the introduction of artificial intelligence

When Covid emerged, CEMs started investing in technologies to adapt to a new, more demanding landscape. Roll forward to 2023 and new challenges are emerging. Once again, CEMs are finding manufacturing solutions in innovative ways.

When considering how Covid-19 impacted the electronics manufacturing industry, chip shortages come to mind. However, it’s a slightly different story for CEM technologies.

As global supply chains increased in volatility—with international lockdowns causing disruption to trade routes and labour shortages—electronics manufacturers turned to cloud-based databases for improved visibility over component availability.

Though once deemed too unsafe to handle sensitive manufacturing information, cloud technology offered valuable real-time insights into supplier inventories and streamlining order processing when needed most.

The pandemic also prompted accelerated uptake of automated healthcare technologies. Electronics manufacturers looked for fast, reliable ways to produce wearable medical devices to ensure high-quality patient care while resources were stretched. For example, CEMs used automated quality control procedures to check for product flaws, resulting in fewer recalls, quicker turnaround times and safer products.

Having overcome the pandemic’s challenges, electronics manufacturers are turning their attention to technologies that promise to solve ongoing issues. Many CEMs are let down by outdated equipment—requiring excessive maintenance—and error prone manual processes. These can lead to downtime, product flaws and production stops which harm customer relationships and cost money.

Right now, many CEMs have their sights set on bolstering production lines with artificial intelligence (AI) technology, which promises to increase efficiency and accuracy. For instance, AI can support predictive maintenance procedures which anticipate when a machine is likely to fail before the event occurs, minimising downtime and making mistakes less likely. Companies achieve higher quality, more cost-effective processes and customers benefit from faster turnaround times.

AI can also support manual processes such as quality control checks: one of the most time-consuming aspects of PCB assembly. By detecting flaws that could be missed by eye, AI can help improve how manufacturers spot and address product issues. Also, because AI provides insights in real-time, it can help manufacturers right wrongs at the earliest possible stage, leading to reduced delays and happier customers.

AI algorithms can be used in machine learning—analysing data from production lines to identify areas requiring improvement. If obstacles regularly arise at one particular stage, CEMs can identify what’s causing the issue and rectify it to streamline processes and continuously improve operations.