Cogiscan adds distribution partner MacTech for representation in Argentina

Looking specifically at electronics manufacturing, with the emergence of Industry 4.0 and the connected factory, we now have access to troves of meaningful production data to elevate the Statistical Process Control (SPC) process. Paired with advanced analytics tools, real-time machine data, and AI-based software, these technologies enable you to react quickly to, and even eliminate, quality issues on your production floor.

In this interview from Mitch DeCaire (Cogiscan) and Martin Strempel (iTAC Software), you'll learn about what makes a successful AI project in electronics manufacturing. In summary, it's not just about the tool itself. It has more to do with the intent you had when you built the tool and the industry expertise you have to make it actionable. We're going from reactive to prescriptive analytics with this model.

Cycle time optimization is essential for manufacturers looking to improve their efficiency and reduce costs – and is commonly one of the top concerns electronics manufacturers want to tackle when exploring our products. In this blog post, we will discuss some of the ways in which cycle time can be optimized in PCBA manufacturing. We’ll look at everything from traditional methods of standardizing processes and systems to newer options with Artificial Intelligence and machine-learning systems.

Eric Miscoll from EMSNow speaks with Julie Cliche-Dubois about the challenges of factory-wide data collection in the electronics manufacturing industry. Never as simple as it seems, data collection and processing has only increased in complexity due to recent digitalization technologies and trends. Cogiscan remains at the forefront of solving these nuances by working with both the machine suppliers and customers to collect the richest data possible. Looking at the hot topic of machine-learning analyses, Julie and Eric also discuss how important it is to ensure that the vast quantity of data generated by the machines is readable for the AI tool.