Dumb data won’t die. And the blame rests squarely on users who resist upgrading to formats that are designed with today’s boards and manufacturing methods in mind.
That’s the message from the PCEA Portland (OR) Chapter at its meeting in late October. The sentiment was shared across a spectrum of users, from designers to fabricators to assemblers, including the host, Axiom Electronics.
We know the issues: Too often, fabricators and assemblers receive conflicting duplicate and erroneous design data files. More often than not the culprit is Gerber-based data packages, which almost always require modification prior to fabrication or assembly.
So while persistent errors from design to manufacturing are often due to manual entry miscues or otherwise obvious omissions such as a missing solder mask layer or discrepancies within the netlist, the industry by and large continues to put up with the pain instead of migrating to a new format.
CAD as we know it for printed circuit design came into existence in the mid-1960s. And while some industry designers still remember the days (more fondly than I would!) of hand-taping components and traces, then using a camera to produce films for fabrication, it didn’t take too long before computers started taking over.
In 1970, Racal-Redac, which later was acquired by Zuken, released its original PCB, schematic and silicon layout tool. A few years later, Scientific Calculations introduced SCICARDS for generating photoplots from Gerber files. Of course, the dimensions back then were epic in size – pads were 70 mils or more, and lines and spaces were 25 mils.
By 1976, the EDA market was starting to pop with companies, and not just for design. Makoto Kaneko founded Zuken. A trio of professors at the University of Texas – James Truchard, Bill Nowlin and Jeff Kodosky – launched National Instruments. A former Tektronix engineering manager, Doug Campbell, started Polar Instruments.
Ultra-high-density interconnects are more smoke than fire right now, but they won’t be that way for long. Driven by high-density BGAs and RF products, UHDI is finding its way into the mainstream.
Given the number of conferences, webinars and the like, readers would be forgiven if they thought UHDI was already standard, however.
First, of course, means agreeing on what, exactly, UHDI is. The working definition of UHDI is product with line widths and spaces of fewer than 50 microns, dielectric thickness of less than 50 microns, and a microvia diameter of less than 75 microns. That’s not a standard definition – yet – and the lower lever parameters have yet to be defined. At some point, there stands to be overlap with semiconductor technology. Stay tuned as the definition evolves.
I am reminded – to a degree – of the chaos surrounding UHDI’s (slightly) larger cousin, high-density interconnects, which hit widespread production in the late 1990s (although the original concept dates much earlier). Then, the issues could be boiled down to two:
Speaking, as we were last month, about artificial intelligence and its adoption into electronics design and manufacturing, we observed that a current obstacle to implementation is the use by vendors of customer data in order to build their models.
And while vendors insist the data are aggregated and anonymized, said customers, naturally, have been generally circumspect over the perceived cost of the lessons they have learned – often painstakingly – being used to enable competitors, not to mention ultimately paying those same vendors for the courtesy.
To that I will add the musings of Neil Thompson, who is the director of the future tech research project at MIT’s Computer Science and Artificial Intelligence Laboratory.
Thompson argues that AI systems must not just be capable of performing “human” tasks but also must overcome the costs of implementation, including redesigning processes and methodologies. “There are a lot of places where ... humans are a more cost-efficient way,” he says.
Over the past couple years, via our PCB Chat podcast and webinars, our editors have spoken with a growing number of AI experts across the spectrum of the electronics supply chain. They include: