Jerome Rousval

Has its time finally come?

I’m honored to be the guest columnist this month and discuss a topic I am passionate about: intelligent technology and the smart factory. Moving toward a more automated process approach with smart, intuitive and integrated systems is an absolute requirement for factories of the future. This is a subject that covers a wide spectrum, of course, but for this discussion we will center on these capabilities from a printing perspective.

For years, the electronics industry has discussed the possibility of a printing utopia: a print process in which all inputs, parameters, inspection and verification are predictive, controlled, self-adjusted, corrected and implemented – automatically. And, while standard solder paste inspection (SPI) systems have moved us toward better verification, SPI alone doesn’t solve many print process issues. What’s missing from SPI measurements is analysis, and today the analytical piece is the responsibility of the manufacturer. Some do it; some don’t.

The other aspect of the printing puzzle that’s been lacking is the ability to efficiently determine printing process parameters for a new product. This NPI dilemma has only escalated as miniaturization has taken hold and process complexity has increased. With these factors now reality at many manufacturing sites worldwide, the old approach that relied on an engineer’s tacit knowledge and procedural trial and error is unsustainable. Time-to-market demands and production cycle constraints require reliable information about process materials and parameters at the outset.

Addressing the challenges around the efficiency of modern printing processes, new self-learning technology with a design for manufacture DfM/NPI component, as well as an SPI system and process knowledge database, has been developed. The first part of the integrated solution helps alleviate problems surrounding current NPI methodologies. Instead of starting from scratch with each new product, the system analyzes the PCB layout from the stencil Gerber data, draws on a continuously enhanced knowledge database of historical data, and makes recommendations regarding the ideal process parameters for the given PCB. These include stencil type, coatings, paste type, squeegee pressure and speed, cleaning frequency, transfer speed, tooling and clamping systems. If the assembly specialist decides to use a different input from those recommended – a different solder paste, for example – the software will display the potential impact of these alterations.

In addition to process parameter recommendations, the DfM/NPI component also checks the stencil for critical areas it has assessed that either cannot be printed reliably or printed at all. Clicking on these highlights reveals an explanation as to whether the stencil layout is suitable for production or where corrections are warranted. With conventional trial-and-error approaches taking days or months to fine-tune, this new solution saves countless man-hours and costs.

The advanced DfM functionality is only one piece of the technology; the other elements relate to the issue raised previously about SPI. While today’s SPI equipment is very capable of collecting and producing massive amounts of data, that information is only as good as its analysis and implementation. Capturing the data, harnessing it, evaluating it and acting on it are the other critical and powerful components of this new print process technology. Utilizing an accurate and integrated SPI measurement system that draws on 2D and 3D technology, the process control software – which is an ever-expanding engineering knowledgebase that corrects current jobs and informs future production runs – monitors the print quality, along with the SPI measurement and analytical data. However, unlike standard process control systems that rely on preset, user-defined thresholds which count the number of defects before implementing change, this technology leverages historical data, statistical characterization of the printing process and current measurement values in real time to make proactive process adjustments. Recommended corrections can be approved manually by the operator or implemented automatically.

“Isn’t that the same as today’s closed-loop systems?” you ask. Actually, no. The recently developed technology takes into account not only post-print measurement data from the SPI, but also performs a thorough analysis of the stencil layout, selecting critical apertures to drive the process. So, unlike a traditional closed-loop system that is typically based on average measurements of the four corners and the center of the PCB regardless of the board design (aperture size, shape, distance, etc.) and is post-print corrective of already out-of-spec offsets, the new solution offers comprehensive, preemptive and informed adjustments. Further, it provides more advanced, defect-free, continuous optimization of the stencil’s cleaning frequency, in addition to supporting print quality optimization campaigns by running automated experiments to improve advanced printer parameters. The system is constantly learning and drawing on an ever-expanding knowledge database. So, it does more than simply control processes; it reliably optimizes them automatically and intervenes to maintain process stability, improve yields and dramatically reduce time and cost.

This is, indeed, a very exciting development for the printing process and one that, in many manufacturing scenarios, is now a necessity. The self-learning system is adaptive and preventative and, in the very near future, may extend its effectiveness to other processes on the assembly line. Stay tuned.

Jérôme Rousval is a process applications manager at ASM Assembly Systems, Printing Solutions Division (;

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