Taking the Gremlins Out of Your Process

Estimated reading time: 1 minute

Every step in your assembly line—bareboard loading, solder paste printing and inspection, pick and place, reflow, optical inspection, testing, unloading the assembly, and panelization—is supposed to be designed to perform optimally for you to have an efficient, reliable, robust and reproducible process.

However, and as isolated as they may seem, "gremlins" sometimes appear and mess up the results of a batch, keeping operators and line engineers figuring out what seems to be wrong in their process.

In our recent survey, we asked our subscribers about their pain points when it comes to their processes, whether they need further automation for more control, and what they would like to know more about with regard to improving their process engineering.

Among the greatest challenges cited were equipment issues, materials, soldering and rework, changeovers, quality, and last but not least, management.

When it comes to equipment, some of our respondents consider the never-ending introduction of new machines as a challenge—despite these machines being designed to streamline the production. Perhaps one reason for this is the lack of time for thorough testing of a new process or machine prior to releasing to production.

Respondents also said there is a lack of data acquisition systems with appropriate sensors for data logging over periods of time, and a need for systems to analyze big data to help their process innovation.

For soldering and rework, the pain points include ensuring a robust soldering and rework process for assembly, soldering BGA components, and solder printing.

The frequent production switches among different products are also among the biggest challenges. This leads to quality issues such as time-to-market pressures, respondents say, which cause them to hurry and possibly overlook key process parameters. Still on quality, the respondents say there is also a need to identify all critical-to-function parameters without having to resort to very high sample sizes.

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Editor's Note: This article originally appeared in the April 2016 issue of SMT Magazine.