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Using Statistical Process Control (SPC) to Eliminate Waste and Drive Your Continuous Improvement Process (CIP)

Using Statistical Process Control (SPC) to Eliminate Waste and Drive Your Continuous Improvement Process (CIP)

By Greg Benoit, Director of Product Marketing, Cogiscan


Photo Greg Benoit

Greg Benoit

Statistical Process Control (SPC) is a critical tool that manufacturers in a wide variety of verticals – from pharmaceuticals to oil and gas to printed circuit board assembly (PCBA) – have used for years to better ensure their products are of the highest quality and match the intended design specifications.

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 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.


Real-Time Quality Verification

Full connectivity and integration with PCBA inspection and test equipment enables the automatic collection and aggregation of measurement data in near-real time. The power to quickly compare each measured value against its tolerance limits – either min & max, or nominal & tolerance values – as defined in the product’s test recipe enables your test team to verify real-time quality during production. With the ability to visualize results using flexible pre-built analytics tools, including control charts, histograms, and scatterplots, electronics manufacturers can quickly gauge whether the process is meeting expectations by calculating process capability indices (Cp & Cpk).


iTAC’s Quality Management (QM) moduleincludes various queries to fully slice and dice data in a myriad of ways, including by product, machine, individual measurements, as well as failure types, to isolate problems down to the proper scopeElectronics manufacturers can also drill down further from any of these analytics directly into the traceability data from iTAC’s Traceability (TR) moduleto see the full details of the product’s build process for enhanced failure analysis, and to even help with quarantining and isolating quality issues.

The following figure illustrates an example use case: how a PCBA manufacturer can first generate a product pareto to identify the most problematic products, then leverage the analytics tools within QM to pinpoint the precise problem, and finally drive corrective action.




For more complex statistical analysis of quality data,iTAC’s MOM Suite is based on an open data architecture that allows for use with 3rd-party stats packages, such as Qs-stat, CAQ.Net, and MinitabData is accessible through various interface types depending on your specific needs, such as via a Data Warehouse, Rest API, or Excel or AQDEF export. This enables your quality team to take the data and use it in other quality applications, such as Failure Mode and Effects Analysis (FMEA). With this flexibility, iTAC’s SPC solutions can act as a key pillar of your overall Computer-aided Quality assurance (CAQ) program.

Flexible Options Based on Your Electronics Manufacturing Landscape

Already have an MES or MOM you’re happy with? No problem, we still have options for you. With iTAC’s modular Business Intelligence (BI) solution, you can still get access to the control charts and other SPC visualizations you need without the full MOM suite.

In this option, measurement data is collected via Cogiscan’s Co-NECT & Data Management solutions and is fed directly into the BI module for robust visualization and alarms. This enables SPC visualization and functionality without requiring you to replace or duplicate your existing MES or MOM platform. And with BI’s self-service design tools, you will also gain the added flexibility of fully customizing your own visualizations and analytics according to your specific needs and preferences.



Next-level Quality Analytics: From Descriptive to Prescriptive

While SPC is a powerful way to gain greater control of your PCBA production quality, it’s now possible to take things to the next level, with advanced analytics that go beyond descriptive and reactive methodologies. iTAC’s AI-powered IIoT.Edge platform provides all the technologies and intelligence you need to enable both predictive and prescriptive analytics.

Powerful algorithms perform streaming analytics on live data from a myriad of sources, including machine-provided defect and measurement data, as well as sensor data, to predict when quality issues will happen and then prescribes corrective actions to stop the problems from occurring to prevent defects in your products.

Robust machine learning models can also crunch massive volumes of quality data to identify patterns and determine root causes that may otherwise remain hidden from the naked eye. And as with the BI module, the IIoT.Edge can be deployed in modular fashion – with or without the iTAC Mom suite, or iTAC’s BI solution – for a truly composable architecture.

The Power of Proactivity in Electronics Manufacturing

As you can see, together Cogiscan & iTAC offer a range of solutions for realizing SPC and proactive management of your process quality depending on your specific needs and environment. These technologies all utilize the power of rich, live machine data to allow you to react quickly to quality issues to minimize their impact – or even prevent them from occurring at all. This allows you to reduce or eliminate waste, and drive your continuous improvement process (CIP), all of which serves to save you precious time and resources.

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