EMS manufacturing industry status on automation and artificial intelligence

By Mark Zetter

EMS providers don’t innovate, they build to OEM spec. EMS providers want to position themselves as capable. Different. Providers like Flex (Elementum), Jabil (Control Tower), Sanmina (42Q), Foxconn (Beacon) have no artificial intelligence, instead they market ‘future’ value supported by mention of AI on their websites. They do this to game SEO and search results. (See also: Comparing Jabil v Flex v Sanmina supply chains)

EMS sales and marketing often exceeds EMS capability and, there is a big difference between using AI to enhance automated optical insertion (AOI) testing for visual inspection of printed circuit board (PCB) (or LCD, transistor) manufacturing v using AI that impacts lowering costs directly associated with costly indirect labor (IDL). The former is relatively easy, but with some important cost savings. This article is about the latter, where IDL savings opportunities and the ability to free up large amounts of working capital can be enormous.

EMS industry is filled with habitual, risk averse, glib thinking that does not encourage innovation or seek out a critical sense. EMS executives are too busy empire building and protecting internal turfs.

This is one of the reasons EMS industry technology trails OEM technology by 18 to 24 months. This is no more apparent than in the semiconductor industry.

EMS providers also have tiny tech budgets and, when EMS providers do innovate its because OEMs are dragging their EMS partner out of the dark ages, forcing the EMS provider to invest (and, only after the OEM gives the EMS provider a PO to hedge EMS tech spend liability).

Sanmina’s MES 42Q is a marketing play on corporate life support. “Sanmina should have spun off 42Q as standalone business, forcing its 42Q team to sink or swim,” said one person familiar with the 42Q tech stack. I agree.

Sanmina mainly uses 42Q as a selling point when trying to woo new customers. Sanmina’s technical depth among its senior executive team is limited, like most tech depth in EMS industry, based on my experience over the years obtaining familiarity with EMS industry challenges, technical limits and capabilities, and service offerings.

Further ahead than Sanmina, Jabil has some machine learning capabilities but no AI that is directly attributable to saving clients money. Jabil spent large amounts of money on its supply chain application (software) but it, too, is an internal build, built by folks with limited technology understanding and also supported by corporate life support to be used when marketing to prospects and existing customers to try and close more deals.

Flex is better positioned than both Jabil and Sanmina, and smarter if only because it spun off Elementum. But Flex also has made no real inroads into AI that I can find in speaking with customers, and former employees, of the Elementum platform. I compare supply chains for Flex, Sanmina, Celestica, and Jabil here.

Foxconn is continuing its push toward robotics automation but AI is still on the drawing table. To enhance its mechanical automation ambitions Foxconn is looking at AI for maintenance, test, quality but everything remains in proof-of-concept stages, according to reliable Company sources and, anything Foxconn is likely to release as artificial intelligence in the future will be limited to planning and materials management functions as part of its Beacon platform.

For nearly ten years, IBM continues to push Watson but it seems no one is buying. As for IBM Watson AI in manufacturing supply chains, I engaged their key contact for IBM Watson manufacturing supply chain capabilities with laser-focused questions but got only glib answers and she pointed me, instead, to awards IBM Watson had won. This person has since been replaced. I breakout and detail IBM Watson AI shortcomings, risks, and challenges here.


“[W]e are one of the [EMS provider] companies who have worked with IBM. We had to find our own way because frankly, IBM over sold and overpriced Watson. Most of the folks I’ve worked on the project with at IBM have moved on to China firms like Alibaba and Baidu.”


The IBM Watson article (link above) also covers claimed AI (vs actuality) by Dassault Systemes (Apriso); GE Digital, ABB, Rockwell Automation, SAP, Oracle, Siemens, Plex Systems, Cogiscan, Epicor, Honeywell Process Solutions, Mentor Graphics, Aegis, and Schneider Electric, to name a few.

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Another Asia-based EMS provider with factories across Asia, and also considering AI, engaged IBM Watson. “[W]e are one of the [EMS provider] companies who have worked with IBM. We had to find our own way because frankly, IBM over sold and overpriced Watson. Most of the folks I’ve worked on the project with at IBM have moved on to China firms like Alibaba and Baidu,” said a senior executive for this Asia-based EMS provider who asked not to be identified. Today this Asian EMS provider still does not have a working AI in their factories.

EMS manufacturing coming out of dark ages

None of the companies mentioned above, including vendors like SAP, Oracle, QAD and others have AI that can be directly attributable to saving clients money by applying AI to costly indirect labor workflows.

And every company and vendor mentioned above has an incomplete technology stack that requires third-party licensing agreements, yet still does not constitute real AI.

Until now.

Here is an artificial intelligence 1-year case study inside a European $1B EMS provider, including immediate cost savings. “We reduced our time to generate a quotation for complex PCB assembly programs to three working days from 10, with a +/-2% difference compared to the same quotation released typically by our five-member RFQ team comprised of costly indirect labor”, said an EVP for this EMS provider.

OEM customer program ramp for new program launches, was also reduced to just four days for full-ramp manufacturing production v. 14 days to 21 days the EMS provider needed, previously.

These accomplishments AI is helping global enterprises achieve extends to workflow accuracy, timeliness, and productivity improvements across all other functional departments as well.

The world’s first manufacturing supply chain AI directly attributable to measurable outcomes and saving clients money is already changing manufacturing supply chains. Those who are late to the game with be consumed.

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