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Artificial intelligence exceeding EMS manufacturing industry expectations

A.I. helped $1 billion, top 50 EMS provider reduce OEM new program launch to 4 days for full-ramp manufacturing production v. 14-21 days previously.

Contract electronics manufacturing is traditionally labor-intensive requiring both direct, and more costly indirect labor (IDL), with costs for the latter hidden among EMS S,G&A.

Whenever contract EMS providers (or electronics original design manufacturers – ODM) respond to request-for-proposals (RFP) from OEM prospects, the EMS provider’s quotation process is resource-intensive and typically over-reliant on outside vendors for cost (v. OEM pricing) information. Add to this, EMS provider quote packages are subject to volatile market conditions and poor forecasting and planning from both EMS/ODM firms, and OEMs.

Neural Corporation has developed a sophisticated M.A.S. (multi-agent system) using its proprietary artificial intelligence platform which accesses every known data source (internal/external) to form a data lake. The resulting A.I. results are promising.

As part of Neural’s one-year study with one of the top 50 EMS manufacturing providers, Neural analyzed 200 quotations on both materials and labor/value-add. Neural then integrated market trend analyses into the algorithm.

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The outcome: “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 with revenues over $1 billion who participated in the Neural study.

“The power of what we learned more than three years ago is just now entering into business processes and streams at clients. The technicality of our solutions are immense much like the savings. We often have to draft more simple versions so everyone can really appreciate the results”, says Mark Swartz, Neural CEO.

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Neural’s algorithm is also able to scan and identify errors in documentation. Easily integrated into the EMS client’s system, Neural’s surrogate was self-taught, and continued to learn, how to recognize different filetype formats and restructure them into a format for the EMS client’s internal system.

Neural also reduced the average time to just four days for this EMS provider to set up an OEM customer program, from new product launch to full-ramp manufacturing production, compared to the 14 to 21 days range this provider typically needed to go from new program launch-to-volume manufacturing production.

Moreover, the Neural surrogate reduced the labor content from a team of four, full-time EMS IDL employees to a single employee supervising the Neural algorithm, all while optimizing the EMS provider’s workflows for accuracy, timeliness, and productivity and execution during the study.




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