Architecting for agility: Incorporating IIoT into your data collection
These slides were presented at SEMICON West, 2018.
Equipment manufacturers are under pressure to reduce costs while maintaining or increasing quality and contributing to overall customer throughput. Increasingly, innovative end users are looking for big data solutions that will help them introduce extra efficiencies in their factories. While modern machine learning and artificial intelligence algorithms hold the promise of near-magical problem solving and fault detection capabilities, they have one major weakness: a voracious appetite for high volumes of data. These trends are increasing the demands on tool makers to provide even faster data collection and sensor data for variables that were not included in their original tool specifications. Meeting these demands from end customers requires the OEM to adopt an agile approach, where additional sensors and data collection plans can be deployed rapidly and customized on existing equipment platforms. The Industrial Internet of Things (IIoT) promises a solution to the hardware side of the problem (through the availability of cost-effective sensors, etc.) and capturing the data at the source, but this leaves unanswered questions around the best ways to share that data. The industry needs to consider equipment performance, security, stability, and long-term maintainability of the solution. Smart Manufacturing and data collection expert, Doug Suerich, discusses practical ways to meet these challenges without massive investment or diversion from existing SEMI Standards.
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