This category contains four articles covering project evaluation, technology roadmaps, delivery scope and acceptance methods.
This article explains how to implement industrial OCR for nameplates, labels, package text, equipment numbers and batch data, covering cameras and lighting, recognition models, data interfaces and MES integration.
This article explains the key considerations for sample collection, lighting design, algorithm evaluation, false-positive and missed-detection control, and acceptance-metric design in machine-vision defect inspection.
This article covers compute selection, model compression, inference services, data interfaces, offline operation and O&M monitoring for edge AI deployment at industrial sites.
This article explains protocol connectivity, data modeling, buffering, alarms and traceability for industrial data-acquisition software connecting PLCs, instruments, sensors and MES.
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