IIoT Quality Sampling Control for Diverse Part Inspection

The patent applies local quality by implementing differentiated sampling standards tailored to specific parts and components based on their individual quality requirements. The system dynamically adjusts sampling parameters (such as sampling frequency, sample size, and inspection criteria) according to the specific characteristics of each component type, rather than applying a uniform inspection standard across all parts. This resolves the contradiction by enabling high inspection accuracy for critical components while reducing inspection intensity for less critical parts, thereby maintaining overall system effectiveness without requiring excessive complexity.

The patent implements dynamics by making the sampling standards adaptive and changeable based on real-time production conditions, quality data, and component characteristics. The system can dynamically adjust sampling parameters during production runs, transitioning between different inspection intensities based on process stability, historical quality performance, and risk assessments. This dynamic approach allows the system to maintain high accuracy when needed while reducing complexity and inspection burden when conditions permit, effectively resolving the static contradiction between precision and complexity.

The patent applies segmentation by dividing the quality inspection process into distinct modules or segments, each dedicated to specific types of parts or components. The system segments inspection tasks based on component categories, criticality levels, and quality requirements, allowing specialized inspection procedures to be applied to each segment. This segmentation enables efficient targeted inspection of diverse parts while managing detection difficulty by handling each segment with appropriate, optimized measurement methods rather than attempting to detect all parameters for all parts uniformly.

The patent introduces an intermediary layer (such as a quality management system or inspection coordination platform) that mediates between the diverse quality requirements of different parts and the actual detection processes. This intermediary manages the complexity of quality parameter detection by standardizing data collection, coordinating inspection resources, and integrating results from multiple inspection activities. It enables efficient targeted inspection by acting as a bridge that simplifies the interface between diverse inspection needs and the underlying detection capabilities, reducing the overall difficulty of quality parameter detection across the entire product portfolio.