Glossary

Quality assurance encompasses all planned and systematic measures designed to ensure that products, processes, and services meet defined requirements. Its purpose is to detect and prevent errors early on and to ensure consistently high quality.

In logistics and automation, quality assurance includes, among other things, inspections of goods, measurement systems, and process flows. Sensors, camera systems, DWS systems, and AI-supported methods enable automatic inspection of dimensions, contours, markings, or the condition of objects. Documented inspection processes and valid data support process reliability, traceability, and continuous improvement.

Practical example:
An automated inspection system checks pallets for correct dimensions, protrusions, and damage before storage, thereby preventing disruptions in the subsequent material flow.

See also: DWS, contour inspection, AI-supported object recognition, process reliability, sensor technology, traceability, validation, certification

Quality control encompasses all tests and measures for monitoring products, processes, and results with the goal of ensuring that defined quality requirements are met. It serves to detect deviations early on and prevent errors.

In logistics and automation, quality control is increasingly carried out by digital systems such as cameras, sensors, DWS systems, and AI-supported image processing. For example, dimensions, contours, markings, packaging conditions, and loading units are automatically inspected. The data obtained enables an objective evaluation, supports process reliability, and improves transparency throughout the entire supply chain.

Practical example:
An AI-powered inspection system checks a pallet before shipment for correct contours, the presence of labels, and possible damage.

See also: Computer Vision, DWS, Detection Accuracy, Camera Sensors, Contour Inspection, Process Reliability, Sensor Technology, Validation

Quality management encompasses all organizational measures, methods, and processes for planning, controlling, and continuously improving quality within a company. It creates structures to reliably meet requirements and ensure consistently high process and product quality.

In logistics and industry, quality management involves defining standards, monitoring workflows, and analyzing and improving processes. Systems such as standards-based quality management, digital inspection solutions, and automated data collection help identify deviations early on and determine appropriate corrective actions. A consistent focus on quality increases process reliability, improves customer satisfaction, and creates transparent workflows.

Practical example:
A company uses documented inspection processes and automated measurement systems to ensure that recorded dimensions and weight data consistently meet defined quality requirements.

See also: Audit, DIN EN ISO 9001, Documentation, Process reliability, Quality control, Quality assurance, Validation, Certification