Glossary

IATA-compliant refers to adherence to the guidelines and standards of the International Air Transport Association (IATA) for air cargo transport. It ensures that shipments meet the applicable requirements for transport, labeling, and documentation in international air transport.

IATA publishes binding regulations for the safe and efficient transport of goods, particularly dangerous goods, special cargo, and temperature-sensitive goods. IATA-compliant processes facilitate collaboration between shippers, freight forwarders, airlines, and regulatory authorities and contribute to smooth handling. Automated measurement and identification systems help ensure that the required transport data is provided completely and accurately.

Practical example:

Before an air freight shipment is handed over, its dimensions, weight, and dangerous goods labels are automatically checked to ensure the shipment can be processed in compliance with IATA regulations.

See also: Advanced Freight Data, dangerous goods labels, air freight, shipment tracking, transport regulations, customs clearance, customs declaration, customs system

Identification involves the unique recognition and assignment of goods, objects, shipments, or load carriers within logistics processes. It forms the basis for transparent tracking and the automated control of processes.

In logistics, identification is often carried out using technologies such as barcodes, RFID, OCR, or camera-based systems. The captured information enables the automatic assignment of packages, pallets, or containers and is transmitted to ERP, WMS, and TMS systems. Reliable identification reduces errors, accelerates processes, and creates the necessary data foundation for automated material flows and end-to-end traceability.

Practical example:

As a pallet passes through a measuring station, it is automatically identified via its barcode, and the corresponding dimension and weight data are assigned to the correct order.

See also: Auto-ID, barcode, data capture, OCR (Optical Character Recognition), RFID (Radio-Frequency Identification), SSCC (Serial Shipping Container Code), Track & Trace, traceability

Image processing involves the automatic capture, processing, and analysis of images using digital technologies. It enables the evaluation of visual information and the derivation of characteristics, states, or decisions from it.

In logistics, image processing is used to automatically recognize objects, contours, labels, and quality characteristics. Camera systems, sensors, and artificial intelligence enable, for example, the inspection of load units, the identification of goods, or the detection of deviations. In conjunction with DWS systems and automated processes, image processing supports reliable data capture, improves process reliability, and reduces the need for manual inspections.

Practical example:

A camera system analyzes a pallet during transport and automatically detects excess film, damage, or defective contours.

See also: Computer Vision, DWS, Identification, Artificial Intelligence (AI), Contour Inspection, Object Recognition, Quality Control, Sensor Technology

In-motion measurement refers to the automatic collection of measurement data from packages or loading units while they are in motion. It enables simultaneous measurement, weighing, and identification without interrupting the flow of materials.

In intralogistics, in-motion measurement is primarily used in DWS systems that capture dimensions, weight, and identification data in a single pass. Modern sensor technology and intelligent evaluation methods ensure precise measurement results even at high conveyor speeds. This increases throughput, data quality, and process efficiency while reducing manual intervention to a minimum.

Practical example:

On a parcel conveyor system, shipments are automatically measured, weighed, and identified via barcode while in continuous motion, without the need to halt the conveying process.

See also: 3D sensors, dimensional measurement, DWS, dynamic measurement, conveyor speed, weight measurement, sensor technology, master data capture

An inbound scan is the initial automatic or manual recording of a shipment or loading unit upon receipt of goods. It is used to identify, document, and track incoming goods within logistics processes.

During the inbound scan, depending on the application, barcodes, 2D codes, or RFID transponders are read and linked to additional information such as timestamps, storage locations, or measurement data. In automated logistics centers, the scan is often performed in conjunction with dimension and weight capture within a warehouse management system (WMS). This ensures that all relevant master data is immediately available for further processing and control of material flows.

Practical example:

When unloading a truck, each pallet is automatically scanned, measured, and weighed before being transferred to the warehouse management system for further processing.

See also: Barcode, WMS, Dimension Capture, Weight Capture, Warehouse Management System (WMS), RFID, Master Data Capture, Goods Receipt

Industry 4.0 refers to the intelligent networking of machines, equipment, products, and IT systems within industrial production and logistics processes. It enables the continuous exchange of data and the automated control and optimization of processes.

Industry 4.0 is characterized by technologies such as sensor technology, the Internet of Things (IoT), artificial intelligence, cloud applications, and digital twins. This connectivity creates transparent processes that can be monitored, analyzed, and adapted to changing requirements in real time. In logistics, Industry 4.0 improves, among other things, material flow control, inventory management, and automated master data capture.

Practical example:

In an automated distribution center, conveyor systems, WMS systems, and warehouse management systems continuously exchange data to autonomously control material flows and prevent bottlenecks early on.

See also: Digital Twin, Internet of Things (IoT), Artificial Intelligence (AI), Material Flow, Process Optimization, Sensor Technology, Smart Factory, Master Data Capture

An infrared fan-beam scanner (scanning laser scanner) is an optical measurement system for the noncontact detection of contours, distances, and object positions. It uses a fan-shaped laser beam to reliably detect objects and determine their position or dimensions.

Infrared fan-beam scanners are used in conveyor and warehouse technology as well as in automated measurement systems. They detect objects with high speed and precision and support applications such as dimensional measurement, presence detection, and collision avoidance. Thanks to their robust design and fast data acquisition, they are particularly well-suited for continuous use in demanding industrial and logistics environments.

Practical example:

On a conveyor line, an infrared fan scanner detects the contours of incoming packages and transmits the measurement data to the DWS system so that the shipments can be automatically measured.

See also: 3D sensors, distance sensor, dimensional measurement, DWS, conveyor technology, laser scanner, object detection, sensor technology

An integration interface is a standardized connection for the automatic exchange of data between different software or hardware systems. It enables seamless communication and collaboration between various applications within a digital system landscape.

Integration interfaces transfer information such as master data, measurement values, orders, or status messages between systems—for example, between DWS systems, warehouse management systems, ERP systems, or transportation management systems. Depending on the application, standardized protocols, APIs, or middleware solutions are used. A high-performance integration interface reduces manual data entry, improves data quality, and ensures end-to-end, automated business processes.

Practical example:

After a shipment is automatically measured, the integration interface transfers all measurement and identification data in real time to the warehouse management system and the ERP system.

See also: API, data exchange, DWS, ERP system, warehouse management system (WMS), master data entry, transport management system (TMS)

Intermodal transport involves the movement of goods using several different modes of transportation within a single transport chain, with the loading unit—such as a container, swap body, or trailer—remaining unchanged. This allows different modes of transport to be combined without having to transship the goods themselves.

In intermodal transport, for example, road, rail, sea, and air transport are combined. Digital transport management systems, standardized load carriers, and transparent freight data support the planning and control of these complex transport chains. An efficient combination of different modes of transport enables flexible logistics planning and can contribute to better utilization of existing transport capacities.

Practical example:

A container is transported by truck from the manufacturer to a terminal, then forwarded by rail, and finally delivered by truck to the recipient at the destination.

See also: Container, Supply Chain, Supply Chain Management (SCM), Supply Chain Visibility, Transportation Management System (TMS), Transportation Optimization, Transportation Routes, Flow of Goods

Intralogistics encompasses the organization, control, and optimization of all material, goods, and information flows within a company or facility. It ensures that goods are made available at the right place and at the right time and that internal logistics processes run efficiently.

Intralogistics includes, among other things, goods receipt, warehousing, order picking, production, conveyor technology, and goods shipment. Modern intralogistics utilizes automated conveyor systems, warehouse management systems, autonomous transport systems, as well as sensor technology and AI to accelerate processes and increase transparency. Reliable master data capture forms the foundation for a cost-effective and error-free material flow.

Practical example:

In a manufacturing facility, conveyor systems and autonomous vehicles automatically transport materials between the receiving area, the warehouse, and production, while all movements are digitally documented and controlled.

See also: Degree of automation, conveyor technology, warehouse management system (WMS), material flow, process optimization, smart factory, goods flow

The Internet of Things (IoT) refers to the interconnection of physical devices, machines, and sensors via digital communication networks. It enables the automatic exchange of data as well as the real-time monitoring and control of processes.

In an industrial setting, IoT technologies connect sensors, measurement systems, and software platforms to form a seamless digital infrastructure. The collected data is continuously analyzed and used for process control, maintenance, or optimization. In logistics, the IoT supports, among other things, automatic master data capture, the monitoring of material flows, and the transparent tracking of goods movements.

Practical example:

In a distribution center, networked WMS systems, conveyor systems, and sensors continuously send their operational and measurement data to a central platform that monitors and controls material flows in real time.

See also: Digital Twin, Industry 4.0, Intralogistics, Artificial Intelligence (AI), Material Flow, Sensor Technology, Smart Factory, Master Data Capture

Irregs is the abbreviation commonly used in logistics for Irregular Shipments and refers to shipments with irregular shapes, sizes, or characteristics. They cannot be transported—or can only be transported to a limited extent—via standardized conveyor and sorting systems.

Examples of Irregs include bulky goods, rolled goods, tires, furniture, long packages, or shipments with protruding edges. Due to their dimensions or shape, they often require special handling, manual processing, or specialized conveyor technology. The automatic detection of Irregs using 3D sensors and AI-powered image processing enables early process control and prevents disruptions in the material flow.

Practical example:

At a package sorting center, an AI-powered inspection system identifies a bulky shipment as an irregular item and automatically diverts it to a separate conveyor line for special goods.

See also: 3D sensors, deep learning, free-form recognition, artificial intelligence (AI), material flow, object recognition, package sorting, bulky goods