Glossary

Advanced Freight Data (AFD) is comprehensive, electronically provided information about a shipment that is captured and processed prior to transport. It is used for planning, managing, and documenting logistics processes, as well as for complying with legal and customs requirements.

Advanced Freight Data includes, among other things, dimensions, weight, identifying characteristics, descriptions of goods, and shipper and recipient data. Modern DWS systems and master data capture solutions automatically collect this information and make it available in real time to warehouse management, transportation management, or customs systems. This accelerates processes, improves data quality, and reduces manual data entry.

Practical example:

Before a shipment is loaded, the Advanced Freight Data is automatically captured and transmitted to the transport management system and customs clearance.

See also: WMS, freight billing, freight data, freight measurement, master data capture, transport management system (TMS), volumetric weight, customs clearance

AI-powered object recognition refers to the automatic identification and classification of objects using artificial intelligence. It enables the reliable detection of packages, pallets, labels, or other objects based on image and sensor data.

AI-based object recognition utilizes camera sensors, 3D sensors, and deep learning models that reliably detect even complex shapes, damage, or markings. Among other things, the technology supports quality control, automatic master data capture, and process control in intralogistics. Thanks to its high recognition accuracy, manual checks can be reduced and processes made more efficient.

Practical example:

In a package sorting center, an AI system automatically detects damaged shipping boxes, hazardous materials labels, and protruding loads, and directs affected shipments specifically for further inspection.

See also: 3D sensors, deep learning, hazardous materials labels, camera sensors, artificial intelligence (AI), object recognition, quality control, sensor technology

Air freight refers to the transport of goods and cargo by cargo aircraft or in the cargo hold of passenger aircraft. It enables particularly fast international transport and is used primarily for time-sensitive, high-value, or delicate shipments.

Air freight is subject to strict international regulations regarding safety, weight, dimensions, and documentation. Automated measurement and weight-recording systems help ensure compliance with these requirements and provide precise cargo data for planning, billing, and loading. Due to high transportation costs, the optimal use of available cargo space plays a crucial role.

Practical example:

Before loading, aircraft spare parts are automatically measured and weighed to ensure they meet the airline’s specifications and can be safely loaded onto an air freight pallet.

See also: Freight data, freight measurement, weight recording, IATA-compliant, contour check, load securing, Load Calculator, ULD (Unit Load Device)

An alibi system is a data storage system designed for audit-proof archiving of measurement and process data. It serves as verifiable proof that measurements and data recordings were properly performed at a specific point in time.

An alibi storage system automatically stores, among other things, measured values, images, identification data, and timestamps. The archived information enables complete documentation, supports quality assurance, and facilitates the resolution of complaints or billing-related issues. The alibi storage system is often an integral part of modern DWS systems.

Practical example:

In the goods receiving area, the measurement data and images of a pallet are automatically archived in the audit trail to provide clear evidence in the event of a later complaint.

See also: Data security, dimensional data capture, DWS, freight data, quality assurance, master data capture, traceability, timestamps

An Autonomous Mobile Robot (AMR) is an autonomous transport vehicle that independently perceives its surroundings and navigates without fixed routes. It performs transport tasks within production, warehouse, and logistics areas and dynamically adapts its route to the current environment.

AMRs use sensors, cameras, laser scanners, and intelligent navigation systems to detect obstacles and safely navigate around them. They communicate with warehouse management, material flow, and control systems, enabling flexible transport processes in dynamic environments. Through their autonomous navigation, they increase efficiency, scalability, and process reliability in intralogistics.

Practical example:

In the goods receiving area, an AMR autonomously transports pallets to the designated storage area and receives its transport orders directly from the warehouse management system.

See also: AGV (Automated Guided Vehicle), automation, material handling, high-bay warehouse, intralogistics, material flow, transport technology, Warehouse Management System (WMS)

Analytical methods are systematic approaches for evaluating data, measurement values, or process information. They are used to identify correlations, detect deviations, and support informed decision-making.

In logistics, analytical methods are used to evaluate master data, material flows, and process data. Modern systems utilize statistical methods, artificial intelligence (AI), or machine learning to recognize patterns, monitor processes, and uncover opportunities for optimization. This enables sustainable improvements in data quality, process reliability, and the efficiency of logistics operations.

Practical example:

At a package sorting center, an AI-powered system analyzes the recorded measurement data, detects erroneous data records, and supports the optimization of material flow.

See also: Data Analysis, Deep Learning, DWS, Artificial Intelligence (AI), Machine Learning, Material Flow, Process Optimization, Master Data Capture

APACHE is AKL-tec GmbH’s product family of intelligent dimension measurement and inspection systems. It is designed for the automatic measurement, analysis, and quality control of packages, pallets, and other loading units in logistics processes.

Depending on the model, APACHE combines technologies such as 3D sensors, camera systems, and artificial intelligence (AI) to reliably capture dimensions, contours, identification features, and quality characteristics. The systems can be integrated into warehousing, conveyor, and production processes and provide the collected data in real time to higher-level IT systems. The product family includes, among other things, solutions for static and dynamic cargo measurement as well as automatic pallet inspection.

Practical example:

In the goods receiving area, an APACHE system automatically captures the dimensions and quality characteristics of a pallet and transmits the data to the warehouse management system.

See also: 3D sensors, automatic pallet inspection, dimensional measurement, DWS, cargo measurement, artificial intelligence (AI), master data capture, system integration

API stands for Application Programming Interface and refers to a defined interface through which software applications and systems can communicate with one another and exchange data. It enables the structured connection of different applications without requiring direct modification of the underlying systems.

In logistics, APIs are used, for example, to connect ERP, WMS, TMS, and automation systems. APIs enable the automated transfer of order data, measurement values, status information, or identification data. They are a key component of digital process chains, support system integration, reduce manual data entry, and enable end-to-end processing of information in networked logistics solutions.

Practical example:

A WMS automatically transmits the recorded dimensions, weight, and identification data of a shipment to the transport management system via an API.

See also: Data exchange, data integrity, data interface, digitization, ERP system, system integration, transport management system (TMS), warehouse management system (WMS)

Artificial intelligence encompasses methods and technologies that enable computer systems to perform tasks that typically require human abilities such as recognition, learning, analysis, and decision-making. It enables the processing of large amounts of data and the identification of patterns or recommendations for action.

In logistics, artificial intelligence is used to automate processes, make predictions, and support complex decision-making. Applications include, for example, image processing, object recognition, quality control, demand planning, and process optimization. In combination with sensor technology, WMS systems, and machine learning methods, logistics processes can be controlled more intelligently and continuously improved.

Practical example:

An AI-powered camera system automatically detects damage, protrusions, or missing markings on pallets, thereby supporting quality inspection in the logistics process.

See also: Computer Vision, Deep Learning, Data Analysis, Machine Learning, Object Recognition, Predictive Analytics, Predictive Vision for Logistics, Process Optimization

Artificial Intelligence in Logistics refers to the use of artificial intelligence (AI) to automate, analyze, and optimize logistics processes. The goal is to intelligently evaluate data, support decision-making, and make processes more efficient and reliable.

In logistics, artificial intelligence is used, among other things, for automatic dimension detection, image processing, route planning, and quality control. Algorithms analyze large amounts of data in real time, identify patterns, and derive recommendations for action or automated decisions from them. This improves process reliability, data quality, and efficiency throughout the entire supply chain.

Practical example:

At a parcel sorting center, an AI-powered system automatically detects damaged packages and supports sorting and quality control.

See also: Computer Vision, Deep Learning, DWS, Artificial Intelligence (AI), Machine Learning, Material Flow, Process Optimization, Master Data Capture

An audit involves a systematic examination and evaluation of processes, systems, or organizational units based on established requirements and criteria. Its purpose is to verify compliance with specifications, identify opportunities for improvement, and provide transparency regarding existing processes.

In companies, audits are conducted, for example, to evaluate quality management systems, IT security, supply chains, or technical processes. During these audits, documentation, procedures, and results are analyzed and compared against defined standards or requirements. In logistics, audits help ensure process quality, data security, and reliable operational workflows.

Practical example:

During an audit of an automated logistics system, process flows, maintenance records, and measurement data are reviewed to ensure compliance with defined quality requirements.

See also: Cybersecurity, DIN EN ISO 9001, IT security, process safety, quality control, quality assurance, validation, certification

Authentication refers to the verification of the identity of a user, device, or system within a digital environment. It ensures that only authorized individuals or components can access specific data, functions, or applications.

In logistics, authentication is used to secure access to IT systems, automation equipment, and digital platforms. Methods such as passwords, access cards, certificates, or biometric features enable controlled use of ERP, WMS, TMS, and control systems. Authentication also plays a key role in networked measurement and automation solutions to ensure data integrity and process security.

Practical example:

A service technician logs into a DWS system via a secure authentication process before retrieving maintenance data or changing system settings.

See also: Cybersecurity, data integrity, digitalization, ERP system, IT security, password management, process reliability, access control

Auto-ID stands for automatic identification and encompasses technologies for the unique identification and capture of objects, goods, or information without manual input. It enables the rapid assignment of data within digital processes.

Auto-ID technologies include, for example, barcodes, RFID, and OCR methods. In logistics, they are used to automatically identify packages, pallets, containers, or shipments and to transmit process data to higher-level systems. Auto-ID forms an important foundation for automated material flows, transparent supply chains, and reliable traceability of goods.

Practical example:

Upon receipt of goods, a pallet is automatically identified via a barcode, and the associated information is recorded directly in the warehouse management system.

See also: Barcode, Data Capture, Identification, OCR (Optical Character Recognition), RFID (Radio-Frequency Identification), Scanner, SSCC (Serial Shipping Container Code), Track & Trace

An Automatic Dimensioning System (ADS) is a measurement system designed to automatically capture the dimensions of packages, pallets, or other loading units. It provides precise and reproducible measurement data that serves as the basis for logistics, operational, and billing-related processes.

Depending on the application, an ADS uses 3D sensors, laser scanners, or cameras to measure length, width, and height without physical contact. The measurement data is transmitted in real time to warehouse management, transportation management, or ERP systems, supporting automated material flows and ensuring high data quality. Many ADS solutions are part of a DWS system and combine dimensional measurement with identification and weight measurement.

Practical example:

In the goods receiving area, an Automatic Dimension Measurement System captures the dimensions of a pallet and transmits the measurement data directly to the warehouse management system.

See also: 3D sensors, dimension measurement, DWS, cargo measurement, weight measurement, master data capture, volumetric weight, goods receiving

Automatic measurement is the non-contact capture of the dimensions of packages, pallets, or other loading units using technical measurement systems. It provides precise and reproducible measurement data as the basis for logistics, operational, and billing-related processes.

Depending on the application, 3D sensors, laser scanners, or cameras are used for automatic measurement. The captured data is processed in real time and transmitted to warehouse management, transport management, or ERP systems. This enables the automation of material flows, the standardization of master data, and a significant reduction in manual measurement processes.

Practical example:

In the goods receiving area, a DWS system automatically measures each pallet and transmits the captured dimensions directly to the warehouse management system.

See also: 3D sensors, dimensional measurement, DWS, freight measurement, weight measurement, in-motion measurement, master data capture, volumetric weight

Automatic pallet inspection is a process for non-contact inspection of pallets to assess their condition, quality, and dimensional accuracy. It is used to reliably detect damage, wear, or deviations based on defined inspection criteria.

Modern systems use 3D sensors, camera technology, and artificial intelligence (AI) to analyze pallets comprehensively and reproducibly. Damaged or non-compliant pallets are automatically detected and can be immediately removed from the material flow. This improves process reliability, product quality, and the availability of suitable load carriers.

Practical example:

In the goods receiving area, an automated inspection system checks every Euro pallet for damage and automatically sorts out defective pallets before they are stored.

See also: 3D sensors, APACHE, dimensional measurement, EPAL, Artificial Intelligence (AI), material flow, quality control, master data capture

Automation refers to the use of technical systems, software, and control solutions to carry out processes autonomously with minimal manual intervention. It enables greater efficiency, process reliability, and consistent quality.

In logistics, automation encompasses, for example, the automatic identification, measurement, weight recording, sorting, and control of goods flows. Sensors, robotics, conveyor technology, and intelligent software solutions handle repetitive tasks and process data in real time. Integration with ERP, WMS, and TMS systems creates transparent and optimized workflows throughout the entire supply chain.

Practical example:

In an automated shipping center, packages are automatically recorded, measured, weighed, labeled, and routed to the appropriate shipping path.

See also: DWS, conveyor technology, Industry 4.0, intralogistics, artificial intelligence (AI), process automation, robotics, sensor technology

Automation technology encompasses technical methods, components, and systems for the autonomous control, monitoring, and optimization of machines and processes. It combines mechanics, electronics, software, and sensor technology to execute processes efficiently and reliably.

In logistics and industry, automation technology enables the implementation of automated material flows, conveying processes, and measurement systems. It includes, for example, control systems, sensors, drives, and communication systems that work together in a networked manner. By processing process data, systems can react flexibly, reduce errors, and optimize operational workflows. Automation technology forms an important foundation for modern logistics solutions and Industry 4.0 applications.

Practical example:

An automated conveyor system uses sensors to detect the condition of a pallet and directs its further transport along the appropriate conveyor route.

See also: Automation, Conveyor Technology, Intralogistics, Process Automation, Sensor Technology, Control Technology, System Integration, Goods Flow