Glossary

A package is a single, shippable packaging or transport unit within a shipment. It can consist, for example, of a cardboard box, a crate, a sack, a pallet, or another transportable loading unit.

A shipment may consist of one or more packages, each of which is labeled, recorded, and transported separately. In logistics, the dimensions, weight, and identification data for each package are often recorded automatically to efficiently manage transportation, warehousing, and sorting processes. The unique identification of each package enables seamless shipment tracking and precise freight billing.

Practical example:

A machine shipment consists of five packages, which are individually measured, weighed, and labeled with a barcode at the outbound goods area before being shipped together.

See also: Barcode, Freight, Freight Data, Load Carrier, Shipment Tracking, Master Data Entry, Goods Flow, Outbound Goods

Package measurement systems are automated measurement systems designed to capture the dimensions of packages and other shipping items. They provide precise measurement data for shipping, warehousing, and freight billing, and support efficient logistics processes.

Depending on the model, package measurement systems use laser, LiDAR, or camera technologies to measure length, width, and height without physical contact. They are often part of a DWS system and can also capture weight and identification data such as barcodes. The collected data is transferred directly to ERP, WMS, or transportation management systems and is used for shipping planning, volume optimization, and automated process control.

Practical example:
In a parcel center, a parcel measurement system automatically measures every incoming parcel and transmits the dimensions in real time to the sorting and billing system.

See also: Dimensioning systems, Dimension capture, DWS, Freight measurement, LiDAR, Multidimensional measuring device, Scanner, Volume measurement

Packaging Optimization refers to the targeted improvement of packaging with regard to size, material usage, protective function, and resource efficiency. The objective is to design packaging in a way that products can be transported safely while reducing unnecessary material consumption and empty space.

In logistics, packaging optimization helps to make better use of transport capacity, reduce costs, and create more sustainable processes. Reliable product and packaging data, such as dimensions, volume, and weight, provide the basis for this optimization. Automated measurement systems and digital master data capture enable companies to record actual dimensions, compare packaging sizes, and identify optimization potential throughout the supply chain.

Practical example:
A company automatically captures the dimensions of its products and packaging, identifies unnecessary empty space, and adjusts packaging sizes to reduce material consumption and improve transport utilization.

See also: Digitalization, Freight Data, Freight Measurement, Master Data Capture, Master Data Management (MDM), Process Optimization, Sustainability, Volume Optimization

A pallet is a standardized load-carrying unit used for the transport, storage, and handling of goods. It groups individual packages into a manageable loading unit and enables an efficient flow of materials.

Pallets are used in nearly all areas of logistics and can be made of wood, plastic, metal, or other materials. Among the best-known types are Euro pallets (EPAL), industrial pallets, and disposable pallets. They are designed for use with forklifts, pallet jacks, and automated conveyor systems and form the basis for safe storage, internal transport, and the national and international movement of goods.

Practical example:
Before being put into storage, a loaded pallet is automatically measured and weighed so that its dimensions and weight can be recorded in the warehouse management system.

See also: Automatic Pallet Inspection (MSPP), EPAL, forklift, load securing, warehouse, pallet measurement, goods receipt, goods issue

Pallet conveying technology encompasses technical systems and equipment for the automated transport of pallets within production and logistics areas. It enables the efficient movement, staging, and transfer of load units between different process steps.

Components of pallet conveying technology include, for example, roller conveyors, chain conveyors, lifting stations, turntables, and automatic transfer units. It is often combined with sensor technology, control systems, and warehouse automation to move pallets safely and reliably. In conjunction with WMS, DWS, and other automation solutions, pallets can be identified, tracked, and directed to the next process steps.

Practical example:
In an automated high-bay warehouse, pallet conveying technology transports a measured and identified pallet from the goods receiving area to the designated storage location.

See also: Automation, Conveying Technology, High-Bay Warehouse, Intralogistics, Load Carrier, Material Flow, Pallet, Warehouse Management System (WMS)

Pallet management encompasses the planning, administration, and control of pallets throughout their entire lifecycle. It ensures that load carriers are used efficiently, tracked, and made available as needed.

Pallet management includes inventory tracking, the exchange of reusable pallets, quality control, and the organization of return processes. Digital systems enable transparent management of pallet movements and help companies reduce losses while optimizing costs and availability. Efficient pallet management contributes significantly to smooth material flows and cost-effective logistics.

Practical example:
A logistics service provider digitally documents the exchange of Euro pallets, thereby maintaining a constant overview of inventory, returns, and pallet accounts.

See also: Automatic Pallet Inspection (MSPP), EPAL, Load Securing, Material Flow, Pallet, Supply Chain Management, Warehouse Management System (WMS)

Pallet measurement involves the automatic or manual recording of the dimensions of pallets and the load units placed on them. It is used to determine length, width, height, and, if necessary, other geometric properties.

In logistics, pallet measurement is used to provide accurate data for warehousing, transportation planning, freight billing, and automated processes. Modern systems use, for example, 3D sensors, laser scanners, or camera technologies to capture pallets quickly and precisely. The data collected supports the efficient use of warehouse space, the secure management of material flows, and the optimization of logistics processes.

Practical example:
A pallet is automatically measured before being put into storage so that the warehouse management system can determine the appropriate storage location and update the transport data.

See also: 3D sensors, DWS, freight measurement, loading unit, load carrier, measurement data acquisition, pallet management, volume measurement

Parcel sorting is the automatic or manual classification and routing of parcels within logistics processes. It serves to efficiently distribute shipments based on defined criteria such as destination, route, or recipient.

In modern package centers, sorting is often automated using conveyor systems, scanners, camera systems, and intelligent control systems. Identification data, dimensions, and other shipment information are used to route packages to the correct outbound route. In conjunction with DWS systems, sorting systems, and digital logistics platforms, package sorting enables the rapid processing of large volumes of shipments and supports transparent flow of goods.

Practical example:
At a parcel center, a shipment is automatically scanned, measured, and routed to the appropriate shipping area via a sorting system based on its destination information.

See also: Barcode, Data Capture, DWS, Conveyor Technology, Identification, Sorting System, Track & Trace, Goods Flow

Password management involves the secure administration, assignment, and use of passwords and login credentials within digital systems. It helps protect against unauthorized access and is a key component of IT security.

A structured password management system establishes requirements for secure passwords, their regular updating, and the secure storage and sharing of login credentials. In logistics and automation environments, for example, it protects access to ERP, WMS, TMS, or plant control systems. Clear guidelines and the use of additional security measures, such as multi-factor authentication, help reduce risks and reliably secure digital processes.

Practical example:
A service employee accesses the control software of an automated measuring system using a personal, secure user account with defined access rights.

See also: Authentication, User Management, Cybersecurity, Data Integrity, IT Security, Access Control, Two-Factor Authentication, Access Rights

A photoelectric sensor is an optical sensor used for non-contact detection of objects or motion. It detects when a light beam is interrupted or reflected and triggers a switching signal based on this detection.

Light barriers are used in conveyor technology, intralogistics, and industrial automation to detect packages, control processes, or trigger measurement operations. Depending on their design, they operate as through-beam, retro-reflective, or scanning light barriers. In automated measurement and DWS systems, they are often used to detect the position of an object and determine the optimal time for measurement or identification.

Practical example:

On a conveyor line, a photoelectric sensor detects the arrival of a package and automatically starts the measurement and scanning process of the DWS system.

See also: 3D sensors, DWS, conveyor technology, infrared fan scanners, laser scanners, object detection, sensor technology, control technology

Pick-by-Light is a picking-supported process in which visual indicators show employees the correct storage location and the quantity to be picked. It enables fast, intuitive, and low-error picking.

In Pick-by-Light, shelf compartments are equipped with light indicators and confirmation buttons. The system guides employees through the picking process by illuminating the corresponding bin and displaying the quantity to be picked. After the item is picked, the operation is confirmed, and the next storage location is activated. This direct user guidance reduces search times, minimizes errors, and increases productivity—especially in warehouses with a high order volume.

Practical example:
In an e-commerce warehouse, the shelf bin containing the required item lights up, allowing the employee to retrieve the correct quantity and then confirm the order with the push of a button.

See also: Order picking, Warehouse Management System (WMS), Material flow, Pick-by-Voice, Goods flow, Goods out, Goods in

Pick-by-Vision is a picking method in which employees are visually guided through the picking process using smart glasses. The necessary information is displayed directly in their field of view, enabling hands-free and efficient order fulfillment.

The system displays the storage location, item, pick quantity, and other work instructions in real time. Using integrated cameras, scanners, or sensors, work steps can be automatically confirmed and synchronized with the warehouse management system. Pick-by-Vision reduces search times, minimizes picking errors, and is particularly well-suited for complex warehouse processes and applications with a high variety of items.

Practical example:
An employee picks replacement parts using smart glasses that display the next storage location and the required quantity directly in their field of view and automatically document the pick.

See also: Order Picking, Warehouse Management System (WMS), Material Flow, Pick-by-Light, Pick-by-Voice, Warehouse Management System (WMS), Data Glasses

Pick-by-Voice is a voice-controlled order-picking process in which employees communicate with a digital system via a headset and receive work instructions via voice. It allows for hands-free performance of warehouse tasks and supports efficient order picking.

With Pick-by-Voice, information such as the storage location, item, and quantity to be picked is provided by the system via voice prompts. Confirmation of completed steps is also done via voice, eliminating the need for additional input devices. The method is used particularly in large warehouses and can be integrated with warehouse management systems. It supports low-error picking and improves ergonomics for employees.

Practical example:
A picker receives instructions via a headset to retrieve a specific item from a storage location and confirms the retrieval directly via voice command.

See also: Barcode, Data Capture, Order Picking, Warehouse Management System (WMS), Pick-by-Light, Pick-by-Vision, Voice Picking

A point cloud refers to a collection of three-dimensional measurement points that digitally represent the spatial structure and geometry of an object or environment. Each individual point contains information about its position in space and can be supplemented with additional attributes such as intensity or color.

Point clouds are generated, for example, by laser scanners, LiDAR sensors, or 3D cameras and are used for the digital capture of objects and environments. In logistics, they enable the precise analysis of contours, dimensions, and spatial characteristics of goods or load units. They form an important data foundation for applications such as automated measurement, contour inspection, and three-dimensional object recognition.

Practical example:
A 3D scanner generates a point cloud of a pallet to capture protrusions, irregular contours, and the actual dimensions for automatic inspection.

See also: 3D sensors, automatic measurement, contour inspection, laser scanners, LiDAR, measurement data acquisition, sensor technology, volume measurement

The PPWR (Packaging and Packaging Waste Regulation) is the European regulation on packaging and packaging waste. It defines binding requirements to reduce packaging waste, make packaging more sustainable, and promote reuse and recycling within the European Union.

The regulation affects manufacturers, retailers, and companies throughout the entire supply chain. Among other things, it requires improved resource efficiency, the avoidance of unnecessary packaging, the reduction of empty space, and higher quality and availability of packaging data. Digital master data on dimensions, volume, and weight of products and packaging helps companies optimize packaging processes and comply with PPWR requirements.

Practical example:
A company automatically captures the actual dimensions and weight of its products and packaging in order to optimize packaging sizes, avoid unnecessary empty space, and meet the requirements of the PPWR.

See also: Digitalization, Freight Data, Freight Measurement, Master Data Capture, Master Data Management (MDM), Process Optimization, Sustainability, Volume Optimization

Predictive analytics refers to the analysis of historical and current data to predict future developments, events, or behaviors. Using statistical methods and artificial intelligence, forecasts are generated that enable informed decisions and forward-looking planning.

In logistics, predictive analytics is used to identify demand, delivery times, maintenance intervals, and capacity utilization at an early stage. Analyzing large volumes of data from sensors, ERP, WMS, and TMS systems helps prevent bottlenecks, optimize resource allocation, and continuously improve processes. This enables companies to increase their efficiency and respond more quickly to changes.

Practical example:
A logistics service provider analyzes shipping data from previous years to predict seasonal order peaks and plan staffing and vehicle capacity in a timely manner.

See also: Big Data, Industry 4.0, Artificial Intelligence (AI), Machine Learning, Predictive Maintenance, Supply Chain Management, Warehouse Management System (WMS)

Predictive maintenance refers to a proactive maintenance strategy in which condition data from machines and equipment is used to identify maintenance needs at an early stage. The goal is to prevent breakdowns, plan maintenance measures in a targeted manner, and increase the availability of technical systems.

In logistics and automation, sensors, measurement systems, and data analysis are used for this purpose. Operational data such as runtime, temperatures, vibrations, or error messages are continuously evaluated to detect changes and potential malfunctions early on. Predictive maintenance enables needs-based maintenance of conveyor systems, measurement systems, and automated equipment, thereby supporting stable processes.

Practical example:
An automated conveyor system uses operational data to detect increased wear on a component at an early stage and triggers a scheduled maintenance task.

See also: Automation, Data Analysis, Maintenance, Sensor Technology, System Integration, Validation, Servicing, Condition Monitoring

Predictive Vision for Logistics refers to an AI-driven approach to the visual analysis of logistics objects and processes based on image and sensor data. The goal is to automatically detect and evaluate relevant features and use them to make predictive decisions and optimize processes.

The technology combines camera systems, deep learning, and image processing to automatically analyze, for example, pallets, packages, hazardous materials labels, packaging conditions, or load carriers. The information obtained can be used for quality control, process control, anomaly detection, and the optimization of material flows. This reduces manual inspections, speeds up decision-making, and increases the transparency of logistics processes.

Practical example:
An AI system automatically analyzes every pallet on a conveyor system, detects tears in plastic wrap, protrusions, and missing hazardous materials labels, and immediately reports any discrepancies to the warehouse management system.

See also: Image processing, deep learning, AI-supported object recognition, camera sensors, machine learning, object recognition, predictive analytics, sensor technology

Process automation refers to the automatic execution and control of recurring workflows using digital systems and technical solutions. It reduces the need for manual intervention, increases process reliability, and improves efficiency and quality.

In logistics, process automation includes, among other things, automatic identification, measurement, weight recording, data transmission, and material flow control. Sensors, camera systems, conveyor technology, and AI-supported applications work seamlessly with ERP, WMS, and transport management systems. By integrating these technologies, throughput times can be shortened, errors avoided, and decisions made based on up-to-date process data.

Practical example:
In a distribution center, packages are automatically identified, measured, weighed, and assigned to the appropriate shipping route—without any manual intervention.

See also: Automation, DWS, Industry 4.0, AI-powered object recognition, logistics automation, material flow, robotics, sensor technology

Process optimization involves the systematic analysis and improvement of existing processes with the goal of increasing efficiency, quality, and cost-effectiveness. This involves adapting processes to make better use of resources, reduce errors, and shorten lead times.
In logistics, process optimization is increasingly based on digital data, automation, and intelligent analytics. Systems such as DWS, WMS, and TMS provide valuable information on material flows, utilization rates, and process times. Through the use of sensor technology, artificial intelligence, and automated controls, bottlenecks can be identified and workflows continuously improved. Targeted process optimization contributes to greater process reliability and improved adaptability of logistics systems.

Practical example:
A logistics center analyzes data from its conveyor and measurement systems, identifies bottlenecks in the material flow, and adjusts process control accordingly.

See also: Automation, Data Analysis, DWS, Artificial Intelligence (AI), Material Flow, Process Automation, Process Reliability, Sensor Technology

Processing speed refers to the time or rate at which logistics processes, orders, or shipments are processed and completed. It is an important performance indicator of the efficiency of warehousing, shipping, and transportation processes.

Processing speed is significantly influenced by automation, optimized material flows, and the availability of accurate master data. Systems for automatic identification, measurement, and weight recording shorten processing times and reduce manual steps. This increases throughput, process reliability, and the efficiency of logistics operations.

Practical example:

At a parcel sorting center, a DWS system shortens the processing time for each shipment by automatically capturing dimensions and weight during the conveyor process.

See also: Automation, Dimension Capture, DWS, Conveyor Speed, Material Flow, Master Data Capture, Transport Management System (TMS), Goods Receiving

Protrusion refers to a package or load extending beyond the permissible dimensions of a load carrier or means of transport. Such protrusions can compromise the safety, handling, and transport of goods.

In logistics, protrusions are automatically detected using camera systems, LiDAR, or DWS systems. Early identification of protrusions helps prevent damage to conveyor systems, warehouse equipment, or means of transport and ensures compliance with safety and transport regulations. Automated contour checks enable reliable detection even at high conveyor speeds.

Practical example:
Before storage, a DWS system detects a lateral protrusion on a pallet and automatically diverts it for rework before it is transported to the high-bay warehouse.

See also: DWS, free-form detection, contour inspection, load securing, object detection, pallet, Predictive Vision for Logistics, protrusion

The PTB (Physikalisch-Technische Bundesanstalt) is Germany’s national metrology institute and the highest technical authority for legal metrology. It develops measurement standards, ensures the traceability of measurements, and supports the uniform application of metrological regulations.
The PTB works closely with manufacturers, testing laboratories, and government agencies and plays a key role in the development, testing, and evaluation of measurement methods. In the field of logistics, it provides an important foundation for the approval and monitoring of scales, dimensioning systems, and automatic weight sorting (DWS) systems. Its technical specifications and reference measurements help ensure that measured values are comparable both nationally and internationally and are legally valid.

Practical example:
A manufacturer has the metrological properties of a new dimensioning system tested in accordance with PTB specifications to meet the requirements for use subject to calibration.

See also: Calibration capability, Measurement and Calibration Act (MessEG), MID (Measuring Instruments Directive), NTEP (National Type Evaluation Program), OIML, OIML R 129, Certification