Industrial AI glossary
42 terms, each in two sentences you can quote, then what it means on the plant floor. Sources on every page.
A
Advanced process control (APC)
Advanced process control (APC) is a set of control techniques layered above basic regulatory control, most commonly model predictive control, that coordinate multiple variables at once to hold a process closer to its economic and operating limits.
AGV (automated guided vehicle)
An AGV (automated guided vehicle) is a driverless vehicle that moves materials along fixed or predefined paths, guided by floor wires, magnetic tape, reflectors or markers, in factories and warehouses.
AI in manufacturing
AI in manufacturing is the use of machine learning and related techniques to support or automate decisions in production, such as detecting defects, predicting failures, scheduling, and tuning processes. It works from plant data rather than explicit rules alone.
AMR (autonomous mobile robot)
An AMR (autonomous mobile robot) is a wheeled robot that navigates a facility using onboard sensors and maps, planning its own route and steering around obstacles. It moves material without fixed guide paths.
Anomaly detection
Anomaly detection is the identification of observations or patterns that deviate significantly from normal behavior in data. In industry it flags unusual sensor readings, process states, or product images that may signal a fault or defect.
B
C
CMMS (computerized maintenance management system)
A CMMS (computerized maintenance management system) is software that keeps a database of a site's assets and maintenance work. It schedules preventive tasks, manages work orders, and tracks spare parts and maintenance history.
Cobot (collaborative robot)
A cobot (collaborative robot) is an industrial robot designed to work in close proximity to people, with safety functions that limit speed, force, or distance so that fencing can be reduced or removed after a risk assessment.
Computer vision inspection
Computer vision inspection is the automated checking of parts or products for defects using cameras and image analysis, increasingly with deep learning models. It replaces or supports manual visual inspection on a line.
Condition monitoring
Condition monitoring is the ongoing measurement of machine parameters such as vibration, temperature, or oil quality to detect significant changes that indicate a developing fault. It is the data foundation of predictive maintenance.
D
DCS (distributed control system)
A DCS (distributed control system) is a plant control system in which control functions are spread across many autonomous controllers near the equipment, linked by a network to central operator stations.
Digital thread
A digital thread is the connected flow of data that links a product's information across its lifecycle, from design and engineering through manufacturing, inspection and service, so each stage can use and feed back into the others.
Digital twin
A digital twin is a virtual model of a physical asset, process, or system that is kept in sync with its real counterpart through live data. It is used to monitor, diagnose, predict, and test changes before making them on the real equipment.
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I
Industrial AI agent
An industrial AI agent is, in loose current usage, a software system that pursues a goal in a plant setting by reading data, reasoning over it, and taking or proposing actions through connected tools, usually built around a large language model.
Industrial IoT (IIoT)
Industrial IoT (IIoT) is the network of sensors, instruments, and machines in industrial settings that are connected to computers and software to collect and use operational data. It applies internet-style connectivity to manufacturing, energy, and other industrial operations.
Industry 4.0
Industry 4.0 is the umbrella term for connecting and computerizing manufacturing through cyber-physical systems, networked sensors, and data analysis. The term originated in a German government high-tech strategy project in 2011.
ISA-95
ISA-95 is an international standard series, also published as IEC 62264, for integrating enterprise business systems with manufacturing control systems. It defines levels, activities, terms and data models for exchanging information between them.
IT/OT convergence
IT/OT convergence is the integration of information technology, the systems that handle business data, with operational technology, the systems that monitor and control physical equipment, so data and practices flow between them.
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M
Machine vision
Machine vision is the use of cameras, lighting, and image-processing software to inspect, measure, identify, or guide automatically in industrial settings. It turns images into decisions or control signals, such as pass/fail or a part position.
MES (manufacturing execution system)
An MES (manufacturing execution system) is software that manages and records production on the shop floor. It turns plans from ERP into dispatched work orders and tracks how raw materials become finished goods.
MQTT
MQTT is a lightweight publish/subscribe messaging protocol, an OASIS standard, in which devices send messages to named topics on a broker and any subscribed application receives them.
O
OEE (overall equipment effectiveness)
OEE (overall equipment effectiveness) is a measure of how effectively a machine or line is used during planned production time. It multiplies three rates: availability, performance, and quality.
OPC UA
OPC UA (OPC Unified Architecture) is a platform-independent, open standard for exchanging industrial data securely between machines, controllers and software, published by the OPC Foundation and standardized as IEC 62541.
OT cybersecurity
OT cybersecurity is the protection of operational technology, the control systems and networks that run physical processes, against cyber threats, with safety, availability and reliable operation as the first priorities.
P
Physical AI
Physical AI is AI that perceives, reasons about, and acts in the physical world, typically through robots, vehicles, or machines. It contrasts with AI that stays in the digital realm, such as chatbots or document tools.
PLC (programmable logic controller)
A PLC (programmable logic controller) is a ruggedized industrial computer that reads inputs from sensors, runs a user program, and drives outputs such as motors and valves in real time. It is the basic control device of most machines and lines.
Predictive maintenance
Predictive maintenance is maintenance triggered by a prediction of failure, based on measured equipment condition such as vibration, temperature, or noise. It aims to act before a failure, but not earlier than needed.
Prescriptive maintenance
Prescriptive maintenance is a maintenance approach that goes beyond predicting when equipment will fail and recommends what action to take, when, and with which resources to prevent or limit the failure.
Process historian
A process historian is a time-series database that collects, compresses and stores data from plant control systems, such as sensor readings, setpoints and alarms, so it can be trended, analyzed and retrieved later.
Purdue model
The Purdue model is a reference model that arranges industrial control systems in levels, from the physical process up to enterprise IT. Today it is mostly used to plan how plant networks are separated from business networks and the internet.
R
S
SCADA
SCADA (supervisory control and data acquisition) is a computerized system that gathers data from remote or distributed equipment and lets operators monitor and control it. It is common in utilities, pipelines, and plants spread over large areas.
Soft sensor
A soft sensor, or virtual sensor, is software that estimates a quantity that is hard or costly to measure directly by calculating it from other measurements that are available in real time.
Statistical process control (SPC)
Statistical process control (SPC) is the use of statistical methods, mainly control charts, to monitor a production process and detect when its variation goes beyond what its normal, stable behavior would produce.
Synthetic data
Synthetic data is artificially generated data that mimics some statistical properties of real data. In industry it is used to train and test AI models when real examples, such as rare defects or failures, are scarce or sensitive.
Sparkplug B
Sparkplug B is the current payload definition of Eclipse Sparkplug, an open specification that tells MQTT clients in industrial systems which topic names to use, how to encode data, and how to report whether a device is online.