# Definitions This section provides key terminology used throughout this lens, focusing specifically on modern industrial data concepts and manufacturing-specific definitions. These definitions complement the standard AWS Well-Architected Framework terminology. + **Operational technology (OT)**: Systems and equipment used to monitor and control industrial processes on the shop floor, such as sensors, PLCs, and SCADA systems + **Information technology (IT)**: Technologies used to manage business operations and data, including enterprise systems like ERP, MES, and cloud computing systems. + **Programmable logic controller (PLC)**: An industrial computer used to control machinery and processes on the factory floor, running real-time logic based on sensor inputs. + **Supervisory control and data acquisition (SCADA)**: A system that provides centralized monitoring and control of industrial equipment and processes, often across multiple sites. + **Manufacturing execution system (MES)**: Software that manages and monitors production operations in real time, bridging the gap between the factory floor (OT) and business systems (IT). + **Enterprise resource planning (ERP)**: A business management system that integrates core processes like finance, inventory, and procurement, often linking with MES for end-to-end visibility. + **Message Queuing Telemetry Transport (MQTT)**: A lightweight messaging protocol used in manufacturing to transmit data from machines and sensors to monitoring systems in real time. + **Advanced Message Queuing Protocol (AMQP)**: A protocol used to provide reliable communication between systems in manufacturing, often for integrating OT and IT layers. + **Open Platform Communications Unified Architecture (OPC UA)**: A standard protocol for secure, system-independent communication between industrial equipment and software systems, enabling seamless data exchange across the manufacturing environment. + **Reliability**: The ability of a workload to perform its intended function correctly and consistently when it's expected to. This includes the ability to operate and test the workload through its total lifecycle. + **Resilience**: The ability of a workload to recover from infrastructure or service disruptions, dynamically acquire computing resources to meet demand, and mitigate disruptions, such as misconfigurations or transient network issues. + **Mean time to detection (MTTD)**: The average time required to detect a failure or anomaly in manufacturing systems after it occurs. + **Mean time to resolution (MTTR)**: The average time taken to fully resolve an incident from the moment it is detected, including the time to restore normal manufacturing operations. + **Recovery Time Objective (RTO)**: The maximum acceptable time to restore a manufacturing process or system after a disruption. + **Recovery Point Objective (RPO)**: The maximum acceptable period of data loss measured in time. For manufacturing systems, this defines how much operational data loss can be tolerated in a recovery scenario. + **Data mesh producer**: Any entity which offers a data product through the data mesh. + **Data mesh consumer**: Any entity who subscribes to a data product in the data mesh. + **Data product**: Today, a data product is scoped to be only an AWS Lake Formation table or database. In the future, this definition may expand. + **Digital thread**: A framework that connects data flows and provides an integrated view of an asset throughout the manufacturing lifecycle, from design through production and in-service operation. + **Manufacturing data lake**: A centralized repository that allows storing structured and unstructured manufacturing data at scale + **Industrial data catalog**: A metadata management solution that helps manufacturing organizations find, organize and access their industrial data assets