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Definitions - Modern Industrial Data Technology Lens

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