// ROBOTICS AND SMART FACTORIES TERM
Failure Mode
The way in which a product or process can fail to perform its intended function.
TECHNICAL DEFINITION
A Failure Mode describes the specific manner or mechanism by which a component, product, or process can potentially fail to meet its design intent or specified performance requirements.
BACKGROUND
Failure mode, effects, and criticality analysis (FMECA) is a method used to identify potential failures in a system and determine how severe their consequences would be. It is an extension of Failure mode and effects analysis (FMEA). While FMEA identifies how a product might fail, FMECA adds a criticality analysis to rank those failures based on their probability and severity.
READ MORE ON WIKIPEDIASYNONYMS & ALIASES
- Failure Mechanism
- Malfunction Type
- Error Mode
USAGE NOTE
Identified during FMEA to assess potential risks and implement preventive measures.
DEVELOPERS
Organizations developing technology related to Failure Mode.
Develops engineering simulation software used to predict how product designs will behave in real-world environments. Its tools allow engineers to model and analyze potential failure modes, such as mechanical stress, thermal issues, and electronic component failure, early in the design phase.
Provides a comprehensive portfolio of software for creating Digital Twins of products and production lines. Their MindSphere (Industrial IoT) and Plant Simulation platforms enable manufacturers to simulate operations, analyze data, and use predictive analytics to identify and mitigate potential equipment failure modes.
A leader in the Industrial Internet of Things (IIoT), GE Digital offers Asset Performance Management (APM) software. This software uses data from industrial assets to predict and prevent equipment failures, helping operators understand failure modes and implement reliability-centered maintenance strategies.
Specializes in 'machine health as a service', using AI and IoT sensors to monitor industrial equipment. Their platform analyzes vibration, temperature, and magnetic data to detect anomalies, diagnose malfunctions, and predict specific failure modes before they cause downtime.
Provides an enterprise AI platform and a suite of pre-built applications, including C3 AI Predictive Maintenance. This application uses machine learning to analyze vast amounts of sensor and operational data to predict equipment failures and identify their root causes or modes.
Offers the ThingWorx Industrial IoT platform, which allows companies to connect to, monitor, and analyze data from industrial assets. The platform facilitates the development of applications for predictive maintenance, enabling early detection of conditions that lead to common failure modes.
Provides cloud services tailored for industrial use, such as Amazon Lookout for Equipment. This service uses machine learning to analyze sensor data from industrial machinery to detect abnormal behavior and identify developing failure modes, helping to prevent unplanned downtime.
A major provider of industrial automation and information technology. Their software suites, like FactoryTalk, and asset management solutions leverage data analytics and AI to monitor asset health, predict failures, and provide insights into specific failure modes in a manufacturing environment.