In the industrial automation industry, where software controls everything from manufacturing robots to complex assembly lines, a single software bug can lead to production downtime, equipment damage, or even worker injury. Requs AI's suite of tools offers a proactive approach to improving software reliability and safety, helping companies move beyond traditional, reactive testing methods.
Proactive Risk Identification and Mitigation
Requs AI Predict and Requs AI Software FMEA are key to identifying potential issues early. Requs AI Predict uses machine learning to forecast software reliability and defect density at the start of a project, even before any code is written. This is crucial for industrial automation, as it allows engineers to identify potential weak points in the software architecture and design for control systems or robotic interfaces. This predictive capability helps teams allocate resources effectively to prevent failures before they happen. Simultaneously, Requs AI Software FMEA automates the labor-intensive process of creating a Failure Mode and Effects Analysis. The tool uses a vast database of software failure causes to generate an FMEA worksheet, helping engineers pinpoint the most likely and high-impact failure modes. For example, it could flag a "timing fault" in a robotic arm's control software, allowing for early design changes to prevent an assembly line crash.
Handling Unforeseen Scenarios with Edge Case Prediction
The industrial automation environment is full of complex, rare, and unforeseen conditions. Requs Edge Case prediction is specifically designed to identify these unique scenarios that fall outside of typical operational parameters. The tool uses AI to simulate and predict how software might behave under these rare combinations of conditions. For a complex industrial process, an edge case could involve an unusual sequence of sensor readings combined with a temporary power fluctuation, which could cause a system to lock up. By proactively identifying and addressing these "unknown unknowns," engineers can design more resilient and robust software. This is vital for safety and productivity, as many real-world malfunctions occur in scenarios that were never tested. This capability helps ensure that automation software is reliable under the full spectrum of real-world operational conditions, not just the ideal ones.
Unplanned downtime in industrial environments can cost thousands (or millions) of dollars per hour. Reliable software ensures that machinery, production lines, and robotics are continuously operated without unexpected failures or crashes. Software errors can cause unpredictable system failures and production halts, leading to significant financial losses due to downtime. Reliable software reduces the frequency of such disruptions, ensuring the continuous and efficient operation of automated processes.
Mission Ready Software can help! Our products and training are proven to:
- Identify edge cases that cause downtime
- Identify edge cases that lead to safety hazards
- Identify edge cases that lead to scrapped material
- Reduce the number of false positives with continuous monitoring
- Ensure that the complex network of machines is available
Contact us today for a demonstration of our AI powered Edge Case Prediction, and AI Powered Defect Prediction software and training classes.
