APM Virtual Assistant SmartSource AI Community

Position: APM Virtual Assistant by SmartSource AI Community

APM Virtual Assistant by Smart Source AI Community

Generative AI (GenAI) has the potential to revolutionize both the user interface (UI) for industrial asset performance management (APM) software, and improving anomaly detection, predictive analytics and root-cause analysis by combining human and machine data.

An APM Virtual Assistant application will offer improved knowledge management, intelligent queries, and dynamic analytics. This enables management, plant operators & supervisors to use a simple mobile chatbot to instantly and easily query and analyze critical equipment health and respond to alarms and alerts in a seamless manner.

The Virtual Assistant web app uses Gen-AI to interpret conversational questions entered by the user about the health and performance of their assets, and returns answers in a user-friendly and intuitive manner. The business benefits are the ability to quickly review and compare performance of various assets across a site or entire region, prioritize and schedule maintenance tasks, deploy as-needed maintenance resources, and improve overall machine lifetime, improving productivity of field resources and the bottom line.

In

the near future, GenAI will further democratize APM, allowing anyone to execute complex queries and synthesis data in seconds. For example:

• Natural Language Interaction (NLI): A GenAI Virtual Assistant can be used to enable NLI in industrial APM software, allowing users to interact with the software using natural language commands and queries.
• Personalized UIs:
  The same Virtual Assistant can be used to create personalized UIs that are tailored to the specific needs and preferences of each user.

Beyond improving the simplicity of the user interface and quickly enabling every stakeholder to benefit from the entire teams’ knowledge capture, GenAI will combine human and machine data to improve nearly every aspect of asset performance management. This includes

• Anomaly Detection and Alerts:
  GenAI can be quickly detect anomalies in data and generate alerts to notify users of potential problems.
• Predictive Maintenance:
  GenAI can be used to predict the future performance of assets and identify potential problems before they occur.
• Root-Cause Analysis:
  GenAI can also be used to identify the root causes of equipment failures by analyzing vast amounts of data and generating hypotheses.

Below are examples of a few tasks that can be quickly be answered by Shoreline AI’s Virtual Assistant:

• Show Assets that have exceeded “client defined thresholds” in the last 1 month.
• Analyze performance of a particular make/model of a pump or compressor operating across all client sites.
• MTTR (Mean-Time-To-Repair) and MTTA (Mean-Time-To-Acknowledge) data to understand if the responses are happening fast enough.
• Which are the three most high-risk assets to review for asset health?
• What are key drivers for low asset health in region X?
• How many unplanned downtime events occurred in the last 30/60/90 days?
• What is the total duration of the unplanned downtime in last 30/60/90 days?
• Tell me the health diagnostics of asset [name].
• Highlight machines where vibration increases with speed on a graph/chart.

GenAI has the potential to make industrial APM software more user-friendly, effective, and valuable for users. By providing personalized UIs, enabling NLI, detecting anomalies and generating alerts, predicting maintenance needs, and performing root cause analysis, GenAI can help users to improve the performance of their assets, reduce downtime, and extend asset lifespan.

About Shoreline AI

Shoreline AI’s plug-and-play asset performance management delivers breakthrough simplicity and cost efficiencies. Completely self-installed by non-experts, smart sensors automatically connect to the cloud and are auto-provisioned via a rich library of 30,000+ pre-built asset physics models.

Shoreline AI helps clients in asset-intensive industries maximize the performance and profitability of their operations, create a proactive and predictive approach to asset management, and accelerate sustainability initiatives.

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