Compare Accruent Observe vs. Aspen Mtell

Accruent Observe offers a comprehensive IoT solution for remote monitoring, management, and energy optimization across various types of equipment, aimed at enhancing energy efficiency and operational performance while also predicting equipment failures, improving air quality, and ensuring compliance with commercial refrigeration standards. By maintaining facilities and assets at their optimal performance levels, organizations can effectively meet both compliance requirements and financial objectives. Unplanned downtime can be significantly reduced by pinpointing the exact moment an asset starts to fail, allowing for proactive maintenance to address issues before they escalate. This approach enables businesses to replace equipment solely when necessary instead of adhering to arbitrary schedules, leading to a reduction in unnecessary service costs and overall maintenance expenditures. Moreover, users can identify which locations and equipment are the largest energy consumers, enabling real-time monitoring of energy usage, with the capability to filter by energy type or date range, thus facilitating timely corrections of excessive energy consumption. Additionally, from the initial purchase to disposal, organizations can gain complete visibility into the entire lifecycle of refrigerant usage, ultimately resulting in substantial cost savings. Finally, by leveraging data analytics, businesses can make informed decisions that further enhance operational efficiency and sustainability.

Identify patterns in operational data that can forecast deterioration and potential failures long before they occur. By employing accurate failure pattern recognition, you can reduce the frequent occurrence of false positives typically associated with traditional model-based approaches. Utilizing low-touch machine learning, you can swiftly distinguish between normal and abnormal behaviors, ensuring equipment protection starts within weeks rather than extending into months. The integration of Aspen Mtell with Aspen Cloud Connect™ provides connectivity to devices that support OPC UA. This method of recognizing operational patterns not only serves as an initial defense against asset decline but also enhances existing maintenance strategies through the deployment of AI-driven agents across various sites or throughout the entire organization. By focusing on precise failure pattern recognition, the challenge of high false positive rates in model-based solutions is effectively mitigated. Moreover, the rapid identification of operational behaviors facilitates timely equipment protection, ensuring that organizations can respond proactively to potential issues as they arise.