
The Asset Guardian (TAG) Mobi: Tackle Downtime with TAG Mobi
TAG Mobi is a fully embedded preventive maintenance and asset management (EAM) solution within Microsoft Dynamics 365 Business Central. Designed for modern manufacturing and infrastructure operations, TAG Mobi helps reduce risk, minimize downtime, and streamline maintenance workflows—all from within your existing Business Central environment.
From proactive asset health monitoring and predictive maintenance to real-time mobility and AI-powered adoption tools, TAG Mobi equips maintenance teams with everything they need to boost performance and take control of asset operations.
Key Features:
• Fully embedded in Microsoft Dynamics 365 Business Central
• Real-time mobile access for on-the-go asset tracking
• Predictive maintenance to reduce unplanned downtime
• AI-assisted onboarding for faster adoption
• Advanced APM tools to monitor asset health and anticipate failures
No silos. No extra software. Just a seamless, native experience that empowers maintenance teams and provides managers with the insights they need—right inside Business Central.
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Maintainly is a cloud-hosted maintenance management solution that streamlines both proactive and reactive maintenance processes. This software enables users to generate, assign, and oversee work orders, offering features such as photo uploads, meter readings, downtime monitoring, and comprehensive audit trails, which can be handled either manually or through automated preventive schedules. Users can organize assets in a hierarchical manner, track movable equipment geographically, and utilize QR codes for easy access, while every maintenance activity is recorded in a detailed history log. Teams and technicians benefit from push notifications, and maintenance personnel can receive and monitor requests using a mobile application that includes functionalities for on-site updates, task comments, and tracking time spent on jobs. Maintainly also offers customizable hierarchy configurations, sophisticated filtering options, and role-specific views, enabling complex operations across various industries to expand efficiently. With a focus on user-friendly adoption, the platform boasts a quick setup process, scalable modular features, and an intuitive design that enhances the user experience. This combination of capabilities makes Maintainly a versatile tool for managing maintenance tasks effectively.
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Aspen Mtell
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.
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aspenONE Asset Performance Management (APM)
Receive precise notifications of potential failures weeks or even months ahead by utilizing real-time information and predictive analytics. Make use of an integrated approach that includes prescriptive maintenance, root cause analysis, and RAM analysis to tackle problems at various levels, including equipment, process, and system. Efficiently implement automated Asset Performance Management solutions using minimal intervention machine learning techniques to foresee asset failures and minimize downtime across the entire plant, across systems, or in multiple sites. This proactive strategy not only enhances operational efficiency but also significantly boosts overall productivity.
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