ALERT (Adaptable Leading Edge Reliability Techniques) is designed and developed to help predict abnormal behaviour of critical machinery and industrial systems, enabling safe and timely remedial response. Guided by rule-based diagnostic logic, corrective actions are supported by ALERT to prevent or mitigate the consequences of serious abnormalities.

Proper prediction of Machinery and System performance requires analysis of long term historical trends of relevant signals from equipment and processes. Applying knowledge, experience, and past history, abnormal trend signatures can be correlated to machinery problems. Such signatures, in coordination with other dynamic conditions detected by sensors, can provide valuable insight into the current health and future behaviour of machinery. This type of equipment diagnosis proves invaluable and leading edge in avoiding expensive downtime and serious health and safety risks.

ALERT provides an affordable and adaptable platform to develop and customize the most appropriate diagnostic rule applicable to detect significant machinery conditions. The possible problem scenarios and their appropriate counter-measures are pre-configurable.

The strength of ALERT lies in its ability to predict a multitude of possible abnormalities and provide timely notification with guidance for recommended remedial response. In short, ALERT provides a platform to model the Failure Modes and their Detection methods.

ALERT diagnostic notifications are designed to guide users to act safely and correctly. Diagnostic recommendations can include written or video guidance on how to approach the fault location and perform the job safely. The architecture of ALERT is essentially a cloud-based application that permits features requiring a large amount of memory. The delivery of diagnostic recommendations on a “Personalized” Dashboard via portable smart devices allows real-time multi user access and collaborative problem solving.

ALERT is designed to help alleviate potentially troublesome situation before it gets serious. The personalization of the ALERT notification will be in accordance with the nature and magnitude of the predicted abnormality. Such targeted and pre-processed notification will prevent inadvertent loss of critical information with an assurance of correct and timely action.


The functionalities of ALERT are based on real-time data acquired from the plant. A Gateway computer called the ALERT Gateway (AG) will be installed in the plant to collect relevant analog and digital signals required for the purpose of diagnostics. The signals are sourced from the existing PLCs or data hubs available in the plant. If the required signals are non-existent, the MCARTech team will provide a suitable techno-commercial proposal for implementing them.

The AG hosts a database that gets populated by the real-time data acquired from the plant. The AG in turn validates and packages the data for onward transmission to the ALERT cloud, utilizing internet or a cellular connectivity. The database in the ALERT cloud receives the analog and digital information, updates itself and shares the data with the various Functional Modules, such as –

  1. Machinery Essential Information Record (MEIR Trending)
  2. Advance Diagnostics
  3. Dashboard
  4. Personalization
  5. Machinery Condition Monitoring (Inspections)
  6. Smart Fault Tracking

The Advance Diagnostics module performs its task as per the algorithm programmed (Failure Mode Models) utilizing the acquired data from the plant. ALERT outputs on the Dashboard and Notifications are delivered via portable smart devices which are connected to the ALERT cloud using internal WiFi network.