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In order to run seamless production on an industrial unit, maintenance of machinery is one key factor that requires close attention. In a typical model, plant engineers survey the industrial units and schedule maintenance of those units on a timely basis in order to avoid any hindrance to the production flow. While this model is ideal in a situation where the factors of production are less complex and the industrial units are located on a strategic location easily accessed by a human. But consider a situation where the industrial units are placed in remote locations or hazardous units that often become hard for manual maintenance (e.g. Oil & Gas industry) in the long run. This is where Predictive Maintenance comes into the fore.

With the rapid proliferation of Industry 4.0 industries are now adapting to a new paradigm – a new technique where an IIOT based system can predict the point of a failure of a component. The anomalies detected by the system help the engineer to take action before a unit fails to work. This method essentially helps the industry to reduce downtime and increase energy efficiency and the longevity of the units.

Following are the key factors that come in effect when an industry opts for predictive maintenance:

  •  Remaining useful life [RUL] prediction
  • Flagging of irregular behavior within the installed units.
  • Diagnose failure and provide recommendation or actions that need to be taken to avoid the failure
  •  Generate predictive models to maximize lifetime of assets and operational efficiency

To build a truly effective predictive model one must understand the role of sensors that are attached to the industrial units and which records data for analysis. The software system on the other hand analyses historical and current data using machine language to build the predictive model.

Data Analytec, as an Industry 4.0 solution provider understands the criticality to build an efficient predictive system. It is for this reason the company put stress on the hardware layer of development to achieve constant data flow from sensors to a central unit for analysis.

As more and more industries are opting for a predictive model to increase energy efficiency and reduce downtime it can be safely concluded that with the years to come this model will turn into standard practice across all production units on a global scale.

With adequate industry experience, custom sensors to accurately record data, secured networking and by applying data science technique Data Analytec has carved out a niche solution explored by many early-stage global industrial entrants.

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