Predictive Maintenance & Asset Management With Advanced Data Analytics

Though technology has helped us build smart systems or products, it can’t prevent them from breaking down. However, as long as we know when, where and how things will break, we can minimize losses and guarantee quality customer service.  As a result, successful manufacturers today leverage the power of digital transformation to reduce costs, improve innovation and transform their business processes. By using IoT sensors, cloud computing, and data analytics, manufacturers are able to gain valuable insights from advance analytics engine

  • proactively prevent issues from happening and
  • avoid unscheduled machines downtime

Let us have a look at some common issues faced by different manufacturing industries and how they can be fixed by implementing predictive maintenance techniques:

“Recently, an airline company, grounded three of its airbuses after the European aviation regulator issued an emergency directive raising concerns over a potential “dual engine failure”. Integrating data from various sources – IoT sensors, flight plans, weather conditions and logs, the airline controllers could proactively detect an engine failure, thus giving instructions for an emergency landing and averting a major catastrophe.

“A shipping company made use of sensors to collect & analyze data on fuel & energy consumption by refrigerators. They realized that overworking their generators was causing excess consumption of energy, fuel & frequent maintenance. Using predictive maintenance model they spread the workload on other generators when required thus helping them save $30 per hour”

Leveraging Data to take Predictive Decisions 

predictive maintenance

Predictive maintenance solutions make effective use of data around us to solve problems. These techniques are designed to help anticipate equipment failures to allow for advanced scheduling of corrective maintenance measures, thereby preventing unexpected equipment downtime, improving service quality for customers, and reducing additional cost caused by over-maintenance. GS Lab’s unique offerings combine manufacturing domain knowledge along with IT expertise to develop intelligent dashboards/platforms which help engineers to

  • View consolidated overview of the entire fleet
  • Track key operational performance indicators
  • Configure alerts by creating an early watch list that draws from predictive analytics
  • View graphical representations of data using Power BI tools
  • Track delays in maintenance activities
  • Schedule maintenance activities at a click of a button which triggers several workflows

This data gives valuable insights regarding engine life, service history, recommended versus actual fuel levels, etc. which are constantly monitored in real time to ensure efficient operations. Predictive maintenance enhances coordination between maintenance team and supervisors, thus assisting them with effective decision making, backed by data. The decision makers can then take a call whether to expedite a service or look for more information. These solutions not only help cut maintenance costs but more importantly avert a crisis leading to enhanced customer satisfaction and stickiness.