About the Customer

The client is a leading global manufacturing group with more than 60 operative subsidiaries and production facilities in 12 countries. 

PRODUCTS & SERVICES

Azure Stream Analytics
Azure Event Hub

HD Insights
Azure SQL Data Warehouse
Power BI Embedded

Clearfix

Business Challenge

  • An increasing need to monitor manufacturing equipment on customer sites.
  • Recurring machine problems.
  • Predict manufacturing equipment problems before it impacts production.
  • Real-time monitoring of equipment and units.
  • Automate troubleshooting.
  • Alerting field executives immediately after equipment issues are discovered.

The SNP Solution

SNP’s predictive analytics solution offers the simplicity and self-service the client needed while meeting the governance and automation requirements of their IT teams.

 

The solution was offered in 2 phases:

Phase 1: Source Analysis & Requirement Gathering

  • Analyze the overall platform for a full-blown predictive analytics implementation.
  • Implement the Azure-based solution to prove the concepts of the cloud and predictive analytics.
  • Create a preventive maintenance dashboard from the log files.
  • Create an Azure channel to extract data files from various machines.
  • Implement an ETL tool and import it into the data model to create requisite dashboards.
  • Track activity by location.

Phase 2: Roadmap for Predictive Analytics Solutions 

  • Set up real-time alerts and data monitoring across complex manufacturing environments.
  • Analyze high volume streaming data to get real-time insight into the Power BI analytics dashboard.
  • Enable data correlation to give clarity on how variability in one area will impact another.
  • Detect and resolve any errors or unruly patterns among departments, machines, processes or individuals.
  • Set up predictive maintenance during streaming forecasting on data and alert when thresholds are surpassed.
  • Use streaming data from sensors and devices to recognize warning signs (e.g., predict equipment failure) and perform maintenance before equipment breakdown occurs.
  • Send notifications to field executives or customers when errors or warnings occur.
  • Set up advanced preventive analytics for periodic machine health check and historical analysis.
  • Establish customer satisfaction and SLA monitoring.
  • Develop exception reporting for failure and error analytics.

 

Customer Benefits

  • Real-time monitoring of performance.
  • Detect equipment failures before they happen and fix them using smart sensors and real-time data.
  • Remote diagnosis by gathering and transforming data from sensors and systems.
  • Replace legacy ETL technique with modern IoT workflows that enable event hubs for real-time analytics and notifications.