Predictive Asset(Device/Equipment)Maintenance
Business Problem
Across industries unexpected and unplanned downtimes disrupt factory schedules leading to lower productivity and risk to on-time deliverables. Organizations constantly explore opportunities that allow scheduling of corrective maintenance to prevent any unexpected equipment failures.
Solution Description
System/application based on predictive analytics that helps reduce unscheduled asset downtime with the following features.
- Real time alerts for equipment failure
- Indications for type and possible time of failure
- Email/messaging to respective personnelto take corrective action
- Standard BI reports / visualization for equipment performance / failures
Solution Overflow
- Build predictive engine for equipment / device failures basis historical information
- Collect equipment’s monitoring information at regular time intervals and feed predictive engine
- Predictive engine to provide alerts on any possible equipment failure and insights on type and time of possible failure
- Communicate alert information to respective personnel for corrective action
Solution Leveraging Hana Capabilities
- Application would be hosted on the cloud and will need to support multiple clients with multiple installations / plants and would leverage on HANAs
- Multi Tenancy and cloud deployment
- This is the typical relationship that exists – Component → Devices → Equipment → Multiple Equipment → Plant. Monitoring information needs to be collected at real timeat a component level if configured so. This would require real time integration of significant volume of records and would leverage on the following HANA components.
- Data Services
- ESP
- And leverage on the following features
- Column & Row store
- Partitioning
- In-memory compression
- Active/Passing & Data Aging
- Multi / Core parallelization
- Predictive engine that runs robust algorithms to match against historical records to determine probability of failure at a component / device / equipment level in real time and would heavily leverage on following HANA components
- Predictive Analytics Library
- “R” HS Integration
- Parallel Calculations
- And leverage on the following features
- Column Store
- Analytics on historical data
- Parallelization
- In-memory
- Standard BI reports / visualization for equipment performance / failures which leverages OLAP features of HANA
- Communicate alert information to respective personnel for corrective action would leverage on the following HANA components
- OData
- SQL
Solution Benefits
- Predict equipment/device failure thereby ensuring high asset availability and performance
- Reduce operational costs and enhance asset productivity
- Increased and timely yields from processes leading to optimization of quality and supply chain processes