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SAP EAM Notification Insights from AG

 

In Asset Maintenance, businesses often require significant statistical maintenance data and the history of a technical object to analyse its performance, efficiency and involvement in production. With this analytical data, the Maintenance professionals can take appropriate action to improve technical object's performance. This data can be captured with the SAP business transaction - the Notification (Maintenance request or Malfunction report). With the Notification, the user can record the Failure modes and their effects, break down durations and maintain Catalogs in the form of predefined code groups and codes. The objective of using codes is to standardise the data across industries. For example, ISO14224 defined reliability and maintenance for Equipment for Oil & Gas industries. Standard SAP allows the user to capture the data related to Object part, Damage, Cause, Task, Activity and Failure mode in the form of codes.

AG uses the analytical data acquired from Maintenance notification history and develops user-responsive Dynamic Graphical report - Analytical reports from Maintenance notification history for practical analysis, using Power BI, an interactive data visualisation software developed by Microsoft. Further, the Analytical reports from Maintenance notification history are analysed based on the following Key Performance Indicators (KPI).

  • Object Damage Analysis
  • Breakdown Analysis
  • Reliability, Availability & Maintainability (RAM) Analysis 
  • Failure Mode and Effect Analysis (FMEA)
 
Damage Analysis:
In an Industry, Root cause analysis is the tool that any Maintenance team needs to address equipment failures. The primary data for the root cause analysis are failures and the damages caused.
 
AG’s Damage analysis focuses on the Object part, Damages, Causes, Tasks & Activities. This report displays all the catalogs of data recorded from the Notification history and their associated Notification, Equipment & Equipment manufacturers, Models etc.; All these data are inter-responsive. i.e., if the user selects any one damage, it will display the number of times the same damage occurred during the specified period, all the causes, plans made, tasks assigned, activities done, affected object part, equipment & manufacturers, and the user can plan a course of action to eliminate these causes. In the same way, if the user selects any Equipment manufacturer/Model, a report will display the total damaged equipment, the damages & their causes. The user can evaluate the manufacturer’s quality standard.
 
damage analysis
 
Breakdown Analysis:
Equipment for production and repair are the two essential maintenance metrics in asset management. Maintenance teams can understand which pieces of equipment are most prone to faults, indicating that those assets may need more maintenance or even replacement. And they will also help the maintenance team assess their failure frequency, assess hurdles in work execution, better workmanship requirements, critical spare parts requirements, and preparations required for repairing equipment.
AG’s Breakdown analysis displays the MTTR & MTBR and their associated Equipment, Model, Notifications & Manufacturer for any selected period. This report lets the user know that the equipment has the highest breakdown duration and its manufacturer, model, and the total number of breakdowns.
 
Reliability, Availability & Maintainability (RAM) Analysis:
Reliability, Availability, and Maintainability (RAM) are major KPI of an asset during asset life cycle management. Organisation profit relies on high reliability (MTBR) and easy maintainability (MTTR).  Those parameters are measured for a period of time, and appropriate actions are taken to improve the asset's reliability. 
 
MTBR
 
AG’s RAM analysis will give the user a complete picture of all three parameters for any selected equipment, Planning / Maintenance plant, Criticality, Object Type, Model, and Manufacturer.
 
Reliability analysis
 
Failure Mode and Effect Analysis (FMEA)
It is a tool to assess the Potential causes and their impact of an Equipment failure. With this, the Maintenance team will learn how serious the consequences of loss of Equipment are. It also lets the maintenance team know the failure's causes and how frequently they occur. The risk priority number (RPN) is derived for each asset.  The maintenance team will address the highest RPN assets and take corrective action to bring them down.
 
RPN = Severity (S) X Occurrence(O) X Detection (D) 
  1. Severity = Effect (Rank -S) count for the period
  2. Occurrence = Cause code count for the period (Rank- O)
  3. Detection = Number of Preventive & Corrective/predictive Maintenance orders/Notifications completed for the period. (Rank -D)
 
AG’s FMEA report will enable users to view the Failure modes, Causes & Effects of an Equipment failure - how many failures occurred for an asset, the causes of failures, how they occur and their impact on the Maintenance Notifications.
 
AG has introduced an indigenously developed Robotic Process Automation (RPA) program to identify the Completed Maintenance Notifications without any failure mode selected and fill-ups the failure mode automatically based on the failure description logged by the User.
 
failure mode
 

Reducing the asset maintenance cost and increasing asset availability is mandatory for any organisation to remain competitive globally. To achieve this, follow the right strategy for maintenance of the asset and its renewal/replacement to optimise the overall life cycle cost of the asset.  The only way to do this is to get the correct data, make the right decision, and get the right resources at the right time.