Overview
Recommendations are actionable maintenance tasks generated from oil sample analysis, alarm investigations, or routine inspections. They provide a structured way to document required actions, assign ownership, track progress, and verify completion.Each recommendation links to specific assets and sampling points, creating full traceability from detection to resolution.
Recommendation Components
Every recommendation includes:- Title: Brief summary of the required action
- Severity: Low, Medium, High, or Critical
- Description: Detailed explanation of the issue and recommended action
- Site: Location where action is needed
- Asset: Affected equipment
- Sampling Point: Specific location on the asset (if applicable)
- Recommender: Person who created or identified the need
- Status: Open, In Progress, Completed, or Overdue
- Attachments: Supporting documents, images, or reports
Creating a Recommendation
Navigate to Recommendations
From the main menu, go to Recommendations and click Add New Recommendation.
Enter Basic Information
In the main form area:
- Title: Write a clear, action-oriented summary (e.g., “Replace gearbox oil due to high copper”)
- Severity: Select Low, Medium, High, or Critical based on urgency
- Description: Provide detailed context:
- What was observed (e.g., “Copper concentration increased from 15 ppm to 45 ppm”)
- Why action is needed (e.g., “Indicates bearing wear”)
- What should be done (e.g., “Inspect bearings, replace if damaged, change oil”)
Link Assets Associated
In the right-hand panel, select:
- Site: Location where the asset is installed (required)
- Asset: The specific equipment (filtered by site)
- Sampling Point: The exact location (filtered by asset)
- Recommender: User who identified the issue (filtered by site)
Dropdowns cascade — selecting a site filters available assets, and selecting an asset filters sampling points.
Add Attachments (Optional)
Upload supporting documents:
- Lab reports
- Photos of equipment condition
- OEM service bulletins
- Previous maintenance records
Severity Levels
Choose severity based on impact and urgency:Low
Routine maintenance — No immediate risk. Schedule during normal service intervals.Example: Filter replacement at next service
Medium
Moderate concern — Plan action within 1-2 weeks. Monitor until completed.Example: Gradual increase in wear metals
High
Significant risk — Take action within days. Failure likely if ignored.Example: Water contamination above 1000 ppm
Critical
Immediate action required — Equipment at imminent risk of failure. Stop operation if unsafe.Example: Sudden spike in iron indicating catastrophic wear
Recommendation Status
Recommendations progress through these states:| Status | Meaning | Actions |
|---|---|---|
| Open | Newly created, not yet started | Assign resources, schedule work |
| In Progress | Work is underway | Update progress notes, track completion |
| Completed | Action finished, pending verification | Review results, verify effectiveness |
| Overdue | Past target completion date | Escalate, reallocate resources |
Viewing Recommendations
The recommendations list shows:- Title and severity indicator
- Site and Asset names
- Status badge
- Creation date
- Quick actions (View, Edit, Delete)
Editing Recommendations
- Click the Edit icon or open the recommendation and select Edit
- Modify any fields:
- Update status as work progresses
- Refine description based on findings
- Change severity if situation changes
- Add new attachments
- Click Update Recommendation to save
When changing status to “Completed”, document what action was taken in the description.
Filtering and Searching
Use the filter panel to find recommendations:- Search: Text search in titles and descriptions
- Severity: Low, Medium, High, or Critical
- Status: Open, In Progress, Completed, or Overdue
- Site: Filter by location
- Asset: Filter by equipment
- Date Range: Created within specific period
Recommendation Analytics
The dashboard provides insights into recommendation trends:Summary Cards
- Total Recommendations: Overall count with trend percentage
- Open & Overdue: Recommendations past due date
- Overdue Count: Number of delayed actions
Trend Analysis
View monthly trends to identify:- Increasing Recommendations: May indicate deteriorating equipment condition
- High Overdue Rates: Suggests resource or prioritization issues
- Seasonal Patterns: Equipment with recurring issues at specific times
Linking Recommendations to Alarms
Recommendations often originate from alarms:- When viewing an Alarm, note the alarm ID
- Create a recommendation with action steps
- Reference the alarm ID in the description
- The alarm will show the linked recommendation
Best Practices
Writing Effective Recommendations
Good Example:Prioritization Guidelines
- Critical: Address within 24 hours, even if off-shift
- High: Schedule within 3-5 days, plan parts and resources
- Medium: Complete within 2 weeks during regular maintenance
- Low: Bundle with next scheduled service
Documentation
- Before: Attach photos or reports showing the issue
- During: Document parts replaced, procedures followed
- After: Upload verification samples, photos of repaired components
Follow-Up
After completing a recommendation:Document Actions Taken
Update the description with:
- What was done
- Parts replaced
- Any deviations from plan
Schedule Verification
If the recommendation involved oil change or component replacement, schedule a follow-up sample to confirm improvement.
Bulk Actions
For multiple recommendations:- Export: Download list as CSV for external analysis
- Print: Generate printable work orders
- Bulk Status Update: Change status for multiple items (if supported)
Attachments
Supported attachment types:- PDF: Lab reports, service bulletins
- Images: JPG, PNG photos of equipment
- Documents: Word, Excel files
Deleting Recommendations
To delete:- Click the Delete icon
- Confirm in the dialog
Related Features
- Oil Sample Analysis: Primary source of recommendation data
- Alarm Monitoring: Link alarms to corrective actions
- Asset Management: View all recommendations for an asset
- Root Cause Analysis: Investigate recurring recommendation patterns