Okay, I've significantly updated the mockMillData.ts to reflect more dynamic and recent data, added a variety of historical issues spread across the last 45 days, and removed the "No Active Faults" entry.

Here's a breakdown of the changes and the updated code:

Key Changes in mockMillData.ts:

1. Dynamic Timestamps:

   • Introduced helper functions getRelativeTimestampISO (for plot event timestamps and internal logic) and formatTimestampForDisplay (for the lastUpdated field shown in the table).
   • The "High Specific Energy Consumption" (Mill 1) is now the most recent event (minutes ago).
   • "Separator Inefficiency" (Mill 2) is set to be slightly before that (still today).
   • All new historical issues have lastUpdated and eventTimestamp values dynamically generated to be within the last 45 days, creating a sense of recent activity.

2. Removed "No Active Faults":

   • The mill1_normal_op entry has been removed.

3. Added New Historical Issues:

   • Mill 1:

     • "Poor Feed Size Distribution" (Warning, ~10 days ago)
     • "Incorrect Ball Charge / Liner Wear" (Critical, resolved to Normal, ~25 days ago)
     • "High Blaine Targets Leading to Excess Energy Use" (Warning, ~40 days ago)

   • Mill 2:

     • "Low Mill Output with High Power" (Critical, ~5 days ago)
     • "Dust Accumulation in Baghouse Filter" (Warning, ~18 days ago)
     • "High Moisture in Feed Material" (Warning, ~33 days ago)

   • For each new issue, I've:

     • Crafted plausible rca details, parameters reflecting the issue, and keyParametersSummary.
     • Populated trendAnalysisDetails including impactMetrics, historicalData, deviationAnalysis.
     • Generated secBreakdown with relevant correlation plots (secVsTphPlot, secVsBlainePlot) and secByProductType data.
     • Created parameterPlots using generateTimeSeries, ensuring the plot data and eventTimestamp are consistent with the issue's lastUpdated time. The generateTimeSeries function now internally calculates its series start time based on the provided eventTimestamp and eventIndex.

4. Data Integrity for Plots & Functionality:

   • Care has been taken to ensure that the data provided for parameters, deviations, and plots is relevant to the specific fault type.
   • Normal ranges, event magnitudes, and trends in generateTimeSeries have been adjusted to reflect the nature of each issue.
   • Correlation plots (CorrelationScatterPlot) now have currentPoint data that aligns with the issue's parameters.
   • SecByProductType data is included where relevant.

No changes were needed in mldp-dashboard-layout.tsx or other UI components for these data updates, as the existing structure is designed to handle the data dynamically. The sorting, filtering, modals, and plots should continue to function correctly with the new, richer dataset.

Here's the updated mockMillData.ts:

This comprehensive update should make the dashboard feel much more dynamic and provide a richer set of historical data for analysis, with all existing functionalities remaining intact. The timestamps are now relative to the current moment, and the new issues are spread across a 45-day window.

Okay, I'll make those changes to the summary tiles. The "Critical Issues" and "Warnings" will be transformed into small chips and moved to the right side of the header, and the "Normal Operations" card will be removed.

Here's the QuickEdit for app/components/mldp-dashboard-layout.tsx:

These changes will relocate the critical and warning counts as small chips to the header area and remove the normal operations display, streamlining the summary information as requested.