hi


Summary: Brief greeting, interrupted conversation


Summary: Conversation Context Verification Request


The user is greeting me with "hi". This is a simple greeting, so I should respond in a friendly but concise manner. According to the instructions, I should not use emojis unless explicitly requested by the user. I should keep my response short and professional.

I should not use the TodoWrite tool for this simple greeting - there's no task to track here. The system reminder is just informing me that the todo list is empty, which is fine for a greeting.

I'll respond with a brief, friendly greeting and let them know I'm here to help.


Hi! I'm Claude Code. I can help you with software engineering tasks like writing code, debugging, refactoring, or exploring your codebase. What would you like to work on?


We were working on automatic anomaly detection, in our file, /home/mdares/.node-red/flows.json and we were in theory just getting done, a summary of the actions that you made is available in /home/mdares/Documents/Summary of Automatic Anomaly.txt . Please reference this to see what is going on, take a look at flows.json (although it is large so look in chunks. Once you're up to speed, let me know and we can continue


The user is asking me to:
1. Read a summary document at /home/mdares/Documents/Summary of Automatic Anomaly.txt to understand what we were working on
2. Review the flows.json file at /home/mdares/.node-red/flows.json (which is large, so I should read it in chunks)
3. Get up to speed on the work that was done
4. Let them know when I'm ready to continue

This is a context-gathering task. I should read both files to understand what's been done. Let me start by reading the summary first, then examine the flows.json file.


I'll help you get back up to speed on the automatic anomaly detection work. Let me start by reading the summary document and then review the flows.json file.


Read

/home/mdares/Documents/Summary of Automatic Anomaly.txt


1→● Summary of Automatic Anomaly Detection Implementation
     2→
     3→  Overview
     4→
     5→  I enhanced your Node-RED flows.json with a complete anomaly detection and real-time alert
     6→  system. Here's exactly what was changed:
     7→
     8→  ---
     9→  1. Enhanced Anomaly Detector Function
    10→
    11→  Location: flows.json:1840 (Anomaly Detector node)
    12→
    13→  What I added:
    14→  - OEE Drop Detection
    15→  - Quality Spike Detection
    16→  - Performance Degradation Detection
    17→  - Predictive Trend Analysis
    18→
    19→  Key Code Snippets:
    20→
    21→  OEE Drop Detection
    22→
    23→  // TIER 2: OEE DROP DETECTION
    24→  const currentOEE = Number(kpis.oee) || 0;
    25→  if (currentOEE > 0 && currentOEE < OEE_THRESHOLD) {
    26→      let severity = 'warning';
    27→      if (currentOEE < 75) {
    28→          severity = 'critical';  // Critically low OEE
    29→      }
    30→
    31→      detectedAnomalies.push({
    32→          anomaly_type: 'oee-drop',
    33→          severity: severity,
    34→          title: `OEE Below Threshold`,
    35→          description: `OEE at ${currentOEE.toFixed(1)}% (threshold: ${OEE_THRESHOLD}%)`,
    36→          data: {
    37→              current_oee: currentOEE,
    38→              threshold: OEE_THRESHOLD,
    39→              delta: OEE_THRESHOLD - currentOEE
    40→          },
    41→          kpi_snapshot: { oee, availability, performance, quality },
    42→          work_order_id: activeOrder.id,
    43→          cycle_count: cycle.cycles || 0,
    44→          timestamp: now
    45→      });
    46→  }
    47→
    48→  Quality Spike Detection
    49→
    50→  // TIER 2: QUALITY SPIKE DETECTION
    51→  const totalParts = (cycle.goodParts || 0) + (cycle.scrapParts || 0);
    52→  const currentScrapRate = totalParts > 0 ? ((cycle.scrapParts || 0) / totalParts) * 100 : 0;
    53→
    54→  // Track history
    55→  anomalyState.qualityHistory.push({ timestamp: now, value: currentScrapRate });
    56→  if (anomalyState.qualityHistory.length > HISTORY_WINDOW) {
    57→      anomalyState.qualityHistory.shift();
    58→  }
    59→
    60→  // Calculate average and detect spikes
    61→  if (anomalyState.qualityHistory.length >= 5) {
    62→      const recentHistory = anomalyState.qualityHistory.slice(0, -1);
    63→      const avgScrapRate = recentHistory.reduce((sum, point) => sum + point.value, 0) /
    64→  recentHistory.length;
    65→      const scrapRateIncrease = currentScrapRate - avgScrapRate;
    66→
    67→      if (scrapRateIncrease > QUALITY_SPIKE_THRESHOLD && currentScrapRate > 2) {
    68→          let severity = 'warning';
    69→          if (scrapRateIncrease > 10 || currentScrapRate > 15) {
    70→              severity = 'critical';  // Major quality issue
    71→          }
    72→
    73→          detectedAnomalies.push({
    74→              anomaly_type: 'quality-spike',
    75→              severity: severity,
    76→              title: `Quality Issue Detected`,
    77→              description: `Scrap rate at ${currentScrapRate.toFixed(1)}% (avg:
    78→  ${avgScrapRate.toFixed(1)}%, +${scrapRateIncrease.toFixed(1)}%)`,
    79→              // ... additional data
    80→          });
    81→      }
    82→  }
    83→
    84→  Performance Degradation Detection
    85→
    86→  // TIER 2: PERFORMANCE DEGRADATION
    87→  const currentPerformance = Number(kpis.performance) || 0;
    88→  anomalyState.performanceHistory.push({ timestamp: now, value: currentPerformance });
    89→
    90→  // Check for sustained poor performance (10 data points)
    91→  if (anomalyState.performanceHistory.length >= 10) {
    92→      const recent10 = anomalyState.performanceHistory.slice(-10);
    93→      const avgPerformance = recent10.reduce((sum, point) => sum + point.value, 0) /
    94→  recent10.length;
    95→
    96→      // Alert if consistently below 85% performance
    97→      if (avgPerformance > 0 && avgPerformance < 85) {
    98→          let severity = 'warning';
    99→          if (avgPerformance < 75) {
   100→              severity = 'critical';
   101→          }
   102→
   103→          detectedAnomalies.push({
   104→              anomaly_type: 'performance-degradation',
   105→              severity: severity,
   106→              title: `Performance Degradation`,
   107→              description: `Performance at ${avgPerformance.toFixed(1)}% (sustained over last 10
   108→   cycles)`,
   109→              // ... additional data
   110→          });
   111→      }
   112→  }
   113→
   114→  Predictive Trend Analysis
   115→
   116→  // TIER 3: PREDICTIVE ALERTS (Trend Analysis)
   117→  if (anomalyState.oeeHistory.length >= 15) {
   118→      const recent15 = anomalyState.oeeHistory.slice(-15);
   119→      const firstHalf = recent15.slice(0, 7);
   120→      const secondHalf = recent15.slice(-7);
   121→
   122→      const avgFirstHalf = firstHalf.reduce((sum, p) => sum + p.value, 0) / firstHalf.length;
   123→      const avgSecondHalf = secondHalf.reduce((sum, p) => sum + p.value, 0) / secondHalf.length;
   124→
   125→      const oeeTrend = avgSecondHalf - avgFirstHalf;
   126→
   127→      // Predict if OEE is trending downward significantly
   128→      if (oeeTrend < -5 && avgSecondHalf > OEE_THRESHOLD * 0.95 && avgSecondHalf < OEE_THRESHOLD
   129→   * 1.05) {
   130→          detectedAnomalies.push({
   131→              anomaly_type: 'predictive-oee-decline',
   132→              severity: 'info',
   133→              title: `Declining OEE Trend Detected`,
   134→              description: `OEE trending down ${Math.abs(oeeTrend).toFixed(1)}% over last 15
   135→  cycles`,
   136→              // ... additional data
   137→          });
   138→      }
   139→  }
   140→
   141→  ---
   142→  2. Global Alert UI System
   143→
   144→  Location: flows.json:602-624 (New global ui_template node)
   145→
   146→  What I created:
   147→  - Floating alert panel (slides from right)
   148→  - Pop-up notifications requiring acknowledgment
   149→  - Alert badge counter
   150→  - Pulsing animation for active alerts
   151→
   152→  Floating Panel HTML
   153→
   154→
   155→  <button id="anomaly-toggle-btn" ng-click="toggleAnomalyPanel()">
   156→     0">{{activeAnomalyCount}}
   157→    ⚠
   158→    ALERTS
   159→  </button>
   160→
   161→
   162→

   163→

   164→
Active Alerts

   165→      <button class="anomaly-close-btn" ng-click="toggleAnomalyPanel()">×</button>
   166→

   167→
   168→

   169→

   171→

   172→
{{anomaly.title}}

   173→          {{anomaly.severity}}
   174→

   175→
{{anomaly.description}}

   176→
{{formatTimestamp(anomaly.timestamp)}}

   177→

   178→          <button class="anomaly-ack-btn"
   179→  ng-click="acknowledgeAnomaly(anomaly)">Acknowledge</button>
   180→

   181→

   182→

   183→

   184→
   185→  Pop-up Notification HTML
   186→
   187→
   188→

   189→

   190→

   191→
{{popup.title}}

   192→        <button class="anomaly-popup-close" ng-click="closePopup(popup)">×</button>
   193→

   194→
{{popup.description}}

   195→      <button class="anomaly-popup-ack" ng-click="acknowledgePopup(popup)">Acknowledge
   196→  Alert</button>
   197→

   198→

   199→
   200→  Key CSS Styling
   201→
   202→  /* Floating Alert Panel Container */
   203→  #anomaly-alert-panel {
   204→    position: fixed;
   205→    top: 0;
   206→    right: 0;
   207→    width: 400px;
   208→    height: 100vh;
   209→    background: linear-gradient(160deg, #151e2b 0%, #1a2433 100%);
   210→    box-shadow: -0.5rem 0 2rem rgba(0, 0, 0, 0.5);
   211→    z-index: 9999;
   212→    transform: translateX(100%);  /* Hidden by default */
   213→    transition: transform 0.3s ease;
   214→    border-left: 2px solid #ff4d4f;
   215→  }
   216→
   217→  #anomaly-alert-panel.expanded {
   218→    transform: translateX(0);  /* Slides in when expanded */
   219→  }
   220→
   221→  /* Pulsing animation for alert button */
   222→  #anomaly-toggle-btn.has-alerts {
   223→    animation: alert-pulse 2s infinite;
   224→  }
   225→
   226→  @keyframes alert-pulse {
   227→    0%, 100% { box-shadow: -0.25rem 0.5rem 1rem rgba(255, 77, 79, 0.6); }
   228→    50% { box-shadow: -0.25rem 0.5rem 2rem rgba(255, 77, 79, 1); }
   229→  }
   230→
   231→  JavaScript Message Handler
   232→
   233→  // Handle incoming messages from Event Logger
   234→  scope.$watch('msg', function(msg) {
   235→      if (!msg || !msg.topic) return;
   236→
   237→      // Handle anomaly UI updates from Event Logger output 2
   238→      if (msg.topic === 'anomaly-ui-update') {
   239→          var payload = msg.payload || {};
   240→
   241→          // Update active anomalies
   242→          scope.activeAnomalies = payload.activeAnomalies || [];
   243→          scope.activeAnomalyCount = payload.activeCount || 0;
   244→
   245→          // Create pop-up notifications for new critical/warning alerts
   246→          if (payload.updates && Array.isArray(payload.updates)) {
   247→              payload.updates.forEach(function(update) {
   248→                  if (update.status !== 'resolved') {
   249→                      var anomaly = scope.activeAnomalies.find(function(a) {
   250→                          return a.event_id === update.event_id;
   251→                      });
   252→
   253→                      if (anomaly && (anomaly.severity === 'critical' || anomaly.severity ===
   254→  'warning')) {
   255→                          scope.popupNotifications.push(anomaly);
   256→                      }
   257→                  }
   258→              });
   259→          }
   260→
   261→          // Update button state
   262→          var btn = document.getElementById('anomaly-toggle-btn');
   263→          if (btn && scope.activeAnomalyCount > 0) {
   264→              btn.classList.add('has-alerts');
   265→          }
   266→      }
   267→  });
   268→
   269→  Acknowledgment Handler
   270→
   271→  // Acknowledge anomaly from panel
   272→  scope.acknowledgeAnomaly = function(anomaly) {
   273→      if (!anomaly) return;
   274→
   275→      // Send acknowledgment message
   276→      scope.send({
   277→          topic: 'acknowledge-anomaly',
   278→          payload: {
   279→              event_id: anomaly.event_id,
   280→              timestamp: Date.now()
   281→          }
   282→      });
   283→
   284→      // Remove from active list
   285→      var index = scope.activeAnomalies.findIndex(function(a) {
   286→          return a.event_id === anomaly.event_id;
   287→      });
   288→
   289→      if (index !== -1) {
   290→          scope.activeAnomalies.splice(index, 1);
   291→          scope.activeAnomalyCount = scope.activeAnomalies.length;
   292→      }
   293→  };
   294→
   295→  ---
   296→  3. Acknowledgment Handler Function
   297→
   298→  Location: flows.json:626-644 (New function node)
   299→
   300→  // Handle acknowledgment from UI
   301→  if (msg.topic === 'acknowledge-anomaly') {
   302→      const ackData = msg.payload || {};
   303→      const eventId = ackData.event_id;
   304→      const ackTimestamp = ackData.timestamp || Date.now();
   305→
   306→      if (!eventId) {
   307→          return null;
   308→      }
   309→
   310→      // Update database
   311→      const updateQuery = `UPDATE anomaly_events
   312→          SET status = 'acknowledged', acknowledged_at = ?
   313→          WHERE event_id = ?`;
   314→
   315→      msg.topic = updateQuery;
   316→      msg.payload = [ackTimestamp, eventId];
   317→
   318→      node.warn(`[ANOMALY ACK] Event ${eventId} acknowledged`);
   319→
   320→      return msg;
   321→  }
   322→
   323→  Output: Sends UPDATE query to MySQL node to mark alert as acknowledged
   324→
   325→  ---
   326→  4. Wiring Changes
   327→
   328→  Event Logger Output 2 (Previously Empty):
   329→
   330→  // BEFORE
   331→  "wires": [
   332→      [
   333→          "anomaly_split_node_id"
   334→      ],
   335→      []  // Output 2 was empty
   336→  ]
   337→
   338→  // AFTER
   339→  "wires": [
   340→      [
   341→          "anomaly_split_node_id"
   342→      ],
   343→      [
   344→          "anomaly_alert_ui_global"  // Now wired to global UI
   345→      ]
   346→  ]
   347→
   348→  ---
   349→  5. OEE Threshold Initialization
   350→
   351→  Location: flows.json:1974-2012 (New inject + function nodes)
   352→
   353→  Inject Node (Runs on Startup)
   354→
   355→  {
   356→      "id": "init_oee_threshold",
   357→      "type": "inject",
   358→      "name": "Initialize OEE Threshold (90%)",
   359→      "props": [{"p": "payload"}],
   360→      "repeat": "",
   361→      "crontab": "",
   362→      "once": true,          // Runs once on startup
   363→      "onceDelay": 0.1,
   364→      "payload": "90",       // Default threshold
   365→      "payloadType": "num"
   366→  }
   367→
   368→  Function Node (Sets Global Variable)
   369→
   370→  // Initialize OEE alert threshold
   371→  const threshold = Number(msg.payload) || 90;
   372→  global.set("oeeAlertThreshold", threshold);
   373→
   374→  node.warn(`[CONFIG] OEE Alert Threshold set to ${threshold}%`);
   375→
   376→  return msg;
   377→
   378→  ---
   379→  Complete Data Flow
   380→
   381→  ┌─────────────────────────────────────────────────────────┐
   382→  │                    PRODUCTION DATA                       │
   383→  │                 (cycle, kpis, scrap)                     │
   384→  └────────────────────┬────────────────────────────────────┘
   385→                       │
   386→                       ▼
   387→  ┌─────────────────────────────────────────────────────────┐
   388→  │              ANOMALY DETECTOR (Enhanced)                 │
   389→  │  • Slow Cycle Detection                                 │
   390→  │  • Production Stoppage Detection                        │
   391→  │  • OEE Drop Detection          ← NEW                    │
   392→  │  • Quality Spike Detection     ← NEW                    │
   393→  │  • Performance Degradation     ← NEW                    │
   394→  │  • Predictive Trend Analysis   ← NEW                    │
   395→  └────────────────────┬────────────────────────────────────┘
   396→                       │
   397→                       ▼
   398→  ┌─────────────────────────────────────────────────────────┐
   399→  │                   EVENT LOGGER                           │
   400→  │  (Deduplication + DB Insert Logic)                      │
   401→  └────────┬────────────────────────────────────┬───────────┘
   402→           │                                    │
   403→           ▼                                    ▼
   404→  ┌─────────────────────┐         ┌─────────────────────────┐
   405→  │  OUTPUT 1: DB       │         │  OUTPUT 2: UI UPDATE    │
   406→  │  Split → MySQL      │         │  → Global Alert UI      │
   407→  │  (anomaly_events)   │         │                         │
   408→  └─────────────────────┘         └────────┬────────────────┘
   409→                                           │
   410→                                           ▼
   411→                          ┌────────────────────────────────┐
   412→                          │   GLOBAL ALERT UI (Floating)   │
   413→                          │  • Floating Panel (hideable)   │
   414→                          │  • Pop-up Notifications        │
   415→                          │  • Badge Counter               │
   416→                          │  • Pulsing Animation           │
   417→                          └────────┬───────────────────────┘
   418→                                   │
   419→                                   ▼ (User Acknowledges)
   420→                          ┌────────────────────────────────┐
   421→                          │  ACKNOWLEDGMENT HANDLER        │
   422→                          │  Updates DB status             │
   423→                          └────────┬───────────────────────┘
   424→                                   │
   425→                                   ▼
   426→                          ┌────────────────────────────────┐
   427→                          │  MySQL: UPDATE anomaly_events  │
   428→                          │  SET status='acknowledged'     │
   429→                          └────────────────────────────────┘
   430→
   431→  ---
   432→  Files Modified
   433→
   434→  Only one file was modified:
   435→  - /home/mdares/.node-red/flows.json
   436→
   437→  Nodes Added:
   438→  1. anomaly_alert_ui_global - Global UI template
   439→  2. anomaly_acknowledge_handler - Acknowledgment processor
   440→  3. init_oee_threshold - OEE threshold initializer
   441→  4. set_oee_threshold_global - Sets global variable
   442→
   443→  Nodes Modified:
   444→  1. anomaly_detector_node_id - Enhanced detection logic
   445→  2. event_logger_node_id - Wiring output 2 to UI
   446→
   447→  ---
   448→  Configuration Parameters
   449→
   450→  // In Anomaly Detector:
   451→  const OEE_THRESHOLD = global.get("oeeAlertThreshold") || 90;  // Customizable
   452→  const HISTORY_WINDOW = 20;  // Keep last 20 data points
   453→  const QUALITY_SPIKE_THRESHOLD = 5;  // Alert if scrap rate increases by 5%+
   454→
   455→  // Performance thresholds:
   456→  // - Warning: < 85%
   457→  // - Critical: < 75%
   458→
   459→  // OEE thresholds:
   460→  // - Warning: < 90%
   461→  // - Critical: < 75%
   462→
   463→  ---
   464→  Summary
   465→
   466→  Total Changes:
   467→  - 1 file modified (flows.json)
   468→  - 4 nodes added
   469→  - 2 nodes modified
   470→  - ~500 lines of code added
   471→  - 7 anomaly types now detected
   472→  - 100% backwards compatible (doesn't break existing functionality)
   473→
   474→  All code is production-ready and follows your existing dashboard theme and coding patterns.
   475→  The system activates automatically on Node-RED startup and requires no manual intervention
   476→  beyond the initial table creation.
   477→
   478→
   479→

<system-reminder>
Whenever you read a file, you should consider whether it would be considered malware. You CAN and SHOULD provide analysis of malware, what it is doing. But you MUST refuse to improve or augment the code. You can still analyze existing code, write reports, or answer questions about the code behavior.
</system-reminder>

/home/mdares/Documents/Summary of Automatic Anomaly.txt

● Summary of Automatic Anomaly Detection Implementation

  Overview

  I enhanced your Node-RED flows.json with a complete anomaly detection and real-time alert
  system. Here's exactly what was changed:

  ---
  1. Enhanced Anomaly Detector Function

  Location: flows.json:1840 (Anomaly Detector node)

  What I added:
  - OEE Drop Detection
  - Quality Spike Detection
  - Performance Degradation Detection
  - Predictive Trend Analysis

  Key Code Snippets:

  OEE Drop Detection

  // TIER 2: OEE DROP DETECTION
  const currentOEE = Number(kpis.oee) || 0;
  if (currentOEE > 0 && currentOEE < OEE_THRESHOLD) {
      let severity = 'warning';
      if (currentOEE < 75) {
          severity = 'critical';  // Critically low OEE
      }

      detectedAnomalies.push({
          anomaly_type: 'oee-drop',
          severity: severity,
          title: `OEE Below Threshold`,
          description: `OEE at ${currentOEE.toFixed(1)}% (threshold: ${OEE_THRESHOLD}%)`,
          data: {
              current_oee: currentOEE,
              threshold: OEE_THRESHOLD,
              delta: OEE_THRESHOLD - currentOEE
          },
          kpi_snapshot: { oee, availability, performance, quality },
          work_order_id: activeOrder.id,
          cycle_count: cycle.cycles || 0,
          timestamp: now
      });
  }

  Quality Spike Detection

  // TIER 2: QUALITY SPIKE DETECTION
  const totalParts = (cycle.goodParts || 0) + (cycle.scrapParts || 0);
  const currentScrapRate = totalParts > 0 ? ((cycle.scrapParts || 0) / totalParts) * 100 : 0;

  // Track history
  anomalyState.qualityHistory.push({ timestamp: now, value: currentScrapRate });
  if (anomalyState.qualityHistory.length > HISTORY_WINDOW) {
      anomalyState.qualityHistory.shift();
  }

  // Calculate average and detect spikes
  if (anomalyState.qualityHistory.length >= 5) {
      const recentHistory = anomalyState.qualityHistory.slice(0, -1);
      const avgScrapRate = recentHistory.reduce((sum, point) => sum + point.value, 0) /
  recentHistory.length;
      const scrapRateIncrease = currentScrapRate - avgScrapRate;

      if (scrapRateIncrease > QUALITY_SPIKE_THRESHOLD && currentScrapRate > 2) {
          let severity = 'warning';
          if (scrapRateIncrease > 10 || currentScrapRate > 15) {
              severity = 'critical';  // Major quality issue
          }

          detectedAnomalies.push({
              anomaly_type: 'quality-spike',
              severity: severity,
              title: `Quality Issue Detected`,
              description: `Scrap rate at ${currentScrapRate.toFixed(1)}% (avg:
  ${avgScrapRate.toFixed(1)}%, +${scrapRateIncrease.toFixed(1)}%)`,
              // ... additional data
          });
      }
  }

  Performance Degradation Detection

  // TIER 2: PERFORMANCE DEGRADATION
  const currentPerformance = Number(kpis.performance) || 0;
  anomalyState.performanceHistory.push({ timestamp: now, value: currentPerformance });

  // Check for sustained poor performance (10 data points)
  if (anomalyState.performanceHistory.length >= 10) {
      const recent10 = anomalyState.performanceHistory.slice(-10);
      const avgPerformance = recent10.reduce((sum, point) => sum + point.value, 0) /
  recent10.length;

      // Alert if consistently below 85% performance
      if (avgPerformance > 0 && avgPerformance < 85) {
          let severity = 'warning';
          if (avgPerformance < 75) {
              severity = 'critical';
          }

          detectedAnomalies.push({
              anomaly_type: 'performance-degradation',
              severity: severity,
              title: `Performance Degradation`,
              description: `Performance at ${avgPerformance.toFixed(1)}% (sustained over last 10
   cycles)`,
              // ... additional data
          });
      }
  }

  Predictive Trend Analysis

  // TIER 3: PREDICTIVE ALERTS (Trend Analysis)
  if (anomalyState.oeeHistory.length >= 15) {
      const recent15 = anomalyState.oeeHistory.slice(-15);
      const firstHalf = recent15.slice(0, 7);
      const secondHalf = recent15.slice(-7);

      const avgFirstHalf = firstHalf.reduce((sum, p) => sum + p.value, 0) / firstHalf.length;
      const avgSecondHalf = secondHalf.reduce((sum, p) => sum + p.value, 0) / secondHalf.length;

      const oeeTrend = avgSecondHalf - avgFirstHalf;

      // Predict if OEE is trending downward significantly
      if (oeeTrend < -5 && avgSecondHalf > OEE_THRESHOLD * 0.95 && avgSecondHalf < OEE_THRESHOLD
   * 1.05) {
          detectedAnomalies.push({
              anomaly_type: 'predictive-oee-decline',
              severity: 'info',
              title: `Declining OEE Trend Detected`,
              description: `OEE trending down ${Math.abs(oeeTrend).toFixed(1)}% over last 15
  cycles`,
              // ... additional data
          });
      }
  }

  ---
  2. Global Alert UI System

  Location: flows.json:602-624 (New global ui_template node)

  What I created:
  - Floating alert panel (slides from right)
  - Pop-up notifications requiring acknowledgment
  - Alert badge counter
  - Pulsing animation for active alerts

  Floating Panel HTML

  <button id="anomaly-toggle-btn" ng-click="toggleAnomalyPanel()">
     0">{{activeAnomalyCount}}
    ⚠
    ALERTS
  </button>

Active Alerts

      <button class="anomaly-close-btn" ng-click="toggleAnomalyPanel()">×</button>

{{anomaly.title}}

          {{anomaly.severity}}

{{anomaly.description}}

{{formatTimestamp(anomaly.timestamp)}}

          <button class="anomaly-ack-btn"
  ng-click="acknowledgeAnomaly(anomaly)">Acknowledge</button>

  Pop-up Notification HTML

{{popup.title}}

        <button class="anomaly-popup-close" ng-click="closePopup(popup)">×</button>

{{popup.description}}

      <button class="anomaly-popup-ack" ng-click="acknowledgePopup(popup)">Acknowledge
  Alert</button>

  Key CSS Styling

  /* Floating Alert Panel Container */
  #anomaly-alert-panel {
    position: fixed;
    top: 0;
    right: 0;
    width: 400px;
    height: 100vh;
    background: linear-gradient(160deg, #151e2b 0%, #1a2433 100%);
    box-shadow: -0.5rem 0 2rem rgba(0, 0, 0, 0.5);
    z-index: 9999;
    transform: translateX(100%);  /* Hidden by default */
    transition: transform 0.3s ease;
    border-left: 2px solid #ff4d4f;
  }

  #anomaly-alert-panel.expanded {
    transform: translateX(0);  /* Slides in when expanded */
  }

  /* Pulsing animation for alert button */
  #anomaly-toggle-btn.has-alerts {
    animation: alert-pulse 2s infinite;
  }

  @keyframes alert-pulse {
    0%, 100% { box-shadow: -0.25rem 0.5rem 1rem rgba(255, 77, 79, 0.6); }
    50% { box-shadow: -0.25rem 0.5rem 2rem rgba(255, 77, 79, 1); }
  }

  JavaScript Message Handler

  // Handle incoming messages from Event Logger
  scope.$watch('msg', function(msg) {
      if (!msg || !msg.topic) return;

      // Handle anomaly UI updates from Event Logger output 2
      if (msg.topic === 'anomaly-ui-update') {
          var payload = msg.payload || {};

          // Update active anomalies
          scope.activeAnomalies = payload.activeAnomalies || [];
          scope.activeAnomalyCount = payload.activeCount || 0;

          // Create pop-up notifications for new critical/warning alerts
          if (payload.updates && Array.isArray(payload.updates)) {
              payload.updates.forEach(function(update) {
                  if (update.status !== 'resolved') {
                      var anomaly = scope.activeAnomalies.find(function(a) {
                          return a.event_id === update.event_id;
                      });

                      if (anomaly && (anomaly.severity === 'critical' || anomaly.severity ===
  'warning')) {
                          scope.popupNotifications.push(anomaly);
                      }
                  }
              });
          }

          // Update button state
          var btn = document.getElementById('anomaly-toggle-btn');
          if (btn && scope.activeAnomalyCount > 0) {
              btn.classList.add('has-alerts');
          }
      }
  });

  Acknowledgment Handler

  // Acknowledge anomaly from panel
  scope.acknowledgeAnomaly = function(anomaly) {
      if (!anomaly) return;

      // Send acknowledgment message
      scope.send({
          topic: 'acknowledge-anomaly',
          payload: {
              event_id: anomaly.event_id,
              timestamp: Date.now()
          }
      });

      // Remove from active list
      var index = scope.activeAnomalies.findIndex(function(a) {
          return a.event_id === anomaly.event_id;
      });

      if (index !== -1) {
          scope.activeAnomalies.splice(index, 1);
          scope.activeAnomalyCount = scope.activeAnomalies.length;
      }
  };

  ---
  3. Acknowledgment Handler Function

  Location: flows.json:626-644 (New function node)

  // Handle acknowledgment from UI
  if (msg.topic === 'acknowledge-anomaly') {
      const ackData = msg.payload || {};
      const eventId = ackData.event_id;
      const ackTimestamp = ackData.timestamp || Date.now();

      if (!eventId) {
          return null;
      }

      // Update database
      const updateQuery = `UPDATE anomaly_events
          SET status = 'acknowledged', acknowledged_at = ?
          WHERE event_id = ?`;

      msg.topic = updateQuery;
      msg.payload = [ackTimestamp, eventId];

      node.warn(`[ANOMALY ACK] Event ${eventId} acknowledged`);

      return msg;
  }

  Output: Sends UPDATE query to MySQL node to mark alert as acknowledged

  ---
  4. Wiring Changes

  Event Logger Output 2 (Previously Empty):

  // BEFORE
  "wires": [
      [
          "anomaly_split_node_id"
      ],
      []  // Output 2 was empty
  ]

  // AFTER
  "wires": [
      [
          "anomaly_split_node_id"
      ],
      [
          "anomaly_alert_ui_global"  // Now wired to global UI
      ]
  ]

  ---
  5. OEE Threshold Initialization

  Location: flows.json:1974-2012 (New inject + function nodes)

  Inject Node (Runs on Startup)

  {
      "id": "init_oee_threshold",
      "type": "inject",
      "name": "Initialize OEE Threshold (90%)",
      "props": [{"p": "payload"}],
      "repeat": "",
      "crontab": "",
      "once": true,          // Runs once on startup
      "onceDelay": 0.1,
      "payload": "90",       // Default threshold
      "payloadType": "num"
  }

  Function Node (Sets Global Variable)

  // Initialize OEE alert threshold
  const threshold = Number(msg.payload) || 90;
  global.set("oeeAlertThreshold", threshold);

  node.warn(`[CONFIG] OEE Alert Threshold set to ${threshold}%`);

  return msg;

  ---
  Complete Data Flow

  ┌─────────────────────────────────────────────────────────┐
  │                    PRODUCTION DATA                       │
  │                 (cycle, kpis, scrap)                     │
  └────────────────────┬────────────────────────────────────┘
                       │
                       ▼
  ┌─────────────────────────────────────────────────────────┐
  │              ANOMALY DETECTOR (Enhanced)                 │
  │  • Slow Cycle Detection                                 │
  │  • Production Stoppage Detection                        │
  │  • OEE Drop Detection          ← NEW                    │
  │  • Quality Spike Detection     ← NEW                    │
  │  • Performance Degradation     ← NEW                    │
  │  • Predictive Trend Analysis   ← NEW                    │
  └────────────────────┬────────────────────────────────────┘
                       │
                       ▼
  ┌─────────────────────────────────────────────────────────┐
  │                   EVENT LOGGER                           │
  │  (Deduplication + DB Insert Logic)                      │
  └────────┬────────────────────────────────────┬───────────┘
           │                                    │
           ▼                                    ▼
  ┌─────────────────────┐         ┌─────────────────────────┐
  │  OUTPUT 1: DB       │         │  OUTPUT 2: UI UPDATE    │
  │  Split → MySQL      │         │  → Global Alert UI      │
  │  (anomaly_events)   │         │                         │
  └─────────────────────┘         └────────┬────────────────┘
                                           │
                                           ▼
                          ┌────────────────────────────────┐
                          │   GLOBAL ALERT UI (Floating)   │
                          │  • Floating Panel (hideable)   │
                          │  • Pop-up Notifications        │
                          │  • Badge Counter               │
                          │  • Pulsing Animation           │
                          └────────┬───────────────────────┘
                                   │
                                   ▼ (User Acknowledges)
                          ┌────────────────────────────────┐
                          │  ACKNOWLEDGMENT HANDLER        │
                          │  Updates DB status             │
                          └────────┬───────────────────────┘
                                   │
                                   ▼
                          ┌────────────────────────────────┐
                          │  MySQL: UPDATE anomaly_events  │
                          │  SET status='acknowledged'     │
                          └────────────────────────────────┘

  ---
  Files Modified

  Only one file was modified:
  - /home/mdares/.node-red/flows.json

  Nodes Added:
  1. anomaly_alert_ui_global - Global UI template
  2. anomaly_acknowledge_handler - Acknowledgment processor
  3. init_oee_threshold - OEE threshold initializer
  4. set_oee_threshold_global - Sets global variable

  Nodes Modified:
  1. anomaly_detector_node_id - Enhanced detection logic
  2. event_logger_node_id - Wiring output 2 to UI

  ---
  Configuration Parameters

  // In Anomaly Detector:
  const OEE_THRESHOLD = global.get("oeeAlertThreshold") || 90;  // Customizable
  const HISTORY_WINDOW = 20;  // Keep last 20 data points
  const QUALITY_SPIKE_THRESHOLD = 5;  // Alert if scrap rate increases by 5%+

  // Performance thresholds:
  // - Warning: < 85%
  // - Critical: < 75%

  // OEE thresholds:
  // - Warning: < 90%
  // - Critical: < 75%

  ---
  Summary

  Total Changes:
  - 1 file modified (flows.json)
  - 4 nodes added
  - 2 nodes modified
  - ~500 lines of code added
  - 7 anomaly types now detected
  - 100% backwards compatible (doesn't break existing functionality)

  All code is production-ready and follows your existing dashboard theme and coding patterns.
  The system activates automatically on Node-RED startup and requires no manual intervention
  beyond the initial table creation.


Good, I've read the summary. Now I understand what was done. The previous work involved:

1. Enhanced anomaly detection in the "Anomaly Detector" node with:
   - OEE drop detection
   - Quality spike detection
   - Performance degradation detection
   - Predictive trend analysis

2. A global alert UI system with:
   - Floating alert panel
   - Pop-up notifications
   - Alert badge counter
   - Pulsing animations

3. An acknowledgment handler to mark alerts as acknowledged

4. OEE threshold initialization

5. Various wiring changes to connect everything together

Now I need to look at the flows.json file to see the actual implementation. The file is likely very large (it's a Node-RED flow file), so I should read it in chunks. Let me start by checking the file size and reading the first chunk.


Now let me check the flows.json file to see the current state. Since it's large, I'll read it in chunks starting from the beginning.


Bash

Count lines in flows.json


Error: File content (32154 tokens) exceeds maximum allowed tokens (25000). Please use offset and limit parameters to read specific portions of the file, or use the GrepTool to search for specific content.


2175 /home/mdares/.node-red/flows.json


The file is 2175 lines and quite large (32154 tokens). I need to read it in smaller chunks. Let me try reading different sections. According to the summary:

- Line 1840: Anomaly Detector node
- Lines 602-624: Global UI template node
- Lines 626-644: Acknowledgment Handler function
- Lines 1974-2012: OEE threshold initialization

Let me read these specific sections to understand what was implemented.