Merge branch 'main' of https://gitea.centraal.wbd-rd.nl/woutverheijen/rotatingMachine

Reviewed-on: RnD/rotatingMachine#2

README.md

@@ -1 +1,23 @@
-# rotating machine
+# rotating machine
+---Explanation KPIs---
+Mean Time Between Failures: MTBF is a key indicator of asset reliability. It represents the average amount of time between two consecutive failures during normal operation. The higher the value, the better.
+- Formula: MTBF = runtime / failures
+
+Mean Time to Repair: MTTR focuses on the speed of failure recovery. It indicates how long it takes on average to repair a failure and restore the system to operational condition. The lower the value, the better.
+- Formula: MTTR = downtime / failures
+
+Asset Availability: Asset availability indicates how often machines are available for use. Higher availability means that the equipment experiences fewer breakdowns and remains operational for a greater amount of time.
+- Formula: availability = MTBF / (MTBF + MTTR) * 100% 
+
+Asset Health Index: A score ranging from 0 (optimal condition) to 5 (worst case) that reflects the overall health status of an asset.
+
+
+---KPI message---
+The message consists of the following components:
+- asset tagnumber: 
+- asset availability
+- mean time between failures
+- mean time to repair
+- asset health index
+- asset health color: Gives a color based on the asset health index (0 = Darkgreen, 1 = Green, 2 = Yellow, 3 = Orange, 4 = Red, 5 = Darkred.)
+- total failures: the total number of failures that have occured for a particular asset

rotatingMachine.html

@@ -1,3 +1,13 @@
+<!--
+| S88-niveau             | Primair (blokkleur) | Tekstkleur |
+| ---------------------- | ------------------- | ---------- |
+| **Area**               | `#0f52a5`           | wit        |
+| **Process Cell**       | `#0c99d9`           | wit        |
+| **Unit**               | `#50a8d9`           | zwart      |
+| **Equipment (Module)** | `#86bbdd`           | zwart      |
+| **Control Module**     | `#a9daee`           | zwart      |
+
+-->
 <!-- Load the dynamic menu & config endpoints -->
 <script src="/rotatingMachine/menu.js"></script>
 <script src="/rotatingMachine/configData.js"></script>
@@ -5,7 +15,7 @@
 <script>
   RED.nodes.registerType("rotatingMachine", {
     category: "EVOLV",
-    color: "#4f8582",
+    color: "#86bbdd",
         defaults: {
 
           // Define specific properties
@@ -41,7 +51,7 @@
     outputs: 3,
     inputLabels: ["Input"],
     outputLabels: ["process", "dbase", "parent"],
-    icon: "font-awesome/fa-tachometer",
+    icon: "font-awesome/fa-cog",
 
     label: function () {
       return this.positionIcon + " " + this.category.slice(0, -1) || "Machine";

src/specificClass.js

@@ -1,48 +1,3 @@
-/**
- * @file machine.js
- *
- * Permission is hereby granted to any person obtaining a copy of this software 
- * and associated documentation files (the "Software"), to use it for personal 
- * or non-commercial purposes, with the following restrictions:
- *
- * 1. **No Copying or Redistribution**: The Software or any of its parts may not 
- *    be copied, merged, distributed, sublicensed, or sold without explicit 
- *    prior written permission from the author.
- * 
- * 2. **Commercial Use**: Any use of the Software for commercial purposes requires 
- *    a valid license, obtainable only with the explicit consent of the author.
- * 
- * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR 
- * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, 
- * FITNESS FOR A PARTICULAR PURPOSE, AND NONINFRINGEMENT. IN NO EVENT SHALL THE 
- * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES, OR OTHER 
- * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT, OR OTHERWISE, ARISING FROM, 
- * OUT OF, OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE 
- * SOFTWARE.
- *
- * Ownership of this code remainregisterChilds solely with the original author. Unauthorized 
- * use of this Software is strictly prohibited.
- *
- * @summary A class to interact and manipulate machines with a non-euclidian curve
- * @description A class to interact and manipulate machines with a non-euclidian curve
- * @module machine
- * @exports machine
- * @version 0.1.0
- * @since 0.1.0
- * 
- * Author:
- * - Rene De Ren
- * Email:
- * - r.de.ren@brabantsedelta.nl
- * 
- *  Add functionality later
-  // -------- Operational Metrics -------- //
-maintenanceAlert: this.state.checkMaintenanceStatus()
-
-
-*/
-
-//load local dependencies
 const EventEmitter = require('events');
 const {loadCurve,logger,configUtils,configManager,state, nrmse, MeasurementContainer, predict, interpolation , childRegistrationUtils} = require('generalFunctions');
 const { name } = require('../../generalFunctions/src/convert/lodash/lodash._shimkeys');
@@ -116,6 +71,37 @@ class Machine {
     this.child = {}; // object to hold child information so we know on what to subscribe
     this.childRegistrationUtils = new childRegistrationUtils(this); // Child registration utility
 
+        // --- KPI tracking ---
+    this.kpi = {
+      failures: 0,
+      totalRuntimeHours: 0,
+      totalDowntimeHours: 0,
+      lastFailureTime: null,
+      lastRepairTime: null,
+      MTBF: 0,
+      MTTR: 0,
+      availability: 0
+    };
+
+    this.assetHealth = {
+      index: 0  // 0 = optimal, 5 = failure
+    };
+
+    this.state.emitter.on('stateChange', (payload) => {
+
+      const stateStr = typeof payload === 'string'
+        ? payload
+        : (payload?.state ?? payload?.newState ?? payload);
+
+      if (typeof stateStr !== 'string') {
+        this.logger.warn(`stateChange event without parsable state: ${JSON.stringify(payload)}`);
+        return;
+      }
+
+      this._handleStateChangeForKPI(stateStr);
+    });
+
+
   }
 
   /*-------------------               Register child events               -------------------*/
@@ -513,13 +499,12 @@ _callMeasurementHandler(measurementType, value, position, context) {
     }
   }
 
-  //  rich context handler for pressure updates
+  // context handler for pressure updates
   updateMeasuredPressure(value, position, context = {}) {
    
-    //  Enhanced logging with child context
     this.logger.debug(`Pressure update: ${value} at ${position} from ${context.childName || 'child'} (${context.childId || 'unknown-id'})`);
     
-    //  Store in parent's measurement container (your existing logic)
+    //  Store in parent's measurement container 
     this.measurements.type("pressure").variant("measured").position(position).value(value, context.timestamp, context.unit);
 
     // Determine what kind of value to use as pressure (upstream , downstream or difference)
@@ -574,6 +559,136 @@ _callMeasurementHandler(measurementType, value, position, context) {
 
     }
   }
+ 
+/////////////////////////////
+        /**
+     * Compute a single drift score in [0..1] using predicted vs measured series.
+     * Uses min/max of the *predicted* window as normalization range.
+     * If no usable data -> returns 0 (neutral).
+     */
+    _computeDriftScore() {
+      try {
+        const metrics = [
+          { key: "pressure", pos: "downstream" },
+          { key: "flow",     pos: "downstream" },
+          { key: "power",    pos: "atEquipment" }
+        ];
+
+        const values = [];
+
+        for (const m of metrics) {
+          const pred = this.measurements.type(m.key).variant("predicted").position(m.pos).getAllValues()?.values;
+          const meas = this.measurements.type(m.key).variant("measured").position(m.pos).getAllValues()?.values;
+
+          if (!Array.isArray(pred) || !Array.isArray(meas) || pred.length < 2 || meas.length < 2) continue;
+
+          const expectedMin = Math.min(...pred);
+          const expectedMax = Math.max(...pred);
+          if (!Number.isFinite(expectedMin) || !Number.isFinite(expectedMax) || expectedMax === expectedMin) continue;
+
+          const drift = this.errorMetrics.assessDrift(pred, meas, expectedMin, expectedMax);
+          if (Number.isFinite(drift)) {
+            // assessDrift is already normalized; keep it in [0..1]
+            values.push(Math.max(0, Math.min(1, Math.abs(drift))));
+          }
+        }
+
+        if (values.length === 0) return 0; // neutral if no data
+        const avg = values.reduce((s, v) => s + v, 0) / values.length;
+        return Math.max(0, Math.min(1, avg));
+      } catch (e) {
+        this.logger?.warn?.(`Drift score error: ${e.message}`);
+        return 0;
+      }
+    }
+
+    _calculateAssetHealthIndex() {
+      try {
+        // 1) Hard fail -> worst health
+        // if (this.state?.getCurrentState && this.state.getCurrentState() === "failed") 
+        if (["off"].includes(this.state?.getCurrentState?.())){
+          this.assetHealth.index = 5;
+          return 5;
+        }
+
+        // 2) Inputs (clamped to 0..1)
+        const availability   = typeof this.kpi?.availability === 'number' ? this.kpi.availability : 1;
+        const unavailability = 1 - Math.max(0, Math.min(1, availability));
+
+        const effPenalty     = Math.max(0, Math.min(1, typeof this.relDistFromPeak === 'number' ? this.relDistFromPeak : 0));
+
+        const driftScore     = this._computeDriftScore(); // 0..1
+
+        // 3) Blend (weights sum to 1.0)
+        // Tweak these if you like: e.g. make drift more/less important.
+        const wAvail = 0.4;   // unavailability weight
+        const wDrift = 0.4;   // drift weight
+        const wEff   = 0.2;   // efficiency distance weight
+
+        const score01 = (wAvail * unavailability) + (wDrift * driftScore) + (wEff * effPenalty);
+
+        // 4) Scale to 0..5 integer, clamp
+        const index = Math.max(0, Math.min(5, Math.round(score01 * 5)));
+
+        this.assetHealth.index = index;
+        return index;
+      } catch (err) {
+        this.logger?.error?.(`AHI calc error: ${err.message}`);
+        this.assetHealth.index = 0;
+        return 0;
+      }
+    }
+
+_handleStateChangeForKPI(newState) {
+  const now = Date.now();
+  const runtime = this.state.getRunTimeHours();
+  const lastState = this.state.getPreviousState?.() || "unknown";
+
+  // --- Treat OFF as failure and start of downtime ---
+  if (newState === "off") {
+    this.kpi.failures++; // always count a new failure when OFF
+    this.kpi.lastFailureTime = now; // mark the start of downtime
+    this.logger.warn(`Machine OFF (counted as failure). Total failures: ${this.kpi.failures}`);
+  }
+
+  // --- When we leave OFF and become OPERATIONAL, book downtime ---
+  if (newState === "operational") {
+    // Only calculate downtime if we had an OFF period before
+    if (this.kpi.lastFailureTime != null) {
+      const downtimeHours = (now - this.kpi.lastFailureTime) / 3600000;
+      this.kpi.totalDowntimeHours += downtimeHours;
+      this.kpi.lastRepairTime = now; // moment of "repaired"
+      this.kpi.lastFailureTime = null; // close downtime window
+      this.logger.info(`OFF → OPERATIONAL. Added ${downtimeHours.toFixed(2)}h downtime.`);
+    }
+  }
+
+  // --- Compute KPI Metrics ---
+  const failures = this.kpi.failures;
+  const downtime = this.kpi.totalDowntimeHours;
+
+  // If no failures yet: MTBF = total runtime; MTTR = 0
+  this.kpi.MTBF = failures > 0 ? runtime / failures : runtime;
+  this.kpi.MTTR = failures > 0 ? downtime / failures : 0;
+
+  // --- Compute Availability ---
+  const mtbf = this.kpi.MTBF ?? 0;
+  const mttr = this.kpi.MTTR ?? 0;
+
+  if (mtbf <= 0 && mttr <= 0) {
+    this.kpi.availability = 1; // Default: 100% if no data
+  } else {
+    const availability = mtbf / (mtbf + mttr);
+    this.kpi.availability = Math.min(1, Math.max(0, availability)); // clamp 0–1
+  }
+
+  this.logger.debug(
+    `KPI updated — MTBF: ${this.kpi.MTBF.toFixed(2)}h, MTTR: ${this.kpi.MTTR.toFixed(2)}h, ` +
+    `Availability: ${(this.kpi.availability * 100).toFixed(2)}%`
+  );
+}
+
+//////////////////////////////////////////////
 
   calcDistanceFromPeak(currentEfficiency,peakEfficiency){
     return Math.abs(currentEfficiency - peakEfficiency);
@@ -748,6 +863,13 @@ _callMeasurementHandler(measurementType, value, position, context) {
     output["cog"] = this.cog; // flow / power efficiency
     output["NCog"] = this.NCog; // normalized cog
     output["NCogPercent"] = Math.round(this.NCog * 100 * 100) / 100 ;
+    output["kpi_MTBF"] = this.kpi.MTBF;
+    output["kpi_MTTR"] = this.kpi.MTTR;
+    output["kpi_assetAvailability"] = Math.round(this.kpi.availability * 100 * 100) / 100;
+    output["kpi_totalFailuresCount"] = this.kpi.failures;
+    output["asset_tag_number"] = 'L001';
+
+    // output["asset_tag_number"] = this.assetTagNumber;
 
     if(this.flowDrift != null){
       const flowDrift = this.flowDrift;
@@ -762,6 +884,21 @@ _callMeasurementHandler(measurementType, value, position, context) {
     output["effRelDistFromPeak"] = this.relDistFromPeak;
     //this.logger.debug(`Output: ${JSON.stringify(output)}`);
 
+
+    /////////////////////////////////
+    // this._calculateAssetHealthIndex();
+    // output["assetHealthIndex"] = this.assetHealth.index;
+
+    this._calculateAssetHealthIndex();
+    output["assetHealthIndex"] = this.assetHealth.index;
+
+    // 0 = darkgreen, 1 = green, 2 = yellow, 3 = orange, 4 = red, 5 = darkred
+    // const healthColors = ["darkgreen", "green", "yellow", "orange", "red", "darkred"];
+    const healthColors = ["#006400", "#008000", "#FFFF00", "#FFA500", "#FF0000", "#8B0000"];
+    output["assetHealthColor"] = healthColors[this.assetHealth.index] || "unknown";
+    //////////////////////////
+
+
     return output;
   }