{ "name": "Case 58: Equipment Maintenance Predictor", "nodes": [ { "parameters": { "pollTimes": { "item": [ { "mode": "everyMinute" } ] }, "triggerOn": "specificFolder", "folderToWatch": { "__rl": true, "value": "1ELj0WguhLszHMQtI61AsLVhrF_w_o4Os", "mode": "list", "cachedResultName": "Case 58 - Equipment Maintenance Folder", "cachedResultUrl": "https://drive.google.com/drive/folders/1ELj0WguhLszHMQtI61AsLVhrF_w_o4Os" }, "event": "fileCreated", "options": {} }, "id": "6ff7cea3-2758-4d4f-a9fe-8083284f9ee2", "name": "Monitor Inspection Reports Folder", "type": "n8n-nodes-base.googleDriveTrigger", "typeVersion": 1, "position": [ -1056, -64 ], "credentials": { "googleDriveOAuth2Api": { "id": "Cf6MNES8JrQntp3r", "name": "Google Drive account" } } }, { "parameters": { "operation": "download", "fileId": { "__rl": true, "value": "={{ $json.id }}", "mode": "id" }, "options": {} }, "id": "de598b41-acd9-4164-b70d-dcdccf3b83f1", "name": "Download Inspection Report", "type": 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{} }, "id": "a1baee55-4581-4304-8178-3c2803cf294e", "name": "Route Based on Status", "type": "n8n-nodes-base.switch", "typeVersion": 3.3, "position": [ -48, -64 ] }, { "parameters": { "url": "=https://api.cloud.llamaindex.ai/api/v1/parsing/job/{{ $node[\"Upload to Parser\"].json[\"id\"] }}/result/markdown", "sendHeaders": true, "headerParameters": { "parameters": [ { "name": "Authorization", "value": "Bearer llx-7BWYrvPwfUhgdXbZMtaNCsr2O0h7JH4dkHjHisxcvq46bkIj" } ] }, "options": {} }, "id": "9f76f0bb-dac2-469d-b52c-0e2a27f039d3", "name": "Extract Parsed Content", "type": "n8n-nodes-base.httpRequest", "typeVersion": 4.3, "position": [ 160, -160 ] }, { "parameters": { "text": "={{ $json.markdown }}", "attributes": { "attributes": [ { "name": "Asset_ID", "description": "Equipment asset ID or serial number" }, { "name": "Equipment_Type", "description": "Type of equipment (e.g., Compressor, Pump, Motor, Generator)" }, { "name": "Location", "description": "Physical location or facility name" }, { "name": "Inspection_Date", "description": "Date of inspection" }, { "name": "Runtime_Hours", "description": "Total operating hours or runtime" }, { "name": "Vibration_Level_mm_s", "description": "Vibration reading in mm/s" }, { "name": "Temperature_Celsius", "description": "Operating temperature in Celsius" }, { "name": "Oil_Condition", "description": "Oil analysis result or condition (Good/Fair/Poor)" }, { "name": "Noise_Level_dB", "description": "Noise level in decibels" }, { "name": "Visual_Condition", "description": "Visual inspection notes (rust, leaks, cracks, wear)" }, { "name": "Last_Maintenance_Date", "description": "Date of last maintenance or service" }, { "name": "Inspector_Notes", "description": "Any additional observations or concerns" } ] }, "options": {} }, "id": "72dc4784-ec09-4e80-9502-4078265cfd3b", "name": "AI Data Extractor", "type": "@n8n/n8n-nodes-langchain.informationExtractor", "typeVersion": 1.2, "position": [ 336, -160 ] }, { "parameters": { "jsCode": "const inspectionData = $input.first().json.output;\n\n// ROBUST NUMBER EXTRACTION\nconst extractNumber = (str) => {\n if (!str) return 0;\n const cleaned = str.toString().replace(/[^\\d.-]/g, '');\n const num = parseFloat(cleaned);\n return isNaN(num) ? 0 : num;\n};\n\n// EMBEDDED EQUIPMENT DATABASE WITH FAILURE THRESHOLDS\nconst equipmentDatabase = {\n \"Compressor\": {\n max_vibration: 7.1,\n max_temperature: 85,\n max_noise: 85,\n maintenance_interval_hours: 8000,\n critical_runtime_hours: 15000,\n replacement_cost: 450000,\n downtime_cost_per_hour: 25000,\n common_failures: [\"bearing failure\", \"seal leak\", \"motor burnout\"]\n },\n \"Centrifugal Pump\": {\n max_vibration: 4.5,\n max_temperature: 70,\n max_noise: 75,\n maintenance_interval_hours: 6000,\n critical_runtime_hours: 12000,\n replacement_cost: 180000,\n downtime_cost_per_hour: 15000,\n common_failures: [\"impeller wear\", \"seal failure\", \"cavitation\"]\n },\n \"Electric Motor\": {\n max_vibration: 3.5,\n max_temperature: 80,\n max_noise: 80,\n maintenance_interval_hours: 10000,\n critical_runtime_hours: 20000,\n replacement_cost: 220000,\n downtime_cost_per_hour: 18000,\n common_failures: [\"winding failure\", \"bearing damage\", \"overheating\"]\n },\n \"Generator\": {\n max_vibration: 5.0,\n max_temperature: 90,\n max_noise: 90,\n maintenance_interval_hours: 5000,\n critical_runtime_hours: 10000,\n replacement_cost: 850000,\n downtime_cost_per_hour: 50000,\n common_failures: [\"alternator failure\", \"fuel system issue\", \"cooling system failure\"]\n },\n \"Hydraulic Press\": {\n max_vibration: 6.0,\n max_temperature: 65,\n max_noise: 80,\n maintenance_interval_hours: 4000,\n critical_runtime_hours: 8000,\n replacement_cost: 320000,\n downtime_cost_per_hour: 22000,\n common_failures: [\"hydraulic leak\", \"cylinder failure\", \"valve malfunction\"]\n },\n \"Conveyor Belt System\": {\n max_vibration: 2.5,\n max_temperature: 50,\n max_noise: 70,\n maintenance_interval_hours: 3000,\n critical_runtime_hours: 6000,\n replacement_cost: 125000,\n downtime_cost_per_hour: 12000,\n common_failures: [\"belt wear\", \"roller bearing failure\", \"motor failure\"]\n }\n};\n\n// OIL CONDITION SCORING\nconst oilConditionScores = {\n \"Good\": 0,\n \"Excellent\": 0,\n \"Fair\": 1,\n \"Satisfactory\": 1,\n \"Poor\": 3,\n \"Bad\": 3,\n \"Critical\": 5,\n \"Contaminated\": 4\n};\n\n// VISUAL CONDITION KEYWORDS\nconst criticalVisualKeywords = [\"crack\", \"leak\", \"rust\", \"corrosion\", \"excessive wear\", \"damage\", \"broken\"];\n\n// Extract inspection data\nconst assetID = inspectionData.Asset_ID || 'UNKNOWN';\nconst equipmentType = inspectionData.Equipment_Type || 'Unknown';\nconst location = inspectionData.Location || 'Unknown';\nconst inspectionDate = inspectionData.Inspection_Date || new Date().toISOString().split('T')[0];\nconst runtimeHours = extractNumber(inspectionData.Runtime_Hours);\nconst vibrationLevel = extractNumber(inspectionData.Vibration_Level_mm_s);\nconst temperature = extractNumber(inspectionData.Temperature_Celsius);\nconst oilCondition = (inspectionData.Oil_Condition || 'Unknown').trim();\nconst noiseLevel = extractNumber(inspectionData.Noise_Level_dB);\nconst visualCondition = (inspectionData.Visual_Condition || '').toLowerCase();\nconst lastMaintenanceDate = inspectionData.Last_Maintenance_Date || 'Not recorded';\nconst inspectorNotes = inspectionData.Inspector_Notes || 'None';\n\n// Get equipment specifications\nconst equipmentSpecs = equipmentDatabase[equipmentType] || {\n max_vibration: 5.0,\n max_temperature: 75,\n max_noise: 80,\n maintenance_interval_hours: 5000,\n critical_runtime_hours: 10000,\n replacement_cost: 250000,\n downtime_cost_per_hour: 20000,\n common_failures: [\"general wear\"]\n};\n\n// INTELLIGENCE 1: Calculate days since last maintenance\nlet daysSinceLastMaintenance = 'Unknown';\nlet maintenanceOverdue = false;\nif (lastMaintenanceDate !== 'Not recorded') {\n try {\n const lastMaintDate = new Date(lastMaintenanceDate);\n const inspectDate = new Date(inspectionDate);\n daysSinceLastMaintenance = Math.floor((inspectDate - lastMaintDate) / (1000 * 60 * 60 * 24));\n \n const expectedMaintenanceInterval = Math.floor(equipmentSpecs.maintenance_interval_hours / 24);\n maintenanceOverdue = daysSinceLastMaintenance > expectedMaintenanceInterval;\n } catch (e) {\n daysSinceLastMaintenance = 'Invalid date';\n }\n}\n\n// INTELLIGENCE 2: Calculate failure risk score (0-100)\nlet failureRiskScore = 0;\nconst riskFactors = [];\n\n// Vibration analysis\nif (vibrationLevel > equipmentSpecs.max_vibration) {\n const vibrationExcess = ((vibrationLevel - equipmentSpecs.max_vibration) / equipmentSpecs.max_vibration * 100);\n failureRiskScore += Math.min(vibrationExcess, 25);\n riskFactors.push(`Vibration ${vibrationExcess.toFixed(0)}% above threshold`);\n}\n\n// Temperature analysis\nif (temperature > equipmentSpecs.max_temperature) {\n const tempExcess = ((temperature - equipmentSpecs.max_temperature) / equipmentSpecs.max_temperature * 100);\n failureRiskScore += Math.min(tempExcess, 20);\n riskFactors.push(`Temperature ${tempExcess.toFixed(0)}% above normal`);\n}\n\n// Noise analysis\nif (noiseLevel > equipmentSpecs.max_noise) {\n const noiseExcess = ((noiseLevel - equipmentSpecs.max_noise) / equipmentSpecs.max_noise * 100);\n failureRiskScore += Math.min(noiseExcess, 15);\n riskFactors.push(`Excessive noise detected`);\n}\n\n// Oil condition analysis\nconst oilScore = oilConditionScores[oilCondition] || 0;\nfailureRiskScore += oilScore * 5;\nif (oilScore >= 3) {\n riskFactors.push(`Oil condition: ${oilCondition}`);\n}\n\n// Runtime analysis\nconst runtimePercent = (runtimeHours / equipmentSpecs.critical_runtime_hours) * 100;\nif (runtimePercent > 80) {\n failureRiskScore += (runtimePercent - 80);\n riskFactors.push(`Runtime at ${runtimePercent.toFixed(0)}% of critical threshold`);\n}\n\n// Visual inspection analysis\nconst hasVisualIssues = criticalVisualKeywords.some(keyword => visualCondition.includes(keyword));\nif (hasVisualIssues) {\n failureRiskScore += 15;\n riskFactors.push('Critical visual defects detected');\n}\n\n// Maintenance overdue penalty\nif (maintenanceOverdue) {\n failureRiskScore += 10;\n riskFactors.push('Maintenance overdue');\n}\n\nfailureRiskScore = Math.min(Math.round(failureRiskScore), 100);\n\n// INTELLIGENCE 3: Determine health status and priority\nlet healthStatus = 'Good';\nlet maintenancePriority = 'Low';\nlet maintenanceUrgency = 'Routine';\n\nif (failureRiskScore >= 70) {\n healthStatus = 'Critical';\n maintenancePriority = 'Emergency';\n maintenanceUrgency = 'Immediate (0-3 days)';\n} else if (failureRiskScore >= 50) {\n healthStatus = 'Poor';\n maintenancePriority = 'High';\n maintenanceUrgency = 'Urgent (1-2 weeks)';\n} else if (failureRiskScore >= 30) {\n healthStatus = 'Fair';\n maintenancePriority = 'Medium';\n maintenanceUrgency = 'Scheduled (2-4 weeks)';\n} else {\n healthStatus = 'Good';\n maintenancePriority = 'Low';\n maintenanceUrgency = 'Routine (next service cycle)';\n}\n\n// INTELLIGENCE 4: Calculate failure probability\nconst failureProbability = Math.min((failureRiskScore / 100 * 80) + (runtimePercent > 100 ? 20 : 0), 95);\n\n// INTELLIGENCE 5: Cost analysis\nconst estimatedDowntimeDays = failureRiskScore >= 70 ? 5 : failureRiskScore >= 50 ? 3 : 1;\nconst breakdownCost = equipmentSpecs.replacement_cost + (equipmentSpecs.downtime_cost_per_hour * estimatedDowntimeDays * 8);\nconst preventiveCost = equipmentSpecs.replacement_cost * 0.15;\nconst costAvoidance = breakdownCost - preventiveCost;\n\n// INTELLIGENCE 6: Generate recommendations\nconst recommendations = [];\n\nif (failureRiskScore >= 70) {\n recommendations.push('STOP OPERATIONS - Schedule immediate shutdown and inspection');\n recommendations.push('Arrange emergency maintenance crew');\n recommendations.push('Prepare backup equipment if available');\n}\n\nif (vibrationLevel > equipmentSpecs.max_vibration) {\n recommendations.push('Check bearing alignment and lubrication');\n recommendations.push('Inspect for loose mountings or imbalance');\n}\n\nif (temperature > equipmentSpecs.max_temperature) {\n recommendations.push('Verify cooling system operation');\n recommendations.push('Check for excessive load or friction');\n}\n\nif (oilScore >= 3) {\n recommendations.push('Perform oil change immediately');\n recommendations.push('Check for contamination sources');\n}\n\nif (hasVisualIssues) {\n recommendations.push('Conduct detailed visual inspection');\n recommendations.push('Document defects with photos');\n}\n\nif (runtimePercent > 80) {\n recommendations.push('Plan major overhaul or replacement');\n recommendations.push('Review equipment lifecycle and ROI');\n}\n\nif (maintenanceOverdue) {\n recommendations.push('Execute overdue preventive maintenance');\n}\n\nif (recommendations.length === 0) {\n recommendations.push('Continue normal monitoring schedule');\n recommendations.push('Document current baseline readings');\n}\n\n// INTELLIGENCE 7: Parts procurement suggestions\nconst partsToProcure = [];\nif (failureRiskScore >= 50) {\n equipmentSpecs.common_failures.forEach(failure => {\n partsToProcure.push(failure.split(' ')[0] + ' replacement kit');\n });\n}\n\nreturn {\n json: {\n Asset_ID: assetID,\n Equipment_Type: equipmentType,\n Location: location,\n Inspection_Date: inspectionDate,\n Runtime_Hours: runtimeHours.toFixed(0),\n Days_Since_Last_Maintenance: String(daysSinceLastMaintenance),\n Vibration_Level_mm_s: vibrationLevel.toFixed(2),\n Vibration_Status: vibrationLevel > equipmentSpecs.max_vibration ? `⚠️ HIGH (>${equipmentSpecs.max_vibration})` : '✓ Normal',\n Temperature_Celsius: temperature.toFixed(1),\n Temperature_Status: temperature > equipmentSpecs.max_temperature ? `⚠️ HIGH (>${equipmentSpecs.max_temperature})` : '✓ Normal',\n Oil_Condition: oilCondition,\n Noise_Level_dB: noiseLevel.toFixed(0),\n Visual_Issues_Detected: hasVisualIssues ? 'Yes - Critical defects found' : 'No',\n Health_Status: healthStatus,\n Failure_Risk_Score: `${failureRiskScore}/100`,\n Failure_Probability_Percent: failureProbability.toFixed(1) + '%',\n Risk_Factors: riskFactors.join('; ') || 'None',\n Maintenance_Priority: maintenancePriority,\n Maintenance_Urgency: maintenanceUrgency,\n Estimated_Breakdown_Cost_INR: breakdownCost.toFixed(0),\n Preventive_Maintenance_Cost_INR: preventiveCost.toFixed(0),\n Cost_Avoidance_INR: costAvoidance.toFixed(0),\n Recommendations: recommendations.join('; '),\n Parts_to_Procure: partsToProcure.join(', ') || 'None at this time',\n Inspector_Notes: inspectorNotes,\n Processing_Timestamp: new Date().toISOString()\n }\n};" }, "id": "07e2e6f8-29da-4b8a-842d-6f5bceabf722", "name": "Maintenance Prediction Analyzer", "type": "n8n-nodes-base.code", "typeVersion": 2, "position": [ 592, -160 ] }, { "parameters": { "operation": "append", "documentId": { "__rl": true, "value": "1gJ4NeeeI6kSYX-3fn-iY2uFPSmYNBMrt8Zu60atp_ec", "mode": "list", "cachedResultName": "Case 58 Equipment Maintenance Log", "cachedResultUrl": "https://docs.google.com/spreadsheets/d/1gJ4NeeeI6kSYX-3fn-iY2uFPSmYNBMrt8Zu60atp_ec/edit?usp=drivesdk" }, "sheetName": { "__rl": true, "value": "gid=0", "mode": "list", "cachedResultName": "Sheet1", "cachedResultUrl": "https://docs.google.com/spreadsheets/d/1gJ4NeeeI6kSYX-3fn-iY2uFPSmYNBMrt8Zu60atp_ec/edit#gid=0" }, "columns": { "mappingMode": "autoMapInputData", "value": {}, "matchingColumns": [], "schema": [ { "id": "Asset_ID", "displayName": "Asset_ID", "required": false, "defaultMatch": false, "display": true, "type": "string", "canBeUsedToMatch": true }, { "id": "Equipment_Type", "displayName": "Equipment_Type", "required": false, "defaultMatch": false, "display": true, "type": "string", "canBeUsedToMatch": true }, { "id": "Location", "displayName": "Location", "required": false, "defaultMatch": false, "display": true, "type": "string", "canBeUsedToMatch": true }, { "id": "Inspection_Date", "displayName": "Inspection_Date", "required": false, "defaultMatch": false, "display": true, "type": "string", "canBeUsedToMatch": true }, { "id": "Runtime_Hours", "displayName": "Runtime_Hours", "required": false, "defaultMatch": false, "display": true, "type": "string", "canBeUsedToMatch": true }, { "id": "Days_Since_Last_Maintenance", "displayName": "Days_Since_Last_Maintenance", "required": false, "defaultMatch": false, "display": true, "type": "string", "canBeUsedToMatch": true }, { "id": "Vibration_Level_mm_s", "displayName": "Vibration_Level_mm_s", "required": false, "defaultMatch": false, "display": true, "type": "string", "canBeUsedToMatch": true }, { "id": "Vibration_Status", "displayName": "Vibration_Status", "required": false, "defaultMatch": false, "display": true, "type": "string", "canBeUsedToMatch": true }, { "id": "Temperature_Celsius", "displayName": "Temperature_Celsius", "required": false, "defaultMatch": false, "display": true, "type": "string", "canBeUsedToMatch": true }, { "id": "Temperature_Status", "displayName": "Temperature_Status", "required": false, "defaultMatch": false, "display": true, "type": "string", "canBeUsedToMatch": true }, { "id": "Oil_Condition", "displayName": "Oil_Condition", "required": false, "defaultMatch": false, "display": true, "type": "string", "canBeUsedToMatch": true }, { "id": "Noise_Level_dB", "displayName": "Noise_Level_dB", "required": false, "defaultMatch": false, "display": true, "type": "string", "canBeUsedToMatch": true }, { "id": "Visual_Issues_Detected", "displayName": "Visual_Issues_Detected", "required": false, "defaultMatch": false, "display": true, "type": "string", "canBeUsedToMatch": true }, { "id": "Health_Status", "displayName": "Health_Status", "required": false, "defaultMatch": false, "display": true, "type": "string", "canBeUsedToMatch": true }, { "id": "Failure_Risk_Score", "displayName": "Failure_Risk_Score", "required": false, "defaultMatch": false, "display": true, "type": "string", "canBeUsedToMatch": true }, { "id": "Failure_Probability_Percent", "displayName": "Failure_Probability_Percent", "required": false, "defaultMatch": false, "display": true, "type": "string", "canBeUsedToMatch": true }, { "id": "Risk_Factors", "displayName": "Risk_Factors", "required": false, "defaultMatch": false, "display": true, "type": "string", "canBeUsedToMatch": true }, { "id": "Maintenance_Priority", "displayName": "Maintenance_Priority", "required": false, "defaultMatch": false, "display": true, "type": "string", "canBeUsedToMatch": true }, { "id": "Maintenance_Urgency", "displayName": "Maintenance_Urgency", "required": false, "defaultMatch": false, "display": true, "type": "string", "canBeUsedToMatch": true }, { "id": "Estimated_Breakdown_Cost_INR", "displayName": "Estimated_Breakdown_Cost_INR", "required": false, "defaultMatch": false, "display": true, "type": "string", "canBeUsedToMatch": true }, { "id": "Preventive_Maintenance_Cost_INR", "displayName": "Preventive_Maintenance_Cost_INR", "required": false, "defaultMatch": false, "display": true, "type": "string", "canBeUsedToMatch": true }, { "id": "Cost_Avoidance_INR", "displayName": "Cost_Avoidance_INR", "required": false, "defaultMatch": false, "display": true, "type": "string", "canBeUsedToMatch": true }, { "id": "Recommendations", "displayName": "Recommendations", "required": false, "defaultMatch": false, "display": true, "type": "string", "canBeUsedToMatch": true }, { "id": "Parts_to_Procure", "displayName": "Parts_to_Procure", "required": false, "defaultMatch": false, "display": true, "type": "string", "canBeUsedToMatch": true }, { "id": "Inspector_Notes", "displayName": "Inspector_Notes", "required": false, "defaultMatch": false, "display": true, "type": "string", "canBeUsedToMatch": true }, { "id": "Processing_Timestamp", "displayName": "Processing_Timestamp", "required": false, "defaultMatch": false, "display": true, "type": "string", "canBeUsedToMatch": true } ], "attemptToConvertTypes": false, "convertFieldsToString": false }, "options": {} }, "id": "009468a8-efb9-45ca-9cf4-25ee27da9ae9", "name": "Log to Google Sheets", "type": "n8n-nodes-base.googleSheets", "typeVersion": 4.7, "position": [ 768, -160 ], "credentials": { "googleSheetsOAuth2Api": { "id": "LOs2dbk9lby0NfDM", "name": "Google Sheets account" } } }, { "parameters": { "jsCode": "const data = $input.first().json;\n\nconst assetID = data.Asset_ID || 'Unknown';\nconst equipmentType = data.Equipment_Type || 'Equipment';\nconst healthStatus = data.Health_Status || 'Unknown';\nconst priority = data.Maintenance_Priority || 'Unknown';\nconst riskScore = data.Failure_Risk_Score || '0/100';\n\nconst isCritical = priority === 'Emergency';\nconst isHighPriority = priority === 'High';\n\nconst emailSubject = isCritical \n ? `🚨 CRITICAL: ${equipmentType} ${assetID} Failure Imminent` \n : isHighPriority\n ? `⚠️ HIGH PRIORITY: ${equipmentType} ${assetID} Maintenance Required`\n : `Maintenance Prediction Report - ${equipmentType} ${assetID}`;\n\nconst emailBody = `Dear Maintenance Team,\n\nAn equipment inspection report has been processed with predictive maintenance analysis.\n\n━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\n🔧 EQUIPMENT DETAILS\n━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\nAsset ID: ${data.Asset_ID}\nEquipment Type: ${data.Equipment_Type}\nLocation: ${data.Location}\nInspection Date: ${data.Inspection_Date}\nRuntime Hours: ${data.Runtime_Hours}\nDays Since Last Maintenance: ${data.Days_Since_Last_Maintenance}\n\n━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\n📊 CONDITION ASSESSMENT\n━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\nVibration: ${data.Vibration_Level_mm_s} mm/s - ${data.Vibration_Status}\nTemperature: ${data.Temperature_Celsius}°C - ${data.Temperature_Status}\nOil Condition: ${data.Oil_Condition}\nNoise Level: ${data.Noise_Level_dB} dB\nVisual Issues: ${data.Visual_Issues_Detected}\n\n━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\n⚠️ FAILURE RISK ANALYSIS\n━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\nHealth Status: ${healthStatus}\nFailure Risk Score: ${riskScore}\nFailure Probability: ${data.Failure_Probability_Percent}\nRisk Factors: ${data.Risk_Factors}\n\n━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\n🎯 MAINTENANCE PRIORITY\n━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\nPriority Level: ${priority}\nMaintenance Urgency: ${data.Maintenance_Urgency}\n\n━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\n💰 COST ANALYSIS\n━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\nEstimated Breakdown Cost: ₹${data.Estimated_Breakdown_Cost_INR}\nPreventive Maintenance Cost: ₹${data.Preventive_Maintenance_Cost_INR}\nPotential Cost Avoidance: ₹${data.Cost_Avoidance_INR}\n\n━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\n✅ RECOMMENDED ACTIONS\n━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\n${data.Recommendations}\n\n━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\n🔩 PARTS PROCUREMENT\n━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\n${data.Parts_to_Procure}\n\n━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\n📝 INSPECTOR NOTES\n━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\n${data.Inspector_Notes}\n\n${\n isCritical \n ? `🚨 CRITICAL ALERT: This equipment requires IMMEDIATE attention to prevent catastrophic failure and production shutdown. Execute emergency maintenance protocol.` \n : isHighPriority \n ? `⚠️ HIGH PRIORITY: Schedule maintenance within the recommended timeframe to avoid unplanned downtime.` \n : `✓ ROUTINE: Equipment is operating within acceptable parameters. Continue normal monitoring.`\n}\n\n━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\nProcessed: ${data.Processing_Timestamp}\n\nThis is an automated predictive analysis from the Equipment Maintenance System.\nFor detailed metrics, refer to the Maintenance Predictions dashboard.\n\nBest regards,\nPredictive Maintenance System`;\n\nreturn {\n json: {\n email_subject: emailSubject,\n email_body: emailBody,\n recipient_email: 'maintenance.manager@company.com',\n cc_email: isCritical ? 'operations.head@company.com, plant.manager@company.com' : 'operations.head@company.com',\n asset_id: assetID,\n priority: priority,\n risk_score: riskScore\n }\n};" }, "id": "b40e41ce-7d12-416c-a8b0-b24b605f6a31", "name": "Generate Email Summary", "type": "n8n-nodes-base.code", "typeVersion": 2, "position": [ 976, -160 ] }, { "parameters": { "sendTo": "={{ $json.recipient_email }}", "subject": "={{ $json.email_subject }}", "emailType": "text", "message": "={{ $json.email_body }}", "options": {} }, "id": "ac1a76ef-6678-4c62-a424-ba4b0b854874", "name": "Send Email via Gmail", "type": "n8n-nodes-base.gmail", "typeVersion": 2.1, "position": [ 1168, -160 ], "webhookId": "1d35cae5-0fe5-4d41-9d6f-92f2ca90ff0f", "credentials": { "gmailOAuth2": { "id": "cyqCGWcggZNMcSOv", "name": "Gmail account" } } }, { "parameters": { "model": { "__rl": true, "value": "gpt-4o-mini", "mode": "list" }, "builtInTools": {}, "options": {} }, "id": "0e1d57b0-aaee-47ff-b7af-cec4571bdd68", "name": "OpenAI GPT-4o Mini", "type": "@n8n/n8n-nodes-langchain.lmChatOpenAi", "typeVersion": 1.3, "position": [ 336, 48 ], "credentials": { "openAiApi": { "id": "ICwxUBbatsF2sDvy", "name": "OpenAi account" } } } ], "pinData": {}, "connections": { "Monitor Inspection Reports Folder": { "main": [ [ { "node": "Download Inspection Report", "type": "main", "index": 0 } ] ] }, "Download Inspection Report": { "main": [ [ { "node": "Upload to Parser", "type": "main", "index": 0 } ] ] }, "Upload to Parser": { "main": [ [ { "node": "Wait for Parsing", "type": "main", "index": 0 } ] ] }, "Wait for Parsing": { "main": [ [ { "node": "Check Parsing Status", "type": "main", "index": 0 } ] ] }, "Check Parsing Status": { "main": [ [ { "node": "Route Based on Status", "type": "main", "index": 0 } ] ] }, "Route Based on Status": { "main": [ [ { "node": "Extract Parsed Content", "type": "main", "index": 0 } ], [ { "node": "Wait for Parsing", "type": "main", "index": 0 } ] ] }, "Extract Parsed Content": { "main": [ [ { "node": "AI Data Extractor", "type": "main", "index": 0 } ] ] }, "AI Data Extractor": { "main": [ [ { "node": "Maintenance Prediction Analyzer", "type": "main", "index": 0 } ] ] }, "Maintenance Prediction Analyzer": { "main": [ [ { "node": "Log to Google Sheets", "type": "main", "index": 0 } ] ] }, "Log to Google Sheets": { "main": [ [ { "node": "Generate Email Summary", "type": "main", "index": 0 } ] ] }, "Generate Email Summary": { "main": [ [ { "node": "Send Email via Gmail", "type": "main", "index": 0 } ] ] }, "OpenAI GPT-4o Mini": { "ai_languageModel": [ [ { "node": "AI Data Extractor", "type": "ai_languageModel", "index": 0 } ] ] } }, "active": false, "settings": { "executionOrder": "v1" }, "versionId": "c3519898-6688-414d-b1a4-242898693946", "meta": { "templateCredsSetupCompleted": true, "instanceId": "3a43da28588548e21903e71cf1dc3ddd65c24bf0c62e7e4b77542ffe87ad79c6" }, "id": "X9gQKBR57tquo6uW", "tags": [] }