{"type":"file-history-snapshot","messageId":"d32e8088-d2aa-4d5b-87b7-ebd0f6cc0dd1","snapshot":{"messageId":"d32e8088-d2aa-4d5b-87b7-ebd0f6cc0dd1","trackedFileBackups":{},"timestamp":"2025-11-30T20:12:29.365Z"},"isSnapshotUpdate":false} {"parentUuid":null,"isSidechain":false,"userType":"external","cwd":"/home/mdares/Desktop","sessionId":"34f05775-65b2-47e4-b8f8-99196eee47e7","version":"2.0.55","gitBranch":"","type":"user","message":{"role":"user","content":"hi"},"uuid":"d32e8088-d2aa-4d5b-87b7-ebd0f6cc0dd1","timestamp":"2025-11-30T20:12:29.356Z","thinkingMetadata":{"level":"high","disabled":false,"triggers":[]},"todos":[]} {"type":"summary","summary":"Brief greeting, interrupted conversation","leafUuid":"681baaaf-f8af-4bb2-88bc-5399cf3ed7b8"} {"type":"summary","summary":"Conversation Context Verification Request","leafUuid":"c8d07f20-c9ee-4139-ac74-fd092ccd8e4d"} {"parentUuid":"d32e8088-d2aa-4d5b-87b7-ebd0f6cc0dd1","isSidechain":false,"userType":"external","cwd":"/home/mdares/Desktop","sessionId":"34f05775-65b2-47e4-b8f8-99196eee47e7","version":"2.0.55","gitBranch":"","message":{"model":"claude-sonnet-4-5-20250929","id":"msg_0188wzy7bL1DG6bMsyNbVXGr","type":"message","role":"assistant","content":[{"type":"thinking","thinking":"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.\n\nI 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.\n\nI'll respond with a brief, friendly greeting and let them know I'm here to help.","signature":"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"}],"stop_reason":null,"stop_sequence":null,"usage":{"input_tokens":9,"cache_creation_input_tokens":5116,"cache_read_input_tokens":12610,"cache_creation":{"ephemeral_5m_input_tokens":5116,"ephemeral_1h_input_tokens":0},"output_tokens":4,"service_tier":"standard"}},"requestId":"req_011CVegdeCEhZg71AN6AKHfL","type":"assistant","uuid":"96ee694d-ff15-4c61-936d-cab5addb8ea3","timestamp":"2025-11-30T20:12:35.955Z"} {"parentUuid":"96ee694d-ff15-4c61-936d-cab5addb8ea3","isSidechain":false,"userType":"external","cwd":"/home/mdares/Desktop","sessionId":"34f05775-65b2-47e4-b8f8-99196eee47e7","version":"2.0.55","gitBranch":"","message":{"model":"claude-sonnet-4-5-20250929","id":"msg_0188wzy7bL1DG6bMsyNbVXGr","type":"message","role":"assistant","content":[{"type":"text","text":"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?"}],"stop_reason":null,"stop_sequence":null,"usage":{"input_tokens":9,"cache_creation_input_tokens":5116,"cache_read_input_tokens":12610,"cache_creation":{"ephemeral_5m_input_tokens":5116,"ephemeral_1h_input_tokens":0},"output_tokens":170,"service_tier":"standard"}},"requestId":"req_011CVegdeCEhZg71AN6AKHfL","type":"assistant","uuid":"4af7f2be-d0e2-4800-8bea-6e6e98b7a412","timestamp":"2025-11-30T20:12:36.355Z"} {"type":"file-history-snapshot","messageId":"0ffebe55-0bba-4241-85dd-ea4459c350e3","snapshot":{"messageId":"0ffebe55-0bba-4241-85dd-ea4459c350e3","trackedFileBackups":{},"timestamp":"2025-11-30T20:15:16.846Z"},"isSnapshotUpdate":false} {"parentUuid":"4af7f2be-d0e2-4800-8bea-6e6e98b7a412","isSidechain":false,"userType":"external","cwd":"/home/mdares/Desktop","sessionId":"34f05775-65b2-47e4-b8f8-99196eee47e7","version":"2.0.55","gitBranch":"","type":"user","message":{"role":"user","content":"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"},"uuid":"0ffebe55-0bba-4241-85dd-ea4459c350e3","timestamp":"2025-11-30T20:15:16.839Z","thinkingMetadata":{"level":"high","disabled":false,"triggers":[]},"todos":[]} {"parentUuid":"0ffebe55-0bba-4241-85dd-ea4459c350e3","isSidechain":false,"userType":"external","cwd":"/home/mdares/Desktop","sessionId":"34f05775-65b2-47e4-b8f8-99196eee47e7","version":"2.0.55","gitBranch":"","message":{"model":"claude-sonnet-4-5-20250929","id":"msg_01G4YsguiXomii4FR7fu69yA","type":"message","role":"assistant","content":[{"type":"thinking","thinking":"The user is asking me to:\n1. Read a summary document at /home/mdares/Documents/Summary of Automatic Anomaly.txt to understand what we were working on\n2. Review the flows.json file at /home/mdares/.node-red/flows.json (which is large, so I should read it in chunks)\n3. Get up to speed on the work that was done\n4. Let them know when I'm ready to continue\n\nThis 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.","signature":"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"}],"stop_reason":null,"stop_sequence":null,"usage":{"input_tokens":9,"cache_creation_input_tokens":283,"cache_read_input_tokens":17726,"cache_creation":{"ephemeral_5m_input_tokens":283,"ephemeral_1h_input_tokens":0},"output_tokens":7,"service_tier":"standard"}},"requestId":"req_011CVegqsKMVNoZLooozDy9o","type":"assistant","uuid":"191e29c1-b716-4510-bbe7-b5f272fcf692","timestamp":"2025-11-30T20:15:20.643Z"} {"parentUuid":"191e29c1-b716-4510-bbe7-b5f272fcf692","isSidechain":false,"userType":"external","cwd":"/home/mdares/Desktop","sessionId":"34f05775-65b2-47e4-b8f8-99196eee47e7","version":"2.0.55","gitBranch":"","message":{"model":"claude-sonnet-4-5-20250929","id":"msg_01G4YsguiXomii4FR7fu69yA","type":"message","role":"assistant","content":[{"type":"text","text":"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."}],"stop_reason":null,"stop_sequence":null,"usage":{"input_tokens":9,"cache_creation_input_tokens":283,"cache_read_input_tokens":17726,"cache_creation":{"ephemeral_5m_input_tokens":283,"ephemeral_1h_input_tokens":0},"output_tokens":7,"service_tier":"standard"}},"requestId":"req_011CVegqsKMVNoZLooozDy9o","type":"assistant","uuid":"ca354a42-80f2-4ef0-97d2-f4339621e55b","timestamp":"2025-11-30T20:15:21.161Z"} {"parentUuid":"ca354a42-80f2-4ef0-97d2-f4339621e55b","isSidechain":false,"userType":"external","cwd":"/home/mdares/Desktop","sessionId":"34f05775-65b2-47e4-b8f8-99196eee47e7","version":"2.0.55","gitBranch":"","slug":"majestic-toasting-fog","message":{"model":"claude-sonnet-4-5-20250929","id":"msg_01G4YsguiXomii4FR7fu69yA","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_01CEixXiRfoBdUakeSN9gpaE","name":"Read","input":{"file_path":"/home/mdares/Documents/Summary of Automatic Anomaly.txt"}}],"stop_reason":null,"stop_sequence":null,"usage":{"input_tokens":9,"cache_creation_input_tokens":283,"cache_read_input_tokens":17726,"cache_creation":{"ephemeral_5m_input_tokens":283,"ephemeral_1h_input_tokens":0},"output_tokens":250,"service_tier":"standard"}},"requestId":"req_011CVegqsKMVNoZLooozDy9o","type":"assistant","uuid":"59cbbf4b-df8e-4c91-8c9b-f1937e052348","timestamp":"2025-11-30T20:15:21.788Z"} {"parentUuid":"59cbbf4b-df8e-4c91-8c9b-f1937e052348","isSidechain":false,"userType":"external","cwd":"/home/mdares/Desktop","sessionId":"34f05775-65b2-47e4-b8f8-99196eee47e7","version":"2.0.55","gitBranch":"","slug":"majestic-toasting-fog","type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01CEixXiRfoBdUakeSN9gpaE","type":"tool_result","content":" 1→● Summary of Automatic Anomaly Detection Implementation\n 2→\n 3→ Overview\n 4→\n 5→ I enhanced your Node-RED flows.json with a complete anomaly detection and real-time alert\n 6→ system. Here's exactly what was changed:\n 7→\n 8→ ---\n 9→ 1. Enhanced Anomaly Detector Function\n 10→\n 11→ Location: flows.json:1840 (Anomaly Detector node)\n 12→\n 13→ What I added:\n 14→ - OEE Drop Detection\n 15→ - Quality Spike Detection\n 16→ - Performance Degradation Detection\n 17→ - Predictive Trend Analysis\n 18→\n 19→ Key Code Snippets:\n 20→\n 21→ OEE Drop Detection\n 22→\n 23→ // TIER 2: OEE DROP DETECTION\n 24→ const currentOEE = Number(kpis.oee) || 0;\n 25→ if (currentOEE > 0 && currentOEE < OEE_THRESHOLD) {\n 26→ let severity = 'warning';\n 27→ if (currentOEE < 75) {\n 28→ severity = 'critical'; // Critically low OEE\n 29→ }\n 30→\n 31→ detectedAnomalies.push({\n 32→ anomaly_type: 'oee-drop',\n 33→ severity: severity,\n 34→ title: `OEE Below Threshold`,\n 35→ description: `OEE at ${currentOEE.toFixed(1)}% (threshold: ${OEE_THRESHOLD}%)`,\n 36→ data: {\n 37→ current_oee: currentOEE,\n 38→ threshold: OEE_THRESHOLD,\n 39→ delta: OEE_THRESHOLD - currentOEE\n 40→ },\n 41→ kpi_snapshot: { oee, availability, performance, quality },\n 42→ work_order_id: activeOrder.id,\n 43→ cycle_count: cycle.cycles || 0,\n 44→ timestamp: now\n 45→ });\n 46→ }\n 47→\n 48→ Quality Spike Detection\n 49→\n 50→ // TIER 2: QUALITY SPIKE DETECTION\n 51→ const totalParts = (cycle.goodParts || 0) + (cycle.scrapParts || 0);\n 52→ const currentScrapRate = totalParts > 0 ? ((cycle.scrapParts || 0) / totalParts) * 100 : 0;\n 53→\n 54→ // Track history\n 55→ anomalyState.qualityHistory.push({ timestamp: now, value: currentScrapRate });\n 56→ if (anomalyState.qualityHistory.length > HISTORY_WINDOW) {\n 57→ anomalyState.qualityHistory.shift();\n 58→ }\n 59→\n 60→ // Calculate average and detect spikes\n 61→ if (anomalyState.qualityHistory.length >= 5) {\n 62→ const recentHistory = anomalyState.qualityHistory.slice(0, -1);\n 63→ const avgScrapRate = recentHistory.reduce((sum, point) => sum + point.value, 0) /\n 64→ recentHistory.length;\n 65→ const scrapRateIncrease = currentScrapRate - avgScrapRate;\n 66→\n 67→ if (scrapRateIncrease > QUALITY_SPIKE_THRESHOLD && currentScrapRate > 2) {\n 68→ let severity = 'warning';\n 69→ if (scrapRateIncrease > 10 || currentScrapRate > 15) {\n 70→ severity = 'critical'; // Major quality issue\n 71→ }\n 72→\n 73→ detectedAnomalies.push({\n 74→ anomaly_type: 'quality-spike',\n 75→ severity: severity,\n 76→ title: `Quality Issue Detected`,\n 77→ description: `Scrap rate at ${currentScrapRate.toFixed(1)}% (avg: \n 78→ ${avgScrapRate.toFixed(1)}%, +${scrapRateIncrease.toFixed(1)}%)`,\n 79→ // ... additional data\n 80→ });\n 81→ }\n 82→ }\n 83→\n 84→ Performance Degradation Detection\n 85→\n 86→ // TIER 2: PERFORMANCE DEGRADATION\n 87→ const currentPerformance = Number(kpis.performance) || 0;\n 88→ anomalyState.performanceHistory.push({ timestamp: now, value: currentPerformance });\n 89→\n 90→ // Check for sustained poor performance (10 data points)\n 91→ if (anomalyState.performanceHistory.length >= 10) {\n 92→ const recent10 = anomalyState.performanceHistory.slice(-10);\n 93→ const avgPerformance = recent10.reduce((sum, point) => sum + point.value, 0) /\n 94→ recent10.length;\n 95→\n 96→ // Alert if consistently below 85% performance\n 97→ if (avgPerformance > 0 && avgPerformance < 85) {\n 98→ let severity = 'warning';\n 99→ if (avgPerformance < 75) {\n 100→ severity = 'critical';\n 101→ }\n 102→\n 103→ detectedAnomalies.push({\n 104→ anomaly_type: 'performance-degradation',\n 105→ severity: severity,\n 106→ title: `Performance Degradation`,\n 107→ description: `Performance at ${avgPerformance.toFixed(1)}% (sustained over last 10\n 108→ cycles)`,\n 109→ // ... additional data\n 110→ });\n 111→ }\n 112→ }\n 113→\n 114→ Predictive Trend Analysis\n 115→\n 116→ // TIER 3: PREDICTIVE ALERTS (Trend Analysis)\n 117→ if (anomalyState.oeeHistory.length >= 15) {\n 118→ const recent15 = anomalyState.oeeHistory.slice(-15);\n 119→ const firstHalf = recent15.slice(0, 7);\n 120→ const secondHalf = recent15.slice(-7);\n 121→\n 122→ const avgFirstHalf = firstHalf.reduce((sum, p) => sum + p.value, 0) / firstHalf.length;\n 123→ const avgSecondHalf = secondHalf.reduce((sum, p) => sum + p.value, 0) / secondHalf.length;\n 124→\n 125→ const oeeTrend = avgSecondHalf - avgFirstHalf;\n 126→\n 127→ // Predict if OEE is trending downward significantly\n 128→ if (oeeTrend < -5 && avgSecondHalf > OEE_THRESHOLD * 0.95 && avgSecondHalf < OEE_THRESHOLD\n 129→ * 1.05) {\n 130→ detectedAnomalies.push({\n 131→ anomaly_type: 'predictive-oee-decline',\n 132→ severity: 'info',\n 133→ title: `Declining OEE Trend Detected`,\n 134→ description: `OEE trending down ${Math.abs(oeeTrend).toFixed(1)}% over last 15 \n 135→ cycles`,\n 136→ // ... additional data\n 137→ });\n 138→ }\n 139→ }\n 140→\n 141→ ---\n 142→ 2. Global Alert UI System\n 143→\n 144→ Location: flows.json:602-624 (New global ui_template node)\n 145→\n 146→ What I created:\n 147→ - Floating alert panel (slides from right)\n 148→ - Pop-up notifications requiring acknowledgment\n 149→ - Alert badge counter\n 150→ - Pulsing animation for active alerts\n 151→\n 152→ Floating Panel HTML\n 153→\n 154→ \n 155→ \n 160→\n 161→ \n 162→
{{anomaly.description}}
\n 176→{{formatTimestamp(anomaly.timestamp)}}
\n 177→{{popup.description}}
\n 195→ \n 197→{{anomaly.description}}
\n{{formatTimestamp(anomaly.timestamp)}}
\n{{popup.description}}
\n \nNo active alerts
\\nAll systems operating normally
\\n{{anomaly.description}}
\\n{{formatTimestamp(anomaly.timestamp)}}
\\n{{popup.description}}
\\n \\nNo active alerts
\\nAll systems operating normally
\\n{{anomaly.description}}
\\n{{formatTimestamp(anomaly.timestamp)}}
\\n{{popup.description}}
\\n \\nNo active alerts
\\nAll systems operating normally
\\n{{anomaly.description}}
\\n{{formatTimestamp(anomaly.timestamp)}}
\\n{{popup.description}}
\\n \\nNo active alerts
\\nAll systems operating normally
\\n{{anomaly.description}}
\\n{{formatTimestamp(anomaly.timestamp)}}
\\n{{popup.description}}
\\n \\nNo active alerts
\\nAll systems operating normally
\\n{{anomaly.description}}
\\n{{formatTimestamp(anomaly.timestamp)}}
\\n{{popup.description}}
\\n \\nNo active alerts
\\nAll systems operating normally
\\n{{anomaly.description}}
\\n{{formatTimestamp(anomaly.timestamp)}}
\\n{{popup.description}}
\\n \\nNo active alerts
\\nAll systems operating normally
\\n{{anomaly.description}}
\\n{{formatTimestamp(anomaly.timestamp)}}
\\n{{popup.description}}
\\n \\n{{ resumePrompt.id }}
\\n\\n {{ resumePrompt.goodParts }} of {{ resumePrompt.targetQty }} parts completed\\n ({{ resumePrompt.progressPercent }}%)\\n
\\nCycle Count: {{ resumePrompt.cycleCount }}
\\n\\n{{ scrapPrompt.orderId }}
\\nProduced {{ scrapPrompt.produced }} of {{ scrapPrompt.target }} pieces
\\n\\nThis interface tracks Overall Equipment Effectiveness metrics, production progress, and incident logging for injection molding operations. Navigate between tabs using the sidebar to access work orders, real-time monitoring, performance graphs, incident reporting, and machine configuration.
\\nGo to the Work Orders tab and upload an Excel file with your work orders, or select from existing orders in the table. Click Load to activate a work order, then navigate to the Home tab where you'll see the current work order details. Before starting production, configure your mold settings in the Settings tab by selecting a mold preset or entering cavity counts manually.
\\nOn the Home tab, press the START button to begin production. The system tracks cycle counts, good parts, scrap, and progress toward your target quantity. Press STOP to pause production. Monitor real-time KPIs including OEE, Availability, Performance, and Quality metrics displayed on the dashboard.
\\nUse the Alerts tab to record production incidents. Quick-log common issues with preset buttons like Material Out, Machine Stopped, or Emergency Stop. For detailed logging, select an alert type from the dropdown, add notes, and submit. All incidents are timestamped and contribute to availability and OEE calculations.
\\nIn the Settings tab, use the Mold Presets section to search for your mold by manufacturer and name. Select a preset to automatically load cavity counts, or manually adjust the Mold Configuration fields below. If your mold isn't available, use the Add Mold button in the Integrations section to create a new preset with manufacturer, name, and cavity details.
\\nThe Graphs tab displays historical OEE trends broken down by Availability, Performance, and Quality. Use these charts to identify patterns, track improvements, and diagnose recurring issues affecting your production efficiency.
\\nSelect a manufacturer and mold from the dropdowns above.
\\nCan't find the mold you're looking for?
\\n \\n| \\n | ID | \\nSKU | \\nTARGET | \\nGOOD | \\nSCRAP | \\nPROGRESS | \\nSTATUS | \\nLAST UPDATE | \\n
|---|
No active alerts
\\nAll systems operating normally
\\n{{anomaly.description}}
\\n{{formatTimestamp(anomaly.timestamp)}}
\\n{{popup.description}}
\\n \\nNo active alerts
\\nAll systems operating normally
\\n{{anomaly.description}}
\\n{{formatTimestamp(anomaly.timestamp)}}
\\n{{popup.description}}
\\n \\nNo active alerts
\\nAll systems operating normally
\\n{{anomaly.description}}
\\n{{formatTimestamp(anomaly.timestamp)}}
\\n{{popup.description}}
\\n \\n{{ resumePrompt.id }}
\\n\\n {{ resumePrompt.goodParts }} of {{ resumePrompt.targetQty }} parts completed\\n ({{ resumePrompt.progressPercent }}%)\\n
\\nCycle Count: {{ resumePrompt.cycleCount }}
\\n\\n{{ scrapPrompt.orderId }}
\\nProduced {{ scrapPrompt.produced }} of {{ scrapPrompt.target }} pieces
\\n\\nThis interface tracks Overall Equipment Effectiveness metrics, production progress, and incident logging for injection molding operations. Navigate between tabs using the sidebar to access work orders, real-time monitoring, performance graphs, incident reporting, and machine configuration.
\\nGo to the Work Orders tab and upload an Excel file with your work orders, or select from existing orders in the table. Click Load to activate a work order, then navigate to the Home tab where you'll see the current work order details. Before starting production, configure your mold settings in the Settings tab by selecting a mold preset or entering cavity counts manually.
\\nOn the Home tab, press the START button to begin production. The system tracks cycle counts, good parts, scrap, and progress toward your target quantity. Press STOP to pause production. Monitor real-time KPIs including OEE, Availability, Performance, and Quality metrics displayed on the dashboard.
\\nUse the Alerts tab to record production incidents. Quick-log common issues with preset buttons like Material Out, Machine Stopped, or Emergency Stop. For detailed logging, select an alert type from the dropdown, add notes, and submit. All incidents are timestamped and contribute to availability and OEE calculations.
\\nIn the Settings tab, use the Mold Presets section to search for your mold by manufacturer and name. Select a preset to automatically load cavity counts, or manually adjust the Mold Configuration fields below. If your mold isn't available, use the Add Mold button in the Integrations section to create a new preset with manufacturer, name, and cavity details.
\\nThe Graphs tab displays historical OEE trends broken down by Availability, Performance, and Quality. Use these charts to identify patterns, track improvements, and diagnose recurring issues affecting your production efficiency.
\\nSelect a manufacturer and mold from the dropdowns above.
\\nCan't find the mold you're looking for?
\\n \\n| \\n | ID | \\nSKU | \\nTARGET | \\nGOOD | \\nSCRAP | \\nPROGRESS | \\nSTATUS | \\nLAST UPDATE | \\n
|---|
No active alerts
\\nAll systems operating normally
\\n{{anomaly.description}}
\\n{{formatTimestamp(anomaly.timestamp)}}
\\n{{popup.description}}
\\n \\n{{ resumePrompt.id }}
\\n\\n {{ resumePrompt.goodParts }} of {{ resumePrompt.targetQty }} parts completed\\n ({{ resumePrompt.progressPercent }}%)\\n
\\nCycle Count: {{ resumePrompt.cycleCount }}
\\n\\n{{ scrapPrompt.orderId }}
\\nProduced {{ scrapPrompt.produced }} of {{ scrapPrompt.target }} pieces
\\n\\nThis interface tracks Overall Equipment Effectiveness metrics, production progress, and incident logging for injection molding operations. Navigate between tabs using the sidebar to access work orders, real-time monitoring, performance graphs, incident reporting, and machine configuration.
\\nGo to the Work Orders tab and upload an Excel file with your work orders, or select from existing orders in the table. Click Load to activate a work order, then navigate to the Home tab where you'll see the current work order details. Before starting production, configure your mold settings in the Settings tab by selecting a mold preset or entering cavity counts manually.
\\nOn the Home tab, press the START button to begin production. The system tracks cycle counts, good parts, scrap, and progress toward your target quantity. Press STOP to pause production. Monitor real-time KPIs including OEE, Availability, Performance, and Quality metrics displayed on the dashboard.
\\nUse the Alerts tab to record production incidents. Quick-log common issues with preset buttons like Material Out, Machine Stopped, or Emergency Stop. For detailed logging, select an alert type from the dropdown, add notes, and submit. All incidents are timestamped and contribute to availability and OEE calculations.
\\nIn the Settings tab, use the Mold Presets section to search for your mold by manufacturer and name. Select a preset to automatically load cavity counts, or manually adjust the Mold Configuration fields below. If your mold isn't available, use the Add Mold button in the Integrations section to create a new preset with manufacturer, name, and cavity details.
\\nThe Graphs tab displays historical OEE trends broken down by Availability, Performance, and Quality. Use these charts to identify patterns, track improvements, and diagnose recurring issues affecting your production efficiency.
\\nSelect a manufacturer and mold from the dropdowns above.
\\nCan't find the mold you're looking for?
\\n \\n| \\n | ID | \\nSKU | \\nTARGET | \\nGOOD | \\nSCRAP | \\nPROGRESS | \\nSTATUS | \\nLAST UPDATE | \\n
|---|
No active alerts
\\nAll systems operating normally
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\\n\\nThis interface tracks Overall Equipment Effectiveness metrics, production progress, and incident logging for injection molding operations. Navigate between tabs using the sidebar to access work orders, real-time monitoring, performance graphs, incident reporting, and machine configuration.
\\nGo to the Work Orders tab and upload an Excel file with your work orders, or select from existing orders in the table. Click Load to activate a work order, then navigate to the Home tab where you'll see the current work order details. Before starting production, configure your mold settings in the Settings tab by selecting a mold preset or entering cavity counts manually.
\\nOn the Home tab, press the START button to begin production. The system tracks cycle counts, good parts, scrap, and progress toward your target quantity. Press STOP to pause production. Monitor real-time KPIs including OEE, Availability, Performance, and Quality metrics displayed on the dashboard.
\\nUse the Alerts tab to record production incidents. Quick-log common issues with preset buttons like Material Out, Machine Stopped, or Emergency Stop. For detailed logging, select an alert type from the dropdown, add notes, and submit. All incidents are timestamped and contribute to availability and OEE calculations.
\\nIn the Settings tab, use the Mold Presets section to search for your mold by manufacturer and name. Select a preset to automatically load cavity counts, or manually adjust the Mold Configuration fields below. If your mold isn't available, use the Add Mold button in the Integrations section to create a new preset with manufacturer, name, and cavity details.
\\nThe Graphs tab displays historical OEE trends broken down by Availability, Performance, and Quality. Use these charts to identify patterns, track improvements, and diagnose recurring issues affecting your production efficiency.
\\nSelect a manufacturer and mold from the dropdowns above.
\\nCan't find the mold you're looking for?
\\n \\n| \\n | ID | \\nSKU | \\nTARGET | \\nGOOD | \\nSCRAP | \\nPROGRESS | \\nSTATUS | \\nLAST UPDATE | \\n
|---|
No active alerts
\\nAll systems operating normally
\\n{{anomaly.description}}
\\n{{formatTimestamp(anomaly.timestamp)}}
\\n{{popup.description}}
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\\nCycle Count: {{ resumePrompt.cycleCount }}
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\\nCycle Count: {{ resumePrompt.cycleCount }}
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\\nCycle Count: {{ resumePrompt.cycleCount }}
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