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    <title>topic Factory Telemetry Analysis – Finding Machine Breakdowns in Data Stories Gallery</title>
    <link>https://community.fabric.microsoft.com/t5/Data-Stories-Gallery/Factory-Telemetry-Analysis-Finding-Machine-Breakdowns/m-p/4999504#M15754</link>
    <description>&lt;H2&gt;&lt;STRONG&gt;Factory Telemetry Analysis – Finding Machine Breakdowns with Power BI&lt;/STRONG&gt;&lt;/H2&gt;&lt;H3&gt;&lt;STRONG&gt;Project Overview&lt;/STRONG&gt;&lt;/H3&gt;&lt;P&gt;I recently completed a data analysis project focused on manufacturing efficiency for &lt;STRONG&gt;Daikibo&lt;/STRONG&gt;, a global client with four major production hubs (Tokyo, Osaka, Berlin, and Shenzhen). The goal was to transform a month’s worth of raw telemetry data (May 2021) into a clear, actionable dashboard that identifies where and why production is being interrupted.&lt;/P&gt;&lt;H3&gt;&lt;STRONG&gt;The Problem Statement&lt;/STRONG&gt;&lt;/H3&gt;&lt;P&gt;The client needed to answer two critical operational questions:&lt;/P&gt;&lt;OL&gt;&lt;LI&gt;&lt;P&gt;&lt;STRONG&gt;Location Analysis:&lt;/STRONG&gt; In which factory location did machines break down the most?&lt;/P&gt;&lt;/LI&gt;&lt;LI&gt;&lt;P&gt;&lt;STRONG&gt;Root Cause:&lt;/STRONG&gt; Which specific machine types were responsible for the highest frequency of failures in that high-risk location?&lt;/P&gt;&lt;/LI&gt;&lt;/OL&gt;&lt;H3&gt;&lt;STRONG&gt;Technical Approach&lt;/STRONG&gt;&lt;/H3&gt;&lt;UL&gt;&lt;LI&gt;&lt;P&gt;&lt;STRONG&gt;Data Source:&lt;/STRONG&gt; Processed a single JSON file containing telemetry messages sent every 10 minutes across 9 machine types.&lt;/P&gt;&lt;/LI&gt;&lt;LI&gt;&lt;P&gt;&lt;STRONG&gt;Data Transformation:&lt;/STRONG&gt; Used &lt;STRONG&gt;Power Query&lt;/STRONG&gt; to flatten the JSON structure and ensure data types were optimized for analysis.&lt;/P&gt;&lt;/LI&gt;&lt;LI&gt;&lt;P&gt;&lt;STRONG&gt;Data Modeling:&lt;/STRONG&gt; Focused on a minimalist star schema to keep the dashboard responsive and user-friendly.&lt;/P&gt;&lt;/LI&gt;&lt;LI&gt;&lt;P&gt;&lt;STRONG&gt;Visualization:&lt;/STRONG&gt; Designed a high-impact, single-page dashboard. I prioritized &lt;STRONG&gt;scannability&lt;/STRONG&gt; over complexity to ensure the "worst-performing" factory and machine types were immediately visible via sorted bar charts and KPI cards.&lt;/P&gt;&lt;/LI&gt;&lt;/UL&gt;&lt;H3&gt;&lt;STRONG&gt;Key Insights&lt;/STRONG&gt;&lt;/H3&gt;&lt;P&gt;By filtering the telemetry for specific "breakdown" indicators, the dashboard clearly identifies the bottleneck factory and the specific machine models that require maintenance or replacement to minimize future downtime.&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;&lt;SPAN class="reportid hidden"&gt;eyJrIjoiYmUzYTkxNzctY2ZhZS00NDdlLTgwMjktMGJiY2E5NDA3MWE5IiwidCI6IjBjM2QwNTc2LTFkOWYtNGM4Ny05OTNjLTg2YjQ0MGE1YjA3OCJ9&lt;/SPAN&gt;&lt;/P&gt;</description>
    <pubDate>Fri, 06 Feb 2026 17:34:26 GMT</pubDate>
    <dc:creator>MohamadJavith</dc:creator>
    <dc:date>2026-02-06T17:34:26Z</dc:date>
    <item>
      <title>Factory Telemetry Analysis – Finding Machine Breakdowns</title>
      <link>https://community.fabric.microsoft.com/t5/Data-Stories-Gallery/Factory-Telemetry-Analysis-Finding-Machine-Breakdowns/m-p/4999504#M15754</link>
      <description>&lt;H2&gt;&lt;STRONG&gt;Factory Telemetry Analysis – Finding Machine Breakdowns with Power BI&lt;/STRONG&gt;&lt;/H2&gt;&lt;H3&gt;&lt;STRONG&gt;Project Overview&lt;/STRONG&gt;&lt;/H3&gt;&lt;P&gt;I recently completed a data analysis project focused on manufacturing efficiency for &lt;STRONG&gt;Daikibo&lt;/STRONG&gt;, a global client with four major production hubs (Tokyo, Osaka, Berlin, and Shenzhen). The goal was to transform a month’s worth of raw telemetry data (May 2021) into a clear, actionable dashboard that identifies where and why production is being interrupted.&lt;/P&gt;&lt;H3&gt;&lt;STRONG&gt;The Problem Statement&lt;/STRONG&gt;&lt;/H3&gt;&lt;P&gt;The client needed to answer two critical operational questions:&lt;/P&gt;&lt;OL&gt;&lt;LI&gt;&lt;P&gt;&lt;STRONG&gt;Location Analysis:&lt;/STRONG&gt; In which factory location did machines break down the most?&lt;/P&gt;&lt;/LI&gt;&lt;LI&gt;&lt;P&gt;&lt;STRONG&gt;Root Cause:&lt;/STRONG&gt; Which specific machine types were responsible for the highest frequency of failures in that high-risk location?&lt;/P&gt;&lt;/LI&gt;&lt;/OL&gt;&lt;H3&gt;&lt;STRONG&gt;Technical Approach&lt;/STRONG&gt;&lt;/H3&gt;&lt;UL&gt;&lt;LI&gt;&lt;P&gt;&lt;STRONG&gt;Data Source:&lt;/STRONG&gt; Processed a single JSON file containing telemetry messages sent every 10 minutes across 9 machine types.&lt;/P&gt;&lt;/LI&gt;&lt;LI&gt;&lt;P&gt;&lt;STRONG&gt;Data Transformation:&lt;/STRONG&gt; Used &lt;STRONG&gt;Power Query&lt;/STRONG&gt; to flatten the JSON structure and ensure data types were optimized for analysis.&lt;/P&gt;&lt;/LI&gt;&lt;LI&gt;&lt;P&gt;&lt;STRONG&gt;Data Modeling:&lt;/STRONG&gt; Focused on a minimalist star schema to keep the dashboard responsive and user-friendly.&lt;/P&gt;&lt;/LI&gt;&lt;LI&gt;&lt;P&gt;&lt;STRONG&gt;Visualization:&lt;/STRONG&gt; Designed a high-impact, single-page dashboard. I prioritized &lt;STRONG&gt;scannability&lt;/STRONG&gt; over complexity to ensure the "worst-performing" factory and machine types were immediately visible via sorted bar charts and KPI cards.&lt;/P&gt;&lt;/LI&gt;&lt;/UL&gt;&lt;H3&gt;&lt;STRONG&gt;Key Insights&lt;/STRONG&gt;&lt;/H3&gt;&lt;P&gt;By filtering the telemetry for specific "breakdown" indicators, the dashboard clearly identifies the bottleneck factory and the specific machine models that require maintenance or replacement to minimize future downtime.&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;&lt;SPAN class="reportid hidden"&gt;eyJrIjoiYmUzYTkxNzctY2ZhZS00NDdlLTgwMjktMGJiY2E5NDA3MWE5IiwidCI6IjBjM2QwNTc2LTFkOWYtNGM4Ny05OTNjLTg2YjQ0MGE1YjA3OCJ9&lt;/SPAN&gt;&lt;/P&gt;</description>
      <pubDate>Fri, 06 Feb 2026 17:34:26 GMT</pubDate>
      <guid>https://community.fabric.microsoft.com/t5/Data-Stories-Gallery/Factory-Telemetry-Analysis-Finding-Machine-Breakdowns/m-p/4999504#M15754</guid>
      <dc:creator>MohamadJavith</dc:creator>
      <dc:date>2026-02-06T17:34:26Z</dc:date>
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