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    <title>Results for "Statistical Process Control"</title>
    <description>Showing 1 - 11 results of 11</description>
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      <title>An implementation framework for statistical process control in small to medium-sized enterprises: A South African context</title>
      <pubDate>Wed, 10 Jun 2026 12:46:09 +0000</pubDate>
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      <author>Appollis, Logan-Lee Miche</author>
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      <dc:date>2019</dc:date>
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      <title>Predicting process performance in the manufacturing and agricultural sectors using machine learning techniques</title>
      <pubDate>Wed, 10 Jun 2026 12:44:14 +0000</pubDate>
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      <author>Khoza, Sibusiso Comfort</author>
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      <dc:date>2021</dc:date>
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      <title>Multiscale process monitoring with singular spectrum analysis</title>
      <pubDate>Wed, 10 Jun 2026 12:41:58 +0000</pubDate>
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      <author>Krishnannair, Syamala</author>
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      <title>Predictive maintenance using clustering methods for the use-case of bolted connections in the automotive industry</title>
      <pubDate>Wed, 10 Jun 2026 12:41:14 +0000</pubDate>
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      <author>Bekker, Emmarentia Lydia</author>
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      <dc:date>2023</dc:date>
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      <title>Development of a Regulatory Performance Monitoring Structure</title>
      <pubDate>Wed, 10 Jun 2026 12:40:48 +0000</pubDate>
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      <title>Distributional properties of ratios of gamma random variables in the context of quality control</title>
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      <title>Univariate parametric and nonparametric double generally weighted moving average control charts</title>
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      <title>The theory and application of bootstrap control charts for statistical process control</title>
      <pubDate>Wed, 10 Jun 2026 12:37:44 +0000</pubDate>
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      <title>Reducing the amount of defects at the quality control station by using statistical process control</title>
      <pubDate>Wed, 10 Jun 2026 12:37:03 +0000</pubDate>
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      <author>Van Loggerenberg, Nichole</author>
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      <title>Nonlinear fault detection and diagnosis using Kernel based techniques applied to a pilot distillation colomn</title>
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      <title>Non-parametric change-point approach for  monitoring shifts in process location and variability</title>
      <pubDate>Thu, 01 Jan 2015 11:20:48 -0500</pubDate>
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