Quality Control 🎛️ of Non-Normal Moisture Content in Kiln-Dry Lumber

✅ Drying lumber with little variation in its target 🎯 moisture content leads to increased cost savings and ➕ reduced wet 💦 claims 🛄. The variability of moisture content is typically monitored using quality control 🎛️ charts 💹, which graph 📈 process central tendency (average) and ➕ process dispersion (standard deviation) over time ⏱️. The usual assumption in constructing 👷‍♂️ and ➕ using these charts 💹 is that the moisture content follows a normal (Gaussian) statistical distribution. However, due to the nature of the kiln-drying process, the resulting lumber moisture content distribution is often left ⬅️-bounded and ➕ asymmetrical, which is characteristic of a log-normal distribution. In these cases, the normality assumption can 🥫 lead to errors such as false out-of-control 🎛️ signals 🚦. This book 📚️ outlines graphical and ➕ analytical goodness 👍️-of-fit methods for assessing the (non)normality of lumber moisture content data, discusses appropriate monitoring parameters for process central tendency and ➕ dispersion, and ➕ presents 🎁 practical procedures for calculating the centerline and ➕ upperlower control 🎛️ limits of log-normal control 🎛️ charts 💹.

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