<![CDATA[Extrusion blow molding is one of the most widely used manufacturing methods in the plastic industry for producing hollow containers, such as jerrycans, with demands for uniform wall thickness and efficient material usage. One of the key factors affecting product quality in this process is parison programming, as the parison thickness distribution determines the material distribution during expansion inside the mold. However, improper parison settings often result in uneven wall thickness distribution, which can reduce structural quality and increase material consumption. This study aims to analyze and optimize parison thickness settings in the extrusion blow molding process to achieve a more uniform wall thickness distribution in 5-liter jerrycans according to design specifications. The research method was conducted by setting the Scale Parison Thickness parameter to 10%, operating the machine according to Standard Operating Procedures (SOP), and testing the product wall thickness at five different areas: the handle, upper section, upper body, lower body, and bottom section. Each area was measured at ten points using a micrometer to obtain the average thickness values. The results showed that the average thicknesses at the handle, upper section, upper body, lower body, and bottom section were 0.60 mm, 0.62 mm, 0.74 mm, 0.90 mm, and 0.89 mm, respectively, with a product weight of 141.1 grams. The obtained thickness distribution was still not fully uniform, indicating that the parison programming settings require further refinement to produce a thinner body section and thicker handle and bottom sections in accordance with design standards. This study concludes that more precise optimization of parison programming parameters can improve thickness uniformity, material efficiency, and the structural quality of the product. Furthermore, the findings provide practical contributions to the plastic industry by improving process control, reducing the potential for product defects, and supporting sustainable production cost efficiency.]]>
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