In this study, using the whale optimization algorithm (WOA), one of the recent optimization algorithms inspired by nature, the plastic injection process parameters of an automotive sub-industry company were tried to be optimized. For this purpose, we tried to provide the maximum weight criterion for the “356 MCA Plastic Housing” (which is an automotive lighting part) produced by plastic injection method. The decrease in the weight of the product indicates that the material injected into the mold is missing and naturally indicates that there will be quality problems. In order to achieve this aim, the best factor levels were tried to be determined for the mold temperature (°C), injection speed (m/s), injection pressure (bar), holding time (s), and injection time (s), which are the controllable parameters of injection process. Factors and factor levels addressed using WOA have not been studied for this type of problem before and this is the novelty aspect of this research. Experiments performed to confirm the findings for optimum process parameters proved that the WOA method can be successfully applied to improve plastic injection process parameters. This study contains information for practicing researchers in terms of showing how the nature-inspired algorithm WOA can be applied in practical field studies.

中文翻译：

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在汽车照明零件制造中使用 Whale 优化算法优化注塑工艺

在这项研究中，使用鲸鱼优化算法（WOA），这是最近受自然启发的优化算法之一，试图优化汽车子行业公司的注塑工艺参数。为此，我们试图为采用注塑方法生产的“356 MCA 塑料外壳”（这是一种汽车照明部件）提供最大重量标准。产品重量的减少说明注入模具的材料缺失，自然说明会有质量问题。为了实现这一目标，尝试确定模具温度 (°C)、注射速度 (m/s)、注射压力 (bar)、保压时间 (s) 和注射时间 (s) 的最佳因素水平。 )，这是注射过程的可控参数。之前尚未针对此类问题研究过使用 WOA 解决的因素和因素水平，这是本研究的新颖之处。为确认最佳工艺参数的结果而进行的实验证明，WOA 方法可以成功地应用于改进塑料注射工艺参数。本研究包含为实践研究人员提供的信息，展示了如何将自然启发的算法 WOA 应用于实际的实地研究。