Abstract:
At present, there is a growing tendency among industries to integrate eco-friendly practices to
comply with the increasingly stringent environmental standards that are being introduced. In this
context, a variety of sustainable machining methods have been investigated with the objective of
optimizing processing parameters. The objective of this study is to optimize processing parameters
for the manufacturing of plastic sheets using a vacuum-forming process. This method is costeffective and versatile, offering superior surface finishes, reduced manufacturing costs, and
increased productivity. It addresses issues that arise from the use of unoptimized parameters, which
are typically determined through a process of trial and error or based on the experience of the
operator. In this study, the heating temperature, heating time, sheet thickness, and distance between
ups were identified as the optimal parameters for optimization. Uniformity and the number of
wrinkles were selected as performance assessment attributes. The experiments were conducted in
accordance with the Taguchi L16 orthogonal array (OA) experimental design plan. It was
determined that the thickness of the sheet and the distance between the ups are significant
consequences in determining the quality of vacuum-formed parts. The experiments demonstrated
that the sheet type, color, and size of the venting hole in the male mold had a negligible impact on
the formation of wrinkles. The results of the ANOVA demonstrated that uniformity and the
number of wrinkles were significantly influenced by the sheet thickness and distance between ups.
The Taguchi analysis identified the optimal process parameters that enhanced the product quality,
as evidenced by the results of the conformance tests. Additionally, regression analysis was utilized
to predict outcomes and assess the model. The developed regression models are recommended for
implementation in manufacturing industries to optimize parameters, reduce material waste,
enhance productivity, and improve cost-effectiveness.
