Determination of Manufacturing Parameters for Maintaining form Accuracy of Packaging Support Block Made with Polyurethane Foam

A support block for packaging valuables usually uses a material with surface elasticity, such as polyurethane foam or polystyrene foam. This is to ensure that the surface can be well contacted and supported so that the contents of the package can be protected from vibration or shock when valuables are transported over long distances. In general, this polyurethane packaging support block is manufactured using an NC milling machine and a ball nosed end mill tool specially designed to cut the cushioned soft materials. However, because the elastic cushion of the material is very large, it is very difficult to implement the 3D form accuracy that can be in good contact with the surface of the packaged contents. This study tried to explore the manufacturing parameters that could maintain the good contact with the surface form of packaged valuables accurately and could support the contents stably, through the Taguchi technique, that minimizes the influence of uncontrollable factors through controllable factors. Using the characteristics value by Taguchi technique based on the experimental accumulated machining data under similar environment, the optimal manufacturing parameters such as the spindle speed, feed rate, step over, and tool path patternweredeter mined. And the manufacturing parameters determined through these analysis techniques have been verified practically by testing experiment usinga group of expert’s machining data. Also, in order to examine the suitability of these parameters, the prediction accuracy was confirmed by comparing it with a large amount of experimental data accumulated by experts. In addition, in order to confirm the packaging performance of the support block manufactured under these parameters, the vibration test were performed on these samples to compare and analyze whether they satisfied the limits of the standard specification.

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The authors declare no conflict of interest.

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The datasets used in this study are openly available at [repository link] and the source code is available on GitHub at [GitHub link].

This work did not receive any external funding.