Abstract

This paper would demonstrate the STEAMS (Science, Technology, Engineering, Artificial Intelligence, Mathematics, Statistics) methodology on how to customize the Dumpling Cooking process based on the Dumpling product types. Most foods like dumplings are made without precise control of cooking parameters. During the dumpling cooking process, the water temperature and cooking duration are the most important factors to determine whether Dumplings are under, fully or over cooked.  The dumpling type, dumpling weight, batch size would also impact the cooking process.  A specially designed and structured Design was conducted to build a predictive model of estimating the cooking duration.  The HACCP (Hazard Analysis Critical Control Point) and ISO 22000 Food Safety Management were adopted.  Modern Data Mining Neural technique was conducted.  The results have observed both main effects mainly from the Boiling Temp, Dumpling Product Type, Dumpling Size/Batch and interaction effects which are constrained by the mixture of the dumpling composition.