This research brings the concept of the Internet of Things (IoT) in creating the Apilastic Robot, a device that aims to reduce customer losses by identifying the causes of rejected items, particularly in frequently returned cups. Through qualitative data collection from a case study with the researcher as the human instrument, the research objective was to develop a device that can recognize the type of damage on the glass, provide support to the user to identify the source of the problem, and take appropriate steps. The results of the analysis showed that product effectiveness had the greatest influence on tool usage satisfaction, explaining 77.2% of the variability in tool effectiveness. It is expected that these findings provide support to users in troubleshooting frequently returned glassware with root cause identification and appropriate steps.