Designing the selection model of smart sensor implementation for capping process in hygiene product manufacturing factory

Fast Moving Consumer Goods (FMCG) is one of the industry sectors that has the potential to grow in Indonesia. One of its subsectors, the home care industry, is expected to grow after the pandemic situation. Due to disruptive developments, FMCG has been forced to adopt an operational model that generates cost savings. The purpose of this study is to determine the best smart sensor technology to use in hygiene product factories, specifically for the capping process, as well as the most important criteria and sub-criteria for doing so. The Best-Worst Method (BWM) and the Preference Ranking Organization Method for Enrichment Evaluation (PROMETHEE) were used in this work to measure the weights of the criteria and sub-criteria and evaluate alternative technologies, respectively. The choice of technology to be evaluated considers 23 sub-criteria, including vision sensor, color sensor, and photoelectric sensor. The research led to the technological recommendation known as the smart color sensor, with the most important factors to consider being productivity, expected benefits, and testing simplicity.