IoT Based Automatic Diagnosis for Continuous Improvement

This work responds to the gap in integrating Internet-of-Things Continuous Improvement processes, especially facilitate diagnosis and problem-solving activities regarding manufacturing workstations. An innovative approach, named Automatic Detailed Diagnosis (ADD), is proposed: a non-intrusive, easy-to-install use, low-cost flexible system based on industrial platforms devices. The ADD requirements architecture were systematized from knowledge field, with help of Lean Manufacturing professionals. developed concept composed network low-power devices variety sensors. Colored light vibration sensors are used monitor equipment status, Bluetooth low-energy time-of-flight operators’ movements tasks. A cloud-based platform receives stores collected data. That information retrieved by an application that builds detailed report operator–machine interaction. prototype was tested case study carried out mold-making company. able detect time performance accuracy between 89% 96%, involving uptime, micro-stops, setups. In addition, these states correlated actions.