Design and Implementation of TAVA – Training Attendance Verification Automation for Non-QMS Documents with MES Configuration at a Medical Device Industry

Abstract

The training process in manufacturing systems, especially in complex environments like MES dispatch, is vital for operational efficiency. At Medtronic's Juncos facility, current training practices have caused delays, inefficiencies, and increased error rates. This study investigates training challenges, including LMS transaction inefficiencies, manual data entry, and lengthy reconciliation times. Using the DMAIC (Define, Measure, Analyze, Improve, Control) methodology, the research targets process improvements, particularly for non-QMS documents configured with MES dispatch. Goals include reducing reconciliation lead times, minimizing errors, and improving overall efficiency. Key findings highlight automation, standardization, and real-time monitoring as essential solutions. The proposed improvements are scalable, enabling adoption across other business units to ensure consistent and efficient training practices throughout Medtronic. A significant anticipated outcome is reducing lead time from 134 minutes to 1 minute for 600 employees, accelerating change implementation and minimizing disruptions. Ultimately, the study emphasizes the value of structured problem-solving in advancing manufacturing training systems. Key Terms -DMAIC Method, MES Dispatch, Quality Management System, Training Attendance Automation.