Filling Process Optimization Through an Automated System in the Cleaning Products Industry

Abstract

This research, with a quantitative approach, analyzes the implementation of an automated filling system using sensors and programmable logic controllers (PLC) in a liquid product manufacturing plant. The study arises in response to inefficiencies identified in the manual process, such as long cycle times, low performance, and a high failure rate attributable to human errors and operational variability. The applied methodology included a technical analysis using tools such as the Pareto Chart, FMEA, and criticality analysis, followed by the design, implementation, and validation of the automated system. Key indicators such as cycle time, performance, and failure rate were used to evaluate operational improvement. The results show a reduction in the average monthly cycle time from 113.1 to 92.8 hours (17.9%), an increase in performance from 70.7% to 86.0%, and a decrease in the failure rate from 29.3% to 14.0%. These changes reflect a significant improvement in the efficiency, continuity, and reliability of the filling process, highlighting the positive impact of automation on productivity and the reduction of human error.