Using the Six Sigma DMAIC Methodology to Enhance the Performance of Control Loops in an Iron Ore Processing Plant

Automation systems have become indispensable in various industries, including mineral processing facilities. These systems enable thousands of continuous automated actions that enhance safety and productivity. At the core of these systems lie control loops, composed primarily of sensors, actuators, and controllers. Their primary function is to maintain a process variable as close as possible to its setpoint, the desired value for that particular variable. When a control loop underperforms, its repercussions can significantly impact plant productivity, resulting in financial losses. While the literature abounds with works concerning the health of control loops, there remains a gap in the knowledge base regarding the effective management of task force members charged with evaluating control loop performance, identifying root causes of issues, proposing effective solutions, and consistently maintaining control loops at peak performance. This paper presents the application of the Six Sigma DMAIC (Define, Measure, Analyze, Improve, Control) approach as a framework to guide and coordinate a team of employees within the mineral industry focusing on enhancing the performance of the control loops. The studywas conducted over a fifteen-month period in an operational unit of an iron ore facility in Brazil. Through the use of the DMAIC approach, the percentage of operating time for control loops in automatic mode increased significantly, going from 52% to 87%. Simultaneously, the percentage of time that the process variable operated under undesirable conditions decreased from 33% to just 12%. Moreover, the percentage of time that the actuators operated in a saturated state decreased from 22% to only 12%.