Integration of Engineering Process Control and Statistical Control in pulp and paper industry

The main goal of this article is to present a methodology and a framework that is able to bring together two important concepts: Engineering Process Control (EPC), which was developed by process engineers to achieve short time control, and Statistical Process Control (SPC), conceived and implemented by statisticians and quality managers for attaining medium and long term control. The integration of both concepts can represent a breakthrough in the final product performance, by creating the necessary conditions to decrease the variability of quality characteristics both in the short and long term. The integrated methodology was designed for the pulp and paper industry and was established in several phases. First, a mathematical model was developed to represent as much as possible the process dynamic behaviour. The transfer function obtained was then used to implement two components of the above mentioned concepts, namely controllers, based on the minimum variance criterion, and statistical control charts. At last, the two components were integrated into the process, which was submitted to several disturbances to ascertain the control achieved with the integration. The methodology was tested in a real industrial process of one of the most important pulp producers in the world and considered several scenarios. To illustrate the methodology, we present one of the scenarios that shows the benefits of EPC/SPC integration. Through the application of the developed methodology to real data, process engineers at the company are now able to use a valuable decision making tool when the production process is affected by certain disruptions, with obvious consequences on product quality, productivity and competitiveness.