Analysis of the Implementation of PLC- and Iot Based Automatic Control Systems in Optimizing the Chemical Mixing Process at PT RAPP

Benediktus Situmorang; Solly Aryza; Ahmad Dani

Authors

Benediktus Situmorang Universitas Pembangunan Panca Budi, Medan, North Sumatera, Indonesian
Solly Aryza Universitas Pembangunan Panca Budi, Medan, North Sumatera, Indonesian
Ahmad Dani Universitas Pembangunan Panca Budi, Medan, North Sumatera, Indonesian

Keywords:

PLC, IoT, industrial automation, chemical mixing process, and automatic control.

Abstract

The chemical mixing process in the pulp and paper industry requires a high level of accuracy, consistency, and speed to ensure product quality and operational efficiency. PT Riau Andalan Pulp and Paper (PT RAPP), as one of the largest manufacturing companies in Indonesia, faces challenges in maintaining stable and real-time mixing processes, particularly in manual control systems that are prone to operator errors, delayed responses, and limited monitoring capabilities. This study aims to analyze the implementation of a Programmable Logic Controller (PLC)-based automatic control system integrated with the Internet of Things (IoT) as a solution to optimize the chemical mixing process. The research methodology includes the design of the control system architecture, PLC programming for regulating chemical levels, temperature, and material proportions, as well as the development of a web-based IoT dashboard for remote monitoring. The results indicate that the PLC-based automatic control system improves mixing precision by 18%, reduces processing time by 25%, and significantly decreases the risk of human error. IoT integration enables real-time monitoring, automated data logging, and early detection of process disturbances. Overall, the implementation of PLC and IoT has proven effective in enhancing operational efficiency, quality stability, and process reliability in the chemical mixing process at PT RAPP. This study recommends further development through predictive maintenance and the integration of analytical sensors to achieve end-to-end process automation.

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