PLC

Distributed Control Systems (DCS) are widely used in industrial automation, especially in sectors like chemical, power, oil, and gas industries. DCS systems are crucial for ensuring safe, efficient, and stable operation of complex industrial processes. Below is a ranking of some of the most popular DCS systems, along with their strengths and weaknesses. 1. Honeywell […]

1. Introduction The concept of Safety Integrity Level (SIL) is fundamental in functional safety, particularly in industries where safety-critical processes are involved. SIL1, the lowest safety integrity level as defined by IEC 61508/IEC 61511 standards, requires basic safety measures to mitigate risks of low-severity consequences. Distributed Control Systems (DCS) are primarily designed for process control

In industrial settings, digital communication protocols like RS232, RS485, and CAN are commonly used for transmitting digital signals. However, when it comes to transmitting analog signals—such as those from sensors measuring temperature, pressure, speed, or angle—a different approach is needed. The most widely adopted method in industry is the use of a 4-20mA current loop for analog signal transmission. This article

Introduction Process control has undergone significant evolution, transitioning from simple feedback control methods to advanced process control (APC) strategies. Initially, control systems were designed to correct deviations, aligning with human problem-solving habits. This fundamental approach remains at the core of feedback control. The early days of process control were driven by practical needs rather than

DCS (Distributed Control System), GDS (Gas Detection System), and SIS (Safety Instrumented System) are distinct control and safety systems used in industrial settings. Each system serves a unique purpose and has specific characteristics. Below is a detailed comparison of these three systems. 1. Distributed Control System (DCS) A Distributed Control System (DCS) is an advanced

Introduction Proportional-Integral-Derivative (PID) control has been a cornerstone of industrial automation since its invention. Despite its long history, modern industry has transformed significantly, requiring control algorithms to adapt and optimize performance under new conditions. In this article, we will explore the historical development of PID control, the challenges it faces in contemporary applications, and the

Introduction Programmable Logic Controllers (PLCs) are widely used in industrial automation, making them an essential skill for many engineers and technicians. While some find PLCs challenging to learn, understanding the right methods can simplify the process significantly. This guide outlines practical steps to help anyone master PLCs efficiently. 1. Understand the Basics To begin learning

When advanced control specifically refers to multivariable model predictive control (MPC), it is not always necessary for every application. Advanced control has become a popular algorithm in process industries, especially in chemical manufacturing, due to the complexity of these industrial systems. The challenges associated with multivariable dynamic constraints and the difficulty of coordinated optimization make

Many consider Advanced Process Control (APC) to be a superior alternative to the traditional Proportional-Integral-Derivative (PID) controller. However, the reality of industrial applications is that the selection of control strategies is not solely determined by whether an algorithm is labeled as “advanced,” “intelligent,” “adaptive,” or “optimal.” Instead, the primary concern of industry practitioners is cost-effectiveness.

In the wave of Industry 4.0 and smart manufacturing, advanced technologies such as online analyzers, the Internet of Things (IoT), AI models, and digital twins are continuously emerging. However, the fundamental principles of manufacturing have remained unchanged: Process, Equipment, Operations, and Control are the four critical elements of production. Understanding and respecting the interplay between