The shift from manual to automated manufacturing marks a significant turning point for the industry, driven by the pursuit of higher efficiency, accuracy, and safety. While traditional manual methods offer flexibility, they often lag in speed and precision and can expose workers to potential hazards. Automation, powered by advanced control systems, enables factories to operate around the clock with exceptional precision and the agility to swiftly respond to changing production requirements. 

This shift has already redefined the nature of manufacturing jobs, moving away from physical labour towards roles centred on managing, programming, and maintaining automated systems. The skills demanded by the modern manufacturing sector are very different than they were 10 to 15 years ago.

When we discuss these big changes in manufacturing, control systems are not just part of the story—they’re central to it. 

Industrial Control Systems – Components and Architecture 

An Industrial Control System (ICS) is a combination of both hardware and software that’s engineered to monitor and manage industrial operations and machinery. These systems act as the central nervous system of modern manufacturing facilities – controlling every aspect of production to meet operational requirements, safety standards, and peak efficiency. 

An ICS is typically comprised of: 

  • Control Hardware – This category includes devices such as programmable logic controllers (PLCs), distributed control systems (DCS), and various sensors that directly interact with the machinery on the factory floor.
  • Control Software – This includes advanced algorithms and software applications designed to analyze sensor input data and execute operational commands based on complex logic. This software is critical for predictive maintenance, process optimization, and real-time decision-making. 
  • Human-Machine Interface (HMI) – HMIs are sophisticated interfaces that provide visualizations of system status, alerts, and operational metrics. They enable operators to interact intuitively with the system, input commands, and adjust settings through graphical interfaces or touchscreens.

Human Machine Interface

  • Communication Networks – These networks utilise standard protocols such as Ethernet/IP, Profibus, or Modbus to ensure reliable and secure communication between the various hardware and software components of the ICS. They enable the integration of disparate systems for unified monitoring and control, and support data exchange with external business and IT systems for analytics and reporting. 

Types of Control Systems 

In the realm of industrial automation and control, systems can be broadly categorised based on their functionality, application, and complexity. Here are some specific types of control systems that play pivotal roles in manufacturing and process management:

  1. Programmable Logic Controllers (PLCs)

PLCs are compact yet powerful ruggedized computers. They are engineered to withstand harsh industrial environments, from extreme temperatures to vibration and electrical noise. What sets PLCs apart is their remarkable flexibility and ease of programming – typically through ladder logic or structured text – which allows them to be quickly adapted to control a wide variety of industrial processes and machinery. Key features include:

  • Real-Time Processing – Capable of handling input and executing control commands in milliseconds, ensuring immediate response to process changes. 
  • Modularity – Many PLCs feature a modular design, enabling easy expansion or modification with additional input/output (I/O) units, communication modules, and other functional components.

PLC

  1. Distributed Control Systems (DCS)

DCSs manage complex and large-scale industrial processes, mainly where operations are spread over large geographical areas. Unlike PLCs, which are used for discrete control tasks, DCSs offer a holistic approach to process management, integrating various control functions into a unified system. They feature a decentralized control architecture, allowing for high reliability and process integrity. Key features include:

  • Decentralized control – This architecture distributes control tasks across multiple controllers, each responsible for a specific process segment. This not only improves system reliability but also reduces the impact of a single point of failure.
  • High-level process integration – DCSs integrate process control, safety systems, and asset management into a cohesive system, offering operators a comprehensive view of plant operations. 
  1. Supervisory Control and Data Acquisition (SCADA)

SCADA systems are designed to provide a bird’s-eye view of industrial operations, enabling effective monitoring and control of processes spread across vast distances. These systems gather data in real-time from sensors, PLCs, and other control devices, funnelling this information to a central control room or HMI. Key features include: 

  • Remote control functionality – Operators can not only monitor but also control process parameters remotely, making SCADA ideal for utilities, oil and gas pipelines, and water treatment facilities.
  • Highly customizable HMI – The HMI in SCADA systems is highly customizable, offering tailored dashboards that highlight critical information and alerts to facilitate informed decision-making.

PLC levels infographic

Benefits of Control Systems 

Control systems have reshaped the production landscape from the ground up. By fundamentally transforming how operations are managed, these technologies and systems yield significant benefits that touch every aspect of production. Let’s break down these advantages with a closer look at some real-world applications: 

Boosted Operational Efficiency 

At the core of any manufacturing operation is the goal to do more, and do it faster—without compromising on quality. Control systems like PLCs are instrumental in meeting these ends.  

Picture an automotive assembly line where each robotic arm and conveyor belt operates under the guidance of a PLC. Complex tasks are executed with laser precision. This coordination allows for an uninterrupted flow of operations, drastically reducing downtime. The real-time data processing of these systems allows for any change in demand or any operational hiccup to be quickly addressed, keeping the production line not just running, but running optimally. 

Superior Product Quality 

The mantra ‘quality over quantity’ holds, but what if you could have both? In industries where the margin for error is slim, like pharmaceuticals or food production, DCS guarantees that every variable in the manufacturing process is well-controlled.  

From maintaining precise temperatures to exact chemical compositions and even visual inspections for defects, these systems ensure quality assurance and consistency in each product batch. This helps businesses meet stringent regulatory standards and builds consumer trust.

Machine

Enhanced Workplace Safety 

Manufacturing plants can be hazardous places, with the potential for accidents lurking around every corner. Control systems have significantly mitigated these risks. Robots, managed by PLCs, now handle the most dangerous or physically intensive tasks – working with toxic chemicals or in extreme conditions. This helps protect the safety and long-term wellness of plant workers.   

With SCADA systems, operational anomalies can be detected in real-time, triggering automatic shutdowns if hazardous conditions are identified. This not only protects the workforce but also minimizes the risk of costly downtime and equipment damage. 

Improved Predictive Maintenance  

Traditional maintenance strategies are often based on generic guidelines that do not account for the actual condition or usage of the equipment. In contrast, reactive maintenance only addresses equipment issues after they occur. Neither of these methods are ideal.  The advanced data analytics and real-time monitoring capabilities of control systems help plant management predict equipment failures before they occur, allowing businesses to avoid the high costs associated with unplanned downtime. The true value of predictive maintenance lies in its precision – repairs and part replacements are executed as needed. This approach can dramatically slash maintenance expenses over time. 

Predictive maintenance system infographic

According to a Deloitte study, predictive maintenance can reduce maintenance costs by 25%, breakdowns by 70%, and productivity by 25%. 

Recent Advancements in Control Systems 

Technological advancements continue to expand the capabilities of control systems in manufacturing. Some of the recent developments and real-world applications include:

  • Integration with the Internet of Things (IoT)—IoT refers to the vast network of physical devices that are connected to the Internet, collecting and sharing data. It’s about making everyday objects ‘smart’ by giving them the ability to send and receive data. For example, sensors placed on equipment can monitor vibration, temperature, and humidity levels in real-time. This data, when fed into control systems, enables precise adjustments to machine settings to prevent wear and tear, thus extending equipment lifespan.
  • Machine Learning and AI – In semiconductor manufacturing, AI and machine learning algorithms are crucial for quality control. These algorithms analyze images from high-resolution cameras to detect microscopic defects in silicon wafers during the fabrication process. 

Cyber-Physical Systems (CPS) –  CPS is a blend of physical machines and digital operations. These systems gather data from the physical environment using sensors, process this data with sophisticated software, and then use the insights to control the physical aspects of the system. For instance, in the realm of 3D printing, CPS continuously monitors and adjusts the printing process. This could mean altering the heat or speed based on the material’s properties or the complexity of the design.