In manufacturing, consistency is king. From the first widget to the last, every product needs to meet an exacting quality standard. This degree of precision is not coincidental; it’s generated by controlled processes. Unappreciated Process control has a thankless job running the factory: someone making sure every variable is under control, each spec is within specification, and nothing happens that isn’t supposed to.
In this guide, we will look at process control systems. We’ll explain what they are, why they’re necessary for contemporary production processes and how they interact with powerful solutions such as a Computerised Maintenance Management System (CMMS) to bring efficiency, safety and profitability to your company.
What Is a Process Control System?
Background: A process control system is a combination of technology and techniques used to monitor and control the production process. Its objective is to control all the "independent" variables that could affect some desired output. Simply put, your production line’s central nervous system executes product consistency, operational safety, and resource efficiency.
At its heart, a process control system follows a simple feedback loop, containing three basic elements:
- Sensors: These devices measure process variables like temperature, pressure, or flow rate.
- Controllers: The "brain" of the system. A process controller compares the sensor's measurement to a desired setpoint and determines if any correction is needed.
- Actuators: These are the "muscles" that take action based on the controller's decision. Examples include valves, motors, or heaters that adjust the process to bring it back to the setpoint.
A CMMS complements this system by managing the health of the physical assets, the sensors, controllers, and actuators that make process control possible. It automates maintenance schedules and work orders, ensuring the control hardware is always reliable.
Why Process Control Matters in Modern Manufacturing
The efficient control of processes is closely related to the increase in OEE. Having stable and predictable processes lets you maximise performance, quality and availability. A good process control strategy ensures human error is minimised, materials are saved, and products meet certain quality criteria consistently.
This process of control is essential for profit in the management of a business. It helps avoid expensive errors and do-overs. This is where the CMMS enters the picture, since it can track how well the equipment performs and when preventive maintenance should be scheduled for these vital control assets that, in turn, ensure that your systems work properly and as long as they’re maintained.
How Process Control Systems Work
"Control loops" are what make process control systems work. A control loop is always trying to keep a process variable at a setpoint that is desirable. There are four steps in this: input (measurement), process, output (adjustment), and feedback.
There are two main types of control systems:
- Open Loop Systems: These operate without feedback. They execute a pre-programmed action without checking the output. A simple example is a microwave oven that runs for a set time, regardless of how hot the food actually is.
- Closed Loop Systems: These use feedback to self-correct. The system measures the output and compares it to the setpoint, making continuous adjustments. A thermostat in a heating system is a classic example.
Closed-loop systems are used in modern production, and they work with digital tools like SCADA, PLCs, and a CMMS. This connection makes a strong ecosystem where operational data from the process control technology (PCS) helps with maintenance tasks, and a good maintenance program makes sure the PCS system works without a hitch.
Types of Process Control Systems
Different manufacturing environments require different control strategies. Understanding the types of process control systems helps you choose the right approach for your facility.
Manual Process Control
An operator physically monitors gauges and readings, then manually adjusts valves or settings. This method is prone to human error and is rarely used for critical processes.
Automatic Process Control
This system uses feedback from sensors to automatically make corrections via controllers. It is the foundation of most modern industrial automation.
Distributed Control Systems (DCS)
A DCS is used in large, complex plants. It features a centralised supervisory control system that communicates with numerous local controllers distributed throughout the facility. This offers robust, plant-wide control.
Supervisory Control and Data Acquisition (SCADA)
SCADA systems are designed for remote monitoring and control over large geographical areas. They collect data from remote locations and send it to a central station for analysis and control actions.
PLC-Based Systems
Programmable Logic Controllers (PLCs) are rugged computers used for automating specific industrial processes, especially in discrete manufacturing. They are known for their flexibility and reliability in controlling machinery and assembly lines.
Examples of Process Control in Action
You can identify an example of process control in nearly every industry.
- Manufacturing: Regulating temperature in a furnace or pressure in a hydraulic press to ensure material integrity.
- Food & Beverage: Pasteurisation processes where milk must be held at a precise temperature for a specific duration to ensure safety and quality.
- Energy: Managing the flow of water through turbines in a hydroelectric power plant to generate a consistent supply of electricity.
- Pharma: Ensuring batch consistency in drug production, where even minor deviations can compromise a product's efficacy and safety.
In each of these examples, a CMMS like Makula helps monitor and maintain the equipment supporting these critical processes. If a pump responsible for flow control starts vibrating abnormally, the CMMS can generate a work order before it fails and disrupts production.
Process Control & Automation: The Backbone of Smart Manufacturing
Though we use them interchangeably, process control is not the same as automation. Constrained process control involves keeping certain variables between limits. Automation encompasses the general notion of using technology to carry out tasks without human involvement. Automated process control is the intersection of these two ideas.
Now, IoT sensors and digital twins are giving us an unprecedented view into factory floors. To utilise this data, a CMMS is everything. It records the history of maintenance and control data in real time so that the full picture is available for improvement pursuits.
Integrating Process Control Systems with CMMS Software
The true power of a modern manufacturing operation is realised when systems communicate. Integrating a process control system with a CMMS bridges the gap between operations and maintenance.
Data Driven Maintenance
A CMMS can collect real-time condition data (like temperature, vibration, and pressure) directly from your PLCs, SCADA systems, and other controllers.
Automated Work Orders
Set triggers in your CMMS to automatically generate a work order when a process parameter deviates from its setpoint. For instance, if a motor's temperature exceeds a safe limit, a work order is instantly assigned to a technician. Ensure technicians always have the necessary components with parts & inventory management.
Predictive Maintenance
By analysing historical control and maintenance data, a CMMS can schedule repairs before a breakdown occurs using preventive maintenance features. This allows you to schedule repairs before a breakdown occurs.
Compliance & Reporting
A CMMS keeps track of calibration records and audit logs for all of your process control devices on its own. This makes it easier to follow industry rules. Makula CMMS can easily connect to PLCs, SCADA, and ERP systems, making it the primary place to store all of your maintenance data.
Benefits of Using CMMS for Process Control Operations
- Reduced Unplanned Downtime: Automated maintenance alerts and predictive insights prevent unexpected equipment failures.
- Improved Data Accuracy: Centralised data from both process and maintenance systems provides a single source of truth for decision-making. Use reports & analytics to track KPIs, monitor downtime, and optimise production efficiency.
- Seamless Collaboration: Engineering, operations, and maintenance teams can work from the same data, improving communication and response times.
- Extended Asset Lifespan: Proactive maintenance ensures your critical control equipment runs efficiently for longer, lowering the total cost of ownership.
Challenges and How CMMS Solves Them
Even the best process control systems face challenges. Sensor drift can lead to inaccurate readings, and fragmented data stored in spreadsheets makes root cause analysis nearly impossible. Tracking downtime and equipment calibration manually on a PCS form is inefficient and error-prone.
A CMMS solves these problems by:
- Centralising Data: All maintenance, calibration, and performance data for PCS equipment is stored in one place.
- Automating Workflows: Calibration schedules and maintenance alerts are automated, ensuring nothing is missed.
- Providing Powerful Analytics: A CMMS makes it easy to analyse downtime, identify root causes, and track trends in equipment health.
Implementing CMMS in Process-Controlled Manufacturing Environments
Step 1: Assess Your Existing Control Systems: Identify your most critical assets and the PLCs, DCS, or SCADA systems they are connected to.
Step 2: Define Maintenance Objectives: Set clear goals focused on improving uptime, reliability, and quality metrics.
Step 3: Integrate with Existing Systems: Connect your CMMS to your control systems to begin collecting live operational data.
Step 4 Train Operators and Maintenance Teams: Operators can follow checklists & inspections to ensure every process step is correctly maintained.
Step 5: Analyse and Optimise Continuously: Use the analytics within your CMMS to gain predictive insights and find new opportunities for process optimisation.
Future of Process Control
The future is intelligent. AI-powered adaptive control systems will soon be modifying processes dynamically based on multiparametric analysis. Leverage the AI Maintenance Copilot to automate routine tasks and predict process issues before they occur. Smart sensors will perform self-diagnostics and self-correct. Central to this development is the merging of CMMS and process data analytics. This pairing will fuel predictive maintenance schemes, so all downtime is wiped out and any minor production glitches are now a thing of the past. The road to full autonomy is under construction with machine automation and automated process control.
Improving Process Reliability with CMMS Integration
A large manufacturing plant was struggling with frequent, unplanned downtime in its packaging line. They integrated Makula CMMS with their SCADA system and PLCs. The CMMS began monitoring motor temperatures and conveyor belt speeds in real time. Technicians could also update work orders and log issues on the go using the mobile app, improving response times and keeping production running smoothly.
Results:
- A 20% reduction in unplanned downtime within six months, as the CMMS triggered predictive maintenance work orders before failures occurred.
- A 15% faster response time to control deviations, as alerts were sent directly to technicians' mobile devices.
- Enhanced process audit and compliance through automated record keeping of all maintenance and calibration activities.
Optimise Your Process Control with Makula CMMS
Cease allowing equipment breakdowns to slow your production. Through linking your process control systems with a robust CMMS, you can transition from reactive fixes to predictive, data-supported maintenance. Makula CMMS integrates easily, delivers strong analytics and real-time insight to help optimise your production floor.
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