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Introduction

In the shift from Industry 3.0 to Industry 4.0, digital automation has transformed manufacturing. Industry 3.0 enhanced productivity via microprocessors and automation but lacked integration across processes. Then, Industry 4.0 brings smart manufacturing, where interconnected systems enable real-time data flow and data-driven decision making. MQTT (Message Queuing Telemetry Transport) facilitates this transformation with flexible messaging for real-time data exchange across large networks.

Industry 4.0 aims to create smarter factories using IIoT for faster, data-driven decisions. Factories need robust data communication to handle large data volumes, connect devices, and scale production. MQTT supports these needs, becoming a backbone for Industry 4.0 manufacturing.

This page explores how MQTT enhances communication across industrial process layers, revolutionizing the leap into Industry 4.0.

The Digital Automation of the
Industry 3.0 Regime

While Industry 3.0 introduced automation to manufacturing, it still lacked integration across the various layers of industrial operations. Manual interventions and proprietary communication systems limited the scalability and real-time data exchange necessary for smart manufacturing.

ISA model

The ISA Model and Manual Data Transfer

At the core of Industry 3.0 was the hierarchical ISA-95 model (Industrial Automation Pyramid), which relied heavily on manual data transfers. Workers monitored machines and manually transferred data to enterprise systems for analysis, limiting data accuracy and slowing decision-making.

  • Level 0: Field Devices (sensors and actuators)
  • Level 1: Control Devices (PLC, RTU)
  • Level 2: Supervisory Control (SCADA)
  • Level 3: Manufacturing Operations Management (MES)
  • Level 4: Enterprise Resource Planning (ERP)

For example, data collected at Level 1 (sensors and PLC) and Level 2 (control systems) was often siloed, making it inaccessible to Level 3 (MES) and Level 4 (ERP) systems responsible for production scheduling and inventory management. This resulted in a disconnect between operational technology (OT) and information technology (IT).

The challenge was to make these levels communicate in real time, and this is where Industry 3.0 fell short.

Peripheral automation

Peripheral Automation

As automation systems improved, they helped ease tasks such as monitoring, controlling, and data logging. Machines became equipped with sensors and Programmable Logic Controllers (PLCs), which provided a measure of intelligence, but often these devices worked in isolation or required proprietary systems for integration. They lacked the flexibility and real-time data exchange needed for modern, interconnected factories. Data had to be pulled manually or through scheduled queries, limiting the agility of manufacturing operations.

DCS architecture

Distributed Control Systems (DCS)

DCS systems were introduced to facilitate local control of complex processes. While DCS systems allowed for some real-time control, they were limited in scalability and struggled to manage data across different levels, especially between the control layer and enterprise systems. Additionally, expanding DCS to include a new equipment or adjust to the changes were often complicated and required high cost. This made it harder for factories to connect all parts smoothly and stay adaptable to their needs.

Integration Gaps Across Levels

Integration Gaps Across Levels

Despite the advancements, a significant gap remained in connecting the real-time operational data from Level 2 (control layer) to Level 3 (manufacturing operations) and Level 3 to Level 4 (enterprise resource planning). This disjointed system prevented seamless communication, making it difficult to synchronize production activities with business operations. This resulted in siloed data, leading to inefficiencies and delays in decision-making. The lack of smooth data flow across all levels significantly impacted productivity and resource allocation, causing companies to slow down in responding to changes.

The Digital Transformation Era: Industry 4.0

With Industry 4.0, the paradigm shifted from isolated automation to interconnected systems that communicate in real time. This transformation introduces smart manufacturing environments where devices, sensors, and systems across all layers of the ISA-95 hierarchy can share data seamlessly. The emphasis is now on creating cyber-physical systems where IIoT devices and cloud MQTT platforms work in sync to optimize production processes, increase efficiency, and reduce downtime.

Industry 4.0 Requirements for Communication Protocols

Industry 4.0 Requirements for Communication Protocols

Industry 4.0 demands a communication protocol that is:

  • Lightweight and scalable: Able to handle large-scale networks of connected devices without overloading the network.
  • Reliable and secure: Ensures data integrity, particularly when transferring critical operational data.
  • Flexible: Can integrate with legacy systems while also supporting new, innovative technologies such as AI and machine learning.
  • Real-time: Supports low-latency communication, enabling real-time monitoring and control of manufacturing processes.

This is where MQTT’s strengths become evident. Its lightweight, publish-subscribe architecture, reliability through QoS levels, and integration capabilities make it an ideal solution for enabling smart manufacturing in the Industry 4.0 landscape.

Benefits of using MQTT in manufacturing systems

MQTT offers several key benefits for manufacturing systems. It enables fast, reliable data exchange between devices, enhancing operational efficiency. Its flexibility allows easy integration with existing systems while ensuring secure communication. Additionally, MQTT's real-time data exchange capability enhances decision-making and process optimization.

Data Exchange Speed

Data Exchange Speed

One of the key benefits of MQTT is its ability to handle large amounts of data with minimal delay and the ability to gather, process, and respond to data in real time. In a manufacturing environment, real-time data exchange is critical for monitoring machine performance, identifying bottlenecks, and reducing downtime. MQTT's lightweight nature ensures that it can efficiently transmit data between machines, sensors, and enterprise systems, even in low-bandwidth environments.

  • Reduced latency in transmitting sensor data from field devices to MES or SCADA systems.
  • MQTT in manufacturing environment enables quicker responses to events, improving production uptime and efficiency.

MQTT’s architecture is designed to handle a many connected devices, which is critical in smart factories with thousands of sensors and machines. MQTT broker can handle millions of messages per second, enabling scalability across entire manufacturing plants. As factories scale their IoT deployments, MQTT’s ability to handle high device volumes ensures that the system grows efficiently without becoming overwhelmed by the increased data load.

QoS data transfer

Quality of Service (QoS) of Data Transfer

Manufacturing processes are often time-sensitive and data-critical. Losing or delaying data can have significant consequences, such as downtime, product defects, or even safety issues. To ensure that data is transferred reliably, MQTT offers three Quality of Service (QoS) levels:

  • QoS 0: This level provides "at most once" delivery, meaning that messages are sent without requiring confirmation of receipt. This is useful for non-critical data such as environmental monitoring, where data loss may not be catastrophic.
  • QoS 1: In this "at least once" mode, the message is guaranteed to be delivered, but duplicates may occur. This is crucial for slightly more critical data, such as machine status updates, where it’s important to ensure the data arrives.
  • QoS 2: The highest level, "exactly once," ensures that messages are received only once. This is essential in highly sensitive areas, such as control commands to manufacturing equipment, where executing a command twice could result in catastrophic outcomes.

Reliable data transfer is critical for smart manufacturing, especially in applications like predictive maintenance, quality control, and automated decision-making. MQTT’s QoS levels offer the flexibility to optimize the tradeoff between speed and reliability, depending on the data’s importance.

MQTT sparkplug

MQTT Sparkplug: Standardizing IIoT Communication

In traditional manufacturing systems, devices often speak different protocols, making integration complex. MQTT Sparkplug, an open-source protocol extension built on top of MQTT, solves this by providing a standard message format that ensures interoperability between different devices and systems.

Why Sparkplug Matters

Sparkplug provides a standardized message format for MQTT-based IIoT communications. It defines the payload structure for publishing data and state information, ensuring that devices from different vendors can seamlessly communicate with each other and with industrial systems such as PLCs, SCADA, and MES.

  • Unified Data Model: Sparkplug uses a stateful data model, where devices continuously publish their state to the MQTT Broker. This makes it easy to monitor devices and keep systems in sync, a critical requirement for Industry 4.0’s real-time needs.
  • Simplified Integration: By adhering to the Sparkplug standard, factories can reduce the complexity of integrating new devices and systems, making it easier to scale IIoT implementations without lengthy custom development.
UNS

Unified Namespace (UNS): Centralizing Operational Data

A key principle of Industry 4.0 is the idea of creating a Unified Namespace (UNS), a centralized repository where all plant data resides. MQTT serves as the backbone of UNS by facilitating real-time data sharing across different systems.

  • Data Centralization: With MQTT acting as the transport layer, data from machines, sensors, and systems is published to a single broker, which organizes and distributes the information as needed. This creates a unified view of the entire manufacturing process.
  • Elimination of Data Silos: Traditionally, data in factories is stored in separate systems, making it difficult to access and analyze holistically. MQTT and UNS eliminate these silos, enabling real-time insights and more effective decision-making.

A centralized UNS is the foundation for many Industry 4.0 applications, such as predictive analytics, digital twins, and real-time performance monitoring.

Use Cases of MQTT in Smart Manufacturing

MQTT plays a crucial role in enabling efficient communication and control in smart factories. It ensures real-time machine control in automated production lines by sending precise information to stop machines if any anomalies are detected. Further, it helps in optimizing production processes, thereby elevating productivity.Following are the two significant use cases where MQTT is making a substantial impact in smart manufacturing.

Machine control

Use Case 1: Machine Control in Automated Assembly Lines

In an automated assembly line, machines perform specific tasks based on data or instructions received in real time. MQTT can be used to send control signals to these machines. For instance, if an anomaly is detected on the line, an MQTT message with QoS 2 can be sent to stop the machine immediately, ensuring that the message is delivered exactly once and preventing any duplication that could lead to system errors or machine malfunctions.

Real-time data exchange

Use Case 2: Real-Time Data Exchange in a Multi-Vendor Environment

Imagine a smart factory using machines from different vendors. Each machine generates performance data, but in different formats. Sparkplug standardizes this data, allowing a central SCADA system to monitor performance, detect anomalies, and make real-time adjustments across the factory floor, regardless of the machine’s origin. This enables better decision-making, improved machine utilization, and reduced downtime.

MQTT and Integration with Traditional Systems

MQTT doesn’t just work with modern IoT devices—it also integrates seamlessly with existing systems in a manufacturing plant. This makes it the perfect protocol to bridge the gap between traditional systems and Industry 4.0 innovations.

REST APIs and MQTT

REST APIs are commonly used to integrate software systems in manufacturing, such as MES or ERP systems. MQTT complements REST APIs by providing real-time communication for data streams.

Real-Time Data Flow: While REST APIs handle transactional data, MQTT can be used to send real-time data between sensors and applications. This ensures that traditional systems can act on real-time data, even if they were originally designed for batch processing.

MQTT Rest API integration allows manufacturers to leverage both modern IIoT solutions and legacy systems, ensuring a smooth transition into Industry 4.0.

REST APIs & MQTT
Web hooks

Web Hooks

Webhooks enable real-time notifications from systems when specific events occur. In manufacturing, webhooks can be used with MQTT to trigger alerts or actions based on real-time data from machines.

For instance, when a sensor detects an anomaly, it can publish a message to an MQTT broker, which then triggers a webhook to alert the appropriate personnel. This ensures that any anomalies detected are addressed promptly, improving responsiveness and boosting proactive maintenance.

By enabling real-time response to events, webhooks help improve overall system efficiency and ensure that critical issues are dealt with before they escalate.

Two-Way Integration

MQTT enables two-way communication, meaning data flows not only from machines to control systems but also in the opposite direction. This allows real-time control commands to be sent from an MES or SCADA system back to field devices, enabling dynamic adjustments to the production line.

For instance, if production speed needs adjustment, an MES System with the help of MQTT can send a control command to the PLCs, immediately updating the machine's settings.

This level of real-time communication improves automation and flexibility in manufacturing, allowing quick adaptation to changes in demand or production requirements.

2 way integration

The Catalyst for Industry 4.0 Success

As Industry 4.0 becomes the norm in manufacturing, MQTT is playing an increasingly important role in transforming how data is exchanged across industrial systems. By enabling real-time communication, ensuring reliable data transfer with QoS, and supporting integration with traditional systems, MQTT helps manufacturers bridge the gap between legacy systems and the IIoT era. With the rise of innovations like MQTT Sparkplug and UNS, manufacturing facilities can now achieve seamless data exchange, improved decision-making, and increased productivity, ultimately transforming the way manufacturing operates in the Industry 4.0 era.

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