Harnessing the power of PLC Data

Introduction

Software continues to devour the world, reaching critical industries and systems. Programmable logic controllers are an excellent example of this evolution: born in the 60s, they are now capable of operating at 2,000 MIPS (millions of instructions per second). That's 50 times the computing power of the computer that landed a rocket on the moon...

The evolution of PLC power has contributed to its widespread adoption in the industrial world. According to Statista, the global PLC market reached a value of around $11 billion in 2020, and is expected to maintain a compound annual growth rate of over 5% until 2026. The rapid expansion of the PLC market is naturally accompanied by an influx of PLC data into enterprises, posing a complex and vital challenge: to effectively harness this valuable resource and secure it.

This article explores the essence of PLC data, navigating the different types of PLC data and addressing the intricacies of PLC data analysis.

What exactly is PLC Data ?

PLC data refers to the information that is processed, stored, and manipulated within a PLC. The PLC will work with different types of data in order to monitor inputs, execute logic, and control outputs.

What is PLC Data inputs and outputs ?

PLC Data inputs : Data inputs for programmable logic controllers (PLCs) refer to signals or information from various sensors, switches, measuring instruments or other external devices that are on machine and used to monitor or control a process or system.

More specifically, the input data can be temperature data from sensors placed in industrial ovens, electric charge on a wire or data indicating the presence or absence of objects on a production line.

PLC Data outputs : The PLC receives input data, processes this data and makes decisions based on the way it has been programmed. These decisions are the output data. Output data is the signals or information generated by the PLC to control actuators, control devices and other elements of an automated system.

Examples of such signals or information include any type of reactions to the signal: sounding alarms, turning a light on or off, or opening or closing a valve.

The PLC works with a wide range of data types and data sources

To address the diverse scope of industrial automation requirements, the PLC exhibits proficiency in understanding an extensive array of data derived from multiple origins. Notably, each industrial element transmits operational data to the PLC, presented in distinct formats corresponding to the unique attributes of each machine.

This proficient data processing by PLCs encompasses a variety of data types, as detailed below, enabling them to efficiently coordinate intricate procedures, be it the regulation of meticulous motion patterns or intricate manufacturing protocols. This remarkable adaptability holds significant prominence in the contemporary industrial world, empowering efficient and comprehensive governance over a wide spectrum of systems and operational facets.

Understanding PLC Data Types

Boolean :

Definition : This data type represents binary values, typically used for conditions like ON/OFF, TRUE/FALSE, 1/0.

Example : a Boolean data type could represent whether a machine is ON (TRUE) or OFF (FALSE)

Integer :

Definition : Integer data type represents whole numbers, both positive and negative, without decimal points.

Example : Tracking the number of products produced in a factory using an integer data type.

Real :

Definition : Real data type represents floating-point numbers with decimal points. It is used for values that require fractional accuracy.

Example : Measuring the temperature of a chemical reaction using a real data type to account for fractional accuracy.

Double Word :

Definition : Double Word data type represents a larger integer range compared to INT.

Example : Monitoring the total energy consumption of a facility using a double word data type.

Word :

Definition : Word data type represents 16-bit unsigned integers.

Example : Counting the number of units in a product package using a word data type.

Byte :

Definition : Byte data type represents 8-bit values. It's often used to store smaller data or status information.

Example : Storing the status of different sensors in a production line using byte data type.

Timer :

Definition : Timers are used to track time intervals. They are used to control events based on elapsed time.

Example : Using a timer to control the duration of a mixing process in a pharmaceutic industry.

Counter :

Definition : Counters are used to count discrete events or pulses. They are often used for tasks like tracking the number of items produced on a manufacturing line.

Example : Counting the number of times a robotic arm completes a specific movement in an assembly line.

String :

Definition : String data type represents sequences of characters, like text or alphanumeric data.

Example : Storing a serial number or product name as text using a string data type.

Array :

Definition : Arrays are collections of data elements of the same data type. They allow storing multiple values under a single variable name.

Example : Storing the daily production quantities for each product type using an array.

Structures :

Definition : Structures allow you to define your own custom data types by grouping different data types together under a single variable name.

Example : Creating a custom data type named "Employee" with fields like name, ID, and department to manage employee information.

Why is it important to run PLC data analysis ?

The Evolution of PLC Technology

The Programmable Logic Controller (PLC) has undergone a significant evolution since its inception, transitioning from a rudimentary device with limited capabilities and a substantial cost, to a sophisticated, data-rich component integral to modern industrial processes.

In its early stages, the PLC was conceptualized as an electronic equivalent of a cerebral system, equipped with a basic programmable memory, a handful of input/output interfaces, and a power supply. Its primary function was to oversee and control rudimentary tasks within industrial operations.However, the ensuing decades have witnessed a substantial metamorphosis in PLC technology. In the context of Industry 4.0, PLCs have become indispensable, not merely as command executors but as prolific generators and collectors of critical data, thereby transforming into substantial repositories of information.

Contemporary PLCs have transcended their initial roles, evolving into creators and curators of vital data. These advanced models are equipped with sophisticated sensor technology and data collection capabilities, enabling them to amass a plethora of information. This includes, but is not limited to: production volumes, operational temperatures, pressure levels, and cycle times.

Previously deemed as inconsequential, this data now provides profound insights into the intricate workings of each component within the production chain. The ability to collect, analyze, and interpret this data has revolutionized our understanding of industrial processes, thereby underscoring the pivotal role of PLCs in the era of data-driven manufacturing and Industry 4.0.

Granular Production Chain Optimisation :

PLC data analysis is emerging as a key pillar within Industry 4.0, offering undeniable benefits for the meticulous optimisation of your production chain. Through a close examination of PLC-derived information, you can now discern previously elusive bottlenecks and make precise adjustments to improve overall efficiency. This granular optimisation not only boosts productivity, but also eliminates waste, reducing your operational costs and boosting your competitiveness in the marketplace.

In-depth understanding of your machines :

PLC data analysis offers a privileged view of the inner workings of your machines, giving you the opportunity to delve into the operational intricacies of your plant. By exploiting this global perspective, you can tactically solve complex problems, anticipate potential malfunctions and make preventive improvements. A deep understanding of machine mechanisms translates into proactive maintenance, reducing unplanned downtime and extending the life of your equipment.

Operational Excellence, Cyber Monitoring and Compliance :

Analyzing PLC data is the foundation of operational excellence. It enables teams to monitor the performance of their systems in real time, predict fluctuations in demand and react with agility to changing conditions. At the same time, PLC data analysis plays a crucial role in cyber surveillance, identifying potential anomalies and strengthening the resilience of systems in the face of digital threats.

What's more, compliance team will find a major ally in PLC data analysis. Increased operational traceability will enable them to demonstrate your adherence to industry standards and regulations, avoiding costly penalties and preserving your reputation.

PLC Compliance :

Compliance requirements for Programmable Logic Controller (PLC) systems can vary depending on the specific industry, region, and application. However, there are several common standards and regulations that often apply:

IEC 61131-3 Standard: This is the international standard for PLC programming languages and specifies the syntax, semantics, and display for five languages: Ladder Diagram (LD), Function Block Diagram (FBD), Structured Text (ST), Instruction List (IL), and Sequential Function Chart (SFC).

IEC 61508 Standard: This is the international standard for functional safety of electrical/electronic/programmable electronic safety-related systems. It is applicable to all kinds of industries. The standard covers the complete safety lifecycle and may be used to establish a safety management system.

ISO 13849-1 & -2 Standards: These standards provide safety requirements and guidance on the principles for the design and integration of safety-related parts of control systems, including the design of software.

UL 508 Standard: In the United States, the Underwriters Laboratories (UL) standard 508 is often required. This standard applies to industrial control equipment such as PLCs.

FCC Compliance: In the United States, PLCs must also comply with Federal Communications Commission (FCC) regulations regarding electromagnetic interference.

CE Marking In Europe, PLCs must carry the CE mark to signify compliance with relevant European health, safety, and environmental protection legislation.

RoHS Compliance: The Restriction of Hazardous Substances (RoHS) directive restricts the use of certain hazardous substances in electrical and electronic equipment, including PLCs.

ATEX Directive: For PLCs used in potentially explosive atmospheres in Europe, compliance with the ATEX directive is required.

Cybersecurity Standards: With the rise of Industry 4.0 and the Industrial Internet of Things (IIoT), PLCs are increasingly networked and therefore subject to cybersecurity risks. Standards such as IEC 62443 provide a framework for securing industrial automation and control systems.

It's important to note that this is not an exhaustive list and specific applications may have additional requirements.

Why does PLC data analysis complement your SCADA and MES systems ?

The integration of Programmable Logic Controller (PLC) data analysis with Supervisory Control and Data Acquisition (SCADA) and Manufacturing Execution Systems (MES) significantly enhances the value proposition of industrial operations. While SCADA and MES systems offer real-time visibility and holistic management of operations, the incorporation of PLC data analysis introduces an additional dimension of precision and insight.

By amalgamating PLC data analysis with SCADA and MES systems, industrial operations can extend their purview beyond macro-level monitoring. This methodology uncovers concealed correlations, facilitating a granular understanding of the interplay between disparate processes. It provides a detailed, machine-level perspective that complements the system-wide view furnished by SCADA and MES systems. Moreover, PLC data analysis augments the capabilities of SCADA and MES systems. While SCADA and MES systems primarily concentrate on instantaneous data collection and orchestration of operations, PLC data analysis transmutes raw data into actionable intelligence. This conversion process underpins predictive maintenance strategies and guides data-driven decision-making processes. For instance, PLC data analysis can reveal patterns such as a gradual increase in machine cycle times or subtle changes in product quality, which could indicate a need for maintenance or adjustments in the production process.

In essence, the synergistic combination of SCADA, MES, and PLC data analytics constructs a comprehensive framework that fosters an in-depth comprehension of intricate industrial processes. This balanced approach caters to the necessity for data-driven decision-making, thereby optimizing operational efficiency and productivity.

How Trout Software can help you perform PLC Data Analysis ? 🎣

Take our compute to your data

Trout Software solution radically transforms industrial data management approach by ushering in a new era of distributed computing. No more data transfers to processing centers. Through cutting-edge WebAssembly technology, teams are able to run binary code (small and fast) where data is generated: on edge systems.

This innovation significantly reduces latency, reduce the needs for data pipeline and centralization, optimizes resource utilization, and completely reimagines how data is leveraged

Expose machine data to operators by providing no-code analysis tool

Empower operators with instant access to real-time machine data, without requiring programming skills. Trout Software no-code interface enables teams to perform in-depth analysis without writing a single line of code. Operators can explore data, identify trends, and make informed decisions to optimize operations, all in a natural and seamless manner. 📊

Perform 24/7 Operations Monitoring

Factories never sleeps, and Trout Software solution ensures continuous monitoring. 📈

Trout Software's Operation Hub goes beyond being a passive monitoring tool; it functions as an active system that streams data input, applies detection and compliance rules, correlates additional context, and triggers alerts when necessary.

In this process, users are empowered to automate the playbooks they have generated, facilitating ongoing checks and receiving notifications upon the detection of rule deviations.

Upon playbook creation, the automation process is streamlined into three simple steps:

• Choose the desired playbook for automation.
• Configure control parameters.
• Initiate scheduling by clicking the designated button.

Leverage Seamless Integration

Trout Software's Operation Hub is extraordinarily lightweight (couple of MB), allowing it to be easily deployed across a variety of architecture, from single rasberry pi to large servers. This ensures seamless integration with existing PLC systems or DIN racks and guarantees low-resource consumption, contributing to the efficient running of your industrial processes.💯

Conclusion

In a world where data is king, mastering PLC data is a competitive necessity, and a security and compliance challenge. Understanding PLC data types and analysis, knowing how to exchange and transfer this data is integral for businesses. Trout Software aims to provide a breakthrough technology allowing teams to deploy PLC level monitoring, correlation with additional systems and enhanced security.

👉 Harness the power of PLC data today