Embracing the Future: A Comprehensive Guide to Transitioning from Industry 3.0 to Industry 4.0

If you are reading this, congratulations on having thrived in the Industry 3.0 era.

SCADA and other Systems of Records (SOR) like MES, Historian, ERP, CRM, or time-series databases have served their time as the pillars of Industry 3.0. You’ve leveraged these tools to excel in an era dominated by automation and computerization, a testament to your organization’s innovation and agility.

However, the dawn of Industry 4.0 brings forth a seismic shift. Initiated by the widespread adoption of the TCP/IP protocol in the 1990s, it champions data exchange and connectivity, demanding a significant update to the status quo. Adapting to this transition is no longer a luxury but a survival necessity.

Your Industry 3.0 tools, while vital for harnessing operational data, now stand as fragmented, siloed systems. Their segmented operation calls for intricate integrations, custom codes, and high maintenance to extract substantial value, thus presenting a challenge in an increasingly interconnected industrial landscape.

Enter Industry 4.0 – and beyond. You need a comprehensive Industrial DataOps approach to unlock the OT data trapped in these siloed systems, activate it, and find a scalable innovation path across your enterprise.

This article steers you deeper into the relationship between prevalent Industry 3.0 systems and the revolutionary Litmus Edge. We delve into how you can leverage Litmus Edge to ride the wave of Industry 4.0 and beyond, without the need to overhaul your existing tools.

SCADA stands for Supervisory Control and Data Acquisition. These systems were first developed in the mid-20th century, with significant advancements occurring in the 1970s and 1980s.

Born out of Industry 3.0’s automation wave, SCADA played a crucial role in streamlining industrial operations, improving efficiency, and reducing manual labor. They are vital for monitoring and controlling industrial processes.

SCADA systems typically consist of hardware and software components. The hardware includes sensors, actuators, and controllers distributed across the industrial environment, while the software provides the interface for monitoring and controlling these devices.

They operate by collecting data from sensors and equipment in real-time, transmitting it to a central computer or server for processing and analysis. Operators can then see this data using graphical interfaces, enabling them to monitor operations and make informed decisions.

SCADA systems are useful for several reasons real-time monitoring of critical industrial processes, remote control of industrial equipment, parameters and settings, and bringing basic automation to processes in the plant floor.

Whether you’re using Ignition, Wonderware, Siemens or any other SCADA solution, it doesn’t matter. Litmus Edge brings your SCADA systems into Industry 4.0, offering a range of features that augment their functionality.

A SCADA system functions as the central nervous system for managing and governing production machinery within a protected environment. Take, for instance, a bottling plant where the SCADA system oversees conveyor belts, filling equipment, and packaging robots ensuring they operate within the set parameters. The inherent design requires that such systems remain isolated from external software or unrelated in-house systems to prevent critical interruptions—akin to a control room that’s off-limits to external influences.

Tapping into the full potential of SCADA systems is not without challenges; it calls for a unique blend of niche, sophisticated expertise. Software engineers, for example, must master complex programming skills to fine-tune these systems—much like a watchmaker delicately calibrating the inner workings of a timepiece.

However, the tides of modern manufacturing require a paradigm shift. The industry’s thrust towards data-centered operation necessitates integrating various data points, such as temperature readings from a heat-sensitive production line or the operating speed of assembly line robots. The goal is to not only aggregate this trove of data but to interpret it with detailed precision, drawing meaningful connections—akin to a data analyst deciphering trends from a mosaic of numbers.

The ultimate objective lies in harnessing this enriched, contextual data to forecast future scenarios, craft more efficient workflows, and enhance overall throughput—all while steering clear of any operational disruptions. It’s a delicate balance, similar to a symphony conductor ensuring every instrument contributes to the harmony without a single note marring the performance.

Litmus Edge is designed to solve these challenges by enabling manufacturers to unlock data trapped in PLCs, CNCs, DCS systems, SCADA and various standalone systems, activate them in place and provide a scalable and repeatable method to maximize the value of OT data both on plant floors and at the enterprise-level.

Manufacturing Execution System (MES) is a crucial software-based system in manufacturing that tracks and manages recipe of production processes. It is designed to ensure efficient operation on the shop floor, providing essential functions like scheduling, resource allocation, production monitoring, quality management, and comprehensive data analysis. By integrating with both enterprise resource planning (ERP) systems and shop floor control systems, MES ensures a seamless flow of information across all levels of manufacturing, facilitating optimized operations and enhanced efficiency.

Key functions of MES:

• Scheduling and resource allocation to optimize production.

• Real-time production monitoring for immediate response to issues.

• Quality management to maintain product standards.

• Data analysis for informed decision-making.

A historian is a specialized database system used in industrial automation and control environments. It collects, stores, and manages time-series data from various sources such as sensors, machines, and processes. It records historical data at regular intervals, allowing users to analyze past performance, trends, and patterns.

Key functions of Historian:

• High-speed data collection

• Compression algorithms for efficient storage

• Support advanced querying and visualization tools to facilitate data analysis and decision-making.

While MES systems are pivotal for day-to-day manufacturing operations and provide valuable data from the shop floor, they often lack advanced analytics capabilities and the context needed for deeper insights. Similarly, the data that historians collect and store data from industrial devices, such as MES and SCADA systems, is crucial. However, it often lacks context and isn’t immediately useful for decision-making.

This is where Litmus Edge comes into play.

Picture a bustling bottling plant where each second of uptime is paramount. Here, historians play the role of archivists, meticulously recording every data point from past production runs—like keeping a detailed ledger of every bottle produced. However, if you try to decipher future trends or immediate hiccups from these historical data alone, the lack of real-time analysis becomes evident, akin to a historian poring over ancient texts without understanding the current context of those times.

Enter Manufacturing Execution Systems (MES), akin to a floor manager in the plant ensuring every stage of the bottle production—from blow molding to filling, capping, labeling, and packing—is executed with precision, sticking to the ticking clock of delivery schedules. Yet, this system often struggles when it comes to making sense of the data in a way that reveals deeper operational insights; much like a manager who can coordinate the team effectively but can’t predict the impact of today’s work on tomorrow’s success.

Moreover, MES systems can be like specialized pieces of equipment that don’t always ‘talk’ well with other machines, potentially leaving integration with the broader tech ecosystem a bit of a jigsaw puzzle.

Now, imagine introducing Litmus Edge into this environment. Litmus Edge acts like a polyglot interpreter and a savvy business analyst rolled into one; it not only speaks the language of your SCADA, PLCs, CNC machines, and links with MES and historians, but it also brings a deeper comprehension to the data gathered. It’s like injecting a dose of intelligence into your bottling line, giving it the ability to visualize the interplay of variables, and draw insightful conclusions that lead to concrete, actionable steps. With Litmus Edge, your bottling plant can identify a problematic valve in near real-time or forecast the need for preventative maintenance on a filler head, without slowing down the pace of production.

Think of this as giving your plant a sixth sense, with the ability to identify issues before they even arise, ensuring the smooth continuation of production cycles without the risk of downtime. This added layer of analysis can lead to rapid corrective measures that are informed, timely, and effective, keeping the rhythm of your bottling plant flowing as smoothly as the beverages it produces.

Time Series Databases (TSDBs) are engineered to store and analyze time-stamped data efficiently. While historians are tailored for industrial settings, focusing on data from automation systems, TSDBs boast a broader application scope, encompassing various industries.

They handle data from IoT devices, web applications, financial systems, and more, demonstrating their versatility. TSDBs facilitate flexible data modeling and schema design, accommodating diverse time series data types and applications. They stand out with their advanced features, including analytics, machine learning integration, and support for complex queries and processing tasks, offering scalability and versatility across numerous sectors.

It’s noteworthy that while historians are predominantly used in industrial contexts for their ability to manage high-frequency data from industrial equipment, TSDBs, with their generalized design, also find utility in industrial settings alongside other domains. This adaptability enables them to serve a wide array of applications, making them a valuable tool for managing time series data in various industries.

Litmus Edge propels the capabilities of TSDBs by integrating advanced data analytics, which are typically absent in standard TSDBs. This enhancement allows for the identification of trends, patterns, and anomalies in time-series data, fostering proactive decision-making and predictive analysis. Such advancements lead to improved operational efficiency and reduced downtime.

By offering prebuilt statistical functions, Litmus Edge empowers TSDBs to not only store and retrieve vast data volumes but also to enable real-time and predictive decision-making. This dual capability enhances the operational value of TSDBs, making them more than just data repositories. Through Litmus Edge, TSDBs are transformed into dynamic tools for comprehensive data analysis, enabling swift, informed decision-making and preventive measures in various operational contexts.

Together, the integration of TSDBs with Litmus Edge’s analytics provides a powerful data management and analysis framework. This synergy enhances real-time and historical data use, giving manufacturers deeper insights to drive data-informed strategies and optimize operational efficiency and productivity.

So, there you have it. A sight for SOR eyes, if you’ll pardon the pun, Litmus Edge is designed to help you unlock the data trapped in your SCADA and other systems of record: bridging the chasm between Industry 3.0 and Industry 4.0 in one fell swoop.

By seamlessly integrating with these systems, Litmus Edge not only breaks down the silos that have traditionally hindered comprehensive data analysis but also enhances their capabilities, ensuring they are not just data repositories but dynamic tools for strategic decision-making.

With Litmus Edge, organizations can unlock the full potential of their operational data, activating it for actionable insights that drive efficiency, productivity, and innovation. This integration is key to adapting in the fast-evolving industrial landscape, where the ability to analyze, predict, and act on data in real time is no longer an “edge”. It’s the new norm.

If you’re reading this and are inspired to embark on your own Industrial DataOps journey, let us know! We’re here to provide you with your very own Industrial DataOps blueprint to accelerate digital transformation throughout the enterprise.