In today’s fast-paced world of industrial automation, keeping up with the latest digital technologies is crucial for boosting efficiency, sustainability, scalability, and innovation. That’s where Digital Plant Services (DPS) come in. When combined with user-friendly interfaces and easily digestible visualization tools, digital plant services provide actionable insights for your entire enterprise - from operators on the plant floor to the C-suite at headquarters.
This guide will break down what digital plant services are, show how they can transform your operations, and provide real-world examples of how companies like yours have benefitted from them.
TABLE OF CONTENTS
- Understanding Digital Plant
- Key Components and Functionalities of Digital Plant Services
- Benefits of Digital Plant Services
- Challenges & Considerations of Digital Transformation
- Digital Plant Case Studies
- Digital Plant: The Foundation of Operational Excellence
Understanding Digital Plant
What is a Digital Plant?
A digital plant–sometimes called a digital factory or smart manufacturing–is an industrial operation that focuses on digitizing and automating all production and business processes. In a fully digital plant, you have seamless communication and unified data so information can flow automatically and freely throughout your enterprise. By connecting the systems and people in your organization, a digital plant empowers efficient planning, informed decision-making, and better operational performance in ways unattainable through traditional manufacturing practices.
What are Digital Plant Services?
Digital Plant Services (DPS) leverage a modern technology stack to develop customized solutions that optimize and automate industrial operations through digital transformation. These services integrate advanced analytics with real-time data acquisition from sources across your entire enterprise, like IIoT devices, PLCs, and digital forms. For instance, you could link building temperature monitoring with power monitoring systems to cut cooling costs.
Key components of digital plant services include data analytics, OEE, Enterprise SCADA, and MES systems. When you combine these with cloud and edge computing, you get centralized access and control with scalable data storage and processing.
DPS streamline processes, optimize resource use, improve sustainability, and accelerate data-driven decision-making. They transform traditional industrial plants into smart, connected operations that adapt to changing conditions and continuously improve both plant and overall business performance–from sales to shipping.
Evolution of Industrial Technologies
First Industrial Revolution
The story of industrial automation starts with the First Industrial Revolution in the late 18th century.1 During this period, mechanization replaced hand tools and manual labor with machines powered by steam and water. One of the most notable milestones was the introduction of mass production through the factory system, which revolutionized manufacturing. This era laid the foundation for industrial automation by demonstrating how machinery could supercharge productivity and efficiency.
Second Industrial Revolution
The Second Industrial Revolution, spanning from the late 19th century to the early 20th century,2 brought huge advancements in industrial technology. With the introduction of electricity and the moving assembly line, manufacturing output increased drastically.3 Early control systems evolved into relay-based automation systems that could control machinery operations more precisely and reliably.4 These early control systems paved the way for the more sophisticated automation technologies that we use today.
Photo credit zayacsk - stock.adobe.com
Digital Revolution
The Third Industrial Revolution, or the Digital Revolution, kicked off in the mid-20th century. Mechanical and analog electronic technology transitioned to digital electronics. In 1968, Dick Morley introduced the first Programmable Logic Controller (PLC), known as the Modicon 084, revolutionizing industrial automation with a flexible, programmable means to control machinery and processes.5 PLCs replaced hard-wired relay logic systems, offering greater efficiency, ease of modification, and reliability. The 1970s and 1980s further propelled the capabilities of automation systems with rapid advancements in communications, computer technology, and software development.
Industry 4.0
The Fourth Industrial Revolution, or Industry 4.0, is characterized by the convergence of digital, physical, and biological systems. It focused on information and turning data into actionable insights. While Industry 4.0 began in the early 2000s, many companies are still struggling to catch up with some of the industry standards this era ushered in: Industrial Internet of Things (IIoT) and Unified Namespace (UNS).
Industrial Internet of Things (IIoT)
Industrial Internet of Things (IIoT) is a key driver of modern industrial automation, connecting and communicating devices and systems across the industrial landscape. This interconnectedness allows for real-time data collection, analysis, and decision-making, enhancing operational efficiency and responsiveness.
Unified Namespaces (UNS)
A unified namespace is a system that identifies, consolidates, and exchanges real-time data in one central location. UNS gives everyone across the company access to one centralized and dependable source of data, no matter where it's stored. UNS simplifies communication, integration, reliability, and resource use and has become the gold standard in industrial data management.
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AI Revolution
Welcome to the AI era, a significant leap for industrial automation that enables automated, real-time, data-driven decisions. Unlike Industry 4.0's reliance on manual data interpretation, AI uses data to automate intelligent decision-making processes. This transition enables businesses to optimize operations, predict maintenance needs, and boost efficiency with minimal human involvement. By building on the technological foundations of previous industrial revolutions, the AI Revolution represents a profound shift toward more autonomous industrial systems.
Comparing Digital Plant with Traditional Plant Management Approaches
Before Industry 4.0, plant management approaches were notorious for inefficiencies, inaccuracies, and limited visibility due to their reliance on manual processes and siloed systems. In contrast, a digital plant integrates Industry 4.0 and AI technologies so that information flows automatically and freely throughout the entire enterprise. This integration reduces errors and enhances overall plant efficiency. And by connecting the systems in your factory, you remove communication barriers and eradicate isolated data.
Key Components & Functionalities of Digital Plant Services
There are four crucial components of DPS that work together to digitally transform plants: Enterprise SCADA, Data Analytics, Efficiency & Optimization (OEE), and MES. Each one plays a unique role in modernizing and streamlining plant operations. Let’s dive into what each component is all about.
Enterprise SCADA
Think of Enterprise SCADA (Supervisory Control and Data Acquisition) as the central nervous system of industrial automation. SCADA is a control system architecture that uses computers, networked data communications, and graphical user interfaces for high-level process supervisory management. SCADA systems monitor and control industrial processes, collecting real-time data from sensors and instruments across the plant floor. Enterprise SCADA takes this a step further by connecting multiple sites across an organization and integrating with enterprise-level systems (ERP, MES, etc.).
Data Collection
SCADA gathers data from field devices (PLCs, RTUs) using various communication protocols (Modbus, OPC, etc.).
Visualization
Visualization provides visual representations of the process through HMI (Human Machine Interface) screens, helping operators monitor system status at a glance.
Control
Operators can send commands back to the field devices to adjust process parameters.
Alarm Management
Alarm management identifies and notifies operators of critical conditions requiring immediate attention while de-prioritizing repetitive and unnecessary notifications.
Enterprise SCADA is essential for real-time monitoring and control of processes. It helps each plant run efficiently, safely, and within regulatory compliance, providing critical insights and control to operators on the plant floor. But it also enables a holistic view of operations by executives, supporting corporate-level planning, coordination, and decision making. Simply put, Enterprise SCADA ensures smooth operations across your entire organization.
Data Analytics
Data Analytics processes and analyzes the vast amounts of data generated by plant operations to extract actionable insights. Integrating analytics within your digital plant helps identify patterns and trends that aren’t immediately obvious. Analytics uses advanced algorithms and machine learning models to find patterns, predict outcomes, and support decision-making.
Data Integration
Aggregates data from various sources like SCADA, MES, and sensors into a unified data source.
Descriptive Analytics
Provides historical data insights through dashboards and reports, helping to understand past performance.
Predictive Analytics
Uses statistical models and machine learning to forecast future events or trends, like equipment failure or production bottlenecks.
Prescriptive Analytics
Recommends actions based on predictive insights to optimize operations.
Data Analytics turns raw data into valuable information that improves operational efficiency, predicts maintenance needs, and optimizes production processes. It’s all about making data practical and useful.
Efficiency & Optimization (OEE)
Overall Equipment Effectiveness (OEE) is a key metric for assessing manufacturing productivity. A digital plant uses several factors to calculate OEE and monitor equipment efficiency: availability, performance, quality, and analytics.
Availability
Measures the percentage of scheduled time that the equipment is available for production, considering planned downtime.
Performance
Assesses how the actual production speed compares to the ideal speed, accounting for slow cycles and small stops.
Quality
Calculates the ratio of good units produced to the total units started, reflecting the defect rate.
Predictive & Prescriptive Analytics
Uses advanced analytics to forecast future issues and recommend actions, optimizing equipment maintenance and reducing downtime.
OEE provides a clear, quantitative measure of where losses occur in the production process. By identifying and analyzing these losses, plants can implement targeted improvements to boost overall productivity and maintain optimal equipment performance.
Manufacturing Execution Systems (MES)
Manufacturing Execution Systems (MES) bridge the gap between business systems (like ERP) and plant floor control, providing real-time execution of manufacturing operations. MES manages and monitors work-in-progress on the factory floor, serving as the nerve center of the plant to coordinate production activities that align with business objectives.
Work Order Management
Tracks and documents the transformation of raw materials into finished goods.
Resource Scheduling
Allocates labor, equipment, and materials to optimize production schedules.
Production Tracking
Monitors the status of production orders in real time.
Quality Management
Ensures products meet quality standards through inspections and tests integrated into the production process.
Traceability
Maintains a detailed history of the product, including materials, processes, and personnel involved.
MES enhances visibility, traceability, and control over the manufacturing process, leading to better coordination and higher operational effectiveness.
These four components—Enterprise SCADA, Data Analytics, Efficiency & Optimization (OEE), and MES—work together to create a highly integrated and intelligent manufacturing environment. SCADA provides the real-time monitoring and control backbone, Data Analytics extracts actionable insights, OEE pinpoints inefficiencies, and MES orchestrates production execution. Together, they enable plants to operate at peak performance, adapt to changing conditions, and continuously improve their processes.
Benefits of Digital Plant Services
Centralized Access & Control
One major perk of a digital plant is centralized access and control. By combining different systems into one platform, managing plant operations is a breeze. Operators can watch and control processes from a single pane of glass, cutting down on complexity and speeding up response times.
This integration brings together disparate systems like SCADA, DCS, and MES. Each is complex on its own, but DPS blends them into a smooth, unified whole. This means data from all over the plant is consistently gathered, processed, and shown in a way that gives a complete picture of performance.
Operators don’t need to jump between different systems, reducing human error and boosting efficiency. For instance, if there’s a fault in one part of the plant, the system can instantly alert the operator and suggest fixes, which can be done right from the same interface. This cuts downtime and keeps production rolling smoothly.
Plus, centralized systems support remote access so engineers and operators can monitor and control operations even when they’re offsite. This is super handy when quick intervention is needed but staff can’t be there in person. It makes operations more flexible and ensures critical issues get addressed fast, no matter where the team is.
Improved Sustainability & Environmental Impact
Digital plant services also play a big role in sustainability by optimizing energy use and cutting waste, which lowers the environmental footprint of industrial operations. This is done through advanced data analytics and machine learning that constantly tweak processes to boost energy efficiency.
Energy management systems in a digital plant track energy use in real time, spotting where energy is wasted or used inefficiently. For example, by analyzing data from sensors around the plant, the system can find out when machinery is using more energy than needed. This info lets operators make quick adjustments or schedule maintenance to fix inefficiencies.
DPS also help integrate renewable energy sources. By managing data from different energy inputs, including renewables like solar or wind power, the system can optimize the energy mix to reduce reliance on non-renewable resources. This not only cuts greenhouse gas emissions but also helps meet sustainability regulations and lower the carbon footprint.
Reducing waste is another key part of improved sustainability. DPS give precise control over material use and process parameters, minimizing waste. For example, OEE and MES can fine-tune chemical use in manufacturing, ensuring only the necessary amounts are used, which reduces excess waste.
Compliance with environmental regulations is easier with DPS’s automated reporting features. DPS can generate detailed reports on energy use, emissions, and waste production, ensuring plants stay within regulatory standards and can easily show compliance during audits.
Increased Efficiency & Productivity
Efficiency and productivity are at the heart of a digital plant, achieved through real-time monitoring and optimization of plant operations. These services help plants spot and fix inefficiencies quickly, ensuring smooth, continuous production.
Real-time data analytics provide immediate insights into equipment and process status. Sensors and IoT devices continuously collect data on things like temperature and pressure. This data is then analyzed to detect any anomalies or deviations from optimal conditions, allowing for quick corrective actions.
Predictive maintenance is a standout feature that boosts efficiency. By using historical data and predictive algorithms, DPS can forecast potential equipment failures before they happen. This proactive approach lets maintenance be scheduled conveniently, minimizing unplanned downtime and avoiding costly breakdowns.
Automation is another key element. Routine tasks that used to need manual intervention can be automated, freeing up human operators for more strategic and complex activities. For instance, Automated Guided Vehicles (AGVs) can handle material transport within the plant, and robotic process automation (RPA) can manage repetitive admin tasks like data entry and inventory management.
DPS optimization algorithms also enhance production scheduling. By analyzing demand patterns and production capabilities, these algorithms create schedules that maximize throughput and minimize idle times, leading to better resource utilization and higher overall productivity.
Data Analytics for Informed Decision-Making
The power of digital plant services lies in their ability to provide real-time, predictive, and prescriptive analytics. Together, these analytical capabilities provide a comprehensive decision-support system. They enable plant managers and operators to make data-driven decisions that improve efficiency, reduce costs, and enhance overall performance.
Real-Time Analytics
Real-time analytics offer immediate insights into current operations, presenting data as it’s collected. This allows operators to monitor the health and performance of equipment and processes in real time, identifying and addressing issues as they arise. For example, if a machine starts operating outside its optimal parameters, real-time analytics can trigger an alert, enabling operators to intervene before a minor issue escalates into a major problem.
Predictive Analytics
Predictive analytics take this a step further by forecasting future trends and potential issues based on historical data and advanced modeling techniques. By identifying patterns and correlations within the data, predictive analytics can forecast equipment failures, production bottlenecks, and other operational challenges before they happen. This foresight allows for better planning and resource allocation, reducing the likelihood of unexpected downtime and ensuring that production targets are met consistently.
Prescriptive Analytics
Going even further, prescriptive analytics recommend optimal actions to mitigate risks and enhance performance. These analytics use sophisticated algorithms to evaluate various scenarios and suggest the best course of action. For example, if predictive analytics indicate that a particular piece of equipment is likely to fail, prescriptive analytics can suggest specific maintenance procedures, replacement parts, and optimal scheduling to address the issue efficiently.
In a nutshell, digital plant services revolutionize plant operations with centralized access and control, making it easy for operators to manage everything from one place remotely. They also drive sustainability by optimizing energy use and cutting waste, helping plants reduce their environmental impact. Efficiency and productivity get a significant boost with real-time monitoring, predictive maintenance, and automation, ensuring smooth and continuous operations. Lastly, analytics empower informed decision-making, keeping everything running at peak performance and allowing plants to continuously improve. With these benefits, DPS can truly transform the way your business operates, making it more efficient, sustainable, and responsive.
Challenges & Considerations of Digital Transformation
Technological Challenges & Compatibility Issues
Rolling out DPS can be a bit tricky, especially when trying to make everything play nice with your existing systems. Seamlessly integrating new tech requires careful planning and the right tools to fit together. Sometimes, it even means upgrading old systems to support modern digital solutions. Getting everything to work smoothly is key to avoiding any bumps in the road.
Data Privacy & Cybersecurity Concerns
As digital tech becomes more central in manufacturing, keeping data private and secure is a big deal. Protecting sensitive information from cyber threats means having strong security measures like encryption, access controls, and regular security audits. Following industry best practices like the NIST Cybersecurity Framework 2.0, ISO 27001, and SOC 2 is a smart move. Plus, sticking to data protection regulations is crucial to keep both company and customer data safe.
Organizational Resistance and Cultural Shifts
Adopting DPS often requires a big cultural shift within a company. Resistance to change is normal, driven by fears of job displacement and unfamiliarity with new tech. Overcoming this means clearly communicating the benefits, offering thorough training, and involving employees in the process. This helps everyone feel part of the change and more comfortable with it.
Regulatory Compliance & Industry Standards
Sticking to regulatory requirements and industry standards is essential when rolling out DPS. Different industries have specific rules to follow, from environmental standards to safety protocols. Making sure digital solutions meet these standards is critical to avoid legal and operational issues.
Implementation Approach
A strategic implementation approach is crucial for successfully deploying DPS. This means conducting a thorough needs assessment, setting clear objectives, and developing a detailed roadmap. Pilot projects can help test the chosen solutions and provide insights for wider deployment. Continuous monitoring and iterative improvements ensure the services stay aligned with business goals.
How Vertech Addresses These Challenges
At Vertech, we tackle the challenges of digital plant services head-on with a comprehensive approach. Our scalable, customizable solutions ensure compatibility with existing systems and compliance with industry standards, making integration seamless. We prioritize robust cybersecurity measures to protect data integrity, keeping your information safe from cyber threats. Our implementation methodology focuses on engaging stakeholders, providing thorough training, and offering continuous support to ease the transition. Our success stories showcase our expertise in overcoming technological and organizational hurdles, making us a trusted partner for your digital transformation journey.
Digital Plant Case Studies
When it comes to digital plant solutions, Vertech’s success stories really show off our skills in using industrial tech to make real improvements for businesses all over the world. We’re proud of the results we’ve achieved and how we’ve helped companies boost their operations.
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Enterprise SCADA Case Study: SB Energy
SB Energy needed a unified platform to manage multiple remote sites, providing their greenfield operations center with full access to monitor and optimize performance. Vertech’s mission was clear: design an Ignition solution capable of real-time data acquisition, consolidation, and validation across six solar sites with comprehensive site monitoring and performance analysis offering clear industry relevance.
The result was a powerful SCADA system that transformed SB Energy's operational capabilities. With complete visibility into each site, asset, and energy production metric, SB Energy can now maximize energy output and quickly address maintenance issues, ultimately saving valuable time and resources.
- 6 NATIONAL SITES
- 1.7GW TOTAL RATED POWER
- 2700+ MODBUS DEVICES
- 10K UPDATES PER SECOND
SB Energy commented:
“Working with Vertech was a great culture fit. They were great communicators, passionate, innovative, and able to provide solutions to any problem we had.”
Charles Fortuno, Sr. Manager SCADA & Control Systems at SB Energy
OEE System Case Study: Amy’s Kitchen
Amy’s Kitchen sought an OEE system upgrade for three production sites to automate tracking and display of production efficiency and equipment downtime. They needed a comprehensive solution that seamlessly integrated with their ERP system, eliminating the manual data compilation from various sources in Excel and enabling effortless display and analysis of all plant data.
Vertech successfully designed and implemented a customized OEE system for real-time, comprehensive data collection. Reports on real-time run data and historical data are now a breeze, enabling Amy’s to easily identify issues and make informed decisions on batch scheduling, equipment maintenance, process execution, and more.
- 1705 SKUS CREATED PER YEAR
- 39 PRODUCTION LINES
- 9842 PRODUCTION RUNS PER YEAR
- 250M ITEMS ASSEMBLED AND PACKAGED PER YEAR
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MES Case Study: AriZona Beverages
AriZona Beverages tasked the Vertech team with delivering an MES and batching system to maximize high-volume production, prioritize sustainability, and convert manufacturing data into actionable analytics.
The results? A best-in-class MES and batch control system that interacts with every level of plant automation – from device control to the ERP. AriZona Beverages now enjoys complete visibility into its business and production processes, producing high-quality, consistent products faster and more efficiently than ever before. By capturing and converting production metrics into digestible data, they can review any line over any period, gain insights into site operations, equipment status, and production history, and pinpoint areas for continuous improvement.
- 62K IGNITION TAGS
- 1,800 ALARMS
- 112 SCREENS
- 2,000 POINTS OF CONTROL
AriZona Beverages commented:
“Since the start of the project, we’ve built this [system] as a centerpiece for best-in-class. Vertech provided us with best-in-class software that integrated well within the whole manufacturing facility.”
Shami Usmani, VP of Engineering and Manufacturing at AriZona Beverages
Digital Plant: The Foundation of Operational Excellence
Digital plant services are revolutionizing the industrial technology landscape, offering unparalleled benefits in terms of efficiency, sustainability, and productivity. By centralizing access and control, providing real-time analytics, and enabling predictive maintenance, digital plant technology empowers companies to make informed decisions, drive continuous improvement, and lay the foundation for success in the AI Revolution.
As technology evolves, becoming a digital plant is crucial for a competitive edge in the industrial landscape. Sure, there are challenges, but with a solid plan and the right partner, you can implement DPS successfully and see significant returns on your investment. Businesses now have a unique opportunity to integrate both Industry 4.0 and AI technologies simultaneously, saving time and money while reaping the benefits of both: better connectivity, real-time data, advanced analytics, and automated decision-making. By embracing these advancements, you can optimize operations, predict maintenance needs, and strengthen your company’s market position.
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