PLCs

WINTER EDITION
Contents
3 — Leveraging the full power of industrial data

13 — The Do-more BRX PLC from AutomationDirect

14 — How to reduce workload using reusable components

for PLCs

18 — Four technologies every modern manufacturer

should adopt

27 — More answers: Tips and tricks for next-generation

automation programming

38 — AI-driven solutions for enhanced plant automation

productivity

2
Leveraging the full power
of industrial data  Back to TOC

For data to have real value to today’s automated manufacturing plants,

industrial networks need critical tools to access and deliver the data to critical
operational and analytical platforms.

T he promise of Industry 4.0 is rapidly being realized across many manufacturing

segments. A wide range of sensors, smart components and advanced automation
drives and controls are routinely integrated into production machines and processes,
furthering the growth of automated manufacturing.

These systems are now generating large amounts of industrial data. The challenge for
many manufacturing operations invested in this digital technology is how to efficiently
access and utilize this data, leveraging its full value with networking systems that are
reliable, secure and scalable to meet both current and future needs.

Several key technologies provide the critical building blocks of high-performance in-
dustrial data networks. Systems integrators, original equipment manufacturers (OEMs)
and manufacturers are seeking strategies to use these tools to gain more complete
access and control of companies’ industrial data and bridge existing gaps between
information technology (IT) and operational technology (OT) within the manufacturing
enterprise. The goal is accessing that data to improve operator performance, plant
safety, predictive maintenance processes and manufacturing productivity.

Connecting islands of data

Today’s manufacturing platforms constantly generate mountains of data related to the
3
Leveraging the full power of industrial data

Figure 1: Leverage the full value  Back to TOC

of your industrial data through
Red Lion’s product portfolio.
Courtesy: Red Lion

performance of individu-
al machine components,
subsystems and pro-
duction lines. It’s being
generated by sensors,
pneumatic valves, con-
trol devices, electric drives and other components. The volume of this data constantly
grows.

However, in many production environments, the data is isolated. This complicates

manufacturers’ efforts to use the data to improve productivity and return on invest-
ment (ROI). In many cases, this isolation is unintentional. For example, temperature
and valve performance data are fed through input/output (I/O) channels to a machine
controller, but may not go any further without manual intervention, limiting its value.

Industrial data is a manufacturer’s most valuable asset. Data’s true value is only real-
ized when it can be easily accessed, aggregated with other machine and line data and
analyzed. These “islands of data” exist because many factory automation plants have
multiple generations of equipment installed — in some cases, decades-old systems
that still provide productive performance.

Incompatible communications protocols are a major reason why full industrial data
networking can be so challenging to implement. Many older machines will be using 4
Leveraging the full power of industrial data

protocols such as Modbus  Back to TOC

RS-232. At the same time
in the same plant, a newer
production system added to
the line will use more current,
open protocols such as OPC
UA. To compensate, some
companies building out their
networks may try to create
specialized software patches
on a case-by-case basis.

The most effective solution

to this challenge is a robust set of protocol conversion Figure 2: Platforms such as Red
Lion’s FlexEdge provide a versatile
capabilities that can be implemented as part of invest- and full-featured solution to
ments in new data access and connectivity systems. bridge the worlds of information
technology (IT) and operations
technology (OT) to realize the
Rise of edge computing systems total value of a manufacturer’s
Edge computing platforms, sometimes called edge gate- industrial data more efficiently and
completely. Courtesy: Red Lion
ways, are playing a fast-growing and critical role in solv-
ing the challenges of disconnected islands of data. Edge
computing often refers to hardware/software networks and devices located at or near
the end user. It enables data access and processing closer to where the data is gen-
erated, for faster processing speeds and higher data volumes that supply actionable
data in real time.

5
Leveraging the full power of industrial data

 Back to TOC

Edge computing platforms are widely used for critical, Figure 3: Red Lion’s N-Tron series
real-time protocol conversion to bridge legacy and NT5000 switches are designed
to keep your network connected,
current generation production systems. Leading pro- protected and provide ease of
viders of these edge platforms are designing them to use, security and reliability today’s
be powerful networking devices, engineered to supply manufacturers and industrial
operations need. Courtesy: Red Lion
critical data access and management tasks.

Leading suppliers offer platforms that can simultaneously process up to 20 protocol

conversions from over 300 supported drivers. These platforms are designed to be all-
in-one edge devices that support other critical functions, such as data logging, easy
access to MQTT-based cloud servers and remote access.

Edge systems are being offered by many different technology suppliers, so picking the
right one calls for careful assessments. In some operations, manufacturers are reluctant 6
Leveraging the full power of industrial data

to invest in edge platform technology out of concern that implementing these systems  Back to TOC
will be costly and time-consuming.

Look for systems that feature user-friendly software and feature efficient, drag-and-
drop programming platforms that make it easy to set up protocol conversion, cloud
connections and data logging features. There also are advantages to utilizing scalable
platforms. For example, one leading platform can serve as a protocol converter, a net-
working gateway or an automation controller via software upgrades.

It’s also important to weigh potential yearly software fees and costs for external sup-
port services. Costs also could escalate beyond established budget parameters unless
properly accounted for when purchasing multiple systems to upgrade networks.

Expanding remote access

In many cases, today’s automated manufacturers are multi-location operations, with
multiple plants situated across the globe. To be competitive and productive, they need
to operate as fully integrated enterprises. This means eliminating data communications
barriers between facilities and leveraging cloud-based analytical tools.

Along with edge computing platforms, a new generation of remote access systems is
now being launched to meet these needs. These systems provide a dedicated platform
to advance remote system monitoring, making it possible to remotely access and inter-
act with production systems in a secure and reliable way from anywhere in the world.

Just as legacy production tools in a plant can become islands of industrial data with-
out effective protocol conversion capabilities, geographically separated plants can
7
Leveraging the full power of industrial data

also become islands. With one remote access device, users can access multiple other  Back to TOC
connected network devices and obtain real-time insights and comparisons about how
similar production systems and plants are performing.

These devices are useful as more multi-location companies use cloud-based analyti-
cal tools to conduct deep dives into their industrial data, extract trends, modify pro-
duction or supply chain processes, improve enterprise-wide predictive maintenance
programs and guide long-term planning. It is impossible to carry out these kinds of
high-level analysis without having robust remote access to help ensure real-time data
is accurate and current.

Cloud-based data management and analysis depend on secure and efficient data
communications from the plant to the cloud. One emerging technology in plant au-
tomation that is shaping the future of manufacturing is the message queuing telem-
etry transport (MQTT) protocol. MQTT was designed for connections with devices in
remote locations with resource constraints or limited bandwidth, making it very light-
weight and efficient at moving data to and from a data broker (either locally or in the
cloud).

MQTT is capable of “report by exception,” which means data is only transmitted when
it has changed. This feature can provide significant bandwidth savings for both internal
and external networks. Specifically configured topics can be stored by the database
during a network outage and forwarded to users once reconnected, which guarantees
delivery of messages about critical topics. MQTT is not necessarily “new” but is still
new to the world of manufacturing with many companies starting to adopt this power-
ful technology. Automation companies seeking to bridge the remote data islands be-
8
Leveraging the full power of industrial data

tween their production facilities will benefit from selecting edge computing platforms  Back to TOC
that support MQTT.

Visualization key to using real-time data

Connecting industrial data with enterprise-level analytical platforms is crucial to gain-
ing deep insights into automation system efficiency and performance. However, that
data has equal value (in some cases greater value) for operators and managers on the
factory floor.

Actionable data needs to be presented in real time to help operators visualize the
information they need to maximize productivity and throughput. The latest generation
of human-machine interfaces (HMIs) and operator panels are designed to deliver that
data in clear and compelling formats. They incorporate features that let them integrate
data across multiple devices and, in conjunction with edge computing platforms, ac-
quire and display data that has been converted from multiple legacy protocols.

Newer generation panel meters feature large, easy-to-read displays that include a
broad range of user-selectable graphics and intuitive screen libraries that are simple to
configure and customize to specific plant and production line requirements.

With this new generation of visualization technology, operators and line personnel are
able to respond to issues faster, process critical information immediately while having
one person monitor multiple machines and processes. These tools let operators see
more than just information. They also see what the information means and are able to
react faster with the right steps.

9
Leveraging the full power of industrial data

Integrating IT and OT and leveraging data  Back to TOC

One of the biggest challenges factory automation companies face to leverage their
industrial data is finding smarter ways to integrate the worlds of IT and OT. These two
worlds have, until recently, functioned independent of each other.

OT’s goal is keeping the plant running smoothly while IT manages all the business ap-
plications within the enterprise. However, as digital transformation continues evolving
in factory automation plants, these two worlds are uniting.

Successful IT and OT convergence depends on enterprise connectivity solutions be-

tween the systems that create the data and the users that consume the data. In order
to extract any actionable insights from this OT manufacturing data, it needs to be
packaged in an interchangeable and flexible format that can be shared between IT and
OT applications.

This is one of the key capabilities that edge computing platforms are providing. Soft-
ware that collects, organizes and contextualizes OT data — and then makes it available
to higher-level IT applications and databases — can unlock actionable plant- and en-
terprise-level insights to guide critical decisions about ways to improve manufacturing
processes, increase energy efficiency, reduce machine downtime and provide a more
flexible and productive manufacturing enterprise.

This data exchange between IT and OT also needs to be as secure as possible. Hack-
ers and ransomware criminals will try and target industrial systems for vulnerabilities so
they can access enterprise IT networks through OT systems. It is critical to select edge
computing platforms with top-of-the-line security features, including a stateful firewall,
10
Leveraging the full power of industrial data

Figure 4: The latest generation of HMIs  Back to TOC

and operator panels incorporate features
that let them integrate data across
multiple devices and, in conjunction with
edge computing platforms, acquire and
display data that has been converted
from multiple legacy protocols. Courtesy:
Red Lion

access control list capabilities,

packet filtering and fully secured
virtual private network (VPN)
connections.

These edge devices deliver valuable, long-term insights into plant floor operations.
With the data collected from OT, operations can transition to proactive and develop
predictive and prescriptive maintenance strategies.

For example, these devices can automatically alert operators to any changes or events
that could lead to a machine shutdown, allowing them to stay ahead of — and avoid —
costly production issues. Finally, thanks to powerful remote access capabilities, users
from anywhere in the world can add alarms or improve logic and data collection pro-
cesses or even monitor traffic on the OT network.

Maximizing industrial data’s value

Digital transformation has woven a wide range of data-generating components and
systems into automated manufacturing systems. Many manufacturers continue to
struggle with accessing that data, particularly from older legacy equipment.
11
Leveraging the full power of industrial data

Sophisticated edge computing, remote access systems and smart visualization systems  Back to TOC
can provide solutions to these challenges, bridging persistent “data islands” so that
each company’s most valuable resource — its industrial data — can be accessed, con-
nected, visualized and analyzed to help drive operational improvements and long-term
decision-making.

Finding and implementing the right technology for each plant and manufacturer can
be challenging. Today’s leading industrial data networking suppliers are experienced
at analyzing each plant’s unique infrastructure and a company’s data needs. They can
apply their expertise to develop strategies to meet those needs, based on an in-depth
appreciation of where data is isolated, as well as insights into future needs as compa-
nies grow and evolve.

Industrial data is a company’s most valuable and useful asset. The right technologies,
combined with smart approaches for using those technologies to improve day-to-day
operations and long-term business strategies, can play a critical role in helping realize
the full potential of digital transformation in factory automation.

Joe Wagner
Joe Wagner is a field application engineer at Red Lion Controls with over eight years
of industrial automation experience in various industries including manufacturing, wa-
ter/wastewater, and utility-scale solar power generation. He holds a Master of Science
degree with a concentration in Automation and Controls and is based out of Sacra-
mento, Calif. Joe’s work focuses on practical applications of cutting-edge technologies
in various industries and helping users get the absolute most out of their data.

12
The Do-more BRX PLC from AutomationDirect

 Back to TOC


The Do-more BRX PLC from
AutomationDirect
Introducing the BEST budget PLC, the newest family of Do-more
PLCs - The BRX. You asked for it: Feature packed, Low Price.
Making it the perfect Budget PLC or the Any budget PLC. This
affordable PLC can do it all, from a small budget PLC all the way
to a large scale installation. This new family gives the best low
cost PLC, without having to settle for less.

13
How to reduce workload using
reusable components for PLCs  Back to TOC

Multiple programmable logic controller (PLC) platforms now support pre-

packaged code to reduce your programming time.

W riting programmable logic controller (PLC) programs from scratch is usually

time-consuming and tedious. Many know about the long-term costs and frustra-
tions of debugging and maintaining code, but there is a method to increase the code’s
dependability and quality while streamlining and simplifying the PLC programming
process. Multiple PLC platforms can now use pre-packaged code to reduce your pro-
gramming time and support.

Three benefits of pre-packaged code

Pre-packaged code is a collection of pre-made libraries and functions that let users
quickly construct PLC applications. Pre-packaged code can help users to:

1. A
 ccelerate your code: Using tested pre-packaged code to perform common
tasks reduces the time spent writing code. Due to this, the code may become
more responsive, resilient and faster. Users also are minimizing errors by using
proven and validated code. This reduces testing and troubleshooting time.

2. S
 tandardize your code: Pre-packaged code can be used across different hard-
ware platforms and projects. Users can use the same functions and libraries for
different projects and follow identical coding conventions and best practices.
Using this can make the code more readable, consistent and more accessible for
others to support.
14
How to reduce workload using reusable components for PLCs

 Back to TOC

3. R
 educe support costs: Using pre-packaged code, Figure 1: The Library Manager in
CODESYS that allows users to add
users can update or replace these packages when
and select pre-packaged code for a
needed. For example, if a machine uses pre-pack- project. Courtesy: Vision Control &
aged code that interacts with an outside platform, Automation
15
 How to reduce workload using reusable components for PLCs

users can update the  Back to TOC

package without redoing
Cutting EDGE control you can the code if it updates its
actually afford communication spec.

CODESYS is a program-
ming software that works
with multiple PLCs. In the
CODESYS, pre-packaged
code is available in the
form of libraries. Users
can download many free
Starting at only $199.00 libraries, but some have
The BRX PLC has advanced features that allow it to easily take on the role
of an edge computing device - gathering, refining, and delivering control a cost or only work with
system data to upstream IT collection and BIG DATA analysis programs.
devicecatalog.azure.com
specific hardware. To use
Embedded Web Server Intelligent Code Execution
With BRX’s embedded Web server, you can instantly With robust task management and a variety of pre-packaged code in
access system status, diagnostic information, and interrupt styles for task prioritization.
monitor memory usage from any Internet-ready
device.
CODESYS, users need to
Extensive Instruction Set
Rest API --| |---| |---( ) Discrete, process, and multi-axis motion follow a few simple steps.
The integrated Rest API and secure HTTPS protocol --| |---| |---( ) control instructions to support even complex
allow BRX to work with flow control tools like applications, executed with familiar ladder
Node-RED® in order to supply high-level IT systems logic programming.
with the plant-floor data they need.

Must-have IIoT Protocols

Powerful Math Functions 1. Identify the library
Enabling scripted math and algebra, to support
With the growing number of IIoT platforms and
cloud computing services, BRX controllers utilize
rich data pre-processing right at the edge. that contains the
the industry-standard MQTT(S) and FTP protocols
to seamlessly integrate with asset management/IIoT
Research, price, buy at:
code you need.
platforms including:

www.BRXPLC.com
• Microsoft Azure®
• IBM Watson®

2. Import the library into

TOP RATED

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BY CUSTOMERS your project.
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16
* See our Web site for details and restrictions. © Copyright 2025 AutomationDirect, Cumming, GA USA. All rights reserved. the #1 value in automation

2502-AutomationNotebook(2)-BRXPLCs-MAG.indd 1 12/13/2024 10:41:58 AM

How to reduce workload using reusable components for PLCs

3. Write the code to interact with the library.  Back to TOC

For example, there was a case where message queuing telemetry transport (MQTT)
messaging to an existing PLC program. While MQTT is a feature not native to this par-
ticular PLC, CODESYS has several different library options, including ones that support
Sparkplug B.

For this application creation, WagoAppCloud library and the Native MQTT support it
offers were used to send messages to the MQTT broker.

Another example would be adding SQL database connectivity, which is not a feature
that comes with the PLC. There are multiple libraries that can connect to a database.
In this case, it was the Microsoft SQL database and used the WagoAPPSQL_MsSQL
library. This hardware-specific library allows users to connect and send SQL syntax to a
database.

Using pre-packaged code can help reduce programming time and support efforts and
improve workflow and development time. Users also can benefit from the advantages
of pre-packaged code and create better PLC programs faster and easier. Users might
be surprised how pre-packaged code can improve their next project.

Brandon Teachman
Brandon Teachman is an application engineer at Vision Control & Automation, where he
helps businesses improve their manufacturing processes through automation solutions.

17
Four technologies every modern
manufacturer should adopt  Back to TOC

Condition monitoring, vision system AI, message queuing telemetry transport

(MQTT) and modern supervisory control and data acquisition (SCADA)
systems can help manufacturers looking to improve their operations.

1. Condition monitoring
Condition monitoring employs sensors to monitor the performance and condition of
equipment. A condition monitoring system can identify wear, problem or failure indica-
tors by gathering and evaluating data from these sensors before they result in signifi-
cant issues. By doing so, companies can schedule maintenance and repairs in advance,
saving money on downtime and increasing the equipment’s lifespan.

Condition monitoring can also improve energy use and reduce carbon footprint. Com-
panies can find areas to save energy by monitoring components’ power usage and effi-
ciency. For example, can an oven’s temperature be reduced when not in use or turn off
motors when not needed? This type of monitoring of environmental factors also may
provide better working conditions and can help reduce variance in the manufacturing
process. Temperature, vibration, noise and moisture are critical for ensuring employee
comfort and minimizing the negative impact on materials.

The sensors used for condition monitoring need a software platform to gather, store,
process and display the data. There are application-specific software platforms and
ones that are general. One of the most popular application-specific platforms revolves
around moving parts like motors, pumps, fans and compressors. This software checks
the vibration, temperature and more from a sensor mounted on the motor. 18
Four technologies every modern manufacturer should adopt

Some of these software packages also tie into the drive on the motor to get addi-  Back to TOC
tional motor information to protect the asset better. The general systems can tie into
multiple types of sensors and other devices from multiple manufacturers. The general
systems require more setup, but have more flexibility. Both platforms can also link with
other systems in the plant such as an enterprise resource planning (ERP) system, man-
ufacturing execution system (MES) or computerized maintenance management system
(CMMS). They also can use AI to predict future failures.

Four aspects to consider when selecting condition monitoring are:

• What equipment has the most significant impact on manufacturing?

• What data do you need to decide when to repair something proactively?

• How do you want this data, and when?

• How much time can you invest in setting up this system?

These criteria help narrow down what is the best fit. For example, if the only concerns
is the uptime of four large grinders, some companies make a prepackaged solution
that can be installed on large motors. This is a pre-made solution, quick to implement
and has a fast return on investment (ROI) for an application.

Another example would be a plastic manufacturer looking to decrease downtime and

quality. Based on preliminary data, they found temperature and humidity in the build-
ing were affecting their products. They also were having unplanned downtime due to
19
Four technologies every modern manufacturer should adopt

motors failing. They went with a highly customizable general system that can be used  Back to TOC
with multiple manufacturers’ products.

2. Vision system AI
Machine vision systems give machines the ability to perceive and comprehend their
surroundings. AI vision uses digital cameras and machine learning to analyze imag-
es and videos of the plant’s products and machines. It can detect defects, errors and
anomalies in real time and adjust settings or alert team members. This allows the AI
Vision system to help reduce waste, rework and downtime while increasing customer
satisfaction and profitability without increasing labor. AI vision is also a scalable and
adaptable solution that can be customized to diverse types of manufacturing plants
and products. It can learn from new data and feedback and adjust to changing condi-
tions and requirements. AI vision is a tool and a partner that can help the manufactur-
ing plant achieve its quality goals.

Manufacturers are constantly seeking ways to increase their production flexibility and
agility. By using vision system AI to recognize several types of products or compo-
nents and adjust their settings accordingly, they can switch between different orders or
batches without wasting time or resources. They also can use vision system AI to moni-
tor their inventory levels and replenish them when needed.

When implementing an AI vision system, there is an investment in the correct camer-

as and lighting for an application. Companies also need a software platform that can
provide pre-made or custom-made algorithms for specific tasks. The software platform
also can integrate with other systems in the plant such as programmable logic control-
lers (PLCs), SCADA or MES to provide real-time feedback and control.
20
Four technologies every modern manufacturer should adopt

Five things to look at when deciding if AI vision is the right option include:  Back to TOC

• Are you making a repetitive product?

• Do you have defects that are visible to the human eye or a thermal camera?

• Can a defect be detected by a measurement check?

• Do you have quality control (QC) documents with the variances you allow for the
product?

• Do you have a culture where automation is accepted?

One example of a successful implementation of vision system AI is the manufacture of

consumer hand tools. During manufacturing, they use vision systems throughout the
line to ensure the parts are in place, ensure components were correctly added and all
required labeling is readable. This allows the machine to make corrections, if possi-
ble, without human interaction. When the machine cannot correct, the product is dis-
charged from the line for manual interaction.

3. MQTT on the factory floor

MQTT is a communication protocol that permits data sharing between devices via the
network. Devices can publish messages on topics and subscribe to topics that interest
them under this publish/subscribe approach, which is the foundation of the system.
MQTT is lightweight, quick, dependable, secure and scalable. It also helps that MQTT
is already commonly found in modern devices.
21
Four technologies every modern manufacturer should adopt

MQTT can benefit manufacturers who want to achieve smart manufacturing by con-  Back to TOC
necting their devices and systems housed locally or on the cloud. Using MQTT on the
factory floor, they can easily collect data from their sensors, controllers and machines
and send it to a central server or broker. They can also receive data from the server or
broker and act on it accordingly. The systems interacting with this data can include an
ERP, CMMS, MES, SCADA and more.

By standardizing on MQTT, a manufacturer can enjoy many benefits, such as:

• Reduced network bandwidth and resource consumption: MQTT uses a publish/

subscribe model, which means that devices only send and receive the data they
need, avoiding unnecessary traffic and overhead.

• Improved scalability and interoperability: MQTT can connect thousands of devic-

es across different platforms and technologies, allowing for easy integration and
expansion of the plant network.

• Enhanced security and reliability: MQTT supports various encryption and authenti-
cation mechanisms, as well as quality of service levels, to ensure the data is secure-
ly transmitted.

• Increased flexibility and agility: MQTT allows for dynamic discovery and configura-
tion of devices, enabling the manufacturer to adapt to changing needs and re-
quirements on the plant floor.

To get started with MQTT on the factory floor, there is little to no investment in equip-
22
Four technologies every modern manufacturer should adopt

ment for most manufacturing facilities due to the wide adoption of MQTT. Companies  Back to TOC
also need a software platform that can act as a broker or server for MQTT messages.

Many brokers have free options to get started. To provide data visualization and ana-
lytics, these platforms may also interact with other systems in the plant including SCA-
DA or MES systems.

4. Modern SCADA systems

SCADA systems allow manufacturers to monitor and control their processes and equip-
ment. They can collect information from a range of hardware such as sensors, PLCs,
VFDs and more. They can show it on graphical user interfaces (GUIs) like dashboards,
charts and maps, among other things.

Modern SCADA systems are far more sophisticated than earlier versions. They also can
provide manufacturers with more than simply monitoring and control options. Modern
SCADA systems can provide these five benefits:

1. U
 niversal connectivity and IIoT readiness: A modern SCADA system can con-
nect to various devices and data sources, such as sensors, controllers, databases
and cloud services by using open standards and protocols, such as MQTT and
OPC UA. This enables the SCADA system to leverage the IIoT benefits such as re-
al-time data, analytics and remote access. Users also can link their equipment and
processes to the cloud or enterprise resource planning (ERP) systems, allowing
users to access data anytime, from any place and via any device. Companies also
may employ the computing capacity of the cloud to do complex data processing
and analysis using artificial intelligence or machine learning methods.
23
Four technologies every modern manufacturer should adopt

2. W
 eb deployment and mobility: Most modern SCADA systems are web-deploy-  Back to TOC
able, which means they can be accessed and operated from any device with a
web browser, such as a smartphone, tablet or laptop. It provides flexibility and
convenience for its users, as they can monitor and control their processes any-
where and anytime. Some modern SCADA systems also support mobile applica-
tions, providing customized and interactive user interfaces for different devices
and roles.

3. D
 ata visualization and analytics: A modern SCADA system provides rich and
intuitive data visualization and analytics capabilities to help users understand and
optimize their processes. It also offers various charts, graphs, dashboards, reports
and alarms that display the data in a clear and meaningful way. The data visualiza-
tion is customizable and can show users just the data they want. The system can
even be scheduled to email the data. Modern SCADA systems support advanced
analytics, such as artificial intelligence and machine learning (AI/ML), which can
provide insights and predictions based on the data.

4. S
 calable and modular: Most modern SCADA systems have been designed to be
very scalable, which allows companies to add more equipment or manufactur-
ing locations. The SCADA system comprises independent modules that can be
added, removed or replaced. Each module has a specific function and communi-
cates with other modules through standardized interfaces, allowing for flexibility
and system customization. A SCADA system can distribute the control functions
among multiple controllers or servers, which can be located at different sites or
regions. This reduces the load and dependency on a single central controller and
improves the availability and redundancy of the system.
24
Four technologies every modern manufacturer should adopt

 Back to TOC
5. M
 ES and HMI functionality: Modern SCADA systems can perform the roles of
manufacturing execution systems (MES) or human-machine interfaces (HMIs),
enabling manufacturers to manage their production planning, scheduling, execu-
tion and tracking in one system. In most cases, this reduces the complexities and
system costs.

Where and how to start implementing

Harness the power of condition monitoring, AI vision systems, MQTT and modern
SCADA systems to embrace the future of manufacturing. The first step is ensuring
companies have the right culture in place. If the team is not open to change, imple-
menting any of these technologies will be challenging. If this is not an issue, it’s best to
start small. Select a smaller area or line with a known issue such as constant downtime,
high rework rate or not hitting production numbers.

From there, determine how to collect data from that line and display it to the larger
team. To start, this collection may be manual. Companies can then use this data to
select the next steps. Once companies have the data, involving outside parties like
system integrators and vendors is easy. This is because they have measurable data to
work with.

If there is unplanned downtime due to motor issues, condition monitoring may be the
solution to plan the downtime, but it also may provide data to find a solution to go
longer between failures. Users also may find that the defects from this machine may be
due to getting out-of-spec parts from downstream, and a vision system may do a bet-
ter job finding this issue before more work is done to the part. It also may come down
25
Four technologies every modern manufacturer should adopt

to having an issue that only occurs when someone is at lunch and therefore becomes a  Back to TOC
training issue.

Modern and intelligent manufacturing for the future

Intelligent manufacturing is here right now; it’s not science fiction. Condition monitor-
ing, vision system AI, MQTT and modern SCADA systems are four essential technol-
ogies that can assist in making it a reality. These technologies can work together or
independently to improve a facility’s production quality, flexibility and sustainability.

Brandon Teachman
Brandon Teachman is an application engineer at Vision Control & Automation,
where he helps businesses improve their manufacturing processes through automa-
tion solutions.

26
More answers: Tips and tricks
for next-generation automation  Back to TOC

programming
Programming instructor provides more answers from audience questions
after the Control Engineering webcast, “Programming tips and tricks
appropriate for next-generation applications.”

M ore tips and advice about programmable logic controller (PLC) programming
follows from an instructor for the Control Engineering webcast, “Programming
tips and tricks appropriate for next-generation applications.” Frank Lamb, founder and
owner, Automation Consulting LLC, webcast speaker and Control Engineering Editorial
Advisory Board member, provides PLC programming instruction, including the answer
to the question: “What are the main languages programming that a good plc program-
mer must know?”

The International Electrotechnical Commission’s standard IEC 61131-3 programming

languages are:

IL – Instruction List, text

LAD – Ladder Logic, graphical

FBD – Function Block, diagram graphical

ST – Structured Text, text

SFC – Sequential Function Charts, graphical.

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More answers: Tips and tricks for next-generation automation programming

 Back to TOC

Webcast instructors answered audience questions during the end of the PLC program-
ming webcast, and Lamb some additional questions below.

What path should a person take who is just starting to work with PLCs but
doesn’t have Ladder programming knowledge?

Use free resources on YouTube and vendor websites to learn ladder logic and other
languages.

What engineering tools are available to help with modern methods of PLC pro-
gramming?

While there are some commercial vendors, I have created my own tools in Microsoft
Excel to aid in rapid code development.
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More answers: Tips and tricks for next-generation automation programming

 Back to TOC
How is artificial intelligence (AI) being used for PLC programming and machine
learning?

AI can generate text-based code, commonly used for Python programming. Neural
networks are used for vision (machine learning). Most professional PLC programming
does not use AI, but may use commercial programs that aid in rapid development.

Could ladder logic programs be more portable to different PLCs?

While the logic works the same in ladder programs, some special instructions are cus-
tom to the platform. The IL versions of the logic also does not usually use the same
mnemonics. Companies have written conversion software for specific platforms, but
major manufacturers’ ladder programming is not directly portable. There is an excep-
tion: CODESYS-based ladder is portable.

What tips and recommendations do you have for communicating with manufac-
turing execution system (MES) software?

I have no specific advice, though something needs to translate native PLC communi-
cations to MES system protocol. Protocol converters, different drivers and field servers
can help, though you may still require assistance from system integrators.

What about language standardization across platforms? It was mentioned that

LLL comes with every platform but others do not.

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More answers: Tips and tricks for next-generation automation programming

Language implementation differs across platforms because of PLC manufacturers’ leg-  Back to TOC
acy [platform design] choices. The more modern the software, the more likely it is to
be fully compliant with standard IEC 61131-3 control programming languages. Styling
and other details are still not standardized across the major PLC manufacturers, and
different manufacturers emphasize different languages.

How do PLC programming languages interact with CIP?

Common Industrial Protocol (CIP) is an [ODVA] communication protocol, not a PLC

language. Not all brands use this.

How do you see programming for building automation systems (for HVAC) differ-
ing from PLC programming?

Building automation controllers may use some text or graphic languages, but are not
compliant with IEC61131-3 requirements.

Do certain programming languages work better with MES systems?

Not really, though movements of large amounts of data may be easier with Structured
Text.

How do you suggest addressing the divide among programmers, users, and tech-
nical staff with these other languages? (Visual nature of LLL is easier to under-
stand for personnel without a programming background.)

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More answers: Tips and tricks for next-generation automation programming

Programmers of necessity have to be very good at writing complete programs and  Back to TOC
will have language preferences. They will understand the code much more easily than
maintenance personnel because they work with code regularly. Maintenance will often
prefer graphical languages because they require less reading. But technicians can be
trained to be comfortable with any language. Time and study are required.

Is structured text a good option if maintenance technicians need to view the PLC
program?

Maintenance technicians will find graphical languages quicker to learn and easier to
read usually.

Do you see companies updating PLCs to take advantage of the newer languages?

Only switching to a newer language usually is not a good reason to update a program.
Newer programming costs money. Companies usually want improved efficiency or
financial return to invest in program changes.

Are the younger generation even attracted to programming in the heavy indus-
tries?

I know young people in every industry. Learning to program is important, but it is just
as important to understand the process/action that you are programming.

What are your observations on engineers/technicians understanding control

strategies?
31
More answers: Tips and tricks for next-generation automation programming

Understanding what you want to do helps determine what language is the best to use.  Back to TOC
Programmers are still going to be biased toward their favorite language. Understand-
ing the process is necessary for the programmer, this is the first thing custom program-
mers do before designing a software project. Large custom machine builders generally
do not get to choose the language they program in; both their company and their
customer will usually have software specs that dictate this.

I’m a mechanical engineer having to specify and program a PLC for a fairly simple
HVAC logic for blower motor control and timers. I read schematics fairly well. Is
ladder logic the easiest to learn, for first-time programming?

In my opinion, in the U.S., yes. There are a lot of online resources to learn simple lad-
der logic [and many applications].

I am in my 50s, so I have used a lot of traditional ladder. One safety-related as-

pect that I like about ladder is that all rungs get scanned (typically) since writing
loops is uncommon. I fear that newer text-based language is prone to creating
unsafe code. Comments?

Text-based languages are still subject to scanning. If a line of code is not active, the
PLC does not wait like other microprocessors, it moves on. Loops can be used in lad-
der also, and do not have to be used in ST. Program control instructions like Jumps are
available in both also, it is up to the programmer how to use them.

Can you speak a little bit more about State Machines Technique for programming
PLCs?
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More answers: Tips and tricks for next-generation automation programming

 Back to TOC
State machines are common and usually used for sequences. There are two types of
sequence, one numerical (state machine) and one bit-based (bit-of-word.) Numerical
sequences are more common.

Isn’t it harder to troubleshoot Structured Text?

Yes, for untrained people ST can be harder to troubleshoot. It requires reading and
a bit of training in logic principles rather than knowledge of electrical circuits. But ST
coders without an electrical background have just as difficult a time reading ladder.

Have you heard of the IEC 61499 standard and, if so, what are your thoughts on
the future of this standard? It defines a generic model for distributed control sys-
tems and is based on the IEC 61131 standard.

Yes, I have seen this. It will apply more to computer and message queuing and telem-
etry transport (MQTT) based systems; major PLC manufacturers are not on board with
this yet. I consider this more of a communication protocol thing rather than something
fundamental to PLC coding.

Do you think manufacturers will adopt IEC 61499?

If they have a financial or competitive reason to do so. Again, I see this initially being
adopted on computer-based systems.

As a follow-up, IEC 61499 focuses on being hardware agnostic. It also uses “event-driv-
33
More answers: Tips and tricks for next-generation automation programming

en” execution rather then logic/code scanning on a cyclic basis. In this respect, it  Back to TOC
requires a very different approach to programming “real-time” control.

Unfortunately, I don’t think major PLC manufacturers will allow IEC 61499 to be hard-
ware agnostic. It will likely not be portable across PLCs any more than add-on instruc-
tions (AOIs) and function blocks (FBs) are.

Do you see more applications demanding the use of Visual Basic or C# or python
in comparison to traditional vendor specific SCADA/ HMI?

A free aid to VB.Net has great graphic capability and, most importantly for me, PLC
drivers. It is harder to use than SCADA/HMI software and requires a knowledge of Visu-
al Studio. It is also shareware under the GNU license, so cannot be proprietary.

What are the benefits and learning curve when switching from ladder logic to
another language?

Languages all have advantages and disadvantages. ST is useful for data and array ma-
nipulation complex formulas, etc. FBD has some instructions ladder doesn’t, like XOR
[exclusive OR]. SFC lends itself to sequences.

What programming language is most easy to use to aid maintenance in trouble-

shooting?

In the U.S., maintenance personnel, by and large, prefer ladder.

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More answers: Tips and tricks for next-generation automation programming

What are the main languages programming that a good plc programmer must  Back to TOC
know?

In order of preference for me: Ladder, ST, SFC, FBD. A good programmer should know all.

There is a big push by computer scientists to move away from IEC 61131 lan-
guages, will other programming languages take over? Which ones?

Just because computer programmers prefer other languages doesn’t mean PLC manu-
facturers will comply. If you can program Python and C#, you can easily learn ST.

I’d like to hear thoughts on programming commenting and ways to break up the
program for ease of troubleshooting.

These are standards in templates, there is a fairly standardized format for breaking up
and organizing programs. I use two different schemas, one for machine control and
another for process control. The are both described in my “Advanced PLC” book.

How can I generate a more flexible PLC programming?

Flexible PLC programming is best done by creating encapsulated objects such as FBs
and AOIs to accomplish tasks. Reusable code is important.

Do you know if there are efforts to update standards?

Updating standards is constantly being evaluated by the IEC [and contributing stan-
dards bodies] as technology changes. 35
More answers: Tips and tricks for next-generation automation programming

 Back to TOC
I am 33. New talent needs to have understanding of ladder logic as well as more
advanced methods to ensure a smooth transition, correct? We can’t just stop us-
ing ladder on a dime.

I agree. There is a need to understand ladder logic, and there will be a transition time.

What AI are you using?

I have used all of the major AI platforms with similar results.

With increased potential complexity of functions, I feel there is also an increase
in the potential of fatal faults like bricking the PLC. How would you recommend
mitigating this?

There are few ideas I have on mitigating this issue. One is to test all code thoroughly
before hand. Both with virtual PLC testing available with some manufacturers or having
a test PLC in your possession to upload and do factory acceptance test (FAT) and other
testing. It is also always good practice, especially with complicated systems and code,
to have another set of eyes pass over your code and catch what you may have missed.

How do you foresee maintenance personnel being able to troubleshoot struc-

tured text?

I believe AI will be beneficial down the road with this. As well, good coding practice is
to comment and document your code explicitly and extensively, and that will help as
well.
36
More answers: Tips and tricks for next-generation automation programming

 Back to TOC
Are you seeing recent graduating engineers who are interested in learning about
PLCs and programming?

Yes, it takes a certain kind of person, but I feel that it is a good intermediate for en-
gineers who like engineering, but also like coding/programming, which is becoming
more common.

Do you have any recommendations for online resources to learn structured text
programming?

YouTube has some great videos out there that will run you through many different situ-
ations and skills you need to know and learn. That’s what I use when in doubt.

Frank Lamb
Frank Lamb is founder and owner of Automation Consulting LLC and member of the
Control Engineering editorial advisory board.

37
AI-driven solutions for enhanced
plant automation productivity  Back to TOC

Artificial intelligence (AI) has become more sophisticated and is enabling

manufacturers to be smarter and more proactive with their operations.

A rtificial intelligence (AI) in manufacturing represents a significant milestone in

industrial history, moving from traditional mechanized processes to intelligent,
data-driven operations. This paradigm shift has revolutionized efficiency and precision
in manufacturing, paving the way for greater levels of productivity and innovation.

This evolution began with simple automated systems and has advanced to sophisti-
cated AI applications capable of complex decision-making and predictive analysis.
While initially reliant on human labor and rudimentary machines, the AI sector has pro-
gressed through many stages of technological advancement.

The introduction of AI has enabled automated systems to learn, adapt and optimize
processes, reducing human error and increasing operational efficiency.

IoT and AI enhancing plant operations

The integration of the Internet of Things (IoT) and AI in manufacturing processes ex-
tends beyond conventional automation and adds another layer of intelligence to the
manufacturing process in digital factories.

IoT devices collect and transmit data from various points in the production line, which
AI algorithms analyze to identify patterns, predict maintenance needs, and optimize
processes. This integration leads to a more responsive manufacturing environment
where decisions are data-driven and operations are more efficient. 38
AI-driven solutions for enhanced plant automation productivity

For instance, AI can optimize energy consumption by adjusting machinery operations  Back to TOC
based on real-time data. It can enhance quality control by identifying and correcting
defects early in the production process. As they’re building a more dynamic and inter-
connected manufacturing system, IoT and AI together drive towards the ultimate goal
of lean manufacturing: creating more value with less waste.

AI’s role in lean manufacturing

Lean manufacturing, which focuses on reducing waste and optimizing efficiency, finds
a powerful ally in AI technology. This approach to manufacturing is dedicated to maxi-
mizing value for the customer while also minimizing waste.

Central to this philosophy is the understanding of value from the customer’s perspec-
tive. It involves a deep comprehension of what the customer needs, ensuring the final
product meets their specific expectations and solves a problem.

An important aspect of lean manufacturing is the implementation of value stream

mapping. This process is critical in identifying and eliminating any form of waste
within the production process. It enhances overall efficiency by streamlining manu-
facturing operations.

Another key principle is the creation of flow within the production processes. This prin-
ciple focuses on maintaining smooth and uninterrupted operations, aiding in the con-
sistent and timely delivery of products.

Lean manufacturing also embraces the concept of pull-based production. This ap-
proach is governed by the principle items should be produced only in response to
39
AI-driven solutions for enhanced plant automation productivity

customer demand. Pull-based production helps reduces overproduction and the waste  Back to TOC
associated with it.

Continuous improvement is an ongoing effort in lean manufacturing. This involves the

ongoing process of refining and improving both the manufacturing processes and the
products themselves, striving for excellence and efficiency in every aspect of produc-
tion. AI technology, with its capabilities in data analysis and process optimization, plays
a crucial role in enhancing these aspects of lean manufacturing.

Innovative technology enhances lean principles by providing deeper insights into

production processes, identifying inefficiencies, and enabling real-time adjustments.
Here’s an example:

Danone uses machine learning to improve demand forecasting. This led to a 20%
increase in the accuracy of their predictions and a 30% reduction in lost sales. The
improved forecasting also contributes to better coordination between departments,
optimizing inventory management and reducing product obsolescence.

Enhancing efficiency and accuracy with AI

AI is enhancing plant operations in many ways and are reshaping how plants operate
with a greater focus on increased efficiency, reduced costs and improved sustainability.
Five notable applications are:

1. M
 anaging energy consumption: AI systems analyze energy usage patterns and
predict peak demand times, enabling plants to adjust operations and reduce en-
ergy costs. This includes shutting down non-essential equipment during low-de-
mand periods and optimizing energy-intensive processes. 40
AI-driven solutions for enhanced plant automation productivity

2. O
 ptimizing inventory levels: AI helps maintain optimal inventory by predicting  Back to TOC
future demand based on historical data, current market trends, and other vari-
ables. This reduces the risk of overstocking or stockouts, ensuring efficient use of
warehouse space and resources.

3. Identifying root causes of issues: Through data analysis, AI identifies patterns

and anomalies that might indicate underlying issues in production processes.
This aids in pinpointing the exact cause of issues like equipment failures or quali-
ty defects, leading to quicker and more accurate problem-solving.

4. P
 redicting maintenance needs: AI uses historical maintenance data and re-
al-time equipment performance metrics to predict when machines are likely to
require maintenance. This proactive approach prevents unexpected breakdowns
and extends the lifespan of equipment.

5. R
 ecommending performance optimization: AI analyzes operational data to
suggest improvements. This can include recommendations for process adjust-
ments, changes in workflow, or updates to equipment settings to enhance overall
efficiency and productivity.

The impact of AI on productivity and quality control in plant operations is profound.

Using its capabilities to automate and optimize processes, AI enables higher through-
put and better-quality products with fewer defects.

AI’s predictive capabilities also contribute to minimizing downtime and enhancing

maintenance schedules, which improves overall productivity and operational efficiency.
41
AI-driven solutions for enhanced plant automation productivity

The predictive capabilities in minimizing downtime and enhancing maintenance sched-  Back to TOC
ules come from machine learning algorithms that analyze historical and real-time data.

These algorithms identify patterns and anomalies that signal potential equipment fail-
ures. Once companies can predict these failures before they occur, maintenance can
be proactively scheduled, avoiding unplanned downtime. This approach helps ensure
machines are serviced only when needed, which saves maintenance resources and
keeps production lines running more smoothly.

Predictive and proactive maintenance through AI

Predictive maintenance uses AI to forecast equipment failures before they occur, al-
lowing for timely maintenance and repair. This contrasts with proactive maintenance,
which involves regular, scheduled maintenance activities to prevent failures.

Both approaches are critical in modern plant operations, with AI providing the neces-
sary insights for effective implementation. AI-driven maintenance employs machine
learning algorithms and sensor data to monitor plant equipment. These tools can
process vast data sets to predict when maintenance is needed on both critical and
non-critical assets, preventing downtime and ensuring operations run smoothly.

The benefits of AI-driven maintenance in plant operations are multi-faceted. Predictive

maintenance reduces downtime and allows for planned interventions that prevent un-
expected equipment failures. This leads to more consistent production, as equipment
availability and reliability improve.

42
AI-driven solutions for enhanced plant automation productivity

Additional benefits include these four aspects:  Back to TOC

1. Increased operational efficiency: AI-driven predictive maintenance ensures

machinery operates at peak performance, leading to smoother and more efficient
production processes.

2. L
 ower maintenance costs: By accurately predicting when maintenance is need-
ed, AI reduces the frequency of unnecessary checks and repairs, leading to cost
savings.

3. E
 nhanced product quality: Predictive analytics and real-time monitoring help
maintain consistent production standards, resulting in higher-quality products.

4. Improved employee satisfaction: A more predictable and efficient work envi-

ronment reduces stress and boosts job satisfaction among employees.

These improvements are not just limited to production metrics — they also contrib-
ute to employee satisfaction by creating a more predictable and less stressful working
environment.

Developing a synergistic approach with AI, connected worker

technology
Connected worker technology integrates digital tools to enhance the capabilities of
plant workers. This includes providing easy access to critical information, like training
materials and work instructions, and enabling real-time communication and collabora-
tion among workers.
43
AI-driven solutions for enhanced plant automation productivity

The benefits are multifaceted. For instance, connected workforce technology acceler-  Back to TOC
ates onboarding and time to productivity, reduces equipment downtime, and minimiz-
es defects and costs by improving knowledge management on the plant floor​​.

Enhancing safety standards involves AI alerting workers to potential hazards in real

time, reducing the risk of accidents. Improved resource allocation is achieved through
AI’s ability to schedule tasks and machinery usage more effectively, ensuring optimal
use of resources.

Continuous learning is facilitated by making training materials more accessible, which

allows workers to upskill as needed.

AI also enables comprehensive data analysis, giving managers better insights to make
informed decisions that lead to overall operational improvements.

The implementation of connected worker solutions promotes employee engagement

in various ways, supporting an older workforce and attracting new generations of work-
ers. It facilitates better communication, ensuring issues are resolved efficiently, thereby
making workers feel valued and reducing turnover.

These platforms also enable workers to provide feedback and suggestions, improving
decision-making processes and fostering a culture of engagement and continuous
improvement.

Four obstacles of AI integration in plant operations

Integrating AI into plant operations involves navigating a series of complex and multi-
44
AI-driven solutions for enhanced plant automation productivity

faceted challenges. These challenges encompass a broad spectrum of technical, op-  Back to TOC
erational, human, and security issues. Accomplishing this integration requires a blend
of technological acumen and understanding the human element. Consider these four
common obstacles:

1. Integrating AI with existing systems: This involves technical complexities like

ensuring compatibility with different software, hardware specifications, and com-
munication protocols. Older systems might not have the capability to handle AI-
based analytics, requiring significant upgrades or even replacements, which can
be costly and disruptive to ongoing operations.

2. M
 anaging large volumes of data: The sheer volume of data generated by AI
systems can strain existing data management infrastructure. It requires substan-
tial storage capacity, efficient data processing capabilities, and sophisticated
algorithms to filter and analyze relevant information from the deluge of data.

3. E
 nsuring worker adaptability to AI systems: Employees might resist adopting
AI due to a lack of understanding or fear of job displacement. Training them to
use AI tools effectively involves overcoming these psychological barriers, pro-
viding comprehensive training, and restructuring workflows, which can be a re-
source-intensive process.

4. A
 ddressing cybersecurity concerns: AI systems, especially those connected to
the internet, are vulnerable to cyber threats. Protecting them requires advanced
cybersecurity measures, regular updates to guard against new types of attacks,
and continuous monitoring to detect and respond to security breaches. This
45
AI-driven solutions for enhanced plant automation productivity

involves both technical solutions and employee training to recognize and avoid  Back to TOC
potential security risks.

The journey of integrating AI into plant operations, despite its challenges, is creating a
future where technology not only enhances productivity, but also contributes to a more
sustainable and resilient manufacturing ecosystem.

As these challenges are navigated and overcome, the path paves the way for future
trends in AI-driven plant operations, which are expected to further merge productivity
with sustainability, leading to more resource-efficient, cost-effective, and environmen-
tally conscious manufacturing processes.

Future plant automation industry trends

Future trends in plant automation point toward more advanced AI and IoT integra-
tions, leading to fully autonomous and interconnected manufacturing systems. These
developments, including more sophisticated AI algorithms for predictive maintenance,
advanced robotics, and enhanced data analytics capabilities, are expected to not only
increase efficiency but also significantly contribute to sustainability by optimizing re-
source use and reducing waste.

AI-driven sustainable practices in plant automation are not just environmentally friend-
ly but also significantly enhance productivity. These practices involve using AI to en-
hance environmental sustainability, while also improving operational efficiency include:

• Predictive maintenance

46
AI-driven solutions for enhanced plant automation productivity

• Energy management  Back to TOC

• Optimized resource utilization

• Supply chain optimization

• Quality control

• Eco-friendly process innovation

• Real-time monitoring and reporting.

The integration of sustainability and efficiency creates a symbiotic relationship where

eco-friendly operations lead to optimized processes, reduced waste, and better re-
source utilization, all contributing to improved productivity.

AI’s advanced data analysis and predictive capabilities enable a more efficient use of
resources. This includes minimizing material waste, optimizing energy use, and improv-
ing overall resource allocation. Since it’s essentially doing more with less, AI contrib-
utes to leaner, more efficient, and more productive operations.

Implementing sustainable AI practices can result in considerable economic benefits

such as AI-driven energy management systems reducing power consumption and lo-
weing energy costs. Efficient waste management through AI not only supports environ-
mental goals, but also reduces operational expenses, positively impacting the bottom
line and enhancing overall productivity.
47
AI-driven solutions for enhanced plant automation productivity

The ultimate goal of all these particles remains the same — achieving higher efficiency,  Back to TOC
reduced costs and improved sustainability in plant operations.

AI’s transformative impact

The transformative impact of AI in plant automation is evident in its ability to enhance
efficiency, accuracy and productivity.

AI-driven solutions have led to significant advancements in predictive and proactive

maintenance, connected worker technology, and overall operational excellence. The
integration of AI has enabled plants to operate more sustainably, adapt to changing
market demands, and remain competitive in an increasingly digital world.

The future of AI in plant automation is promising, with the potential for further ad-
vancements in technology integration, process optimization, and workforce develop-
ment. As AI technology continues to evolve, we can expect even more sophisticated
applications that drive efficiency, improve safety, and foster a culture of continuous
improvement and innovation in the manufacturing sector.

Eric Whitley
Eric Whitley is senior account manager at Leading2Lean.

48
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