Ali Kashi, Business   Development Manager | Downstream & Chemicals  Extracting AI value and dispelling AI hype is not an easy journey for asset-intensive companies to take. Yet, when employed correctly, AI provides the ability to boost asset-intensive operations to new heights – making the journey worth it, if they follow the right path. Demystifying Hybrid AI      In a relatively brief time, AI technology at Radix has grown from using a simple language model only capable of responding to if/then statements into a deep learning program capable of solving complex problems using large language models that contain a vast amount of human knowledge. This includes using new, generative AIs that baseline knowledge to foster connections and make predictions that elude many human users.     At Radix, we first started combining the 1st principal equations with Machine Learning (ML) algorithms to help us develop tools to leverage physics with the ability to monitor and find trends in vast amounts of data.  This “hybrid AI” lead to tools that could be used to predict failures, thereby, allowing users to get away from dependence on manual maintenance programs for equipment.      Being able to predict potential failures is important when dealing with hazardous operations. In addition, maintaining accurate models can be a time-consuming task. A person can build optimization models in spreadsheets using tools such as Solver, but it can be a challenge to devote enough time and people to build the models within the required period. This is of course before you factor in maintaining the model and distributing the information to those who need it the most. Leading to a spaghetti bowl of custom spreadsheets throughout the operations of an organization.    In some cases, it's easier because you have online and connected instruments or continuous processes in the process. But when you go to, for example, what is the deactivation time for that specific catalyst, it is an extremely hard problem or variable to predict – and one made more accurately and effectively by AI and ML.     Radix + AI = Peace of Mind Operations   Asset-intensive companies operate a wide variety of equipment and machines with complex parts, and Radix is always looking for ways to help them protect their capital investments. By utilizing AI to better understand the condition of the various parts and their potential failure points, we have helped prevent downtime, optimize maintenance schedules, and develop ways to use less fuel or energy. With Radix and AI, you can avoid the 3:00 AM phone calls to come into the plant to perform maintenance or perform calculations.     As a side note: the safety benefits, which AI provides, are also a real benefit for downstream companies. For example, there are programs we run at Radix where we utilize image processing to ensure that operators are wearing the correct personal protective equipment in restrictive areas. If the AI detects that an employee is not wearing all the right equipment, or is wearing it incorrectly, it can trigger an alert or an alarm until that employee fixes their gear. The same AI-based image processing software also ensures that escape routes and emergency access points are free of debris in case of an emergency.     Despite AI still having a long development road ahead of it, companies like Radix are already using it to improve both safety and operational efficiency. Additionally, AI has given engineers in downstream and beyond more understanding over complex processes that have a substantial chance for error if mixtures or parameters are not precise and correct.     Given its impressive early gains and the massive potential to help with future operations, we can expect many companies to follow Radix’s lead in AI application development and implementation. To get started today contact me at Connect with us | Radix ( radixeng.com )

By Citalouise Geiggar, Ph.D and Vice President of Marketing at Radix North America Extracting AI value and dispelling AI hype is not an easy journey for asset-intensive companies to take. Yet, when employed correctly, AI provides the ability to boost asset-intensive operations to new heights – making the journey worth it, as long as they follow the right path below.     Recently, I sat down with my colleague, Natalia Klafke, EVP of Energy & Sustainability at Radix, to discuss her last article on how Radix uses AI to solve  supply chain disruptions and global inflation challanges across asset-intensive industries. Natalia also shared with me additional insights on how Radix helps leaders leverage AI to streamline operations and it led to the insights below.     Demystifying AI Value     In a relatively brief time, AI technology at Radix has grown from using a simple language model only capable of responding to if/then statements into a deep learning program capable of solving complex problems using large language models that contain a vast majority of human knowledge. And the new generative AIs use that baseline knowledge to foster connections and make predictions that elude many users.    This has allowed business leaders throughout the corporate world to test the limits of what AI can do for them.    At Radix, we first started using AI - in areas like Petrochem - to help us understand the physics of the equipment being used, especially the thermodynamics and chemical reactions. This includes using AI to boost the first principal models we built, resulting in an ability to now predict failures without having to physically experiment with actual chemicals.    Being able to predict potential failures is important when dealing with hazardous materials such as petrochemicals. In addition, maintaining accurate models can be a time-consuming task. A person can build optimization models in spreadsheets using tools such as Solver, but it can be a challenge to devote enough time and people to build the models within the required period. This is of course before you factor in maintaining the model and distributing the information to those who need it the most.     In some cases, it's easier because you have online and connected instruments or continuous processes in the refining process. But when you go to, for example, what is the deactivation time for that specific catalyst, it is an extremely hard problem or variable to predict –and one made more accurately and effectively by AI.     Asset-intensive companies operate a wide variety of machines with complex parts, are Radix is always looking for ways to protect their capital investments. By utilizing AI to better understand the condition of the various parts and their potential failure points, we helped prevent downtime, optimize maintenance schedules, and develop ways to use less fuel or energy.     According to Natialia, “AI can avoid the 3:00 AM phone calls to come into the plant, perform maintenance, or find a vendor to perform maintenance at a moment’s notice. You want to optimize downtime. And if you manufacture specialty chemicals then you want to make sure you don't lose production because the demand for that product is so high. AI can help in these and other situations.”     As a side note: the safety benefits, which AI provides, are also a real benefit for petrochemical companies. For example, Natalia mentions that there are programs we run at Radix where we utilize image processing to ensure that operators are wearing the correct personal protective equipment in restrictive areas. If the AI detects that an employee is not wearing all the right equipment, or is wearing it incorrectly, it can trigger an alert or an alarm until that employee fixes their gear. The same AI-based image processing software can also be used to ensure that escape routes and emergency access points are free of debris in case of an emergency.     Despite AI still having a long development road ahead of it, companies like Radix are already using it to improve both safety and operational efficiency. Additionally, AI has given engineers in Petrochem and beyond more control over complex processes that have a substantial chance for error if mixtures or parameters are not precise and correct. Given its impressive early gains and the massive potential to help with future operations, we can expect many companies to follow Radix’s lead in AI application development and implementation.

Successful use of real-time data transforms industrial operations and elevates data-driven decisions. But not so fast, success requires 3 activities.   Authored by: Justin Conroy, Vice President, Digital Product Portfolio - Radix.   “You can’t manage what you don’t measure.” This sage comment resonates as true today as it did when I first read it in an old Harvard Business Review  study, over a decade ago.   In today's data-driven world, real-time data has become a critical component in optimizing asset performance. By leveraging the latest technologies, enterprises can act on data as it is generated, leading to significant improvement in their operations.  Real-time data enables continuous monitoring of asset health, allowing enterprises to detect anomalies and potential issues before they escalate into major problems.   With the ability to access live data from sensors and other IoT devices, maintenance teams can track performance of machinery and infrastructure, ensuring they operate within optimal parameters.  As an example, a chemical processing plant can use real-time data to monitor flow rates, temperatures, and pressures of various processes, ensuring they operate at peak efficiency. This not only reduces energy consumption but also minimizes waste and improves product quality.  “Caveat emptor!” or as we translate from Latin, “let the buyer beware!”  Achieving real-time data integration is a journey fraught with costs, delays, and challenges, unless you follow these next three steps.   Step 1: Choose Wisely   The first step in real-time data integration is selecting the right tools. When choosing tools, consider factors such as scalability, ease of integration, data security, ability to handle diverse data formats, and protocols.   Selection depends on the needs of an enterprise, existing infrastructure, and required outcomes. Essential tools include Extract, Transform, Load tools, data lakes, streaming analytics platforms, and data visualization tools.  Extract, Transform, Load tools, such as Azure Data Factory, AWS Glue, SAP Data Services, and others, are important for integrating data from multiple sources and transforming data into a usable format, before loading it into a centralized system.   For processing and analyzing data in real-time, event streaming platforms like Apache Kafka are useful. These platforms enable you to handle data as it streams from various sources.  Optimizing your data management strategy and approach, and leveraging these and other solutions, is made more effectively when partnering with experts who have a track record of robust data management and data optimization.    Step 2: Use What Works Efficiently   It sounds simple – but few do it. Integrating real-time data requires adherence to best practices to ensure data quality, consistency, and security and the enablement of data governance programs. An important practice is data normalization. By standardizing data from various sources, enterprises can ensure consistency and accuracy, making it easier to analyze and compare.  Establishing a unified data model is another best practice. This model defines how data is organized, stored, and accessed across the enterprise, ensuring that stakeholders have a collective understanding of data and its relationships.   Strong data quality measures are also important. Regular validation and cleansing of data helps prevent errors and inconsistencies, ensuring that data remains reliable.  In addition, data governance and security are vital. Developing a comprehensive data governance framework that defines roles, responsibilities, and policies for data management helps maintain data integrity. Ensuring data security measures are in place protects sensitive information from unauthorized access and breaches.  Step 3: Conquer Common Inhibitors   The path to real-time data integration has its share of challenges. One common obstacle is legacy system compatibility. Integrating data from outdated legacy systems is difficult. To address this, consider using middleware solutions or APIs to bridge the gap between legacy systems and modern data platforms. Gradual modernization of legacy systems can improve compatibility over time.  Data latency is another challenge that needs addressing. Minimizing latency is necessary for real-time integration. Optimizing network infrastructure, using data processing algorithms, and edge computing reduces the time taken for data to travel from source to destination.  Costs of real-time data integration are a concern, and such projects are expensive. To manage costs effectively, prioritize high-impact areas and start with pilot projects to demonstrate value. Leveraging cloud-based solutions reduces upfront investments.  What is at Stake?   By understanding diverse data sources, addressing data silos, and managing scalability issues, enterprises unlock the potential of their assets.  Real-time data integration offers the ability to continuously monitor asset health, predict maintenance needs, make informed decisions, and optimize resource utilization. These advantages translate into reduced downtime, cost savings, and enhanced operational efficiency - which are essential for any industry aiming to thrive in today's competitive landscape.  As industries evolve and the volume of data grows, those who embrace real-time data integration will be better positioned to achieve operational excellence and long-term growth.  To learn more, visit www.radixeng.com

After COP28, 50 oil companies representing half of the world’s global production have promised  to reduce methane emissions to near zero by 2030. Simultaneously, the Biden administration unveiled new methane reduction regulations  to reduce methane, which are considered among the most harmful greenhouse gases (GHGs).       Hitting emission reduction numbers requires that governments implement ambitious policies and regulations to promote renewable energy, energy efficiency, sustainable transportation, and sustainable agriculture. For oil and gas sector companies, these targets require an approach that focuses on optimizing operational efficiency, increasing production, and reducing costs simultaneously.       There are disruptive technical challenges that Radix is focusing on in the midstream market, precisely to monitor methane emissions better to reduce this pollutant. Our approach includes finding and implementing better ways to predict and thus prevent pipeline stress and corrosion that lead to cracks and subsequent methane leaks.       Addressing the Disruption & Leaks at the Pipeline          Until recently, the only way to identify potential cracks that have already happened was through manual inspections, which are both costly and time-consuming. However, with the flood of data, satellite images, and AI-based analytics available, the oil and gas sector can leverage better, more accurate solutions to predict where there is stress and corrosion to a level that signifies an impending crack along a pipeline.       While there will still be a requirement for manual examination, anything that narrows what needs to be inspected cuts the time and expense of lengthy manual inspections. If repairs can be made before a crack occurs, that is cost avoidance- which for oil and gas companies equates to higher profits and safer operations.         This approach fits in with Radix’s efforts to leverage data and AI (Artificial Intelligence) to improve forecasts and predictions that companies can use to help optimize their operations. Making repairs to a pipeline before it is damaged will allow a planned, temporary shutdown for a company, which will also be better reflected in its production schedule.         By focusing on solutions to methane leaks and methane burning, such as ending the practice of flaring the methane from new wells or capping old wells when they are taken out of production, energy companies can take great strides in meeting desired emission outcomes. By taking these measures and leveraging data to prevent pipeline leaks and other production issues, companies can accomplish all sustainability and emission goals for 2024 and beyond.       To learn more, visit www.radixeng.com

"ROI From Technology Solutions The return on investment from a technology solution is crucial. In this competitive technology industry, company leaders need to justify their investments to stakeholders, including investors and management." It enables leaders to strategically align with the company’s long-term goals. - Alexander Clausbruch , Radix "

- Natalia Klafke, EVP of Energy & Sustainability, Radix   Supply chain disruptions and global inflation continue to cause revenue crunches across many different industries. These disruptions have hit petrochemical companies especially hard as they deal with challenges in various consumer goods prices and a volatile energy market. There is simply too much going on, too quickly, for those studying the market to pick out every trend and make accurate predictions, especially with enough forewarning to enable supply chain changes to keep ahead of market forces.    Artificial intelligence (AI), however, is uniquely designed to be able to relentlessly scan through millions of data points to uncover hidden connections, dependencies, and trends. It just takes a team of knowledgeable experts to hone the AI’s skills and abilities for a specific task, like forecasting complex market forces and applying them to business operations. It is a technique that Radix Engineering has pioneered for its petrochemical companies since the early days of AI deployments.    Some typical processes that companies need to perform are the sales and demand forecasts. We have been using AI for that for a while now and employing it to predict trends regarding what will be going on with the market. We have also been using AI to enhance our demand forecast activities so that we can provide higher visibility and accuracy for what sales will look like in the next week, month, and quarter.    Petrochemical and downstream companies require accurate forecasts for upcoming sales numbers to determine their complex resource allocations and production schedules. While many large companies maintain skilled data scientists on staff to run these complex reports, they can be very time consuming to build and maintain. AI allows companies that work with Radix to construct those complex optimization models extremely quickly, letting the highly tuned AI do most of the hard, repetitive work for its human counterparts.    Radix has a track record of leveraging AI to empower specific resources like engineers to gain actionable, real-time insights from available assets - from pipelines to ships. Using Radix and AI as part of your operational logistics delivers calculable value across your entire operating model, regardless of size or scope.    This approach also removes constraints that you must often meet, from regulatory to production challenges. Most valuable, the Radix approach towards leveraging AI lets companies better predict the most economical way to allocate resources based on an optimal production plan. AI trained by Radix can do all that, and keep the plan constantly updated with new data as market conditions change.    Remove Scarcity from Your List of Challanges      Petrochemical and downstream companies also face the challenge of having to source raw materials that have a high degree of scarcity. Like the challenge of rising production costs, Radix is solving the increase in fees and costs associated with raw materials transportation by optimizing our client’s transportation logistics. On the petrochemical side, Radix uses AI to precisely determine what raw materials will be needed, both for today and in the future, and how to efficiently transport them to refineries so that they arrive as soon as they are needed – and at the lowest possible cost.    Radix is already experimenting with ways to employ AI in other areas. Soon, we will use AI to help set dynamic pricing for chemicals and petrochemicals, ensuring that its customers can get every bit of profit from each sale or contract.    Most notably, AI will eventually allow chemical and downstream companies to build customer-specific items and products. That capability has enormous potential to enable petrochemical companies to forge incredibly strong relationships with their major clients.    Radix is committed to using the most effective tools, services, and solutions to meet our customers' needs at every stage of their production and operational lifecycle. Our ability to replace AI hype with AI value is a testament of that commitment for downstream petrochemical companies and engineering firms as they face an increasingly complex set of market and environmental forces.

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When “digital transformation” first entered the Energy lexicon several years ago, it did not seem daunting – leverage tools to handle IT/OT interfaces, increase cybersecurity, and create a dashboard to present the analytics. Companies had years, sometimes decades, of data they could use.      Nevertheless, to this day, one of the significant challenges in Energy, and for the oil and gas industry, is determining how to best integrate and innovate newer digital technologies - while capitalizing on existing efficiencies and reducing risk and downtime to near zero.      When companies started integrating digital transformation and instituting changes within their operating environment, small, incremental steps yielded positive results. New challenges arose as energy companies took those steps to integrate innovative solutions. For instance, discovering that much of the data they counted on was either unusable in its existing form or far more incomplete than they had realized was one issue that plagued the industry early on. It stems from the fact that one of the consequences of being a mature industry is how much Information Technology (IT) has evolved over the past 40 or 50 years, including data formats, data silos, legacy systems, and deferring degrees of data availability and management with ineffective or non-existent data governance.      Digital transformation is not a one-and-done set of actions, and meeting one business challenge with a new tool does not mean a company’s market challenges are solved permanently. That is why when Radix talks about “digital transformation,” we put it in terms of interrelated frameworks for best-leveraging data through the proper integration of tool sets, which evolve every two or three years.      This approach empowers our clients with flexibility and scale relative to the integration of newer solutions, but more importantly, it improves their understanding and management of the data in a manner that improves their data maturity posture. This approach also boosts operational efficiency by integrating a robust data governance structure needed to integrate and extract value from solutions like digital twins, Artificial Intelligence (AI), machine learning, and containerization.      Solving the Energy Trilemma with Data- Driven Results     Establishing a data architecture and infrastructure helps set the stage for a long-term foundation of operational excellence in any industry - especially oil and gas, which deals with many IT and Operation Technology (OT) data levels. Addressing the challenges of old formats, incomplete data, and rules for introducing new data flows gets the decades-old problems out of the way, making it easier to revisit what has been done and look at new ways to apply data insights and analytics.      Doing so lays the groundwork to tackle challenges in the O&G industry that the market references as the Energy Trilemma.       The energy market today faces the macroeconomic challenge of balancing three competing needs:     Universal Access: Ensuring universal access to Energy for domestic, industrial, and commercial purposes.    Supply & Demand: Meeting current and future demand and being capable of accommodating and responding to potential system shocks.    Environmental Impact: Mitigating the impact of climate change.      These three dimensions are encapsulated by the “Energy Trilemma,” which aims to simultaneously ensure affordable, resilient, and sustainable energy. For Radix’s clients and the market at large, this translates into three significant challenges:      Cash Flow Generation:  Transitioning to cleaner, more sustainable energy technologies requires significant investments. Companies must generate sufficient cash flow to sustain these investments, especially in technologies needing consolidation.      Portfolio Diversification:  Faced with uncertainties and challenges associated with adopting renewable energy sources, many companies are diversifying their portfolios. It involves exploring various renewable energy source options to reduce risks and ensure resilience in the face of market changes.      Decarbonization of Existing Assets:  Optimizing existing assets is crucial in reducing the carbon footprint. More efficient and sustainable production increases profitability and minimizes environmental impact.      It is important to note that balancing renewable and fossil energy sources is a global challenge. Even in more aggressive pro-renewable energy policies, fossil sources have become essential in the energy supply for some time. Therefore, the challenge in the coming years will be to find ways to ensure that this transition is made sustainably and in a balanced manner, addressing economic, environmental, and social needs.       The role of data, data management, data architecture, and data governance are more critical in solving these challenges. For instance, Radix has a solution currently being used by one of our customers where we developed a control tower that integrates the value chain from end to end. It is a replicable solution that can be applied in many parts of the industry and across industries. However, doing so requires a solid data architecture, the first step we now employ in a new engagement.      By building a foundation of data management and subsequent governance that can produce the architecture and infrastructure to manage data best, organizations within this industry are also better prepared for inevitable market and environmental changes that occur.      For example, in a recent podcast discussion with Michael Hotaling, Operations Excellence Digital Manager at ExxonMobil, Michael described the changes they are spearheading towards how they approach data regarding the integration of newer technologies.      Specifically, they are creating a “digital reality ecosystem” that ExxonMobil is putting together to visualize better how to work in oil and gas. This approach includes developing an open asset digital twin representing existing facilities, but in a manner that is not driven by solving an individual use case but instead built on an ecosystem where multiple use cases can be solved or worked on from a single Twin.       Leaving silos in place – or creating standalone islands that do not connect to the whole – hurts the scalability, the profitability of the whole enterprise – making solutions like ExxonMobil’s digital reality ecosystem more challenging to achieve.      Energy companies can take great strides toward demystifying digital transformation by starting with data, data management, and data architecture. An essential element of solving this challenge is partnering with a company like Radix that leverages a data-driven approach toward helping companies turn their challenges into opportunities through intelligent engineering – with scalability.         To learn more, visit www.radixeng.com .

Key Insights on How Manufacturing Leaders Achieve Operational Excellence  As profit margins tighten due to inflation and supply chain stress, improving efficiency has become a necessity in almost every industry. To that end, companies that rely on complex logistics networks and supply chains are looking for new ways to optimize their networks.   But real process optimization is not an easy or quick fix, especially for firms like those in the Manufacturing industry, whose networks rely on both information technology (IT) and the much older, and arguably more critical, operational technology (OT) components. Specifically, optimizations that span into highly complex assets, and trying to apply traditional optimization methodologies that address single variable improvements may not equate to the kind of real change that a company needs.  “There are simply too many variables in some processes. You can't just oil a single gear and expect the whole machine to run smoothly,” said Radix’s Head of Manufacturing for North America, Justin Conroy. According to Conroy, decision-makers often assume that just because they focus on optimizing one part of their process that they will succeed in optimizing their entire host of processes. Each industry has specific processes and assets that require specific domain knowledge in order to understand the best paths toward optimization. No one person or group can know everything and no one knows this better than the engineers at Radix. We take a holistic approach to developing stronger and more optimized OT for each and every customer, system, process, and asset.   “I cut my teeth in a very niche part of the process industry in my early years,” said Conroy. “The domain knowledge required was incredibly specific and the work we did carried a high amount of risk for our customers. If we made a mistake like recommending the wrong size relief device, not desiging a flare stack to be tall enough or not sizing knockout drums to have adequate liquid/vapor separation, people may get hurt, or worst.”  Almost every process has complexity and requires a deep understanding of the subject matter that a general philosophy cannot address. From textile makers to automobile manufacturing and everything in between, there are numerous processes that require a nuanced approach to solve. Radix understands this and works with clients to first, understand their needs and their incredibly unique situations, before then developing a process optimization solution.   “The manufacturing industry is still kind of stuck in the 'Digital Transformation’ mindset of trying to optimize their business through some magic bullet of technology,” said Conroy. “And in the last few years, they've realized that what they've been trying to attempt for the past 15 years isn't working.”  In fact, sometimes the highly customized solutions that Radix creates for clients may counter some of the more traditional wisdom found in popular optimization philosophies and guidelines. For example, Conroy says that a company shouldn’t move all of its assets and decision processes over to a digital format just for the sake of doing so. Instead, the end goal is the ability to make better decisions with their data, whatever format that takes.   Radix instead develops solutions that will achieve the desired end result for their clients in the most optimal way possible. “While a bespoke solution may not be as quick or flashy as some commercial, off-the-shelf software, it might ultimately provide better process optimization and increased efficiency,” Conroy said.   While the process of optimizing both the OT and IT within an organization’s networks can sometimes seem overwhelming, having a company like Radix as a partner can alleviate much of the stress. Radix engineers like Conroy’s team know what it takes to develop an efficient solution that takes into account all of the unique aspects of their business and manufacturing processes. And Radix is there for the duration too, from the planning stages, into the rollout and beyond.  Pioneering the Future, Today So, how will the landscape of process optimization look in the next decade?   From Digital Twin to generative artificial intelligence, Radix is already implementing some of the most innovative technology solutions leveraging a model that facilitates the integration of new solutions for the most effective impact to production, productivity, and revenue.   According to Conroy, artificial intelligence and advanced machine learning will likely make a big impact in the near future, and Radix engineers are already working to show how their implementation can lead to better optimization solutions. But whatever the future holds, almost any company or industry could benefit by adopting the Radix philosophy of deploying highly customized optimization solutions to help both OT and IT networks achieve maximum efficiency and productivity.  For more information, please contact an expert at  Contact | Radix ( radixeng.com )  today!

Cleveland, OH, April 23, 2024 : Radix ,   a global technology solutions  company,   announced its participation as a Sapphire sponsor at  TAPPICon 2024 , which is being held at Huntington Convention Center in Cleveland, OH, from April 28 - May 1, 2024.   Senior executives and experts from Radix will present multiple papers, which will support this year’s conference theme, " Unleashing the Harmonies of the Paper Industry”,  by demonstrating the role that AI can play in the evolution of the industry. These presentations will include participation in the New Technology Showcase that highlights the success of employing Hybrid Intelligence that consists of Artificial Intelligence (AI) tools to accomplish tag mapping in the Pulp and Paper industry providing customers with data-driven transformation at scale.   Radix will demonstrate how historical challenges, such as detecting and troubleshooting unplanned breakdown conditions during manufacturing, can be eased by using machine learning tools and techniques, which results in a much better data-driven understanding of the relationship between target output quality properties and upstream process variables. Similarly, by integrating health monitoring IoT devices into the pulp and paper process, the systems can learn equipment behavior and detect deviations that might be missed during routine inspections.    “ TAPPICon is  a focused exhibition for the paper and pulp industry and an important platform for Radix to meet our customers and partners and share our expertise and successes with them. We are a diverse group of engineers that have the expertise of specific industries and technology, and the best solutions to deliver continuous asset performance improvement --- At Radix, we are using data analytics to help our customers identify where their bottlenecks are, where their value waste streams are. And from those value waste streams, we help define a problem statement to find the gap and then create solutions that our customers can scale with” On Tuesday, April 30th, at the “Transforming the Industry with IIoT, AI, and Digital Strategies” session, John Rudd, Director of Operations - IOT-Mfg  will present on the topic, “Why IIoT is important to your Digital Environmental Strategy”.      Other presentations include sessions by:   Elcio Cardoso da Silva, Radix Consultant on the New Technology Showcase that highlights  “How We Had Success Employing AI Tools to Accomplish Tag Mapping in the Pulp and Paper Industry”    Zachary Burke, Radix Account Manager, who will speak during the Data Driven Applications session on “Using AI to Detect Root Causes of Abnormal Conditions and Boost Equipment Reliability”    Bruno Baggio, Radix Technical Program Manager will cover the subject of Digital Twins with “Successful application of a Process Digital twin in an Integrated Paper Mill”    Stephen Janes, Radix Senior System Engineer will speak on Transforming the Industry with IIoT, AI, and Digital Strategies with “ Digital Support for Maintenance Teams: Utilizing Machine Learning and IoT to Assist in Equipment Reliability”.     Radix will be at TAPPICon 2024  Booth 326 to meet with their paper and pulp customers and partners to share their global success stories with them. For more information please visit Radix at TAPPICon 2024 ( radixeng.com ) .     -Ends-  About Radix   Founded in 2010, Radix is a privately held global technology solutions company providing consulting, engineering, operations technology, and data and software technology solutions. Radix combines key capabilities and practices to empower customers to thrive along their digital transformation journey. Radix provides technology-based, data-driven solutions to industrial and non-industrial companies worldwide. Radix has experience leading projects in more than 30 countries and has more than 1,700+ employees around the globe, with North American headquarters in Houston, Texas, main headquarters in Rio de Janeiro, additional offices in Sao Paulo and Belo Horizonte, and a presence in Singapore and Amsterdam. To learn more, visit www.radixeng.com .

"The drive to bring down energy consumption – and its cost – has spread to higher education. The University of Florida, for instance, is investing almost $30 million to save roughly $5 million over the next two decades. Overall, investing large sums upfront to save money on energy costs can have many motivations. Many colleges and universities face financial pressures, so bringing down the trajectory of energy costs is sensible." To access the full article on #KnowledgeReview, please click the link below: