‘Poor management of energy consumption and wastage of energy are some of the reasons for the runaway situation around carbon emissions from facilities and integrating data through smart technologies implemented onsite are steps in the right directions says Marcela Ximenes, Head of Education Technologies at Radix.’ The world is facing on urgent crises of limiting the runaway global warming and must reach net-zero emissions by 2050. But what is less realized, and similar to most fluid consumption models, of the energy consumed by facilities in the US, 68% of the energy is actually wasted while buildings across the facilities are responsible for 80% of the energy consumption. Research buildings or competency centers, usually present inside sprawling facilities, and legacy engineering practices for ventilation, heating and cooling, are also responsible for these runaway emission trends.

HOUSTON, Oct. 13, 2020 (GLOBE NEWSWIRE) -- Pro- Frotas , a 100% digital fuel supply management start-up created in partnership with Ipiranga, is growing its operations with technology developed by Radix Engineering and Software . Ipiranga, a subsidiary of U l t r a , is the largest private player in the Brazilian fuel distribution market, with nationwide coverage and a network of approximately 7,200 service stations. Pro-Frotas was conceived with the purpose of reinventing the fleet refueling business, with technology that would supply 100% digital, free supply management and payment. Pro-Frotas contracted Radix, IIOT digital transformation experts, to create an application and web portal for management and control of fueling.

-by Geraldo Luiz Rochocz  THE AI BOOM  Take a simple test: type "Artificial Intelligence" into any internet search engine. At the time of writing, the term already amassed hundreds of millions of results, an impressive number for a technology that only recently reached the mainstream. Despite the recent boom, driven by tools like OpenAI's ChatGPT and Google's Bard (Gemini), AI's history dates back years. Its roots lie in advances in deep learning, a field familiar to scientists and researchers for quite some time. Few may recall, but as early as the early 2000s, the topic was already being discussed, including the release of the movie A.I. - Artificial Intelligence, directed by Steven Spielberg in 2001. But even that does not express the true age of this technology: The concept of Neural Networks appeared in 1943! Though the boundaries of this technology and its potential remain uncertain, unlike other recent innovations such as the metaverse, AI has quickly gained popularity in its use and concepts- and the numbers don’t lie. WHAT IS THE POTENTIAL IMPACT OF AI?  Gartner predicts AI Software will grow to $297 Billion By 2027. And this is only the beginning. Gartner forecasts the market will grow at a 19.1% compound annual growth rate in the next six years. Generative AI specifically (GenAI software spending) is expected to boom from 8% in 2023 to 35% by 2027.  The industry´s digital transformation is expected to continue at an accelerated pace. But, if the plans for the future of this technology appear grand, the challenges are no smaller: AI adoption is not simple or out of the box - companies need clear access to clean data to create effective AI solutions, and IT needs to bridge the gap between technology and business to ensure that data and AI lead to operational improvements.  It is essential that industry players carefully analyze how AI fits into their current digital strategies and prepare for the pitfalls that exist when attempting to fully leverage its potential.  THE ROLE OF DATA IN AI  The potential of AI to drive growth and reduce costs cannot be overestimated, especially in energy and manufacturing, where data dependence and analysis are crucial for innovation. These sectors are built on increasingly complex and subtle processes and AI, specifically GenAI, provides a potential for a much-needed reduction in complexity.   It’s one of the many reasons firms like GlobalData are predicting that, "AI can generate $2.4 trillion in value for the energy sector by 2035, representing an 11% increase in sector revenue."    Achieving the benefits of AI requires that companies define AI, recognize the challenges in effectively implementing these solutions, and develop the roadmap and strategies needed to overcome these challenges.   Defining AI  According to Gartner, AI is the process of applying advanced analysis and logic-based techniques, including machine learning (ML), to interpret events, support and automate decisions, and take actions.   The key to this definition is the view that AI adds actionable intelligence to good data, empowering decision-making, and operational performance.   At Radix, we leverage this approach to AI to help our clients and customers, specifically in sectors that generate an enormous amount of data, achieve Asset Performance Management (APM) insights that:    Drive production and productivity.   Boost operational efficiency, sustainability, and safety.   Scale better to meet demand, uncover, and remove bottlenecks.  From sensor logs and engineering reports, to work orders and maintenance records, we help our customers implement AI solutions and programs such as generative AI to better understand and leverage their rich data sources to optimize operations and make better decisions.  The Challenges to Effective AI   Some of the main pitfalls when implementing AI include:  Definition of terms and explainability around what AI systems are, how they function, and the expected outcomes and potential challenges.   Select the proper AI techniques (there are dozens of them) for each use case, avoiding current fads.   Efficient access to the right data in real-time.   An approach to building a multi-agent intelligent-based platform that   allows the integration of AI models and tools from third-party providers.   Improving the ability to monitor controls continuously, throughout model and application development, testing and deployment, and ongoing operations.   A need for new methods to test, validate, and improve AI-powered workflows.  Addressing the changing regulatory landscape, from the EU AI Act to regulatory frameworks in North America.  What can A.I. with Radix Do for Me?    The short answer is converting your asset performance to asset excellence across your entire enterprise and at every stage of your operational lifecycle.     Recently, Radix leveraged Generative AI, along with other solutions, to optimize operations in a large industrial client looking to transition from manual tools and spreadsheets to a digital platform – on a global scale. With help from Radix, they leveraged A.I. to boost asset performance management in over 100 plants globally.     The results of partnering with Radix for A.I. integration led to:  Streamlined and more accurate financials that netted millions in annual savings.   Decreased electricity and utilities costs obtained from energy optimization in plant equipment and better decisions based on operational insights from real-time forecasting of electricity usage for real-time price monitoring during price hikes to prevent overspending.  Savings of over $5 MM yearly with maintenance by mitigating unexpected downtime and optimizing planned downtime (revenue increase not accounted).  Accurate real-time materials balancing model for real-time tracking of production, inventory, raw materials, production, waste, and unaccounted losses. The model runs with less 0.5% deviation and allows real-time forecasts of monthly production.  Reduction of $ 2 MM per year in production losses with real-time prediction of physical properties of polymers and enhanced control strategies.  How to Start?  Companies need to partner with firms to help them through the journey of successful AI integration. At Radix we not only solve the challenges above, but we also design and validate the target architecture and include the program and project rigor that provides communication and governance planning.   AI Implementation should be driven by business needs. The same thinking applies to governance. Value streams prioritize specific tasks and details after establishing the first set of guidelines and security boundaries.  Radix already offers advanced AI solutions for companies worldwide by making intelligent and strategic use of this technology. We help navigate all these challenges to optimize asset integrity, improve maintenance efficiency, accelerate new product discovery, create virtual consultants, and assist and optimize production.  We have a record of accomplishment of helping our customers successfully implement AI so that they can realize the following Gartner benefits:   By 2026, organizations that operationalize AI transparency, trust and security will see their AI models achieve a 50% improvement in terms of adoption, business goals and user acceptance.  By 2026, enterprises that have adopted AI engineering practices to build and manage adaptive AI systems will outperform their peers in the number and time it takes to operationalize AI models by at least 25%.  If you want to learn more about AI and how we can help you leverage this solution for your business results, follow the lead of some of the world's largest companies and contact Radix today at www.radixeng.com .

Natalia Klafke with Radix and Michael Hotaling with ExxonMobil deliver insights on leveraging open-source tools and digital twins to maximize value in Energy, industry, and beyond.

Pulp and Paper mills across the globe are facing the challenge of being more productive and delivering more quality, while minimizing and optimizing costs. In a scenario where companies seek to provide solutions without large investments, using existing facilities most efficiently becomes not only desirable, but necessary. The Pulp and Paper industry faces the challenge of making decisions dynamically and quickly, while production areas are coordinated individually and not as integrated as they should be. Mill-wide Optimization tools could be the next step toward more efficient operations. Specifically, since solutions for coordinating process areas are uncommon and opportunities often exist between process areas for optimizing operations with new capabilities, like Digital Twins.... Interested in reading more? Click below to download and discover:

The Pulp and paper industry is historically an industry that boosts production by increasing operational utilization rates. Need more output? Buy more wood, put in more machines and vats and presses, add another work shift – and repeat as needed. The challenge with this approach is that the processes being used have a lot of variability, and machines degrade and wear out quickly. While digital technology, automation, and analytics can move P&P away from this “brute-force” roots, like many manufacturing fields, P&P faces new and additional challenges when incorporating IT into its operational technology (OT). To read the full article please click the link below:

Applying the power of data to the pulp and paper (P&P) industry is a game-changing approach towards potentially driving profits and minimizing downtime. The Pulp and paper industry is historically an industry that boosts production by increasing operational utilization rates. Need more output? Buy more wood, put in more machines and vats and presses, add another work shift – and repeat as needed.  The challenge with this approach is that the processes  being used have a lot of variability, and machines degrade and wear out quickly. While digital technology, automation, and analytics can move P&P away from this “brute-force” roots, like many manufacturing fields, P&P faces new and additional challenges when incorporating IT into its operational technology (OT).  For example, one of the main challenges stemming from the addition of new technologies, like the Internet of Things (IoT), is the added data and complexity that ultimately slows production and often creates operational confusion.  The P&P process is multi-variant, that is, there are numerous steps to go from raw wood to finished product, and each step has its own process, with its own performance characteristics, tolerances, etc. Operators and engineers, though, often look at each step on its own. For instance, if I’m running a digester, it’s just from raw wood to pulp. Yet from an organizational perspective, the view leaders often need goes from raw wood to final sellable product. The result is a much larger, more complex process than users often see or plan for. Another challenge in this industry is the fact that many, long-established industrial companies, including pulp and paper, don’t necessarily have all the data they need to crunch through multi-variant analyses. This come from a history where plants were all standalone and not connected to any main system for a long time.  Step One: Open the Data Envelope Companies that lack the data they need to improve operations need to start by capturing the data for future analytics. Finding the disparate data sources and utilizing the proper data management is essential for any integration of technology, to bring innovation to a digital transformation effort. If you do have the data, you want to use multi-variant analytics to remove the impact of time from the process – remove time from troubleshooting, or remove time from dwell times, for instance. It may be in small segments, but anything that shortens the manufacturing process is a gain. Then the same kind of multi-variant analytics can be applied to each step of the end-to-end process, for instance during mechanical pulping and chemical pulping, to identify where small incremental improvements are possible. With this caveat: each time one small piece of the process is adjusted and improved, it is likely to create new bottlenecks, upstream and/or downstream. If the pulping process is streamlined, just a little bit, then more wood needs to be brought in (upstream) and/or more capacity is needed at the cleaning stage (downstream).  Partnering with an organization like Radix that shares a deep history in Pulp and Paper helps address these and other challenges. Radix provides data-driven guidance to execute these small adjustments, identify their ripple effects, and find the adjustments that are needed to smooth out those ripples. Radix can also help align all stakeholders - from senior leaders who need to be aware of the data insights and optimization results to better act on the information, to plant managers who need to make data-driven decisions and work with the operations team and the maintenance team to improve data-driven decisions.  You have to open up the data envelope, have it accessible to everyone with a role in the end-to-end process, not build it into a cloud where very few people have access to it. To learn more about how Radix is leveraging data to drive operational value for our customers visit www.radixeng.com .

A Suite of Predictive Maintenance Software Tools for FPSOs/FPUs Radix Engineering and Software and Shape are collaborating at both a strategic and tactical level with a mutual goal to sustain cash flow certainty and mitigate EHS impact for our FPSO/FPU clients using state-of-the-art digital innovations. Currently, they are developing a unique software suite of predictive maintenance tools focused on client FPSO/FPU operations to optimize production and mitigate unplanned stoppages and downtime. The suite utilizes data contextualization and machine learning algorithms, plus embedded process, extensive mechanical engineering intelligence, and experience from actual FPSO/FPU operations. The unified operational experience is a differentiator. Specifically, Radix is applying FMEA (Failure Mode and Effect Analysis) methodology to FPSO/FPU operations, monitoring symptoms and signals that are frequently the first sign of potential failure. In parallel, Shape is providing data management tools to deliver a holistic view of the FPSOs’ maintenance status to the operators. This data helps determine KPIs and variables that must be monitored during operation to anticipate potential problems, better plan interventions, to reduce downtime, and maintenance costs, and extend equipment life. The next challenge is to map/model FPSO/FPU flaring systems with the goal being to predict potential process upsets and take corrective action to prevent flaring all in the pursuit of ZERO Flaring. “We are extremely honored to strengthen this relationship with Radix, a leading technology company. This new predictive maintenance tool reinforces our capacity to deliver meaningful bottom-line impact through the usage of data to top market players” said Henrique Domakoski, VP of Marketing and Sales at Shape. About Shape Digital Shape is a digital service provider for industrial companies that has a clear mission: To transform the way the industrial sector makes decisions through data and technology. Emerged from an initiative within MODEC focused on applying Machine Learning and Advanced Analytics tools for predictive maintenance solutions. Shape's solutions are unique in the market because they are highly customizable and scalable, they meet the specific needs of customers, and for using data from the entire plant to make inferences about their equipment. While typical solutions look at basic variables such as vibration and its harmonics, Shape goes beyond predictive models for insulated equipment, offering a scalable holistic predictive maintenance solution for the entire plant and its respective systems. To learn more, reach out to our experts: contact@radixeng.com.

Radix Engineering presented solutions for industrial digitalization at Rio Oil & Gas. Radix’s consulting services combines traditional engineering and digital solutions to meet current and future energy challenges. Radix Congress Presentations Radix presented five presentations at the Rio Oil & Gas Congress: “Technical and economic feasibility study for digitalization and PoB (People On Board) reduction on an offshore asset” by Anderson Carvalho, Automation Engineer at Radix. “Benefits from the use of integrated simulators in the commissioning and operation activities of a FPSO” by Jose Ramos, Technical Leader at Radix. “Benefits of a centralized system for managing an FPSO’s assets” by Ricardo Scheid, Project Manager at Radix. “Benefits of data governance and abnormal condition models for asset management” by Mark Roose, Project Manager at Radix. “Artificial Intelligence – the Digital Revolution in Oil & Gas” by Geraldo Rochocz, CTO and Founder Partner at Radix. Academic Competition The show will host a student competition for young people in the Engineering and Technology areas, to stimulate interest and participation in the O&G field and recognize excellence. The Competition is co-sponsored by the Brazilian Oil & Gas Institute (IBP) and Petrobras, with Radix organizing. This project also has technical support from SBM Offshore and Shell Brazil. In addition of a cash prize, the winning team will have the opportunity to do an internship with Radix. About Radix Engineering & Software Founded in 2010, Radix Engineering & Software (www.radixeng.com) is a privately held, global engineering, software, and Industrial ET/OT/ IT Consulting company. Radix provides technology-based solutions to industrial (O&G, Chemicals, Power, Metals & Mining, Pulp & Paper, Food & Beverage) and non-industrial (Transportation, Education, Health Care, Financial, Entertainment) customers. Radix’ North American headquarters is in Houston, TX, with offices also in Atlanta GA. The global HQ is in Rio de Janeiro, Brazil, with offices also in São Paulo and Belo Horizonte. With strong focus on results, people, and long-term relationships, Radix has developed projects in more than 20 countries worldwide. To learn more, reach out to our experts at contact@radixeng.com.