Where is your company in its digital journey? Whether you are just creating a foundation or actively deploying digital technologies, we have a workshop for you. The Connected Plant Conference will kick off the event with two simultaneous one-hour digitalization workshops with CPC Advisory Committee members. One workshop will focus on the foundational discussions needed to initiate the process of taking advantage of available digitalization technologies. The other workshop is for companies that are further along in the digital journey. In it, committee members and attendees will share lessons learned to enable progress in the digital journey.

This workshop is designed to introduce those less-versed in the concepts of industrial digitalization to the sessions offered throughout the conference, and to help you answer the following questions: • What business or technical problem are you looking to address using digitalization technologies? • How do you progress from identifying the problem to applying tools to solve it? • What data do you need to gather and how do you ensure that data will be of adequate quality?

In this session, industry leaders will share the challenges and lessons learned from their experiences with digitalization initiatives. By discussing real-world projects with others with direct experience, attendees can gain perspective on how to take the next steps in their own digitalization journey. The objective of the workshop is to help attendees strategize how to move past the testing and piloting phase to deploying digitalization tools at scales that achieve real business results. Speakers will discuss strategy versus tactical integration planning. Also addressed: How to make sound decisions about which projects to scale up and which to abandon. The distinction between “products” and “projects” will be explored.

• Dr. Yves Gorat Stommel, Head of Cognitive Solutions, Evonik Digital
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  Yves Gorat Stommel

  Head of Cognitive Solutions

  Evonik Digital

  

  Yves Gorat Stommel is currently working as the head of the Cognitive Solutions team, with a strong focus on setting-up and implementing a comprehensive, company-wide Artificial Intelligence and data analysis strategy. In his current function, Yves’ motivation stems from bringing together people, technology and positive change. By continuously questioning, improving and re-imagining operational and business processes – amongst others by looking at the company through the new “lens” of enabling and disruptive Artificial Intelligence – value is created for both the company and its employees. This does not only require identifying, benchmarking and implementing best practices, but more importantly targeted communication, linking knowledge and an emphasis on global instead of local mindsets and approaches.

• Cheryl Ingstad, Director, Office of Artificial Intelligence & Technology Office, US DOE
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  Cheryl Ingstad

  Director, Office of Artificial Intelligence & Technology Office

  US DOE

  

  Cheryl Ingstad serves as the Director of the Artificial Intelligence & Technology Office (AITO) for the Department of Energy (DOE). AITO was created on September 5, 2019, to serve as the central body responsible for the development, coordination and application of Artificial Intelligence, building upon the Department of Energy’s capabilities as a world-leading enterprise in scientific discovery and technological innovation. Ingstad comes to DOE from 3M Company, where she led critical commercialization efforts in AI/Machine Learning research and development. Before 3M, Ingstad was an early leader in the Defense Intelligence Agency’s Information Operations Branch. Ingstad holds a MA in International Economics and International Relations from Johns Hopkins University’s School of Advanced International Studies, and a BS from Georgetown University. She is also a graduate of the US Army Signal Officer Basic Course and the US Army Intelligence Analysis Course.

All industry sectors suffered significant disruptions in 2020, from stringent public health countermeasures that required remote work on a widespread basis, to supply chain challenges and slumping end-use markets. This session, formatted as an expert panel discussion, will feature plant managers from different sectors of the CPI and power generation industries. The experts will share key takeaways about why and how they tackled digital adoption during a global pandemic. Topics of discussion will include: remote operation needs; pandemic-related supply-chain disruptions; cybersecurity concerns; and other pandemic on digitalization efforts.

Digitalization and Industry 4.0 are as much about humans as they are about digital technologies. Understanding how humans interact and use technology are just as important as the technology’s attributes. This session will explore how equipment experts can integrate capabilities with data scientists; where wearable technologies are best suited; and how digital professionals can garner support and buy-in for digital initiatives. It will also explore how job profiles could shift in the future.

• Walter Curley, *Invited, Senior Engineer - Continuous Improvement, Nova Scotia Power
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  Walter Curley

  Senior Engineer - Continuous Improvement

  Nova Scotia Power

  
• Luis Ruano, Technical Commercial Engineer, Beyond Limits
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  Luis Ruano

  Technical Commercial Engineer

  Beyond Limits

  

  Luis Ruano is a Technical Commercial Engineer at Beyond Limits with a background in chemical engineering. Prior to joining Beyond Limits, an industrial AI technology company, supported clients in the Oil & Gas industry by strategically analyzing their needs and discovering opportunities to help them implement AI solutions that will generate the greatest value by addressing their most pressing problems. As a technical product expert, Luis consults with clients to identify areas that are ripe for disruption and a good fit for Beyond Limits’ suite of solutions to maximize efficiency and transform workflows. Luis has also spearheaded the digital transformation development for a multinational oil and gas corporation, as well as worked as an offshore maintenance and production engineer in the Gulf of Mexico. Luis received his bachelor’s degree in Chemical Engineering from Brigham Young University.
• Paul Simmons, *Invited, Maintenance Superintendent, Phillips 66 - Lake Charles Refienry
  Digital Tools for Workers

  Digital Tools for Workers

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  Paul Simmons

  Maintenance Superintendent

  Phillips 66 - Lake Charles Refienry

  

Digitalization’s most prominent value in the power sector is perhaps its ability to boost an entity’s competitiveness while keeping it in step with customer and stakeholder expectations. This session will break down how different technologies and their implementation can help achieve real business value.

• Angela Langner-Thiele, Digital Strategist, Evonik Industries
  Tools Alone Do Not Create Value: Technology Acceptance at Evonik

  Tools Alone Do Not Create Value: Technology Acceptance at Evonik

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  Angela Langner-Thiele

  Digital Strategist

  Evonik Industries

  
• James Martin, Global Operational Excellence Manager, Allnex USA
  Driving Energy Efficiency with Advanced Analytics

  Driving Energy Efficiency with Advanced Analytics

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  Many manufacturers list sustainability as one of their main corporate objectives. These companies that optimizing their processes to reduce energy consumption and waste gives them a significant competitive advantage. However, identifying opportunities for continuous improvement in this area is difficult, as process engineers often do not have the advanced analytics applications required to investigate their process in a rapid, in-depth way. It is extremely difficult for plant engineers to eliminate waste and improve efficiency when they spend most of their analytics time sifting through time series data in spreadsheets. One analytical technique that engineers can use to improve energy efficiency is through energy modeling. In a process plant, there are hundreds of items of equipment that contribute to the total energy use. Sensor data from this equipment are stored in time series data historians. Subject matter experts (SMEs) can use this data to build predictive models of total energy consumption using each individual item’s sensor data as inputs. With this method, they can determine if each piece of equipment is operating efficiently based on the coefficients in the model. Using traditional analytics tools like spreadsheets, energy models are difficult to build and maintain, and they quickly become outdated and obsolete. Companies like Allnex, however, use Seeq Workbench’s Prediction Tool to construct energy models that they use to decrease their total energy consumption with minimal capital expense. In addition, Allnex engineers operationalize these models by building monitoring dashboards in Seeq Organizer Topic to detect, in near real time, if energy use is deviates from the model. Compared to the hundreds of hours required to build energy models with spreadsheets, the engineers at Allnex have used the Seeq to build and monitor energy models in significantly less time.
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  James Martin

  Global Operational Excellence Manager

  Allnex USA

  

Viewing “data as an asset” is becoming the new industry norm and companies are beginning to invest heavily in digital tools and technologies to help them leverage their data to generate valuable business insights. However, the value generated from that data is often limited by poor data quality, thereby greatly reducing the return on investment to the business. With the growing need to integrate data across different systems—both internal and external—and the expanding enterprise value chain, the need for trusted high-quality data is greater than ever before. This session will explore real-world pitfalls in data collection and review data management best practices.

• Naimi Mattos Nassiffe Souza, *Invited, Braskem
  PIMs Connectivity Where We Connected All Industrial Data To The Cloud Using Osi Solution

  PIMs Connectivity Where We Connected All Industrial Data To The Cloud Using Osi Solution

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  Naimi Mattos Nassiffe Souza

  Braskem

  
• Chris Welch, *Invited, Enterprise Improvement, Tennessee Valley Authority (TVA)
  • Sensors That Provide Real Quality Information and Proper Connectivity

  • Sensors That Provide Real Quality Information and Proper Connectivity

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  Chris Welch

  Enterprise Improvement

  Tennessee Valley Authority (TVA)

  

  I’ve been involved in some fantastic projects over the years. They tend to be bleeding edge technologies, which is a blast! Wired networks, wireless networks, servers, and everything in between are my modus operandi. My goals in life include solving problems with new technologies, and using technology to make a difference in the lives of those around me. Specialties: My specialties include engineering solutions, and translating between those who speak technology and those who need it. I love to build strong/passionate teams that can reach the moon and beyond. Come to us with your problems, and we will solve them. Recent Projects: Industrial sensors (IIoT), non-ip based wireless communications, machine learning, AI, robotics, hybrid manufacturing, and changing the world bits at a time. Putting the techy stuff aside for a bit, my other passion is developing leadership and making connections between amazing people. Taking advantage of my experiences from a broad range of fields, I have been able to leverage my time around some very different thinkers. I like to share those thinking styles to others over discussions and sessions while we develop ideas and solutions. I cannot think of anything that is more fun than that at work.
• Gabe Prado, PRODUCT MARKETING DIRECTOR, POWER & UTILITIES, Cognite
  IT/OT Data Contextualization: The Key to Delivering the Connected Plant

  IT/OT Data Contextualization: The Key to Delivering the Connected Plant

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  With the rise of data engineers, citizen data scientists, and other industrial data consumer roles, why is it still that only a fraction of all industrial data created actually gets used to its full potential? The bottleneck lies in not having automation in the high-overhead process of finding meaningful data relationships in big data. This is difficult enough for homogenous data sets with thousands of variables but is significantly more challenging when mapping relationships between disparate data sources and formats in IT (ERP, work orders) and OT (asset time series, P&IDs) domains. When done well, contextualization approximates a significant amount of industrial subject-matter expertise and empowers data consumers and the digital applications that deliver operational value. When done poorly, data continues to go unused, consumers lose trust in the data they have to work with, and new applications struggle to get momentum and adoption. The good news is that emerging technology and automation is improving the process of contextualizing data from around the organization and setting up dashboarding, analytics, and machine learning applications for operationalized deployment and scale. This Connected Plant session will define and demo how data contextualization works across IT and OT data silos and explore the variety of nontraditional data sources like 3D visualizations that can be contextualized as a result. Then we’ll examine a customer case study and lessons learned from the Oil and Gas industry where field operators were able to reduce wrench times by 50-70% because of the contextualized data served to them in a mobile application.
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  Gabe Prado

  PRODUCT MARKETING DIRECTOR, POWER & UTILITIES

  Cognite

  

  With eight years in the industrial test and measurement industry and two years working with energy customers to deploy ML and advanced analytics solutions, Gabe has seen firsthand the challenges that major industrial companies face when they can’t map the right data to their digital applications. At Cognite, he aims to help customers understand the challenges with their data infrastructure and identify how it can best be applied to solve problems across the Power & Utilities value chain.

Learning how to select the right automation technologies and software applications is crucial to any operations and maintenance project. This session will review data visibility software, automation, flexibility, and safety solutions through case studies.

• Isabelle Lacaille, Data Infrastructure Engineer, Lonza AG/Ltd
  Operations Data Visibility fuels Productivity at Lonza

  Operations Data Visibility fuels Productivity at Lonza

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  Chemical processing companies do not have to wait for advanced analytics to benefit from digitalization. Simply increasing operations visibility provides immediate and significant value. This was Lonza’s experience when implementing its own digitalization initiative, PIVOT (Productivity Improvements via Operations Technology). As a global company, Lonza had to adopt a strategy to support small, diverse production sites. One example was a chemical plant with less than 100 employees, facing a growing demand for its product. Lonza implemented a global data infrastructure using OSIsoft’s PI System, and put in place tools for data visualization and analysis such as SEEQ and Microsoft Power BI. The PI System allowed raw data from disparate systems (e.g. control systems, analytical instruments) to be combined and contextualized. Power BI presented an aggregated view of the data that could be filtered by batch, production line or production period of interest. SEEQ provided engineers with a powerful analytics tool to drill into raw data signals and uncover insights. With these tools, it became possible to track key performance indicators and anticipate production issues before they occurred, helping the site adopt a proactive approach to operations. Remote support groups were able to access the same data in real-time, and provide recommendations for process changes. These improvements yielded significant improvements in cost benefit and production volume for the plant. Increased operations visibility also enables advanced digitalization projects. The combination of analytical results with process data provided a clear picture of in-process samples for each batch. This allowed the team to identify a strong use case for on-line analytical instruments and model predictive control. The strong foundation of operations visibility at Lonza will fuel its digitalization roadmap for years to come.
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  Isabelle Lacaille

  Data Infrastructure Engineer

  Lonza AG/Ltd

  

  Isabelle is a Data Infrastructure Engineer at Lonza. She is a member of the Operations Technology group, which supports the Specialty Chemicals division. Prior to this, Isabelle was working as a Systems Engineer at OSIsoft, helping customers gain insights from their operations data. She holds a Master’s degree in Chemical Engineering from McGill University.

Technology innovation and software development are continuing at a bewildering pace. Emerging technologies hold much promise, but separating the hope from the hype can be challenging. In this session, attendees will hear from leading technology developers along with their end-users, about how they identified and implemented new technologies or how they developed novel applications for “tried and true” digitalization technologies.

• Misbah Syed, Data Scientist, Evonik Corporation
  Forecasting the concentration of chemical components in a production plant through AutoML

  Forecasting the concentration of chemical components in a production plant through AutoML

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  Misbah Syed

  Data Scientist

  Evonik Corporation

  

  Misbah has worked on applications of Advanced Process Controls and Machine Learning based predictive models in the chemical manufacturing industry. With background in Chemical Engineering, he augments theoretical process engineering with modern data driven approaches to optimize production processes.
• Gupreet Kainth, Principle Design Engineer, Cyient, Inc
  Multi-Objective Design Optimization of Hydro Generators using Genetic Algorithm

  Multi-Objective Design Optimization of Hydro Generators using Genetic Algorithm

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  Hydro generator design optimization poses an engineering problem constituting conflicting multi-objectives and constraints. Finding a techno-commercially competitive value proposition for the client by arriving at a design uniquely defined by a set of independent design variables (e.g. parameters related to magnetic core, rotor pole, stator & rotor winding etc.) is the challenge. The conventional design approaches have limitations of not adequately exploring the vast design/solution space and missing potential good solutions. An intelligent application to adequately address exploration in the multi-dimensional solution space has been developed by utilizing Genetic Algorithm (GA) in the design process. GAs are a branch of Artificial Intelligence and derivative-free equivalent of Reinforcement Learning. These are nature inspired evolutionary computations relying on Darwin’s principle of survival of the fittest and mimic the operations of natural selection, crossover, and mutation to evolve a population of solutions over generations. Being derivative free, GAs can operate on discontinuous and non-differentiable objective functions. This paper presents, the experience of software application development employing the advanced version of GA namely Non-Dominated Sorting Genetic Algorithm with elitist strategy (NSGA-II) for generator design optimization. The objectives of optimization include cost minimization and efficiency maximization while respecting associated constraints (e.g. temperature rises, transportation constraints, Inertia requirement etc.) The optimization application developed, within the purview of established synchronous generator design principles, caters to optimization tasks corresponding to a vast range of generator specifications. The optimization run delivers not one but a set of Pareto-Optimal solutions enabling stakeholders to make a choice. The choice empowers OEMs and power plant developers with enhanced flexibility in techno-commercial decision making. This application is being used by Hitachi Mitsubishi Hydro, Japan. A typical optimization run intelligently scans approximately 100,000 solutions in 6-7 hours. The methodology has potential for new insights and solutions for widespread applications in machinery and system design.
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  Gupreet Kainth

  Principle Design Engineer

  Cyient, Inc

  

  Is Principle Design Engineer at Cyient Limited, Hyderabad in Turbo Machinery Group. He received a Bachelor of Technology Degree in Mechanical Engineering from IIT Delhi in the year 2001. He has around 18 years of engineering design & management experience in Green Field & Brown Field projects while working with OEMs like Hitachi Mitsubishi Hydro, Japan; Voith Hydro, Austria; Alstom Power, India & BHEL, India with particular focus on Hydro Generators. Apart from core mechanical engineering experiences, he is an Optimization, Artificial Intelligence & Machine Learning enthusiast.
• Leslie Rittenberg, Refinery & Process Manufacturing Product Manager, Beyond Limits
  Machine Learning and AutoML

  Machine Learning and AutoML

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  Leslie Rittenberg

  Refinery & Process Manufacturing Product Manager

  Beyond Limits

  

  Leslie Rittenberg is the Refinery & Process Manufacturing Product Manager for Beyond Limits, an industrial-grade artificial intelligence technology company built for demanding sectors including energy and utilities. Leslie has over 30-years of experience in the Power and Oil & Gas industries. Prior to joining Beyond Limits, Leslie held leadership positions with a major O&G company for multiple refining assets as well as their Corporate Downstream Technology Center, where she led the development of their downstream manufacturing digital strategy. Leslie recently joined the Beyond Limits team that brings in a unique brand of Cognitive AI to solve complex business and operational problems in manufacturing settings such as refineries. Beyond Limits’ use cases go beyond conventional AI by incorporating and encoding human business reasoning in combination with live plant data to impact operational frontline decision making. Leslie holds an MBA and a degree in Chemical Engineering.
• Michael Fahrion, Chief Technology Officer, Advantech
  Open Nature of Edge Connectivity & Compute

  Open Nature of Edge Connectivity & Compute

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  Michael Fahrion

  Chief Technology Officer

  Advantech