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Marketing

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  1. Machine Learning (ML) is a top priority for most manufacturing organizations— and for good reason. Machine Learning models can simulate processes and predict outcomes, drive continuous improvement cycles, and enable manufacturers to proactively maintain and optimize equipment. That’s a big deal; it can mean millions of dollars in savings and efficiencies in a short amount of time. However, leveraging Machine Learning in manufacturing settings is not as simple as finding the right algorithm or hiring data scientists. The engineers and plant operations personnel that understand their processes and the associated sensor data are critical participants in any effort to apply ML in an industrial context. They’re the folks that must understand and trust the predictions. They will want to carefully vet changes and then verify results. In these scenarios, Information Technology (IT) personnel like sysadmins and data scientists bring the algorithms and software knowledge – often including programming skills. Operational Technology (OT) employees like chemical engineers and operations managers bring the real-world manufacturing and process knowledge. The last necessary piece is an environment where they can collaborate effectively. Otherwise, promising ML initiatives can end up as frustrating failures. Seeq provides key components to enable IT/OT teamwork for successful Machine Learning efforts: data access, cleansing and contextualization; algorithm development and iterative workflow; collaboration and knowledge capture; publishing of Machine Learning models with simple point-and-click, workflow-centric interfaces for the OT personnel; and now a rich ecosystem of community-based ML solutions for manufacturing environments via the Seeq Open Source Gallery. View the full article
  2. Process control engineers focus on optimizing the automatic control of the process operation, designing control strategies, specifying controller tuning, implementing advanced process control and real time optimization applications, and troubleshooting sources of abnormal process variation. In contrast to process engineers, control engineers focus much more on dynamic operational responses and signal trajectories. Control engineers often want to identify and analyze transient, non-steady modes of operation (e.g., setpoint ramps, startups, batch sequences, etc.)—for which Seeq’s extensive contextualization capabilities (capsules and conditions) were purposely built. Process engineers and control engineers typically work in different roles within the process automation pyramid. While they both derive analytics value from Seeq’s contextualization and calculation tools, there are several capabilities that control engineers can specifically utilize for their unique roles. View the full article
  3. For electric utility organizations, prioritizing maintenance and replacement strategies across fleets of complex assets is critical to avoiding costly downtime. But without the right combination of subject matter expertise, data connectivity, and analytics tools, these organizations are left with a number of questions and roadblocks. View the full article
  4. Technology investments, regardless of industry, come with risk, and startup investments are often met with even more hesitation. While startups promise to bring greater innovation, major organizations fear these young, unestablished companies could bring even greater risk to mission-critical projects. View the full article
  5. Facilities large and small rely on machinery (rotating equipment) to make their operations tick. Reliable and efficient machinery operation is instrumental in ensuring facilities meet their safety, environmental, and production targets. World-class machinery performance is the result of good design practices, effective and skilled maintenance, and operation within appropriate design conditions (which, depending on operating requirements, can be challenging). View the full article
  6. For many years, finding insights in data using analytics—and data collection and storage strategy—have been considered a package deal. This is because operations data is often siloed, has limited analytics options, and is in difficult-to-reach places. As a result, some companies embark on huge data strategy and migration efforts, often lasting months or even years. They believe data must be centralized to begin extracting value with advanced analytics technologies. And in the meantime, companies miss out on valuable insights that can optimize assets and processes, minimize waste, and prevent incidents. View the full article
  7. Sustainability is critical to the health and survival of our planet, and now, more than ever, companies are prioritizing it as part of corporate social responsibility initiatives. According to a recent McKinsey survey, more than 50 percent of executives believe sustainability is very or extremely important for brand reputation and overarching corporate strategies. Unfortunately, only 30 percent of those executives believe their companies actively invest in sustainability or have implemented measures to reach goals. While many companies set goals, the ability to affect change often fails to trickle down the front-line employees who can make the most difference. View the full article
  8. In the process manufacturing world, there’s been a significant increase in the accessibility into operational and equipment data. Teams now have visibility into both historical and near real-time data from their operation, and can even monitor this as it’s happening at remote locations. But the problem with this is that teams are drowning in data—”DRIP”—data rich, information poor. View the full article
  9. When I graduated with a degree in chemical engineering, I was excited to join the workforce and make a positive contribution. Being part of different engineering teams at various companies made me believe that mining the many years’ worth of big data stored in the process manufacturing historians could be a gamechanger. There were many opportunities to contribute to sustainability, reliability, and profit maximization goals that would result in happier customers and a more environmentally responsible industry. View the full article
  10. Seeq began offering our advanced analytics applications as Software-as-a-Service (SaaS) in 2018. SaaS offers many benefits to end users including higher performance, better supportability, and lower overall costs. However, there can be a perceived risk associated with SaaS offerings because end user data is in the cloud on computing resources managed by a vendor. The “Security, Availability, Processing Integrity, Confidentiality, and Privacy” of customer data largely depends on the controls used to operate both the vendor’s organization and specifically the controls used to operate the SaaS service. View the full article
  11. Seeq recently conducted a poll of chemical industry professionals—process engineers, mechanical and reliability engineers, production managers, chemists, research professionals, and others—to get their take on the state of data analytics and digitalization. Some of the responses confirmed behaviors we’ve witnessed first-hand in recent years: the challenges of organizational silos and workflow inefficiencies, and a common set of high-value use cases across organizations. Other responses surprised us, read on to see why. View the full article
  12. In batch processing operations, the combination of numerous concurrent and independent steps can lead to bottlenecks, causing the process to pause and wait for a downstream operation to finish before the preceding steps can move forward. This introduces latent time to the cycle and lengthens the time required to complete each batch. View the full article
  13. Data integrity is of prime importance to companies in the process industries because data is valuable and therefore must be managed and protected. This encompasses information security (infosec), which considers issues like authentication and authorization to ensure that only the right people can get into the system and see the proper data. View the full article
  14. Things of quality have no fear of time. - Author Unknown There’s this thing that crisis does. It makes us reevaluate, think about what brought us to this point and what can we do about it. It’s an opportunity to reset, reframe, and redefine what’s possible. Crisis activates disruption which sets the stage for innovation, the next act. View the full article
  15. Seeq customers know Seeq drives significant value for their organizations and they also know the ROI of their time spent using Seeq is quite high. However, simply finding time to develop high value insights using Seeq can be challenging because process engineers are so busy running their plants. View the full article
  16. Earlier this month (November 2020 ) I was honored to be asked to present at the American Fuel and Petrochemicals Manufacturers Women in Industry event and speak to over 100 attendees on leading during uncertain times. My talk focused on what I believe are key leadership themes and what those look like when a crisis strikes. These types of crises will stretch and grow us, forcing us to make choices we never thought we’d be faced with, while determining the types of leaders we want to become. When I asked the group what they think when they hear the phrase “leadership in times of uncertainty,” many used words like listening, empathy, communication, and inspiring. As women, we are leaders in our industries, communities, education, and family lives. Each of these areas of life are different, yet we have the ability to listen, empathize, communicate, and inspire in every single one. The group was spot on in identifying these skills as the cornerstone of how we lead through any challenge. Now, we must lean on those abilities more than ever while taking risks, building a healthy network, and communicating to drive alignment. The first topic we explored was taking risks. When I asked the group what they picture when they hear the word risk, many said failure, danger, reward, opportunity, being vulnerable, and potential mistakes. All of these are true, and more than one can be true at the same time. We’ve all taken risks, for better or worse, and we’ve all failed. However, by taking those risks we acquired new skills and experiences, preparing us for leading in a crisis. Calculated risk taking is actually the foundation of a good leader. When we look back at our lives, it’s clear we’ve all taken a series of risks to get to where we are today. We went out and got an education to enable us to succeed in traditionally male-dominated fields. We chose jobs that would give us the experience we wanted to reach career goals. All throughout this journey we’ve shared our ideas, and there is certainly risk in that. Beyond sharing what we think, we also navigate day-to-day risks, such as where we sit in a meeting and when we speak. I took a risk by coming to Seeq and growing the analytic engineering team. One of my goals has always been to encourage my team members to freely share their ideas. That has proved to be an effective strategy as we’ve navigated the COVID-19 pandemic. When travel came to a screeching halt, we were forced to pivot our entire training model. My team sprang into action to create an incredible virtual training setup, enabling Seeq to reach our customers anywhere in the world, while accommodating their different learning styles. It was absolutely a risk, but we had to try—and our efforts netted success. We are on pace to complete just over 300 virtual trainings by the end of the year, with 50-100 attendees per session. Another key element of leading during uncertainty is networking. While most people think of networking in the context of a social event, this type of networking is based on trust and energy. That is imperative for leading during a crisis. So how do we build the type of network that goes beyond swapping business cards? It’s not easy and, when asked, many in the group said the hardest part is following up, keeping up with relationships, and interactions feeling forced. However, when we shift our mentality to focus on building trust and energy, we take the long view. Trust only evolves with time—from initiating a relationship, to developing and sustaining it. We build that trust by doing what we say we will do and showing that we have the best interest of everyone on the team in mind. One of the best ways we can network to build trust is to be an energizer. Energizers create enthusiasm in part because they engage in a set of foundational behaviors that build trust. Energizers approach situations with a clear head, giving them endurance to lead. When you interact with an energizer, try not to worry that you will be judged, dismissed, or devalued. Without fear of rejection, it’s easier to share fledgling ideas or novel plans—to innovate, take risks, and think big. Energizers create trust, but trust isn’t all that they create. The real power of energizers is that they enable others to realize their full potential. While taking risks and networking to build trust and energy are critical to leading during uncertainty, ultimate success hinges on combining these endeavors with effective communication and leading by example. We must align our teams (and our customers!) towards a common goal so we can make efficient and effective progress. In addition, we must be willing to take the risk of putting our own ideas out there for all the world to see. After all, in every crisis there is an opportunity to consider new and exciting ideas to pave new paths, elevate team members, and reap the rewards of hard work and ingenuity. Many thanks to each and every woman who participated in the AFPM Women in Industry event. Your feedback and willingness to engage in discussion made the risk I took to speak pay off. The organizers did a fantastic job and it was a terrific experience overall. I am grateful for the opportunity and I can’t wait to see the impact each of you will have on your teams, your companies, and the industry as a whole. View the full article
  17. In the process industries, manufacturing requirements for an individual company can vary significantly over time due to lengthy research and development timelines and differences in market demand compared to forecasts. In pharmaceuticals, for example, companies may not have the capital or desire to invest in and build a manufacturing plant for their products as their expertise lies in research and development. Whether a smaller biotech or a large-scale producer, they must also contend with patent expirations on their most profitable drugs. These uncertainties for both big and small pharma have led to a significant increase in outsourcing of clinical and commercial manufacturing to contract manufacturing organizations or CMOs. While the pharmaceutical industry has seen a dramatic increase of projects being outsourced in recent years, contract manufacturing is also prevalent in many other industries including food and beverage, semiconductors, and upstream oil and gas. View the full article
  18. In the process industries, manufacturing requirements for an individual company can vary significantly over time due to lengthy research and development timelines and differences in market demand compared to forecasts. In pharmaceuticals, for example, companies may not have the capital or desire to invest in and build a manufacturing plant for their products as their expertise lies in research and development. Whether a smaller biotech or a large-scale producer, they must also contend with patent expirations on their most profitable drugs. These uncertainties for both big and small pharma have led to a significant increase in outsourcing of clinical and commercial manufacturing to contract manufacturing organizations or CMOs. While the pharmaceutical industry has seen a dramatic increase of projects being outsourced in recent years, contract manufacturing is also prevalent in many other industries including food and beverage, semiconductors, and upstream oil and gas. View the full article
  19. Dr. Margret Bauer is the Professor of Automation in the Faculty of Life Sciences at HAW Hamburg University in Germany, and she’s an expert in data-driven process monitoring. And Seeq is a leader in advanced analytics for manufacturing and is the analytics provider of choice for many leading companies in the oil & gas, pharmaceutical, chemical, and other process manufacturing sectors. Recently, Dr. Bauer and Seeq combined efforts to provide graduate students at Hamburg University of Applied Sciences with a hands-on experience in the critical skills of analytics in process manufacturing. View the full article
  20. Depending on the type of problem a subject matter expert (SME) is trying to solve, there are countless different ways they can monitor for changes in process data. As simple as it seems to look at data and identify a change in the way it is behaving, this methodology is not always straightforward due to the lack of advanced analytics capabilities in the engineering toolbox. View the full article
  21. Depending on the type of problem a subject matter expert (SME) is trying to solve, there are countless different ways they can monitor for changes in process data. As simple as it seems to look at data and identify a change in the way it is behaving, this methodology is not always straightforward due to the lack of advanced analytics capabilities in the engineering toolbox. View the full article
  22. If 2020 has proven anything, it is that agility and resilience are imperatives for process manufacturers. Demands on technology infrastructure, a critical enabler for business continuity, along with demands for data-driven operational decisions, are increasing rapidly. Add to this the expanding number of team members working from home, and you have a situation where the ability of IT organizations to support operational needs is being pushed to the limits of both capacity and capability. View the full article
  23. Lately, there’s been a lot of talk about data cleansing. But is it possible to clean your data too much? What does that even mean? Many engineers don’t even realize that they are cleaning their data and are just doing so because they are forced to by whatever tool they are using (i.e. to comply with Excel’s limit of 1,048,576 rows or because they are just used to seeing their data in a certain way). View the full article
  24. William Shakespeare once wrote, “...the readiness is all.” I think he was onto something... View the full article
  25. Many manufacturers today list sustainability as one of their main corporate objectives. These companies understand that “going green” is more than just a trendy catchphrase—they realize that optimizing their processes to reduce energy consumption and waste gives them a significant competitive advantage. View the full article
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