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Seeq Team
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  1. 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
  2. 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 s
  3. 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
  4. 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
  5. 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
  6. 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
  7. 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
  8. 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,”
  9. 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
  10. 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
  11. 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.
  12. 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
  13. 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
  14. 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
  15. 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
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