ABOUT SEEQ

Seeq® is an advanced analytics solution for process manufacturing data that enables organizations to rapidly investigate and share insights from data in historians, IIoT platforms, and database web services—as well as contextual data in manufacturing and business systems. Seeq’s extensive support for time series data and its inherent challenges enables organizations to derive more value from data already collected by accelerating analytics, publishing, and decision making. With diagnostic, monitoring, and predictive analytics powered by innovations in big data and machine learning technologies, Seeq’s advanced analytics solutions help organizations turn data into insights to drive process improvement and increase profitability. 

 

 
5 Questions To Ask Before Selecting A Process Data Analytics Solution   Leveraging Predictive Analytics: A Case Study    

5 Questions To Ask Before Selecting A Process Data Analytics Solution

 

Leveraging Predictive Analytics: A Case Study

 

 

FEATURED PRODUCTS

Organizer is Seeq’s application for engineers and managers to assemble and distribute Seeq analyses as reports, dashboards, and web pages.

Workbench is Seeq’s application for engineers engaged in diagnostic, descriptive, and predictive analytics with process manufacturing data.

VIDEOS

Across water and wastewater organizations, engineering decisions are too often made based on subjective judgements. Considering how inexpensive and easy modern automation makes it to generate and collect massive amounts of process data, the propensity to make decisions by gut feel may seem far-fetched to a bystander. For plant personnel, however, the struggle to improve upon instinct is often all too real.

Learn how to leverage data to implement proactive approaches to manufacturing issues through the use of predictive analytics.

SEEQ WEBINARS

View this on-demand webinar to learn how advanced analytics applications help pharmaceutical and life sciences companies integrate and investigate important data for improved decision-making.

Improve pharmaceutical technical transfer and accelerate product approval.

CONTACT INFORMATION

Seeq Corporation

1301 2nd Avenue Suite 2850

Seattle, WA 98101

UNITED STATES

SEEQ SOCIAL MEDIA

        

FEATURED ARTICLES

  • Seeq Corporation, a leader in manufacturing and industrial internet of things advanced analytics software, announced today its gold level sponsorship in the Amazon Web Services, Inc. (AWS) booth at Hannover Messe, the world’s foremost trade fair for industrial technology, in Hannover, Germany from May 30-June 2, 2022.

  • Seeq Corporation, a leader in manufacturing and industrial internet of things advanced analytics software, announced today its gold level sponsorship of AVEVA PI World, the largest annual gathering of AVEVA customers and partners in the world. Seeq will present and exhibit at the event in Amsterdam from May 16-19, 2022.

  • Seeq Corporation, a leader in manufacturing and industrial internet of things advanced analytics software, launched Conneqt, the company's expanded global industry conference designed for manufacturing leaders to explore the latest innovations in advanced industrial analytics. From May 2-4, 2022, in Austin, Texas, Conneqt brought together a community of Seeq customers, partners, and experts in a fully immersive experience that provided access to transformative business trends, use cases, and proactive conversations through a series of interactive sessions.

  • Seeq Corporation, a leader in manufacturing and industrial internet of things advanced analytics software, today announced its 2021 Reseller and Service Partners of the Year. These partners have been selected for their excellence in providing value to customers, their continued investments in technical expertise with their Seeq-certified employees and training professionals, and for creating awareness of Seeq through collaboration in marketing activities and events.

  • Seeq Corporation, a leader in manufacturing and Industrial Internet of Things (IIoT) advanced analytics software, announced today that it has achieved Amazon Web Services, Inc. (AWS) Energy Competency status. This designation recognizes that Seeq has demonstrated deep expertise helping customers leverage AWS cloud technology to transform complex systems and accelerate the transition to a sustainable energy future.

  • Seeq Corporation, a leader in manufacturing and Industrial Internet of Things (IIoT) advanced analytics software, announced today that the company’s board of directors has appointed former chief operating officer Dr. Lisa J. Graham, PE as chief executive officer, effective immediately. Former CEO and co-founder Steve Sliwa will remain at Seeq in an advisory role as vice chairman and co-founder. Seeq also appointed Ashley Kramer to the company’s board of directors.

  • Seeq Corporation, a leader in manufacturing and Industrial Internet of Things advanced analytics software, announced today additional integration support for Microsoft Azure Machine Learning. This new Seeq Azure Add-on, announced at Microsoft Ignite 2021, an annual conference for developers and IT professionals hosted by Microsoft, enables process manufacturing organizations to deploy machine learning models from Azure Machine Learning as Add-ons in Seeq Workbench. The result is machine learning algorithms and innovations developed by IT departments can be operationalized so frontline OT employees can enhance their decision making and improve production, sustainability indicators, and business outcomes.

  • Seeq Corporation, a leader in manufacturing and Industrial Internet of Things (IIoT) advanced analytics software, announces the expansion of its efforts to integrate machine learning algorithms into Seeq applications. These improvements will enable organizations to operationalize their data science investments, and their open source and third-party machine learning algorithms, for easy access by front-line employees.

  • Improving the collection and analysis of the data a drug manufacturer produces is key to driving innovation. Novel technology solutions safeguard scale up and optimize processes.

  • Across water and wastewater organizations, engineering decisions are too often made based on subjective judgements. Considering how inexpensive and easy modern automation makes it to generate and collect massive amounts of process data, the propensity to make decisions by gut feel may seem far-fetched to a bystander. For plant personnel, however, the struggle to improve upon instinct is often all too real.

  • Learn how to leverage data to implement proactive approaches to manufacturing issues through the use of predictive analytics.

  • In batch processing operations, numerous concurrent and independent steps can lead to bottlenecks, causing a process pause as downstream operations finish before preceding steps can move forward. 

  • At many process manufacturing operations, bearings fail exponentially and with little notice, leading to downtime that can become expensive and making scheduled maintenance difficult. System interdependence often means that a failure of one bearing results in the subsequent failure of other system bearings. Being able to prepare for and prevent the first bearing failure can reduce the costly and harmful effects of unplanned bearing failures.

  • Seeq Corporation, a leader in manufacturing and Industrial Internet of Things (IIoT) advanced analytics software, announced today it has closed a $50 million Series C funding round, led by global venture capital and private equity firm Insight Partners. The round includes participation from existing investors Altira Group, Chevron Technology Ventures, Cisco Investments, Saudi Aramco Energy Ventures, and Second Avenue Partners. This round brings Seeq’s total funding since inception to approximately $115 million.

  • Manufacturing sites can have hundreds, or even thousands, of automatic controllers, but most sites don’t have insight into how these controllers are actually performing. 

  • Seeq Corporation, a leader in manufacturing and industrial internet of things (IIoT) advanced analytics software, announces a new packaging of Seeq features and applications as Seeq Team and Seeq Enterprise editions.

  • There are several challenges to effectively analyzing CIP operations. Seeq Tools help create a process model that can be applied across cleaning circuits and amended with circuit-specific data.

  • This use case demonstrates a solution that empowers users by connecting to all relevant data sources to visually represent batches and perform analytics with process data.

  • Abbott’s nutrition business manufactures a wide variety of science-based nutrition products. Here we review how the company uses Big Data and analytics to improve manufacturing productivity.

  • How a biotech captured quality and yield of chromatography peaks and created the ability to share column integrity, process yield, and quality metrics throughout the organization in near real-time.

  • Seeq helps users to save time and increase efficiency with a tool that allows users to identify a statistically good control scheme based on the actual process variable and to detect deviations.

  • Batch manufacturing of chemicals entails many distinct phases. Learn how one developer overcame its struggle to analyze batch phase times for process improvement. 

  • A large molecule pharmaceutical manufacturer was struggling to predict batch quality results in near real-time. The solution created a better way to predict batch quality and enabling process optimization.

  • How Seeq allows navigation to past production runs to find past production settings and visibility into the relationship between the production settings and key process KPIs, like quality or production rate.

  • All manufacturing industries suffer a variety of different performance losses including production losses, product quality losses, energy losses, raw materials losses, environmental/regulatory losses and others. These losses can negatively impact profitability, environmental stewardship, and even license to operate. A manufacturer needed a way to gain insight into the leading causes of production losses, finding those times when equipment was not running at capacity and categorizing the loss by reason. 

  • Increased visibility into unproductive process time is necessary to reduce inefficiencies. With the ability to increase production opportunities when reducing waiting times, overall profitability can also increase. 

  • It is important for IT professionals to support the efforts of driving operational excellence to improve quality and safety in production operations. 

     

     

  • Seeq Corporation, a leader in manufacturing and industrial internet of things (IIoT) advanced analytics software, and an AWS Industry Software Competency Partner, announces expanded support for Amazon Web Services cloud services.

  • Looking at the human aspect of Pharma 4.0 may be the most crucial part of how you ready yourself and your teams to take full advantage of industry 4.0-based manufacturing concepts.

  • The need to analyze data more quickly with continuous manufacturing requires a robust data collection and integration strategy across your entire organization.

  • For clinical or commercial-scale manufacturing in the pharmaceutical and biotech industries, just finding the right data to analyze can consume significantly more time than it does to perform the analysis. 

  • Digitization offers the promise to connect everything on the plant floor but will also bring challenges such as storing, capturing, contextualizing, visualizing and analyzing the tremendous volumes of data. 

  • This pharmaceutical manafacturer's goal was to minimize the traditional scale-up challenges when moving from pilot production to commercial manufacturing. Read how they are utilizing the OSIsoft PI System data infrastructure and piloting Seeq’s analytics to optimize its product and processes to support continuous manufacturing.

  • During a commercial campaign, a small-molecule pharmaceutical company needed to investigate the cause of crystallization deviations at the end of its batch processing. The manufacturer’s engineering team was experiencing difficulty in trying to get to the root of the problem using spreadsheets. By implementing a root cause analysis to determine the changes that might explain the circumstances surrounding the slow-filtering batch they were able to dramatically shorten the analysis time for the engineering team through integrative calculations and data analytics.

  • A pharmaceutical company was finding it difficult to aggregate data and perform analytics across multiple assets, as well as monitor KPIs for continuous pharmaceutical processes in near real time. 

  • A major pharmaceutical manufacturer needed to improve the QbD modeling process it used in R&D, enabling it to avoid failed batches and deviations in production. A solution allowed them to analyze a continuous pharmaceutical drug product wet granulation step with a Design of Experiments (DOE) to determine a multivariate QbD process model. The goal was to apply the multivariate design space to commercial production for process monitoring and identification of deviations.

  • A pharmaceutical company was better able to meet clinical timelines by combining lab and pilot plant data to visualize trends and perform advanced analytics resulting in faster process development.

  • The data generation and collection strategies at the center of manufacturing processes have evolved dramatically, especially in recent years. Process manufacturers now collect and store huge volumes of data throughout their operations, both on and off premise, across multiple geographic locations, in an increasing number of separate data silos. In this paper, we propose five questions we believe every process manufacturing buyer should ask when evaluating a data analytics solution.