ABOUT SEEQ CORPORATION

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.

CONTACT INFORMATION

Seeq Corporation

1301 2nd Avenue Suite 2850

Seattle, WA 98101

UNITED STATES

Phone: 206-801-9339

Contact: Jennifer Bentzel

SEEQ SOCIAL MEDIA

        

FEATURED ARTICLES

  • Valve Health Diagnostics

    Valves are one of the most common assets in the process industry, spanning all verticals. Chemicals, refineries, and petrochemicals, however, will find improved valve health diagnostics useful for critical valves and controllers in their plants, while upstream and midstream oil and gas companies may be focused on much larger, critical valves like pipeline or subsea valves. Using Seeq, process manufacturers are able to implement a condition-based monitoring analysis to monitor valve health across an entire fleet. Engineers can utilize the historical data to accurately create a predictive maintenance forecast and preemptively detect valve failures before they occur.

  • Seeq For Operators - Find Production Settings

    Process operators are responsible for making production target settings when changing product grades. Typically, operators use a written logbook to record production settings, and when they make grade changes, they reference the logbook. While the logbook may contain information about finished product quality or other process KPIs, they do not get the full context about the last production run. Seeq for operators allows you to create conditions for the production runs of product grades. Easily navigate to past production runs to find past production settings. View the relationship between the production settings and key process KPIs, like quality or production rate.

  • Pump Health Monitoring

    In process industries such as oil and gas, pharmaceutical and chemical, it is essential to maintain and prolong the lifetime of critical assets including pumps, valves, heat exchangers and compressors. Process companies need better insight into the condition of pumps and other assets. The goal is to gain a clearer understanding of when pumps are not operating efficiently–and the root cause of the degraded performance–instead of waiting until there is a catastrophic failure. Optimizing asset maintenance saves time and money.

  • Loss Monitoring And Categorization

    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. 

  • Filter Membrane Predictive Maintenance

    At manufacturing operations using ultrafiltration systems, the ultrafiltration membranes are used for numerous batches without replacement, using Clean-In-Place (CIP) operations in between batches to maintain filter performance. However, ineffective CIP cycles or long-term fouling or degradation of the filter membrane can result in increased cycle times to move the desired amount of product through the filter, lost yield as the product is unable to permeate the filter, or poor product quality as membrane failure may occur.

  • Evaluation Of Operation Of Facility

    Highly-efficient and improved facility operations require the management of chemical and energy usage to ensure that both air and water quality meet goals while minimizing cost. It can be difficult to attain this level of productivity within a comfortable working environment while avoiding the excessive use of chemicals and energy. Excess chemical use and energy consumption mean reduced profits. Solutions are necessary to allow for maximum operation efficiency.

  • Asset Utilization (OEE) Monitoring

    In order to raise efficiency and production standards, it is important to be able to analyze the performance of batch processes and identify time spent in each of the different process phases. Increased visibility into unproductive process time (for example during cleaning and maintenance and shift v shift differences in manual re-cleaning events) is necessary in order to enable users to take actions to reduce them. With the ability to increase production opportunities when reducing waiting times, overall profitability can also increase. 

  • Enabling Engineers With Data Science

    Engineers and subject matter experts within operations settings are tasked with driving operational excellence to improve quality, safety, and throughput in production operations. The new technologies proliferating as part of Industry 4.0 initiatives are raising and expanding performance expectations. Rapid, data-driven insights are becoming critical to balance resiliency and agility with efficiency. As an IT professional, supporting these efforts is imperative as operations leaders grapple to get the most out of investments in technologies that generate and use large volumes of data.

  • Seeq Expands AWS Cloud Services Support To Encompass Amazon Timestream

    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.

  • Seeq Expands Support For Microsoft Cloud Services

    Seeq Corporation, a leader in manufacturing and industrial internet of things (IIoT) advanced analytics software, and 2020 Microsoft Partner of the Year Award finalist (Energy), announces expanded support for Microsoft Cloud services.

  • Seeq Recognized As A Finalist For Energy 2020 Microsoft Partner Of The Year

    Seeq Corporation, a leader in manufacturing and industrial internet of things (IIoT) advanced analytics software, today announced it has been named a finalist for the Energy 2020 Microsoft Partner of the Year Award.

  • Seeking Efficiency? Analytics Makes It Easy

    Despite the availability of advanced software, spreadsheets are still the default data analytics tool for operations managers at many municipal water systems and water distribution companies. However, an investment in analytics technology can pay for itself quickly by providing a relatively easy method to extract process data from various sources and then by performing an analysis to provide answers to previously difficult questions.

  • Seeq Wins Control Engineering 2020 Engineers’ Choice Award In Data Analytics Category

    Seeq Corporation is pleased to announce it is the winner of the Advanced Analytics for Process Manufacturing Data category award for Control Engineering 2020 Engineers’ Choice Awards program.

  • Advanced Analytics And Situational Awareness For Manufacturing Data

    Advanced analytics is a key innovation for digital transformation. While many industrial companies are rolling out pilots and enterprise analytics projects, it is important for users to understand the features and capabilities of the analytics offerings.

  • Seeq Announces Availability Of R22 And Beta Release Of Seeq Data Lab At ARC Industry Forum

    Seeq Corporation, a leader in manufacturing and Industrial Internet of Things (IIoT) advanced analytics software, announces availability of their latest release, R22, and beta availability of Seeq Data Lab, at the ARC Industry Forum 2020.

  • Seeq Corporation Announces AWS Industrial Software Competency Achievement

    Seeq Corporation, advanced analytics applications for process manufacturing data, announced today it has achieved Amazon Web Services (AWS) Industrial Software Competency status.

  • Water Treatment Filter Monitoring

    A municipal water utility follows a straightforward method for providing clean water to its residents: It pulls water out of a nearby river, filters out the impurities, and then funnels the water into a reservoir to be ready when residents turn on their taps. The water provider needed to improve sand filter consistency and boost performance of its overall fleet of filters in its water treatment plant. To do this, it needed to identify and monitor for poor filter performance while prioritizing filter maintenance.

  • Multi-Phase Flow Meter (MPFM) Analysis

    Multi-phase flow meters are important for well surveillance and production allocation where there is multiple ownership. It is therefore important to track the accuracy of multi-phase flow meters, identify issues and ensure rapid corrective action. Read more to learn how the Seeq tools were used to analyze and monitor performance.

  • Seeq And Amitec To Sponsor Ignite Conference

    Amitec, a leading system integrator in Norway, and Seeq, a provider of advanced analytics solutions, will jointly exhibit at the Ignite conference on June 12-13 in Oslo.

  • Knowledge Transfer For Water’s Better Informed Future

    Water industry managers are caught in a squeeze. On one hand, they need to capture institutional knowledge from long-term baby boomer employees before they retire. At the same time, they need to manage current operations optimally and attract and train next-generation replacements. Here is how advanced analytics solutions are making it easier to achieve all those goals while improving business outcomes.

  • How To Leverage Water Data To 'Make Your Case'

    Efficiently managing potable water treatment and distribution or wastewater collection and treatment involves many moving components, not the least of which are cost implications. If only there was a way to quantify and analyze those factors to leverage them for better decision-making. There are, and they reach far beyond tactical treatment plant adjustments, all the way up to strategic decisions as well.

  • Find More Insight In Your Deluge Of Water Data

    With the proliferation of new sensors and Industrial Internet of Things (IIoT) initiatives now feeding SCADA systems, water industry managers lament how they are drowning in a sea of data yet starving for insights that really matter. With concepts like data democratization starting to bear fruit, advanced analytical capabilities are creating new opportunities for water insights without requiring a degree in computer science.

  • Gas Processing Data Analysis From Afar

    Unmanned well sites in remote locations present operational challenges. Data must not only be collected, but it also must be monitored to uncover any discrepancies, and ideally predict any problems before they occur. Advanced analytics software, coupled with a sophisticated data collection system, can address these issues, and also provide additional benefits.

  • Adding Value With Analytics

    The oil and gas industry, like many others, is collecting and storing ever larger volumes of data. Although, there is value in this data, it is often difficult to unearth using conventional analysis tolls such as spreadsheets. To address this issue, new data analytics software platforms are being introduced specifically to deal with time-series data.

  • 5 Questions To Ask Before Selecting A Process Data Analytics Solution

    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.

  • Leveraging Predictive Analytics: A Case Study

    Often the first notification of a spill comes from a member of the public, hours and sometimes days after the first spill. This can intensify public health and environmental impacts and the cost of clean-up efforts. Following a sewer spill at an environmentally significant site at Midway Point in August 2017, TasWater sought a way to reduce the likelihood and impact of spill events occurring in the future.

  • Optimize Process Unit Results With Advanced Analytics For Condition-Based Monitoring

    Businesses rely on process units meeting or exceeding their operational plans. To ensure that operational plans are achieved, it is important that equipment operates as designed (i.e., delivers the required performance) and continues to operate in an optimum manner (i.e., remains reliable, in a good condition). The most common causes of missing operational plan targets are equipment failure, which results in unplanned downtime, and low quality or yields from production processes.

  • Industrial IoT-Enabled Remote Monitoring Improves OEM Service Performance

    The prime reason most industrial plants still have internal, on-site maintenance staffs is to reduce repair times and unplanned downtime, which negatively impact revenue, customer satisfaction, cost, and other key business metrics. In most plants today, contracting with the equipment manufacturer for maintenance usually results in unacceptably long periods of downtime for critical equipment while waiting for a technician to arrive – particularly with the typical two passes required for inspection and repair.

  • Leveraging IIoT Technologies To Reduce Unplanned Downtime

    At ARC Advisory Group’s 20th Annual Industry Forum in Orlando, Florida, Shawn Anderson, Senior Research Specialist for Fisher Valves, a division of Emerson Process Management, gave a presentation on how the company is leveraging the Industrial Internet of Things (IIoT) to help end users reduce valve-related unplanned downtime.

  • Analytical Software Predicts Sewer System Blockages

    Using historical data and Seeq analytical software, Nukon calculates when sewer blockages will occur up to 13 hours before occurrence, preventing spills.