Predictive Analytics

Tridiagonal Solutions Partners with Seeq for Advanced Process Data Analytics

Tridiagonal Solutions expands its digital solutions portfolio by providing state-of-the-art insight-based data analytical solution –Seeq (www.seeq.com). With its large customer-base in Process Industry (Pharma, Specialty Chemicals, Oil & Gas, Food & Beverages, etc.) worldwide, we are uniquely positioned to provide the data contextualization, cleaning and advanced analytics solution. Tridiagonal is a global implementation partner and Value-Added-Reseller (VAR) of Seeq worldwide.

With Seeq, you and your team can rapidly investigate and share analyses from operations and manufacturing data sources to find insights and answer questions. Designed specifically for analyzing process data, Seeq works across all verticals with time series data in historians or other storage platforms. Leveraging innovations in big data, machine learning, and web technologies, Seeq delivers easy to use features for your users and supports all phases of analytics from cleansing to reporting.

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

It includes features to expedite the full arc of the analytics process, from connecting to historians to data cleansing, visualization, modeling, and calculations.

Workbench also enables organizations to leverage the work of engineers with features for real-time collaboration, knowledge capture of analytics processes for easy reuse, and the sharing of Seeq workbooks and queries among teams.

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

Organizer “Topics” may include text, images, scorecard items, and analyses generated in Seeq Workbench such as trending displays, scatter plots, bar charts, etc.

Employees across the organization can leverage insights created in Seeq with a “read only” view of the information and when Organizer documents are viewed in a web page (as a URL) viewers may annotate or comment on the document to share feedback with other viewers.

Data Lab is Seeq’s application for data scientists and process engineers to access Python libraries to expand their analytics.

Using Seeq Data Lab process engineers can expand their Seeq analytics efforts to the rich ecosystem of Python libraries and data scientists can participate directly in industrial analytics by leveraging Seeq for data access, cleansing, modeling, and other features.

Seeq Data Lab is built on Jupyter Notebooks and a Seeq Python library, called SPy, to access Seeq functionality and managed by the same administration features as other Seeq applications.

HOW SEEQ SOLVES THE PROBLEM?

  • Reduce unplanned downtime by addressing asset problems before failure
  • Lower maintenance costs through early warning maintenance alerts
  • Extend asset life by ensuring that assets are constantly adjusted to function at optimal environment settings
  • Improve product quality by managing custom defined boundaries in near real time.
  • Increase yield while reducing waste as assets work at optimal speeds and within expected boundaries
  • Optimize maintenance schedules by enabling predictive, data-driven asset maintenance evaluation and prioritization
  • Create reports quickly and easily that are segmented by audience, easily updated on pre-determined schedules, and can be distributed across multiple avenues (e.g., monitors, PCs, tablets, phones, PDFs)
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