Seeq: Improving Operations and Business Outcomes Through Advanced Analytics

Since its initial product launch in 2016, Seeq has provided an advanced analytics application for manufacturing data with low/no-code tools for engineers to help them investigate time-series data, mostly in process manufacturing. Analyzing patterns in time-series data empowers engineers to maximize production, yield, and uptime by optimizing predictive maintenance and comparing production cycles to identify issues’ root causes. Seeq can run on-premises or in the cloud and can connect to any historian, IIoT platform, or database web service, making it adaptable to customers’ needs and data management architectures.

With Seeq’s newest release, R21, users may easily publish analytics-based views to other employees or managers. It has expanded scorecards for tabulated metrics, measurements, and summary data in user-defined tables where managers can view performance and operations data by batch or plant.

These sorts of solutions provide valuable management tools to help executives make strategic decisions based on the up-to-date, real world performance of their companies’ plants. Basic management science tells us that managers should provide measurable goals for their employees to reach and incentivize them to do so. These scorecards provide access to patterns in performance data that can help managers figure out what has worked, where it has worked, and why.

All that Seeq does touches Industry 4.0 at its core. This movement revolves around the idea of making smarter decisions based on real-world, real-time patterns in data. Where, previously, a plant manager took notes on a piece of paper on a clipboard and then entered them into an Excel spreadsheet, we now have predictive maintenance, production control, and quality control leveraging sensor data and historian data. The next step will involve lambda hybrid architectures where historians, edge gateways, and servers process streams of data on-premise while batching results to the cloud or data center for further analysis. Seeq does this with its application running on-premise or in the cloud as SaaS on Azure and publishing the newer scorecards for managers off-premise.

This combined offering means Seeq can help companies get started leveraging data for their Industry 4.0 strategy while also acting as a catalyst into the next level of Industry 4.0 Maturity. For more information on the levels of Industry 4.0 Maturity, please see ABI Research’s Industry 4.0 Maturity Model.

Seeq differentiates itself by serving multiple levels of the Industry 4.0 Maturity Model. Whether a process manufacturing firm sits at Level 1 on the Industry 4.0 Maturity Model, with only the beginnings of automation, or at Level 4 as a Digitally Transformed firm, Seeq can prove itself a valuable application. Because it does not classify as a platform or totally new type of technology, it does not require any sort of systems overhaul. Manufacturers can install it on whatever systems they currently use to start analyzing whatever data they have. Seeq has experience working with a wide variety of different types of systems and time-series data with clients and case studies in many industries, including food and beverage, oil and gas, consumer packaged goods, metals and mining, pharmaceuticals, petrochemicals and other chemicals, power generation, pulp and paper, and utilities.

At its most basic, this means Seeq can use data in siloed industrial PCs and any operational historian, and users with direct access to those historians can find patterns in the data for predictive maintenance or optimized batches of that specific part of the operation. Moving up to Level 2, where manufacturers have consolidated some data on edge servers or production systems such as MES, Seeq can connect to those sources for contextualization of sensor data in the historian.

Seeq can also run in the cloud for manufacturing firms at Level 3 and, for those at Level 4, on lambda hybrid architectures to provide even more value. Wherever a manufacturing firm finds itself in Industry 4.0 maturity, if it has time-series data, then Seeq can help it get the most out of that data in its current form and improve operations and business outcomes through advanced analytics. This means analyzing time-series data, delivering analyses to users who need them (whether on the plant floor or in the C-suite), and driving results that those users can ultimately measure in business outcomes, lower operational costs, or increased efficiencies.

These customer benefits have set Seeq up to continue its tremendous growth from last year not only into this year, but over the next five to ten years, too. ABI Research recognizes Seeq as one of the leaders among advanced analytics vendors for process manufacturing. Seeq has always had useful low/no-code analytics, but now it has expanded its use cases beyond the plant floor to affect even greater business outcomes.

For more insights and perspectives on manufacturing and the Industrial Internet, please check out ABI Research’s Industrial Solution.