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TrendMiner new software available

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Latest version of self-service industrial analytics software delivers new features and extended data visualisation to enable multi-site analytics and contextualise asset performance.

TrendMiner NV, provider of self-service industrial analytics software, announced today that it has released a new version of its software: TrendMiner 2017 Release 1. This release focuses on enabling large organisations to increase efficiency across multiple sites through analytics-based insights.

Thomas Dhollander, VP Products, said: “The latest iteration of our software is a pivotal step for TrendMiner’s growth. We promised our customers that we would keep delivering new innovations to help them achieve their goals, and that is exactly what we’re doing. TrendMiner 2017 R1 solves the critical needs in our markets: deeper insight, faster action and cross-site analytics.” 

What’s New in TrendMiner 2017 R1?

TrendMiner 2017 R1 is a major release in line with the company’s rapid growth. Since its launch, market adoption of TrendMiner has been high, so to meet the rigorous demands of the world’s largest chemical producers, the software has been extended and broadened. In addition to new features and functionalities, this release includes significant enhancements to speed up root cause analysis, identify new areas for further process optimisation and enable cross-site analytics.

Contextualising asset performance with process data


TrendMiner 2017 R1 delivers two new data visualisation options that allow subject matter experts to solve process issues more quickly. Multivariate scatterplot charts allow users to look at relationships between pairs of measurements in a broader context, with the option to drill down per pair of active tags and view the details in that bivariate scatterplot. Using area search within scatterplot graphs, users can draw directly on the scatterplot graph to perform analytics on a multivariate operating zone of interest. These new operating zone analysis features reveal previously hidden relationships within the process data and speed up root cause analysis. They may also be used to monitor for anomalies of interest or receive alerts for deviations from the best operating zone.

Enhancing interoperability

The new TrendMiner release helps large companies operating across multiple sites with different historian/MES systems to gain analytics insights without changing their existing systems. Tags from a variety of historians can now be indexed and searched within a single analytics environment. This enables multi-site and cross-system analytics insights. In addition, all indexed tags – regardless of their originating system – can be utilized in influence factor searches. TrendMiner 2017 R1 ships with several standard connectors, including connectors to Wonderware Historian, OSIsoft PI, Honeywell PHD, Yokogawa Exaquantum and AspenTech IP.21.

Solving previously unsolvable process questions


TrendMiner now supports global search for influence factors. In the past, analytics users had to manually select instrument tags for analysis to determine which could have the most influence on process performance. The selection of those items depended entirely on the subject matter expert’s knowledge of the process and the assets involved in the situation. 

With this release, users no longer have to select tags themselves. Instead, the software searches through all the indexed data, shows all tags exerting an influence and how much influence each of them has on the process behaviour. This allows users to identify previously hidden influence factors that may not have been taken into account initially. As such, it is a key enabler for identifying the most impactful causes for anomalies in process behaviour.

TrendMiner delivers self-service data analytics to optimize process performance in industries such as chemical, petrochemical, oil and gas, pharmaceutical, metals & mining and process manufacturing. TrendMiner software is based on a high-performance analytics engine for data captured in time series that allows users to question the data directly without help from a data scientist. The plug and play software adds value immediately after deployment, eliminating the need for infrastructure investment and long implementation projects.  Search, diagnostic and predictive capabilities enable users to speed up root cause analysis, define optimal processes and set fingerprints to monitor production. These can be used to send out automated early warnings to control room staff in case of deviation. TrendMiner software also helps team members to capture feedback and leverage knowledge across sites. 

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