Predictive Analytics for Processes Manufacturing

TrendMiner, a self-service analytics platform, applies predictive analytics for production processes in a variety of different industries.

What is predictive analytics?

Predictive analytics is the third step in the analytics journey, preceded by descriptive, and diagnostic analytics, and followed by prescriptive analytics.

Traditionally, predictive analytics is the examination of historical data, statistical algorithms and machine learning to identify the likelihood of future outcomes. Simply put, predictive analytics refers to the examination of data to answer the question, ‘what is likely to happen?’. 

The goal of predictive analytics is to go beyond understanding what has happened, why and how it has happened, to provide an assessment of what is likely to happen in the future.

What is predictive analytics for process manufacturing?

Predictive analytics in the process manufacturing industry helps process and asset engineers to monitor performance, safeguard best operating zones, and predict when maintenance is needed.

Process evolution can be used for early warnings and can also be extended to the level of predictive maintenance. This allows engineers to perform maintenance at a time when it is the most cost effective, and when it will have the least impact on operations. 

TrendMiner for predictive analytics

TrendMiner’s interactive and model-free predictive mode is based on patented technology and fundamentally works differently from classical model-based predictive technologies. Our software calculates possible trajectories of the process and predicts future evolutions of key variables and process behaviors.

TrendMiner software also supports creating and deploying soft sensors using an interactive and step-by-step approach with access to all process data. Again, allowing process and asset experts to build predictors for future performance without the need for a data scientist. 

Another way TrendMiner applies predictive analytics is by capturing events of interest. When specific events occur, these can be automatically labeled and captured as events of interest. This allows engineers to monitor how often these events happen and if so, prevent and control overall production performance. 

Whether analyzing batch or continuous processes, TrendMiner applies predictive analytics to help process experts monitor performance, safeguard best operating zones, and predict when maintenance is best scheduled. Read more about how Trendminer software applies predictive analytics here.