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I have just returned from Calgary and the 2018 Global Petroleum Show. We were very pleased to have our submission accepted for the Operational Excellence section of the technical conference, in [...]

We often see extremely simplistic approaches used to forecast utility usage in complex manufacturing or refining processes – estimating the amount of electricity you’re going to use [...]

Having just returned from a trip to Florida, I am full of enthusiasm for the analytics work we are doing here at Sabisu. I was attending the American Institute of Chemical Engineers (AIChE) 2018 [...]

Process modelling is used to identify behaviour on a plant and in some cases predict what’s going to happen next. The basic goal is to build an approximate “picture” of the [...]

Sabisu Events are a great way to mark sections of data that are of interest, either manually in a chart or automatically using either Pipelines or Machine Learning. Sabisu now provides a [...]

We were very happy to be invited to participate in the Industry 4.0 Academia Summit in Manchester and sit on the conference’s scientific committee. As the Head of R&D it was exciting to [...]

Sabisu has added a suite of new project analytics to Widget Working View. These analytics allow you quantitatively measure project progress and health using Earned Schedule. Earned Schedule (ES) [...]

As you’ll have seen from previous blog posts, we’re enthusiastic about the applications of using Machine Learning with industrial data. Machine Learning identifies features more [...]

Machine learning allows users to leverage the inherent information contained within large datasets. This is not the top level information that is the raw data itself, but rather the secondary [...]

Weak signals are a crucial in the effective analysis of complex data, but due to the very nature of weak signals, they are not an easy thing to interpret. What are Weak Signals? Weak signals are [...]