Blog Archives – Viking Analytics

Not sure if your sensor data is reliable? Add population context to it

One of the fundamentals of condition monitoring is being able to trust the data you get from your sensors. Normally, there is a set of checks that an IIoT installation goes through to become fully functional, like connectivity and authentication tests to ensure that the sensor is in the right operational state or, in other

Science Behind Industry 4.0: The Origins of Bayesian Statistics

Bayesian methods have become widely used in machine learning and pattern recognition. Talking simplistically, traditional – or ‘frequentist’, statistics see probability as the limit of relative frequencies of events as the number of trials increases, assuming a fixed set of distribution parameters. Bayesian statistics, on the other hand, is more concerned with adapting a model’s

How can AI find black sheep machines in an industrial plant?

Even companies that are playing in the advanced league of the condition monitoring game may face the challenge of knowing which machines need to be prioritized for maintenance. For example, how can a professional responsible for the maintenance of compressors in a company realize which ones need to go to the top of priorities list?

Maximizing value in small scale data science projects

In our latest blog post, my colleague Arash Toyser wrote about data and its relation to value using a very intuitive and informative analogy of gold and goldmines, making the point that raw data is the goldmine and the extracted insights are the actual gold. Continuing the analogy, one can argue that gold in itself

Data is the new gold… or is it?

Many industrial companies have been collecting data for several years if not several decades with varying degree of success in terms of the quality of the data collected. We asked ourselves, if data is the new gold, why are companies struggling with converting it to real tangible revenue? Afterall, this was the reason we started

Infographic: 5 steps for productive work with process data

The new MultiViz is here!

When we founded Viking Analytics in 2017, our mission since day one has been to put manufacturing data – and all its possibilities – in the hands of professionals that know the most about the production lines, the processes, the machines. Our self-service data analytics software, MultiViz, became the embodiment of this mission. Three years

Viking Analytics joins the IBM Accelerator Program

Viking Analytics is very proud to join the IBM Accelerator Program Sweden. In the next months, we will work together to integrate and establish a sales partner program to MultiViz through IBM Ecosystem and RedHat marketplace. “This is a major step for Viking Analytics, as it relates directly to our scalability and attests to the

The science behind Industry 4.0: theoretical foundations of Deep Learning via Sparse Representations

Each day, it increases the frequency we hear terms such as artificial intelligence (AI), machine learning (ML) and deep learning (DP). A lot of time these terms are used interchangeably and the relationship between them is not always clear. Artificial intelligence is the intelligence demonstrated by machines to creatively solve problems. Machine learning is a

In the media: Three Challenges in Using Machine Learning in Industrial Applications

Machine learning (ML) is present in many aspects of our lives, to the point that is difficult to get through a day without having contact with it. The most common example is doing a simple Google search, trained to show you the most relevant results. But ML can also be found in our smartphones, through