Making value to Virids and Data Science

Creating value to Arnis Platform  through data analysis

Virids' Energy Auditory: decision making from Data Science and Machine Learning to help reduce energy consumption and improve energy efficiency.

The data: Furnace Features and Raw Material features

The Vetta Data Science Team worked with those source data. Some review to understand how the team had worked is listed below: 

The period of time analyzed was:        
        from January 1, 2019 to August 28, 2021 for both data source.

The Furnace features dataset has some relevant atributtes to the data analysis, like: 
        Raw and charge material 1, raw and charge material 2, furnace first and raw material temperatures, energy consumption (kWh).

The Raw Material Features dataset has two relevant atributters to the data analysis:
      S content which represents the silica. 
      C content which represents the carbon.
          
Raw Material 1 has Raw Hot1 most
while Raw Material 2 has a third material most. (Classified as '0' in the graph).

The third material is expensiver than the others.
 
We conclude that it is generating high costs.

S content has a moderate-strong correlation when its content rate is next to zero.

C content has a very strong correlation when its content rate is up to 1.50


Is there any differences between the initial furnace temperature and raw material temperature

We see a very weak correlation between the two variables. It indicates a great difference.

Furnace First temperature is normally too high.

If it is decreased, it will result in lower energy expenditure.

Azure is an important cloud-based platform to increase our data analysis performance in the future!

    With Azure we can do:

    Build Python web apps in the cloud from the same code used in this presentation. Dataset will be safe and access to the data and code will be online driven. 

    Quickly and easily build, train, host, and deploy models from any Python environment with Azure services for data science and machine learning. It will be resulting in better making decisions for the consultants after all data analysis from the Data Science team.

    The Virids Platform can be hosted and accessed anywhere.

For further information