Tips for Implementing Big Data in Your Factory

Apr 20, 2022

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Big Data is one of the fundamental technologies of Industry 4.0 responsible for processing, managing, and analyzing large amounts of data and its digitization. Before implementing Big Data in your factory or company, our big data experts recommend following these steps:

Set The Objectives Of Your Factory or Company

It is essential to recognize and specify the flaws in the production process of your factory, as well as the manufacturing errors or processes that you want and need, to improve, optimize, and correct.

It is important to recognize, locate and make sure of the origin and credibility of the data and databases you want to analyze.

Based on the recognition of these failures, the objectives will be:

  • Use Big Data analysis to overcome them.
  • Improve, streamline, optimize and increase factory production.
  • Reduce costs.

Implement The Analysis

At this point, you must decide what tools, what type of Big Data analysis you will use, and where you will apply it. It is always recommended to start the implementation of Big Data little by little and by areas or sections within the factory. Of course, the implementation of the analysis must be done based on the objectives that you need to achieve, for example: If one of your objectives is to ensure that the machines in the production area have better performance. You should start with data analytics from smart machines. Or maybe if you need to improve the flow of web pages or social networks, analyze the data they generate.
Big Data Implementation - BainsLabs

Deepening of the Big Data Plan

Before the implementation of the Big Data plan, we must carry out a study of the behavior, the characteristics, and the data that we store and that our current clients and potential future clients generate.

In this way, we will apply a correct Big Data analysis that will allow us to create marketing strategies that help us attract more customers.

The same in-depth study must be applied in the various areas of the factory, such as quality control, manufacturing, or human resources.

Execution and Infrastructure of the Big Data Implementation

Before the implementation of the Big Data plan, we must carry out a study of the behavior, the characteristics, and the data that we store and that our current clients and potential future clients generate.

In this way, we will apply a correct Big Data analysis that will allow us to create marketing strategies that help us attract more customers.

The same in-depth study must be applied in the various areas of the factory, such as quality control, manufacturing, or human resources.

Execution and infrastructure of the Big Data implementation

The execution is nothing more than carrying out all of the above, while constantly checking the variation of the data.

Carrying out the execution will not be possible without installing the necessary infrastructure and technology for the implementation of Big Data.

The operation and installation of the Big Data infrastructure are not easy, because the Big Data system must work with large amounts of data in real-time without storing them in a computer memory since it is not possible.

This is why a cluster must be used within a Framework environment, the most used is Hadoop, capable of doing all the necessary work with the data. At the same time, this entire process could be hosted in the cloud. The installation of such infrastructure in your factory will likely take several days, while the entire process is carried out and tested. As we mentioned before, the simultaneous activation of Big Data in all areas of the factory is not recommended, it is recommended to do it gradually. In this way, to be able to correct and verify its proper functioning in each section, while at the same time the workers and employees adapt to the new technology. Now that you have surely realized that the implementation of Big Data in your factory is not so difficult, surely you have already decided, if so, and you need more information.
If your organization is looking for big data consulting or data architecture consulting, feel free to contact us..