Big Data Use Cases in the Manufacturing Industry - A guest Post by Renu Bisht | SansSQL

Tuesday, August 14, 2018

Big Data Use Cases in the Manufacturing Industry - A guest Post by Renu Bisht

Big data is processing of data collected from various sources in different formats. Big data may contain sensitive information which is important for the organisation to make decisions. According to a research, the market value of the Big data will achieve around $1.1 billion by the next year. Today, many industries are using Big data, and companies which are not using are going through big data use cases to understand the benefits of stats in the organisation.

The insights of data are only possible because of Big data. Many industries are looking for the professionals which are skilled and knowledgeable about Big data so to become that person you need to enroll in courses like Big Data Certification Course which is available over the internet. Through this course, the person can learn and enhance his/her skills on Big data, without leaving personal systems. After completion of the course, the user gets a proved certification regarding completion.

How Big data assist manufacturers?
  1. By data tracing
  2. To determine the need of customer
  3. To determine the units need to be produced 
  4. Helps in the maintenance of equipment
  5. Helps in monitoring the production
  6. By maintaining the quality level
Why manufacturers need to use Big data cases?

In supply chain management, Big data helps the manufacturer to track the location of the product. Tracking of data is the primary need of the manufacturer. Why? It helps them to know the count of release, goods which are lost and are difficult to trace. The coordinates of the goods can be traced with the help of radio frequency transmission device and barcode scanners.

It provides the data related to the need and requirement of the customer. Prediction of the demand and assisting the product on time is the prominent reason behind the use of Big data. Forecasting is done when the supply chain is referred by companies and this helps in increasing the profit margin and improving the workspace. 

In product designing, the company analyses the behavior of customers with the Big data analytics. The result of the analysis is critical to understand, how to deliver in a profitable manner and on-time goods. 

Around $2billion revenue is generated by the TCS by just following the order/demands while manufacturing. With the help of analysis, the company predicts which product needs to be manufactured and which needs to be scrapped. In this way, the company makes strong contracts. 

In Quality Assurance, Big data predictions reduce the number of choices which in result reduce the time of testing and efforts. According to Intel’s survey, each manufactured chip had to go under 19,000 tests after production. So, to cut down the test time and giving emphasis on some important test was the biggest challenge faced by the Intel. 

The result was enormous, Intel saved around $3 million in manufacturing cost on a single line production of a chip. And the number may increase upto $30 million if Big data is used in the whole process of chip manufacturing.

In machine maintenance, the Big data helps to plan the maintenance of the machinery. It keeps the data regarding the machine operating time, past maintenance details, updation etc such that the machine runs smoothly and continuously. Sensors and other recognition devices help in collecting the data from the machine. Analysis helps the manufacturer in tracking the efficiency of machine continuously and to focus how it can be further improved.  

About Renu Bisht
Renu Bisht is a doyen of governing the digital content to assemble good relationships for enterprises or individuals. Renu is specialised in digital marketing, cloud computing, web designing and offer other valuable IT services for organisations, eventually enhancing their shape by delivering the stupendous solutions to their business problems. 

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LinkedIn: https://www.linkedin.com/in/renu-bisht-5b813759

243 comments:

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