Manufacturing is one industry that has always been ahead of other industries when it comes to technology. Space is competitive when it comes to innovations. Hence, as soon as the concept of Big Data was introduced, manufacturing was one of the industries that started using it to boost profitability and productivity for many companies. In this article, Nichole Heydenburg explores how big data is helpful for manufacturers.
Most manufacturing companies generate large quantities of data throughout the year. This data that has been collected by the company from various sources can be utilised to create plans and to learn more about their customers. Big data has seen much use in the growing manufacturing companies as well. Here is a list of seven ways in which big data has helped manufacturers.
1. Helps Analyse Performances
The companies need to analyse and assess the performance of their products before they are used or sold to other companies. A thorough analysis of the products prior to manufacturing and post manufacturing can be accomplished with the help of big data.
2. Predictive Maintenance
Big data has always played a massive role in predictive maintenance. Since a lot of sensors and devices are connected to all the equipment that is used in the manufacturing of products, it is easy to know about minor or major problems as soon as possible. Therefore, it also becomes straightforward to fix them when there is still time. This is one of the ways big data has been able to save millions of dollars for manufacturers per year.
3. Customisation of Product Design
In the past, the majority of companies sold products that were designed with the thought of “one size fits all.” However, now the trends in the industry have changed and companies are moving towards customisation of the product design. How can a company analyze the repetitive behavior patterns of the customer so that they can be given all the products they need in the shortest time possible? The answer is simple: big data. With the help of big data, the repeated customer behavior is analysed, and the company can design products according to the results.
4. Management of the Supply Chain Risk
One of the most significant problems in the manufacturing business is the risk in the late delivery of the products or the raw material. With the help of big data, companies can predict the delays on the map such as weather, traffic, and natural calamities. The predictive analytics can be used to check the probability of the delays, so the companies can provide backups.
5. Faster Quality Assurance
In some manufacturing companies, each product must be tested to see whether it is working or not before it is approved. Big data makes it easy for the manufacturers to understand which parts of the product need to be tested and which, if not tested, can still affect the product. This saves companies a lot of time, as well as resources that were used in the testing of unnecessary products.
6. Making the Manufacturing Process Faster and Easier
The overall manufacturing process gets improved with the help of big data. The process of manufacturing can be divided into clusters and can be automated. This division into clusters makes it easier for the company to manufacture and test the products in a reduced amount of time. The end result products have less flaws than the ones that were produced before big data was used.
7. Increases Yield of Production
All of this eventually comes down to the increase in the production rates. The faster the production of the product, the more products that can be created in a decreased amount of time. This means the company will gain profit more quickly than before.
Big data has dramatically impacted how the manufacturing industry currently functions. It has been of a lot of help in increasing productivity, reducing the time of manufacturing, and improving the overall manufacturing process. For these reasons, big data is essential to the manufacturing process.
Nichole Heydenburg is a Content Writer for Apex Waves, an electronic test equipment company based in Cary, NC.