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How Is Big Data Used In Manufacturing?

Big Data is making its way into all the industries, mainly because it is cheaper to store and use. As there is a need for perfection in the environment of factories, they make the best place to implement automation technology. In fact, the market of big data in manufacturing forecasts growth of $9.11 billion by 2026, according to a business survey group.

The manufacturing industry faces a lot of challenges in dealing with the supply of such a large population. Besides, slight mistakes can incur huge losses for manufacturing and logistics companies. With automation, it becomes possible to manage supply chains efficiently. Whereas in physical units such as factories and warehouses, monitoring gets easier. Big data can also help manufacturers create a better product according to customer reviews. Before that, they can receive insights on the features of a potential product before even starting the production. Apart from all this, there are some fascinating use cases of big data in manufacturing.

Efficiency In Operations

Big data analytics in internal operations of manufacturing controls excessive finances wasted on the customization of products. With Automation and ML, there is a lesser chance of human error, which traditionally takes more time and energy out of the project. Machines would detect anomalies in operation, suggest certain changes, and automatically shut down if necessary. Managers can monitor a larger area in comparatively lesser time with the help of AI-driven analytics software. Data in manufacturing usually comes from past reviews of the machinery. It is useful in determining product quality, the efficiency of machinery, and speeding up the manual processes. Companies can simulate designs and detect the probable flaws beforehand, instead of wasting resources on actual production.

In external operations such as transportation and logistics, managers can access real-time movement of shipping and keep a track of inventory. Many of the processes are interdependent in manufacturing, in which data creates a better flowchart of ongoing work. Apart from this, insights from geospatial data optimize the shipping route and predict any delay.

Hidden Insights and Risks

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Machines have a lifetime and they may behave abnormally if any damage is incurred. Manufacturers can predict the life cycle of the machinery, set up automated periodical check-ups, and have a pre-planned backup in case of emergencies. After a certain time period or the production of a certain amount of units, they can schedule maintenance. Such automated regulation reduces up to a tenth of costs and risks. Again, such damages in machinery cost heavy in terms of expenses and time, so self-optimization without human intervention is better in such an environment.

Dynamic Pricing and Production

Warehouse storage is a big concern that manufacturers have to deal with post-production. Overstocking leads to a lot of wastage that no company can afford. Big data helps in analyzing the market and matching the supply approximately with the demand, instead of producing goods non-stop. This would reduce the maintenance costs too, along with production costs. Such a balance of supply-demand would also establish a better timeline and assign specific periods to the rest of the tasks like shipping, managing transactions, etc. Moreover, the managers will be able to forecast the demand and plan the production accordingly.

Big Data can deliver insight on optimal pricing after considering all the factors such as investments, costs, competitor market, and customizations. The prices might keep changing according to these factors, which can be beneficial for consumers as well. If a product has any variants, data analytics will assign appropriate prices to them. Some manufacturers are into customization as per consumer needs. In such cases, too, the prices would be trustworthy even if they are varying.

Apart from such big data applications, manufacturing is undergoing huge automation with advanced robotics, ML-driven processing, 3D printing, and artificial intelligence. Altair, a SaaS and Cloud solution headquartered in the US, is a well-known company that provides software and solutions for manufacturing automation and monitoring.

Read More: What US’s Federal Aviation Administration New Drone Operation Rules Mean for the Market

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