How does big data play a part in the manufacturing industry?
A wide variety of software is used in the manufacturing industry, from ERP to CMMS, but until they are integrated via big data, it is not easy to get an overview of things like how a factory floor is running. By integrating manufacturing software, and information from other sources, with big data, patterns can be found, and problems can be solved.
What type of information can be collected, and how can it be used?
The information collected from individual software can include sensor, maintenance, quality, and design data. By utilizing such information, big data can come up with things like productivity data and how much power consumption, amount of water, or amount of air specific machines use. So, you can obtain data from machinery like CNC Machines to create big data, and at the same time, you can get a better insight into individual machines.
In addition to big data being generated from software machinery like motors, pumps, compressors, and conveyors, it is also produced from outside vendors, partners, or customers. Basically, big data is everywhere within a company or industry’s infrastructure. Wherever there is data, it can be used to feed into the larger concept of big data.
Which manufacturing sectors use big data?
Big data is used by all manufacturing industry sectors, including car manufacturers, refineries, chemical producers, oil and gas companies, and chemical producers. Indeed, because big data can be analyzed to provide many solutions and benefits to companies, it is now being used in almost every type of industry there is.
How is big data beneficial to manufacturers?
Without analysis, big data does not mean anything. But when big data is analyzed in the correct way, it can make a monumental difference in how a company operates and how much it can grow. Here are some ways in which big data is advantageous to manufacturers.
Big Data Can Optimize Production and Improve Efficiency
Data that is gained from individual machine logs and via sensors and assets of the Internet of Things can enable personnel to quickly capture and analyze machine data and find ways of improving the machine’s performance. Therefore, big data can optimize production and enhance efficiency.
Big Data Can Reduce Downtime and Predict Machine Failure
Breakdowns of equipment and scheduled maintenance are regular features of the manufacturing industry. But it is estimated that by using big data analytics, machine breakdowns can be reduced by as much as 26 percent. Furthermore, it can reduce unscheduled downtime by as much as 23 percent. By utilizing big data in the right way, you can dramatically increase productivity and reduce downtime and machine failures, and for that reason selecting a data integration platform is key for a successful implementation.
Big Data Enables Companies to Better Understand and Predict Customers’ Behavior
Supply chain data is just as valuable to manufacturers as data about machinery. The data is compiled from various sources and can include information like shipping details, weblogs for customer shopping patterns, and suppliers’ orders. Companies that analyze such information can leverage it to understand better and predict customers’ and clients’ needs and personal preferences.
Big Data Can Reduce Manufacturing Costs and Improve Product Quality
By using big data for predictive analysis, you can dramatically lower the number of tests required for quality assurance and cut down the test times. That means there is more time to focus on specific tests. It also means you can reduce manufacturing costs while improving the quality of a product at the same time. For example, Intel once used to run every chip that came off its production line through 19,000 tests. Once Intel started using big data for predictive analysis, the number of tests required was significantly reduced, and Intel saved a massive $3 million in manufacturing costs, for one single product line!