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Three Ways Big Data Helps Manufacturers Think Bigger

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Everyone is talking about Big Data—and yes, databases are immense. A gigabyte used to sound like a lot. Today, we talk about terabytes without blinking. And while Big Data isn’t anything new for manufacturers, leveraging it for competitive leadership is.

Just ask Inteva Products, a major automotive component maker. Inteva doesn’t just inspect their sunroof motors visually—they actually listen to them run to make sure they’re not too loud. The company stores thousands of audio files of these motor tests each day, gaining insights that enhance their future product development—insights their competitors lack. Leveraging Big Data allows manufacturers, like Inteva, to keep a much closer eye—or ear—on product quality, which is a true competitive advantage.

Big Data is changing the way manufacturers operate and execute on the shop floor. Let’s look at just three of the ways it’s helping them think bigger than ever before.

#1: Monitoring Product Quality Proactively

In the recent State of Manufacturing Technology Report, 31 percent of respondents reported they are either evaluating their Big Data needs and opportunities, or plan to do so in the coming year. Another 35 percent believe data analysis is the most important skill set for the next generation of employees.

Stop and think about where all of this data can take manufacturing.

Manufacturers already provide incredible amounts of data on their products’ construction and testing, establishing up front that they’re producing high-quality products. Soon, they’ll be able to eliminate statistical process control from their quality control process. Instead, manufacturers will use today’s increasingly affordable sensors to gather real-time data on every item that comes off the assembly line. The bottom line will be greater accuracy with less human involvement.

#2: Seeing the Future—and Changing It

Operational analytics are great at telling us what just happened and why. Manufacturers have been doing that kind of analysis for years. But they’re now using the predictive aspects of Big Data to monitor their operations against their quality standards. That often means predicting when a machine or tool is about to break—before it starts churning out defective products.

Predictive analytics tell us what’s about to happen. Prescriptive analytics show us how to make machines do what we want. These disciplines are the crown jewels of business intelligence. Both require vast amounts of data—and the ability to analyze it effectively. That’s what Big Data delivers for today’s manufacturers.

It’s one thing to look at the history of maintenance issues or failures on a specific machine. But today, manufacturers factor in so many other variables. They’re looking at a press and factoring in not only all the metrics around it—such as temperature and tonnage—but also who’s working on the machine, how long of a shift they’ve worked, what tools are in the press, and much more. They then factor all of this data into their predictions of when future failures will occur.

Predictive analytics isn’t a new discipline. But until recently, its high cost made it practical for only very expensive products or equipment. New tools make predictive analytics a way of life for manufacturers of all sizes. And as the Internet of Things continues to mature, manufacturers are gathering more data automatically.

#3: Getting Customers into the Data-Collection Game

The winners in our new data-driven economy will be the companies that can gather vast amounts of data and turn it into actionable processes within their supply chain. For manufacturers, the data gathering doesn’t stop at the boundaries of the organization—it includes information collected at customer sites.

Sensors come into play here, too. It’s becoming highly cost-effective for manufacturers to embed sensors into the products they deliver to customers—and the data they’re getting back is worth the small investment in hardware. By extending the quality control process beyond purchase and throughout the life of their products, manufacturers can gather information that catapults their products to higher levels of performance, better design, and longer lifespan.

This kind of innovation relies on a delivery agent that can put vast amounts of data at the fingertips of every stakeholder. Traditional ERP systems only create roadblocks. But cloud-based business applications and cloud storage let manufacturers replicate best practices and technical advancements quickly throughout their global enterprises.

With the cloud, every worker, every forklift, and even every wrench will tap into vast volumes of data to improve the way they work. It’s a platform for dramatic change on a global scale.

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