Go to a meeting of any trade group or association and someone is going to mention "big data." I know of scores of companies that have scores of servers dedicated to storing all this data.
So what? If they are not using the data to improve their business, storing it is a waste of server space and money.
What is big data?
According to Edd Dumbill, a contributor to Forbes Magazine: "Big data is data that exceeds the processing capacity of conventional database systems. The data is too big, moves too fast, or doesn't fit the strictures of your database architectures."
Just to be clear, you do not need 70 terabytes for your data to be big. Data in formats that your database system manages is by definition, big data.
There are a number of programs available to help you analyze your big data, and Forbes provides a good starting place with an article called "Big Data Solutions Through The Combination Of Tools."
However, you need to know which data you need and how to use it to improve your company.
How can big data help manufacturing?
A huge area that is great territory for using big data is for measuring untold numbers of little things in factories.
Data drives quality
For example, Raytheon is a major defense contractor to the United States government with almost no wiggle room when it comes to quality. Raytheon has installed advanced automated systems that measure all the things that go into building a missile.
They have machines that measure how many times a screw turns. If it should be turned 14 times but is only turned 12, then it is too loose; turn it 15 times, and it is too tight. If the screw is not turned the right number of times, production stops and the computer dashboard flashes an error message.
This amazing kind of software is "manufacturing execution systems" (MES), and there are many companies who make it. Randy Stevenson, a missile-systems executive at Raytheon has nothing but praise for the tasks performed by the company's MES:
"The new capabilities mean Raytheon is catching more flaws as they occur," Stevenson tells The Wall Street Journal. "In the past, some of those flaws would have been discovered later by inspections; others might never have been noticed. Screws aren't a minor detail in the defense industry. If a missile-maker fails to use the right fastener or attach it exactly right, the device could fail."
Using big data for maintenance
Sherwin Williams Co. is a well-known manufacturer of paint. After studying data it collected, the company realized that after 10,000 batches of paint, some equipment at its Richmond, Kentucky, plant failed.
To avoid costly interruptions of its paint production, the company does preventive maintenance after 9,000 batches.
Other uses for big data
The way manufacturing companies can level the use of big data is nearly endless. Some other important uses of big data beside production, quality and maintenance include:
- service and aftermarket
- sales and customer management
- financial and support services
- supply chain and inventory
Where does the data come from?
Manufacturing equipment is more advanced than ever. Nearly every piece of equipment in a plant is "smart" and able to communicate with an MES. An MES helps companies understand the data collects.
Gartner Inc. analyst Simon Jacobsen says the global market just for MES software is around $1.5 billion per year. When a company includes MES hardware, software and training, costs for a single factory can reach $500,000. Yet companies such as Raytheon, Sherwin Williams, Harley Davidson, BMW and Chrysler are among the thousands of companies that think the investment is worth the cost.
The manufacturers really have little choice in letting big data on the factory floor. Customers demand it, even if they do not use those words. Customers expect programs that bring about zero defects, and investors want a higher return on investment.
The one part of the factory that can give departments the data they want and need is the MES.
