[Image above] Credit: dirkcuys; Flickr CC BY-SA 2.0
The ACerS Bulletin recently featured a profile and forecast of the ceramic and glass manufacturing industry, which showed that although manufacturing jobs in the U.S. may be declining, manufacturing productivity is increasing due to the rise of automation and increased efficiency on factory floors.
But how can companies boost manufacturing efficiency?
Short answer: big data.
While you may be more familiar with big data’s role in research, that’s not the only place where big data has potential.
Because analysis of big data offers the ability to comprehensively assess many nuanced variables at once, it’s particularly well suited for complex processes such as manufacturing.
According to an article from McKinsey & Company, a management consulting firm, “In manufacturing, operations managers can use advanced analytics to take a deep dive into historical process data, identify patterns and relationships among discrete process steps and inputs, and then optimize the factors that prove to have the greatest effect on yield.”
In other words, collecting and analyzing big data in manufacturing can increase efficiency by saving time and money. Even voices from some of the biggest names in manufacturing agree that big data is key to boosting production and making manufacturing competitive.
In fact, combining big data with flexibility in manufacturing can increase productivity by 30% and decrease development and assembly costs by 50%, according to a news story from Ohio University. The university recently created this infographic, which provides several more figures about big data in manufacturing.
Big data can increase productivity and decrease manufacturing costs in several different ways, including product development and manufacturing processes.
Designing, building, and testing prototypes is time- and labor-intensive—but using big data can enable modeling and simulations that inform smarter prototype design and even reduce the number of prototypes a company builds and tests.
Plus, data analytics can help manufacturing facilities run more efficiently by monitoring equipment and processes, offering the potential to sense and predict problems before they occur.
The results can drive rapid, optimized product development and prevent costly downtime—ultimately boosting productivity.
How else is big data affecting the manufacturing landscape? Forbes lists ten ways.
And the future is bright—the potential of big data in manufacturing is just starting to be realized. “The big data era has only just emerged, but the practice of advanced analytics is grounded in years of mathematical research and scientific application,” according to the McKinsey & Company article. “It can be a critical tool for realizing improvements in yield, particularly in any manufacturing environment in which process complexity, process variability, and capacity restraints are present.”