Big data has the power to deliver immense and lasting value to manufacturers in all industries. It involves applying statistics and mathematical tools to business data to continually assess and enhance plant processes. By aggregating and analyzing previously isolated data sets, companies can uncover insights, patterns, and relationships that can be leveraged to optimize processes, gain a competitive edge, reduce costs, and identify areas of improvement.
Although new applications for big data in manufacturing are constantly emerging, there are currently a few key metrics that the majority of plants focus their efforts on. They include:
Assembly speeds: Big data is a powerful way tocapture machine-level information, which can help manufacturers identify how often the line assembles certain types of products, and exactly how much effort and time goes into the production. Companies can then analyze this data to determine which products are easiest to produce and deliver the highest margins. Those insights can then be leveraged to inform plant strategy, for example by shifting the big-picture focus toward the most profitable products.
Granular plant data: Manufacturers in all industries are using big data to understand precisely how the plant works on a granular level. When applied correctly, analytics can reveal what days, hours, products and employees deliver the greatest output. Companies can then use those insights to consistently reproduce optimal conditions and ensure ideal outcomes.
Error and defect data: By tracking error and defect rates according to product type and employee, manufacturers can avoid mistakes and prevent quality problems. This data can also be used to design training and employee incentive programs, further supporting the plant’s continued success moving forward.
Prototyping costs: And finally, many companies are using big data in manufacturing to measure the time, costs and resources involved in developing a working prototype. That information is immensely valuable because it can be used as a benchmark in the bidding process to ensure the profitability of any given project.
