How Big Data is Revolutionizing Manufacturing in 2016

Big Data is in its heyday, and while it’s causing all sorts of privacy concerns in some sectors, the Manufacturing Sector is another story. Big use cases, evolutionary improvements, and next-level efficiency are all here.

Big Data is making news all over the place, and unfortunately its usually for ill. Recently, Google has taken flack for its approach to messaging from none other than Edward Snowden. AT&T also made the news for profiting from data mining its customers and selling to various government organization.

But, fear not…there is great news on the Manufacturing front. Here you go…

Big Data is Big Business in Manufacturing

A Honey Well and KRC Research Inc study just competed in June of 2016 showed how important IIOT (Industrial Internet of Things) and the insight of Big Data and analytics is to the industry:

  • Insights gained from Big Data are essential to 68% of manufacturers
  • 67% of manufacturers are planning to increase investments in Big Data even though they are reducing costs in other areas due to tough business conditions
  • 46% of manufacturing executives see Big Data as pivotal to improving supply chain

Executives see the following Big Data benefits:

  • Better real-time decisions (63%)
  • Reduced waste of resources (57%)
  • Predicted risk of downtime (56%)
  • Identification of defects (43%)

Manufacturers deal at very high scale, so these improvements in efficiency are ground breaking in their ability to drive bottom-line results. In fact, unscheduled downtime ranked as the top threat to maximizing revenue.

The Top 3 Use Cases for Big Data in Manufacturing

Below are some real-life use cases as highlighted by Ingram Micro.

Use Case 1 – Reduce Manufacturing Flaws

Quality Assurance is a significant cost for manufacturers. But while the effort is huge, it is worth it. Consistent quality is key to brand and developing loyal customers. Even minor slip ups can result in absolute disaster. Look no further than the staggering financial impact to Samsung from the manufacturing defect of the Note 7. This disaster sunk overall operating profits by 30%!

The more complex the product being manufactured, the more challenging the Quality Assurance.

Intel, for example, runs each chip through 19,000 tests. Turning to Big Data, Intel has been able to enable predictive analysis and shave huge amounts off its Quality Assurance spend while still improving quality.

Thanks to Big Data, Intel shaved off $3 million in manufacturing costs from a single product line, and expects to save an additional $30 million by expanding the process to other lines.

Use Case 2 – Yield and Output Improvements

A pharmaceutical manufacturer was faced with the challenge of improving yield of its vaccines. Two seemingly identical batches would produce a yield variation of between 50 and 100 percent.

That’s a big difference! This problem was particularly daunting as there were 200 variables utilized to track the purity of the process. Simple split testing would take massive amounts of time and money.

Fortunately, this is exactly the problem Big Data and analytics is suited to solve. Big Data cut through the clutter and identified the proper inter-dependencies and narrowed the problem down to just 9 variables that impacted yield.

By using the output, the company was able to increase production by 50%, resulting in a $5-$10 million annual savings.

Use Case 3 – Identifying Behavior and Patterns of Buyers

The manufacturing leg of Tata Consultancy claims that it makes most of it’s $2 billion revenue through manufacturing products to order.

Tata has an extensive Big Data practice which gathers data on repeat customers, analyzes their behavior, and predicts orders. This allows Tata to deliver products quickly and at higher profits.

Fundamentally, it has allowed Tata to employ Lean manufacturing methodologies, providing customers what they need when they need it, but without sacrificing delivery time.

Additionally, Big Data analytics provided Tata next-generation, fine-toothed insight into how each product and variable performed financially. This allowed Tata to focus on high-profit manufacturing and step away from lower-margin areas.

Big Data Transforming the Manufacturing Industry – 21 Minute Video

Last up, here’s an excellent round table discussion from earlier this year that highlights:

  • Evolution of Big Data in manufacturing
  • Examples in today’s processes
  • How engineers are affected
  • Open vs closed data
  • Predictions for the future

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