Don’t risk your profitability by ignoring advanced analytics

One of the world’s largest hard disk drive manufacturers has maintained its competitive edge by using big data analytics to predict failures and protect product quality.

Hard disk drive - image courtesy of Depositphotos.
Western Digital is one of the world’s largest hard disk drive (HDD) suppliers and a pioneer in hard disk drive storage manufacturing – image courtesy of Depositphotos.

Western Digital is one of the world’s largest hard disk drive (HDD) suppliers and a pioneer in hard disk drive storage manufacturing.

The company’s ability to succeed despite competition from new players can in part be attributed to its strong commitment to quality.

Quality improvements are driven by complete product and component traceability across the entire lifecycle of every unit of hard disk drive manufactured, from suppliers and production, to testing, shipment and customer use.

To maintain its competitive edge, Western Digital must ensure volume and efficiency in the manufacturing and distribution of its hard disk drives. Thanks to SAS Asset Performance Analytics, the company can achieve exactly that.

To learn more about Western Digital’s proactive approach to big data analytics, The Manufacturer spoke with Tim Clark – Head of Manufacturing at SAS.

“The most important areas for manufacturers to maintain and improve are production quality and machine uptime,” Clark explains. “Those two factors feed directly into being a productive, profitable business capable of satisfying the demands of customers; and not by coincidence, these two areas are where data and advanced analytics can unlock significant returns.”

SAS e-book screenshotIndustry 4.0 is commonly understood as the trend toward automation and data exchange in manufacturing technologies, including cyber-physical systems, the Internet of things and cloud computing.

However, this is often misinterpreted to just mean the automation of basic physical and digital processes. Many manufacturers have already achieved this level of automation. So, they stop innovating, believing they’ve already achieved Industry 4.0.

In reality, Industry 4.0 encompasses so much more. We define it as using data across the entire value chain, and using that data to generate actionable insights and release monetary value.

Download our exclusive free eBook to learn how your business can realise the future of manufacturing today.

Protecting the bottom line

The Western Digital subsidiary that SAS partnered with produces millions of hard disk drives every year – roughly one device every six seconds, according to Clark.

While the success rate is maintained at such high levels, the failure rate of even a fraction of a percentage can result in the production of a million defective drives. Therefore, minimising customer losses is critical to its operations, and the company’s priority has been minimizing the distribution of such defective units.

“Should yield drop or a device of poor quality find its way into the marketplace, that will impact Western Digital’s bottom line through brand advocacy, perceived reliability and returns handling,” notes Clark.

Industrial Data Summit advanced analytics Big Data Digital - image courtesy of Depositphotos.
Manufacturers want to transition from a reactive to a predictive approach, and need a solution able to handle the increasing amount of data they are producing – image courtesy of Depositphotos.

While the Hard Disk Drive (HDD) Analytics department had been using software to perform root-cause analysis of yield excursion for several years, KH Sim, Director of HDD Analytics at Western Digital, wanted to transition from a reactive to a predictive approach.

Western Digital also needed a solution able to handle the increasing amount of data its systems were producing.

Western Digital had built a comprehensive data mart with thousands of variables comprising data from various manufacturing and supply chain processes. Due to the large volume of data, Western Digital sought an enterprise solution, and it wanted to build predictive models on that data. The company turned to SAS for a big data analytics solution.

How does it work?

SAS Asset Performance Analytics monitors equipment sensors and tags machine-to-machine data to identify hidden patterns that predict failures.

“Our comprehensive analytics software solution captures and analyses production information through MES, sensor data, image data, and applies that to AI and machine learning to generate a level of predictive quality failure,” says Clark.

“SAS has given Western Digital the ability to do complex data analysis generating new useful analytics insights for its business. With a built-in case management system, the solution gives Western Digital engineers the insights they need to identify possible failures early in the production process and make timely decisions to avoid a yield excursion, ensuring Western Digital hard drives are of the highest quality.”

Data collecting and display Stock Image
Engineers can perform a series of functions, including data extraction, data conversion and data analysis.

The engineers can perform a series of functions, including data extraction, data conversion and data analysis.

All device performance indicators are monitored, so once an exception occurs with the device, the system can provide an alert to the engineers so they can make critical decisions quickly.

Western Digital’s precision in identifying a yield excursion lowered the overall number of returned units, which in turn has boosted customer loyalty and trust, having a direct bearing on the company’s revenue.

“Overall, SAS was able to increase the efficiency and the output, and the overall drop in yield excursion had an impact by reducing the number of units being returned, boosting customer loyalty and trust, and having a direct bearing on Western Digital’s revenue,” Clark concludes.

Western Digital is a prime example of how a large organisation can leverage SAS advanced analytics to achieve greater production quality. However, it is important to highlight that manufacturing businesses of any size can leverage the capabilities offered by SAS. 
 
With a simple and easy engagement model, SAS also provides a full analytics capability as-a-service. This empowers every and any organisation to begin an analytical journey to drive greater insight around profitability, margins and cost reduction. 
Tim Clark, Head of Manufacturing, SAS
Tim Clark, Head of Manufacturing, SAS.

To learn more, please contact Tim Clark on:

[email protected] 

+44 (0) 161 888 2065

+44 (0) 7979 366 142