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For a pioneer in materials engineering, the sun never really sets
Applied Materials’ sophisticated analytics strategy helps realize critical productivity advantages across its worldwide operations
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Challenge: Speed the future of microchip and display technologies by engineering creative materials solutions that enable Applied Materials’ customers to make their vision a reality.
Solution: Create systematic efficiencies and cost advantages by using JMP to explore multifactor opportunity spaces and overcome the challenges of incomplete data. Lean on data visualization to deepen collaboration between Applied Materials and its customers.
Results: JMP continues to help Applied Materials achieve quantifiable productivity savings and pricing advantages by facilitating the use of vanguard data analytics across labs and customer sites worldwide.
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Over the course of its 50-year history, Applied Materials has left an indelible mark on the evolution of the electronics industry. As the world’s leading materials engineering company, Applied Materials has pioneered many of the products that not only make advanced electronics better, faster and more flexible – but also more affordable. To solve what have become some of the highest value technological problems confronting the industry today, Applied Materials relies on two things: a $1.8 billion investment in R&D that outpaces the industry standard and an integrated, global strategy that builds productivity directly into development cycles.
“Catching inflection points early and making a product that has distinct technical productivity advantages is so important,” says Sidharth Bhatia, Director of Systems Engineering for Applied Materials. “When you say there’s value in productivity, there's an actual dollar amount that can be illustrated.” The easiest way to realize opportunities for optimization in a characteristically cyclical market? Bhatia says that top decision makers need to look at the data.
A data-driven strategy for experimentation and signal processing helps engineers achieve quality targets faster
Applied Materials embraced the movement toward data analytics early on, with top-level management affirming that statistics is helping deepen product knowledge and increase differentiation. Analytical methods are now widespread across the organization. And these techniques are increasingly integrated with IoT concepts. 
Within Applied Materials’ Systems Engineering group, Bhatia’s team uses analytical approaches for structured experimentation and hypothesis testing for a range of functionalities. The important thing, Bhatia says, is for his teams to understand how analog systems interact with each other. “It comes down to trying to control these systems... And to have very good precision, which is basically [differentiating between] signal and noise. That's where a lot of focus is on the analytics because it can definitely… curtail exponential costs and give the product more technical pricing advantages.”
A large part of the work requires engineers to pinpoint and reduce defects within existing systems. “Doing this requires a lot of structured experiments, lots of discipline, lots of analysis in terms of identifying sample sizes for the experiments and doing the right kind of hypothesis testing,” Bhatia says. By understanding which factors affect performance, engineers can specifically replicate these conditions. Signal processing helps them match the performance of an entire fleet of systems to one “golden” system that may outperform the others.
The statistics can be hugely complicated and timelines are tight. But the key, Bhatia says, is data visualization. Graphs do far more than just convey results; they become part of the analytical process. With an interactive graph, you can explore your data and deepen your understanding of how factors interact. And when it comes to data visualization and designing optimal multifactor experiments, JMP is the team’s go-to tool.
A tool for exploring multifactor opportunity spaces, even when data is incomplete
“The first time I saw JMP,” Bhatia recalls, “I knew that with any other software, design of experiments methods would take much longer than what these engineers were showing me.” Bhatia says the most powerful aspect of JMP is visualization; “after that, all the other pieces in the puzzle fall into place.”
JMP provides robust capabilities for efficient and effective information gathering with an unparalleled design of experiments platform that enables engineers to explore multifactor opportunity spaces with interactive visualizations. “We have to figure out how to talk about the data – or visualize the data – in a different way, where the root cause can be drawn out more clearly,” Bhatia says. “For example, [with JMP] you can see the surface of the parameter that you're trying to optimize in three dimensions and you can cut different planes.” Interactive data models like this help Bhatia’s team recognize patterned responses quickly. And these productivity savings really add up with fewer experimental runs needed to optimize outcomes.
One of the biggest challenges Bhatia’s team faces has to do with data access and quality. Applied Materials’ engineers rely on customer data to provide these crucial insights. But customer data is often incomplete; hence the need to think creatively about how engineers can generate the insights they need from customer data that falls short of Applied Materials’ standards. Fortunately, data visualization plays a role here too. Interactive visuals in JMP make it possible to explore and clean up messy data sets before designing the experimentation strategy.
In experimentation and customer communications alike, data visualization is the common language
“In terms of how quickly we can now visually analyze different types of layouts and formats, I can say that what's going in JMP is very, very powerful,” says Bhatia, noting also that visualizations are an important means not just of analysis, but also of communication.
Effective collaboration with customers is central to Applied Materials’ ability to harness productivity advantages. In order to drive innovation in line with inflection cycles, Bhatia’s team must present the results of their analyses to customers – and get feedback – in real-time so that systems can be continually improved and updated. When time is of the essence, Bhatia says that visuals are a central part of communications. A visual can quickly communicate relationships between factors or other important data trends. JMP helps construct a narrative in ways customers can readily understand and react to.
JMP helps Applied Materials teams work smarter, globally
Efficiency in collaboration is not only a concern of customer-facing interactions; internal productivity is also a key to bringing new technologies to market quickly. “The turnaround time to get the data and to publish your key findings is very, very limited in this industry,” says Bhatia. “Moreover, with colleagues and customers around the world, there’s a time-gap that makes a big difference too.”
For example, Bhatia says, “experiments will be done by the end of the day in Asia around 6:00 or 7:00 pm and by that time it's early morning in California and we’re ready to have a meeting with the customer. Sometimes [the data you get from the lab] aren't in the best shape or the plots aren’t the way you want to present to the customer. You can quickly redo all those things using JMP so as to make it easier to communicate with the customer.”
Analytics makes global collaboration so much easier, Bhatia says. And if you have a common data language that you can share and interpret with JMP, you’ll be able to synthesize all the data and process information coming in from labs around the world. And do so around the clock. The growing ubiquity of data – augmented by the nascent possibilities of IoT technologies – are dramatically expanding the benefits of global operations. And thanks to the efforts of Bhatia’s team and others like it, Applied Materials remains well ahead of the curve.
