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Nike Uses IRIS Explorer to Design Hi-Tech Footwear

Mark Johnston, Project Manager, Advanced R&D Group, Nike Inc.

Flexible and powerful computer visualisation software is helping a world-famous sports and fitness company’s ‘R&D SWAT Team’ look for technological developments that can take it into the future with improved products and processes.

Mark Johnston, Project Manager, Advanced R&D Group, and his Footwear Design and Development Group in Beaverton, Oregon are carrying out a corporate mandate to study promising technologies and major product opportunities at Nike Inc.

“We evaluate everything,” Johnston says of his cross-functional team of computer programmers, biomechanics experts, and mechanical engineers. “The department looks at all opportunities from low-level technologies - computer tools that could help us design products faster to meet the needs of the individual - to new systems for how to fit a shoe.”

With a background in mechanical engineering and computer science, and over 10 years in the mould making/tool and die industry, Johnston has spent the last 4 years with Nike’s Advanced R&D Group, analyzing thousands of foot shapes, and using this information to define the internal volume of a shoe.

Designing a shoe means creating various components - the outsole, midsole, and upper - and then fitting these components around a foot support unit called the last. Johnston and his team are interested in understanding and perfecting this shape which represents the internal volume of the shoe.

“Traditionally, the shoe last has evolved based upon manufacturing constraints,” Johnston explains. “We are trying to take the opposite approach - having the last evolve through better understanding of foot morphology.”

Today, Johnston and his team know that while the shape of the last somewhat resembles a foot, in some very important ways it does not. Much of the research they are doing - especially including the use of computerised visualisation tools - is to get a better understanding of what the internal shape of a shoe should be.

Armed with a Silicon Graphics Indigo 2 Extreme desktop workstation R4400 processor, four gigabyte hard drive, and 128 megabytes of RAM, Johnston uses IRIS Explorer™, an interactive data visualisation system to analyze data provided by NAG.

The team’s datasets range in size from 4 to 20 megabytes (based on foot scans producing 300,000 points in x-y-z spatial datasets).

“We involve IRIS Explorer in two very important aspects of our research,” he says. “The first is for rapid application prototyping. When we want to try to test a new analysis algorithm - or if we simply want to do ‘what if’ experiments - IRIS Explorer gives us a fast and flexible way to pull together prototype code. The low programming overhead associated with IRIS Explorer is a big advantage to us. To a large degree, understanding our analysis results and the morphology of the foot requires fast and accurate visualisation, and this is where IRIS Explorer delivers the second big benefit. Whether our data is from a laser scanner or a touch probe, IRIS Explorer consistently handles any dataset.”

“The flexibility of IRIS Explorer visualisation tools - especially the Render module - is very important to us.” he says. “We often want to flip very quickly through surface representations - solid, wireframe, point. Exactly what was that bump on the top of the foot that we just looked at? Is that an abnormality in the dataset? Or is that actually a growth on that person’s foot? Cycling rapidly through a number of variations helps us to probe the dataset.”

Johnston says that fitting shoes to feet is further complicated by the fact that feet change shape significantly during the course of the day - even over the course of an hour. “We may have two shapes of a person’s foot from one day to the next, and they may be very different,” he says. “With IRIS Explorer and the additional tools we’ve written for it, we can very quickly look at the two related shapes, compare them, and identify the differences between them.”

The Render module displays geometry data. It is built using the Inventor Scene Viewer which allows a large number of different viewing paradigms. There are two major modes in Render: viewing and selection/picking. In viewing mode, the camera parameters can be changed, and users can toggle between a perspective and orthographic view. Other features include a Fly viewer that simulates constrained flight through space, a Walker viewer for a walk-through allowing motion, a camera pointed with constant eye level, and a Plane viewer that lets the user manipulate the camera with respect to the viewing plane.

Part of the uniqueness of Johnston’s task is that there are very few computer visualisation tools that can do the same functions that the team asks IRIS Explorer to do. The problem, as he describes it, is that off-the-shelf tools expect to see fairly regular shapes and datasets. Feet, however, are amorphous, and they generally break the rules or assumptions that are made by mechanical engineering and CAD packages.

So Nike’s solution is to use IRIS Explorer to bring in datasets, and then probe those datasets with IRIS Explorer so they can see the results in a visual, understandable form. Then they export the data to CAD packages only after it is fully understood.

For screen presentations, the team frequently will do screen captures, then embed them into presentations, documents, or feed them directly into a large format colour plotter that can print images in cross section.

Because the Nike organization employs so many creative people who are visually orientated, top-notch visualisation software is absolutely integral to communicating results. “The people our team talks to couldn’t care less about whether I use a surface normal comparison or if I have 18 decimal points of precision,” Johnston explains. “They want to be able to understand what’s going on at a gut level. The only way to communicate that is through visualisation.”

“And because Nike is so orientated to visual images, if the visualisation is at all ‘clunky’ - if the response is not rapid, if things aren’t rotating smoothly, if colours are off - that can derail the discussion of the results. We take great pains to make sure that whatever we’re going to present will appear as a seamless dataset. And IRIS Explorer visualises, renders and rotates our data just that way.”

For further information on how IRIS Explorer can help you, please contact us today, or visit the IRIS Explorer™ section of our website.