Bearings manufacturer and distributor SKF held a virtual webinar last month to discuss the company’s three-pronged strategy shift to better meet client requirements.
“The strategy has encouraged every part of the company to rethink the way it works, especially SKF’s core research and development (R&D) functions,” said SKF chief technology officer and innovation and business development president Dr Victoria van Camp during the webinar.
She explained that becoming a service provider, rather than a product manufacturer, required a completely different mindset in R&D.
The strategy, which considers artificial intelligence (AI), agility and accessibility includes addressing three topics – usability first, learning from data and innovating through a crisis.
Usability First
One result of the change in strategy is a new focus on making products more accessible and easier to use. This involves combining commonly used products while making them simpler to buy, manage and install.
The mobile application (app), SKF Bearing Assist, is part of the focus on usability first and provides guidance for mounting a new bearing.
The app guides users through the best process for a specific bearing and generates an installation report that can be stored with company maintenance records. The information can be stored in the SKF cloud, making future maintenance and replacement easier.
The company is also working on new products, designed with usability in mind, such as bearing housings that can inform the operator when they are properly aligned.
Learning from Data
SKF is also making better use of the data generated by modern industrial products such as bearings that can be equipped with sensors that measure temperature and vibration.
Connected machines and digital management tools can generate detailed records of the way equipment is used and maintained. However, turning that data into “machines that run and run is a different kind of challenge”, Van Camp said.
She pointed out that adopting a more collaborative approach to R&D was a big change for a 113-year-old company with a strong record of independent research, but highlighted that engaging with the “wider world” was paying dividends “very quickly”.
The SKF AI group made contact with software company Presenso, in Israel, which was working on the application of automated machine learning in industrial reliability.
“It was immediately clear that there was a good fit between what Presenso was doing, and what we wanted,” Van Camp enthused.
SKF’s industrial customers are already benefiting directly from Presenso’s technology, which can automatically sift through the data generated by a factory, identifying issues and improvement opportunities.
“The real power of the AI-driven approach will come from its application to the aggregated data that SKF collects from thousands of customer sites.”
The AI technology can identify the specific issues associated with higher rates of failure, consequently helping SKF to fine-tune its research and making customers’ machines perform better.
“Our engineers spend a lot of time investigating products that fail in the field. The overwhelming majority of our products don’t fail – they outlast the machines in which they are installed,” she stressed.
Innovating Through a Crisis
While SKF’s new strategy was under way before the Covid-19 pandemic, the crisis has proved to be a catalyst for further change.
“Lockdowns were extremely challenging for many of our customers. They needed to keep their operations running despite staff shortages and access restrictions,” Van Camp stated.
SKF brought forward the launch of new products and services, such as its Bearing Assist app – a viable development when innovating through a crisis to provide better support for customers.
“With Bearing Assist, even a relatively inexperienced member of staff can work like an expert,” she added.
Van Camp concluded that SKF’s R&D teams are much more focused on addressing customers’ most pressing challenges to release new solutions in weeks or months.
Edited by: Zandile Mavuso
Creamer Media Senior Deputy Editor: Features
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