Predictive maintenance: How does data science revolutionize the world of machines?
In today’s world of machines, there are two leading maintenance techniques to support a standard machine lifcycle. Predictive maintenance revolutionizes the future of machines. It tracks each of the machines’ unique lifecycle and doesn’t generalize. It allows us to know if our machines need to be attended to in advance.
This maintenance method provides information on upcoming, unknown, or unpredicted critical failures and creates an effective and innovative environment. Using data science to solve predictive maintenance revolutionizes the way we look at machines. It changes the data collection approach, enhances its quality, and allows proper usage of the collected data.
Victoriya Kalmanovich shares a special maritime case study and discusses the big promise of predictive maintenance. In a world full of machines, we need to be the bridge connecting the methods of the past to the opportunities of the future.
Victoriya Kalmanovich is an R&D group lead at a large maritime corporation in Israel. She specializes in healing work environments by addressing them as startup companies and promotes and leads innovative and broad processes throughout the organization. In her day-to-day experience, she deals with all technological issues, product management, budgets, and client handling of her group. She’s an education enthusiast and often uses educational directives as a part of her management strategies, especially guiding group members and leadership. She’s also a firm believer in deploying data science where there’s a great value for data. She’s organized a successful data science hackathon and is forming a data science community within her organization. She also gives talks about management, leadership, and workplace challenges.
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