Engineer & Experimentation Station
Eminent Professor of the INVENT Lab
Texas A&M
Enabling technology with a focus on business innovation and processes, Cynthia Hipwell is bringing her industry knowledge to academia by bridging the gap at the Texas A&M’s Invent Lab.
Hipwell shares how we’re just at the beginning of Industry 4.0. The importance of capturing data to draw correlations to drive innovation and how humans play a role in determining the ‘why’ behind machine learning technology. Especially in manufacturing, the Digital Twin fuels improvement models by laying the foundation for data-feedback loops. Thanks to machine-to-machine connectivity and IoT devices being able to capture sensing data.
To drive innovation, Hipwell shares a few models of improvement. But first - you must ask yourself ‘What are you trying to improve? What parameters do you know are important for the system?’. The answers that come out of that exercise will help you determine how to set up the right infrastructure to sense, capture and process the data for learning. Developing machine learning may seem intimidating to start, but a good way to begin is by creating the algorithms to develop basic correlations that drive insights.
Hipwell clearly defines two paths for innovation: ‘breakthrough innovation’ and ‘incremental innovation’. Both are necessary to enable growth at an organization, and each has their own management practices that she shares, from waterfall, agile process and build-measure-learn frameworks.
To truly bring change to a company, it is important to bring on the right team, get buy-in from leadership and align on budget to bring ideas-to-life while keeping the bottomline in mind. Hipwell shares practical experiences on how to introduce innovation and how to schedule a miracle into your R&D and innovation schedule.
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