In today’s market, industries are changing and business models are evolving faster than anyone could have imagined.

Data is driving a new revolution and we are in the midst of a truly transformative period of time. From smart connected products to predictive and prescriptive analytics, the ideas of yesterday are quickly becoming the reality of today.  As companies continue to innovate and disrupt industries, one thing is for certain: there will be companies disrupted by this change. Now is the time for you to harness the power of emerging technologies to become a disruptor in your space and redefine your industry.

Join our webinar and learn:

• What emerging technologies really mean for your business and why it’s important to embrace it
• Current market trends for AI and ML, edge vs. cloud and business transformation, and where the landscape is headed
• Real-world examples of how businesses are leveraging emerging technologies to gain a competitive edge
• Best practices and considerations for getting started on the right track

Speaker

Jonathan Weiss, Vice President – Emerging Technologies, Software AG

Jon is an innovation and technology thought leader with extensive experience in leading customer engagements, explaining technical topics in an easy-to-digest fashion and understanding not just technical architecture, but also the strategy behind implementing effective solutions. He has proven skills in team leadership, technical management, IoT/IIoT and software sales.

Jon has spent the last decade working with some of the world’s largest companies, such as: P&G, GE, Pfizer, PepsiCo, Intel, HPE, Foxconn and many others seeking to undergo digital transformations in their manufacturing facilities, supply chain initiatives and enterprise applications. He has a very successful track record in leading teams throughout the entire SDLC process, from pre-sales engagements to global roll-outs for hundreds of factories in AJP, EMEA and the Americas.

Jon prides himself on being a trusted advisor for his customers, responsible for leading technical workouts, managing technical teams, assessing technical and business needs, and delivering market leading solutions that provide quality and value beyond the customer’s expectations.

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Join us for this webinar by the team led by Dr. Qian Wang, Professor of Mechanical Engineering, The Pennsylvania State University. This project is supported by a 2018 DCED Manufacturing PA Innovation Program Award.

Laser-based additive manufacturing (AM) processes involve a large number of process parameters that affect the final geometry, mechanical property, material microstructure, and surface roughness. Existing analytical models are often restricted by over-simplified assumptions and thus not suitable for real applications, whereas high-fidelity numerical models such as finite-element-analysis based models can be computationally expensive to be used in real-time build control.

This project proposes a machine learning approach to model the relationship between process parameters and the build geometry, by utilizing physics-based insights to define input features as well as modeling architecture. A suite of machine learning algorithms will be examined for their efficacy in model prediction. Simulated data generated from the Autodesk’s Netfabb Local Simulation are mainly used for model training and testing, and experimental data will also be collected to further calibrate the model. Success of the project will help reduce the level of trial and error currently required in AM industry and thus help reduce the associated cost.

As noted in Garry Kasparov’s most recent book, a good team + a good computer will consistently beat having only a great computer or a grandmaster. The same is true for manufacturers looking to compete in the new world of Industry 4.0, and the wave of technologies being introduced as the Industrial Internet of Things (IIoT).

The winning companies will not simply be those who purchase the best or the most technology, but those who can iteratively integrate it into their current systems in a way that incrementally improves cash flow, reduces cycle time, and minimizes downside risk through many, small steps and continuous learning in between. The companies with the best problem solvers will win. In this view, new technologies will enable our employees to solve new classes of problems more quickly, with deeper visibility into the entire supply chain. Join Dr. John F. Carrier from MIT on March 13th to learn a systems thinking approach to the IIoT.

• Review the 5 key technologies of the IIoT
• Discuss the concept of the “hidden factory,” and how the IIoT will help companies better address this classic, systemic problem inherent in all systems
• Show how the IIoT can be used to re-invigorate your Lean and Six Sigma efforts to produce a new level of synchronization and performance
• Provide examples of companies “winning” the problem-solving game in the age of IIoT, and how they are building dynamic competitive advantage within their supply chains

Speaker

Dr. John F. Carrier, Senior Lecturer, System Dynamics Group, MIT Sloan School of Management

Dr. John F. Carrier is a Senior Lecturer in the System Dynamics Group at the MIT Sloan School of Management. He has spent over 25 years diagnosing and eliminating hidden factories in the oil & gas, petrochemical, discrete manufacturing, and research laboratory facilities, saving these organizations hundreds of millions of dollars while reducing operating risk. He also works with companies to successfully integrate the technology of the Industrial Internet of Things into their existing organization, with a distinct focus on developing front line leaders in the culture of improvement.

He currently runs a popular MIT Executive Education course on Implementing IIoT through Continuous Improvement Leadership (https://tinyurl.com/yafmbdqe). He also co-teaches an MBA course with Professor John DC Little (Little’s Law).

Dr. Carrier holds a BS in Chemical Engineering from the University of Michigan, an ScD in Control Systems from MIT, and an MBA from the Harvard Business School.

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