8. The Digital Twin for Geometrical Variations Management 4.0
Release Date: 03/13/2019
Robin Teigland explains how digitalization is changing the competitive paradigm of “traditional” businesses, where multinational corporations perform on the basis on size, structure and ownership of resources. Robin gives us many examples of how the digital disruption can start actually small, based on principles of resource sharing and open innovation. Robin Teigland is a Professor in Management of Digitalization in the Entrepreneurship and Strategy Division at Chalmers University of Technology.info_outline 10. Smart Manufacturing: a Simulation-based Perspective
What does the Industrial Internet of Things mean when put into the context of Smart Manufacturing? Sanjay Jain from George Washington University, Washington, DC, breaks it down in three pillars: connectivity, intelligence and automation. Sanjay focuses on the intelligence part mainly. He shows how synthetic data generated by manufacturing simulation models, when feeding data analytics techniques, helps us to predict cycle times and delivery rates accurately, even with a limited training dataset.info_outline 9. Assessing Smart Maintenance
Jon Bokrantz, Chalmers University of Technology, explains: This shared understanding of smart maintenance is rooted in the Swedish manufacturing industry. They really defined what it is. He also talks about "Smash – assessment of smart maintenance". The aims to SMASh project was to enable digitalization of the Swedish manufacturing industry. Many different management roles were involved in the development of the assessment tool.info_outline 8. The Digital Twin for Geometrical Variations Management 4.0
Professor Rikard Söderberg, Chalmers University of Technology, takes us to a journey from the dawn of the engineering discipline of geometrical assurance to the digital twin as key to manage product tolerances and adjust the production according to the varieties of the upcoming products.info_outline 7. Big Data for Big Decisions in Maintenance
Instead of defining big data in terms of “what” and “how”, Mukund Subramaniyan invites us to asks: “why” big data? In this episode, Mukund Subramaniyan, Chalmers University of Technology, shares his adventure and precious knowledge as cross-disciplinary PhD student, bridging the gap between computer science and production engineering.info_outline 6. Optimal Factory Layout thanks to Virtual Reality
“With a realistic model of the factory [in VR], actors affected by changes in factory layout are actively involved in the planning process”, says Liang Gong. He is a PhD student at Chalmers University of Technology (Production Systems), and is the expert of Virtual Reality technologies adoption in his research group. He talks about why computer aided design (CAD) and simulation tools are great for estimating quantitative measures in factory layout planning.info_outline 5. Utilizing Data from the Production System
This is a special episode, because Maja Bärring and Daniel Nåfors are the first PhD students who have been interviewed in DigiTalk Pod. Maja’s research focuses on understanding the value of data brought by digital technologies in production, such as the 5G and blockchain, whereas Daniel’s research focuses on supporting layout planning in factories via 3D laser scanner technology applied to virtual reality.info_outline 4. The Future of Maintenance
How to achieve a failure-free production? Listen to Anders Skoogh, Associate Professor and research group leader for Production Service Systems & Maintenance at Chalmers. Anders brings a perspective that combines technology, management and strategy and that transforms the concept of maintenance from reactive and insular to proactive and collaborative. Anders, being the Director of the Production Engineering Master Programme, describes how digitalization has been brought into curricula.info_outline 3. The Digital Factory
Professor Björn Johansson talks about virtual production and digital twins, and shares with us how digital tools can help improve the sustainability performance of factories.info_outline 2. Sustainable Manufacturing
Assistant Professor Mélanie Despeisse takes us to a journey starting from the quintessence of manufacturing – using valuable resources to produce value for society – to sustainable manufacturing and related concepts.info_outline
Guest: Professor Rikard Söderberg, Chalmers University of Technology, Head of Department of Industrial and Materials Science and Director of Wingquist Laboratory.
“If we feed our simulation algorithms with real-time data, we can compensate [geometrical deviations] and optimize the production”.
Professor Rikard Söderberg takes us to a journey from the dawn of the engineering discipline of geometrical assurance to the digital twin as key to manage product tolerances and adjust the production according to the varieties of the upcoming products.
The goal? Reduce costs, waste, and improve quality. Speaking about research utilization and marketable innovation, Rikard invites current budding researchers-entrepreneurs to keep their vision tight and to work hard in a journey that can last for up to 20 years.
• Rikard introduces the episode by talking about how his different professional roles act in synergy. He also stressed the importance of focus, vision (personal effectiveness) and elimination of time waste (personal efficiency).
• Rikard Söderberg continues with the history of geometrical variation and geometrical assurance as engineering discipline in manufacturing/production research. Despite this discipline being quite “traditional”, he stressed the importance of bringing it to the industrial practice in order for companies to achieve cost reduction and value-creation opportunities in terms of quality, both “real” and “perceived”.
• Rikard explained the alternatives of securing quality upfront by putting proper tolerances on key features of the product (the stricter tolerances are, the more expensive they will be), as opposed to be “more relaxed” in product design but run higher quality-related and functionality-related risks during the use phase of the product. Software packages can help companies manage this trade off in early product development phase.
• Rikard introduced the concept of the digital twin, a digital copy of the real world product. This digital twin of the product “works” through simulation algorithms that are fed with real-time data from the shop floor. The digital twin needs to be precise and accurate. But, again, what’s good enough? Can we scan same takt time as the production line?
• Rikard talks about the “reparatory” power of software programs combining analytics and production simulation that compensate in production what goes wrong as the product gets manufactured. However, calculations of these “compensations” need to be made in the same takt time of the production line, and this is a challenge. Opportunities exist, though. Components can be scanned when they leave the supplier’s site.
• In relation to the software packages with the capabilities described above, Rikard added that the tougher the competition is in the market for manufacturers, the higher the need for tools for tolerancing is.
• Speaking about innovation, Rikard invites current budding researcher-entrepreneurs to keep their vision tight and to work hard. Results can show up in up to 20 years.
• A final line from Rikard: “Coming from product development, the final validation is when somebody buys your product”.
Check out some of his publications:
Rikard Söderberg, Kristina Wärmefjord, Julia Madrid, Samuel Lorin, Anders Forslund, Lars Lindkvist. An information and simulation framework for increased quality in welded components. CIRP Annals, Volume 67, Issue 1, 2018
Edward Morse, Jean-Yves Dantan, Nabil Anwer, Rikard Söderberg, Giovanni Moroni, Ahmed Qureshi, Xiangqian Jiang, Luc Mathieu. Tolerancing: Managing uncertainty from conceptual design to final product. CIRP Annals,Volume 67, Issue 2, 2018, Pages 695-717.
Rikard Söderberg, Lars Lindkvist, Kristina Wärmefjord, Johan S. Carlson, Virtual Geometry Assurance Process and Toolbox. Procedia CIRP, Volume 43, 2016, Pages 3-12,