The podcast explores the use of digital tools in materials science and their applications in various industries. It highlights the importance of data collection and community adoption of digital tools in materials science. The chapter also discusses the predictions for the future of digital tools in materials science and the potential for sustainable manufacturing.
Data collection and aggregation is crucial for digital tools in materials production, enabling optimization and real-time feedback.
Digital tools face challenges in adoption due to limited investment, resistance from employees, and the need for de-risking and proving their value.
Deep dives
Importance of Digital Tools in Materials Production and Development
Digital tools play a crucial role in materials production and development. One key aspect is the collection and aggregation of data, which forms the basis for these tools. Advancements in computing power and sensor technology have made it possible to collect more data than ever before, even in harsh industrial environments. This data can be used to optimize processes, improve efficiency, and provide real-time feedback to operators. Additionally, digital tools integrate the physical and digital aspects of production, allowing for seamless communication and interaction between different systems. However, the adoption of digital tools in the foundation industries can be challenging due to cash constraints and resistance from more senior employees. Overcoming these challenges requires starting small, demonstrating the value of digital technologies, and gradually scaling up.
Role of Data and Turning Data into Actionable Information
Data collection is essential for digital tools, but the real value lies in turning that data into actionable information. This involves organizing and aggregating the data in a way that is useful for operators and decision-makers. Digital tools can provide real-time insights, optimize processes, and identify patterns and trends that might not be apparent through traditional means. To achieve this, tools such as machine learning and artificial intelligence can be employed. However, it's important to strike a balance between functionality and usability to ensure that operators can effectively interact with these tools and understand the reasoning behind their suggestions or recommendations.
Barriers and Challenges in Implementing Digital Tools
The implementation of digital tools in materials production and development faces several barriers and challenges. One significant challenge is the limited investment and cash constraints in the foundation industries, which make it difficult to prioritize digital technologies over other initiatives. Another challenge comes from the resistance and reluctance of some employees, particularly more senior ones, who may view digital tools as IT projects rather than crucial tools for improving processes. Overcoming these challenges requires de-risking and proving the value of digital tools, demonstrating their potential through small-scale projects, and highlighting the long-term benefits they offer.
The Future of Digital Tools in Materials Production
In the future, digital tools are expected to become an integral part of materials production, seamlessly integrated into everyday operations. The distinction between digital and physical tools will blur, as digital tools become the norm rather than a novelty. Integrated workflows, where digital and physical tools interact and communicate, will be the standard. Smart factories and data factories will emerge, where AI and machine learning technologies control the production process, and humans have oversight and contribute to AI development. The nature of jobs will change, with a shift towards higher-skilled roles focused on AI and machine learning development, while traditional manual and dangerous jobs are automated.
There are many benefits for the adoption of digital tools, including machine learning, in materials production and development. However, widespread use remains low in part due to a lack of knowledge and understanding of its applications. What is the state-of-the-art and how could the deployment of digital tools shape materials production in the future?
This episode was sponsored by Innovate UK Transforming Foundation Industries Challenge. This challenge is providing funding and support to create a cleaner, more efficient and more competitive sector that is fit for our future. Find out more by searching ‘Transforming Foundation Industries’ or going to this link.
Guests:
Chris Oswin – Manager of Digital Technologies group – Materials Processing Institute
Dr Tom Whitehead– Head of Machine Learning – Intellegens
Thanks to Kolobyte and Alphabot for letting us use their music in the show!
If you have questions or feedback please send us emails at materialism.podcast@gmail.com or connect with us on social media: Instagram, Twitter.
Materialism Team: Taylor Sparks (co-creator,co-host), Andrew Falkowski (co-creator), Jared Duffy (production, marketing, and editing).
Keywords: UKRI Construction Digital Tools Machine Learning
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