Episodes
-
Merging AI with operational technology (OT) is no simple
task, between concerns about robustness and reliability as well as data
privacy, there are many challenges to overcome. With that said, the potential
benefits make the endeavor worth the effort. Rather than bringing AI into every
aspect of manufacturing right away, the key for long-term success will be adopting
it gradually through small tasks with immediate benefit that also support
broader, long-term goals.
In this episode, host Spencer Acain is joined by Ralf
Wagner, Senior Vice President of data-driven manufacturing at Siemens, to look
at the steps it will take to bring AI into the manufacturing and operations
world, the key insights he and his team have gained along the way and finally,
what the future will hold for AI in industry.
In the episode you will learn:
·
Challenges of bringing AI into operations (00:57)
·
The future of AI in manufacturing (7:36) -
Artificial intelligence and data go hand in hand together, whether
that’s as data used to train AI models or as AI models used to analyze and
retrieve data. In the industrial world, there’s a fine balance between leveraging
data to fine-tune shop floor AI systems meaning data intelligence is an equally
valuable asset as well. Similarly, AI itself can provide a form of data
intelligence through the lens of an Industrial Copilot capable of aggregating
vast quantities of data into easy to access and understand formats. Bringing
these elements together will be vital in realizing the future of data-driven
manufacturing.
In this episode, host Spencer Acain is joined once more by
Ralf Wagner, Senior Vice President of data-driven manufacturing at Siemens as
he examines the applications of pretrained AI solutions compared to fine-tuning
them for specific deployments. Additionally, he looks at the ways the
Industrial Copilot can be applied to the data-driven manufacturing process.
In the episode you will learn:
·
Out-of-the-box vs. fine-tuned models (0:42)
·
Applications of the Industrial Copilot (5:02) -
Missing episodes?
-
AI will drive the future of data-driven manufacturing with
tools like Siemens Insights Hub already adopting AI in key areas today. For the
manufacturing industry, leveraging data and taking advantage of AI means
leveraging out of the box solutions and robust, easy to use models that don’t
require teams of data scientists. Leveraging data-driven manufacturing will be
vital for companies to traditionally siloed domains and unlock broad-ranging
optimizations.
In this episode, host Spencer Acain is joined once again by
Ralf Wagner, Senior Vice President of data-driven manufacturing at Siemens, to explore
core applications of AI within Siemens Insights Hub, with everything ranging
from out of the box solutions to powerful customizations for expert users.
Beyond that, Ralf examines the importance of data-driven manufacturing going
forward, and why AI will play a key role in that.
In the episode you will learn:
·
What are the 4 applications of AI in Insights
Hub? (00:28)
·
Importance of data-driven manufacturing (11:50) -
Data is playing an increasingly important role in the manufacturing
process but leveraging it to its fullest potential and intelligently applying
it to optimize production process and systems can present many challenges. AI provides
a path to leveraging production and IIoT data to support continuous
optimization and achieve insights faster than traditional methods allow.
In this episode, host Spencer Acain is joined by Ralf
Wagner, Senior Vice President of data driven manufacturing at Siemens, to discuss
the importance of tools like Siemens Insights Hub for smart manufacturing.
Additionally, he will examine the key role AI is playing in these types of
tools and why it will be crucial in achieving the next step in smart
manufacturing.
In the episode you will learn:
·
What is Insights Hub? (2:11)
·
Major AI applications in Insights Hub (10:11) -
Artificial intelligence is already finding a place across
many different areas of the design and manufacturing process but its benefits
aren’t limited to supporting individual, siloed, applications. As both AI
technology and the digitalization of the complete product design process
continue to develop, AI will become a key tool that spans across the entire
breadth of industry, reshaping the entire process from end to end.
In this episode host Spencer Acain is joined by guests Boris
Scharinger, Senior Innovation Manager and Technology Strategist for Siemens
Digital Industries, and Dr. Justin Hodges, Senior AI/ML Technical Specialist in
Product Management for Siemens Digital Industries Software, as they look to the
future of what AI will offer the product design and manufacturing process. They
highlight key AI trends and they impact they are already having at every stage
of the design process, while also examining the impact those trends will have
in the future.
In this episode you will learn:
·
The impact of AI across the breadth of product
design (1:25)
·
The future of AI in industry (7:18) -
Artificial intelligence is having a major impact on the way products are designed and manufactured. Applying AI to the manufacturing industry can help bring a new layer of speed and adaptability to an industry that has traditionally been slow to adopt new trends. AI offers the ability to understand, package, and transport information between systems and users in a more efficient and intuitive way than ever before, enabling new approaches and innovations across the breadth of a factories operations.
In this episode host Spencer Acain is joined by guests Boris Scharinger, Senior Innovation Manager and Technology Strategist for Siemens Digital Industries, and Dr. Justin Hodges, Senior AI/ML Technical Specialist in Product Management for Siemens Digital Industries Software, to examine the ways AI is being applied to the manufacturing process. They cover topics focused on applying AI/ML to critical data within factories, encompassing both usage and analysis.
In this episode you will learn:
· Applications of AI in manufacturing (1:17)
· How AI is accelerating operations (5:01)
· Packaging data with ML models (7:46) -
Advanced software methods, like simulation and the digital twin, are at the core of modern product design, enabling new designs to be tested and validated quickly and efficiently based on real-world data without the need for expensive prototypes. Now, thanks to the latest advances in AI, these key technologies can be taken a step further, allowing for even greater efficiency and new ways of tackling complex problems.
In this episode host Spencer Acain is joined by guests Boris Scharinger, Senior Innovation Manager and Technology Strategist for Siemens Digital Industries, and Dr. Justin Hodges, Senior AI/ML Technical Specialist in Product Management for Siemens Digital Industries Software, to explore the applications of AI in simulation and design, including applying AI to unify different elements of the digital twin and deepening the connection between the virtual and physical worlds.
In this episode you will learn:
· The benefits of moving to smaller models (0:37)
· How reduced order models help bring together digital twins (3:16)
· AI enables DevOps for hardware (7:46) -
With the continuing digitalization of industry, the product design and manufacturing process is becoming more connected from end to end. Taking advantage of that connection and digitalization, artificial intelligence is starting to take a bigger and bigger role across every stage of the design and manufacturing process. Bringing AI into the design process helps organizations achieve both long- and short-term goals while simultaneously accelerating traditionally slow processes, help enable new, innovative approaches to historic problems.
In this episode host Spencer Acain is joined by guests Boris Scharinger, Senior Innovation Manager and Technology Strategist for Siemens Digital Industries, and Dr. Justin Hodges, Senior AI/ML Technical Specialist in Product Management for Siemens Digital Industries Software, to discuss the applications of AI in the early stages of the design process. They discuss key topics such as the application of AI as a decision support system, as well as ways AI is helping address important concerns such as sustainability.
In this episode you will learn:
· What are the applications of AI in the early stages of product design? (4:06)
· How AI is helping address sustainability concerns (6:27)
· How AI enables faster decision making (9:15) -
PLM systems are at the heart of modern, digitally integrated
manufacturing and design companies, helping to support the digitalization of
industry and the advancement of next-generation manufacturing. However, with as
complex as these systems are and with the vast quantities of data available
within them, leveraging a PLM system to its fullest potential isn’t always a
simple task.
In this episode, host Spencer Acain is joined by Charles
Aldave, Product Marketing Manager for Teamcenter, to discuss the ways AI is
impacting PLM systems, both as a means for directly interfacing with users and as
a way to silently speed things up behind the scenes.
In this episode you will learn:
·
What is Teamcenter? (0:43)
·
Creating hallucination free generative AI (2:37)
·
How Teamcenter seamlessly integrates AI (6:00) -
Microchips are getting smaller, denser and more complex with
each passing year not only incurring increased costs, but greater manufacturing
challenges as well. To help drive the continued advancement of semiconductor
technology, the design and testing of these new chips must be ready to
accommodate AI and ML from the ground up.
In this podcast, host Spencer Acain is joined by Ron Press,
Senior Director of Technology Enablement at Siemens Digital Industries, looks
to the future of AI and ML in the chip design and verification process. Ron
explores the needs for cutting edge technology in a field as complex as IC
production, as well as the challenges of adopting that same technology into a
multi-billion-dollar industry.
In this episode you will learn:
·
What is analytical AI? (0:37)
·
Challenges of bringing AI into IC design and
test (4:48)
·
The need for cutting edge technology in leading
processes (6:36) -
Microchips are an integral part of modern society,
controlling devices big and small, simple and complex. Designing these chips
isn’t a simple process by any means but equally so, fabricating and verifying
completed parts is not only incredibly complex, but a vital step in the
manufacturing process. Cutting edge microchips are so expensive to manufacture
that improving yields by even 1% can represent multi-million dollar
improvements in revenue.
In this podcast, host Spencer Acain is joined by Ron Press, Senior
Director of Technology Enablement at Siemens Digital Industries to explore the
ways he and his team are applying AI and ML in Tessent, a key tool in the chip
verification and design process. Additionally, Ron explains the importance of
testing and why the process takes so well to AI/ML.
In this episode you will learn:
·
What is Tessent? (1:04)
·
Applications of AI/ML in Tessent (5:58)
·
What makes IC verification a good fit for
machine learning? (8:56) -
AI is a constantly changing field, sometimes with a
staggering pace of innovation so when considering the development and
deployment of AI solutions it’s important to also understand where the
technology will go in the future. Adapting to the challenges of today while
preparing for the advancements of tomorrow must be key considerations when
developing any AI technology, especially broad-reaching ones like the
Industrial Copilot.
In this episode, join host Spencer Acain and guests Michi
Lebacher and Alessia Bortolotti as they examine the challenges of bringing an
ambitions project like the Industrial Copilot to life, how that project will
evolve in the future, and where AI is leading the industry as a whole.
In this episode you will learn:
The
future of the Industrial Copilot (0:31)
What
it takes to bring AI to industry (5:20) -
The Industrial Copilot is already beginning to prove its
value across industries but ensuring such a powerful AI tool is industrial
grade and ready to deploy not in months or years but in days, isn’t without its
challenges. Addressing these challenges requires a smarter approach to data and
training, as well as extensive cooperation both between new and existing
software tools and with partners seeking to deploy these AI solutions.
In this episode, host Spencer Acain is joined by Michi
Lebacher and Alessia Bortolotti to examine the approaches to data and
deployments, trade-offs and customer benefits of the Industrial Copilot.
In this episode you will learn:
How
the Industrial Copilot integrates across the Siemens ecosystem (0:28)
Training
AI across different disciplines (9:20)
RAG
vs. fine tuning for industrial grade AI (13:55) -
Chatbots and digital assistants aren’t anything new, but their
abilities and perceived intelligence were often extremely limited, giving them
no place in the complex world of industrial design and manufacturing. Now,
thanks to advances in industrial grade generative AI, that’s all beginning to
change. The Industrial Copilot is the first step in that change, offering
human-like assistance and intelligence to users at every level of the
industrial value chain.
In this episode, host Spencer Acain is joined by Michi
Lebacher and Alessia Bortolotti to discuss the applications of AI in the Industrial
Copilot, a generative AI-based tool that assists users across a broad range of
tasks and with intuitive natural language abilities.
In this episode you will learn:
What
is the Industrial Copilot? (2:48)
What are the key areas the Industrial Copilot is
applying AI? (6:08 -
Implementing AI into a complex and often mission-critical
application is rarely an easy task even though it is often highly worthwhile.
Even as AI experts work to bring AI into the applications where it can provide
the greatest benefits, their efforts also have a democratizing effect on both the
tools its being added to and the AI models themselves. This ensures that
everyone will have full access to the tools they need to capitalize on their
own domain knowledge without needing to become an expert in the tool itself.
Join host Spencer Acain in a conversation with Subba Rao,
Director of Manufacturing Industries Cloud for Mendix, a part of Siemens
Xcelerator as he discusses the challenges, benefits and future of AI within
Mendix and the industry at large.
In the episodes you will learn:
·
Challenges of bringing AI to Mendix (0:00)
·
Mendix democratizes industrial AI (4:16)
·
What the future holds (8:08) -
Going forward, AI will be an important part of many
industrial processes, from data analytics to development to manufacturing, there
are many places where AI could step in to boost productivity. However, it is
equally important to make sure that AI is suitable for the roles it takes –
that of an assistant, not a replacement for human expertise.
Join host Spencer Acain along with Subba Rao, Director of
Manufacturing Industries Cloud for Mendix, a part of Siemens Xcelerator as he examines
the application of AI within Mendix, their limitations, and why they chose the
AI integration path they did.
In the episodes you will learn:
·
AI augmented vs. AI assisted (0:48)
·
Applications of AI in industry (8:02) -
When it comes to developing industrial software and
workflows it’s not just expert domain knowledge that is a limiting factor, but
also the ability to transfer that expertise into the required software and
programming languages. Low- and no-code solutions combat this by helping anyone
with an idea translate it, with little to no coding knowledge, into a
full-fledged application and generative AI is at the heart of this process.
Join host Spencer Acain in a conversation with Subba Rao, Director
of Manufacturing Industries Cloud for Mendix, a part of Siemens Xcelerator as
he discusses the ways Mendix leverages AI in low-code application development
and how it is supporting the integration of AI withing industrial apps.
In the episodes you will learn:
·
What is Mendix? (1:19)
·
Key applications of AI within Mendix (4:27)
·
How AI helps build AI apps (7:11) -
When designing a product, there are countless parameters
that must be considered and balanced to arrive at a final, optimal result. In a
traditional design cycle, this is a highly manual process that seeks to reduce
the number of variables as much as possible to simplify the process. Now thanks
to advances in AI, it’s possible to not only handle a greater number of
variables but extract additional information from each one – allowing for
further design refinement.
In this episode, host Spencer Acain is joined once again by
Dr. Gabriel Amine-Eddine, Technical Product Manager for the HEEDS Design
Exploration Team, to examine the ways AI can be used to aid in design space
exploration and what that will mean for the future.
In this episode you will learn:
·
Using AI to handle high dimensionality models
(1:09)
·
Reuse of AI models (9:37)
·
How AI will change the design process (12:24) -
Bringing AI into the fold isn’t always easy. Sometimes, even
knowing when and where it makes sense to apply it can prove challenging and
once potential applications are identified, building trust in the model is also
a critical factor. These are common challenges faced by AI applications in
every industry and while the solutions each one reaches will be unique, they
all share some commonalities.
In this episode, host Spencer Acain is joined once again by
Dr. Gabriel Amine-Eddine, Technical Product Manager for the HEEDS Design
Exploration Team, to continue discussing the creation of HEEDS AI Boost and how
such a complex tool can find its place in industry.
In this episode you will learn:
·
What prompted the creation of HEEDS AI Simulation
Predictor? (0:43)
·
How uncertainty-aware AI can build trust (6:24) -
Design space exploration is a critical step in any product
design lifecycle but just as it’s important, so too does it present numerous
challenges. Designing a product requires balancing a multitude of, often
contradicting, requirements to arrive at as close to an optimal solution as
time constraints allow. Now, thanks to advances in AI, it’s possible to reach
those optimal designs faster and more efficiently than ever.
In this episode, host Spencer Acain is joined by Dr. Gabriel
Amine-Eddine, Technical Product Manager for the HEEDS Design Exploration Team, to
explore the ways HEEDS AI Simulation Predictor is leveraging AI to speed up the
design space exploration process, and what impact that will have on the product
design process.
In this episode you will learn:
·
What is HEEDS? (2:04)
·
How AI is accelerating design space exploration
(5:03)
·
Balancing simulation vs. inference (9:34) - Show more
