MATLAB EXPO 2024 UNITED KINGDOM

In automotive, it’s called a “software-defined vehicle.” But the move toward software-defined products is also happening in aerospace, industrial systems, medical devices, and other industries. Until now, most customer-visible capabilities in products have been implemented as mechanical and electronic subsystems, with certain critical operational functions implemented using embedded software. As a result, much of the functionality has been set at production. Going forward, the features that represent brand-distinctive attributes and customer-perceived value will be defined through software, providing the ability to generate new value throughout the lifespan of the system. This transformation to “software-defined” requires changes in development processes, new synergies between teams, and new ways to leverage products like MATLAB^® and Simulink^®. In this talk, discover key approaches to capturing the value while mitigating the risks associated with the disruptive changes.

JLR's Reimagine strategy is creating a sustainable electric-first modern luxury business. Learn how JLR is using the virtual world, multi-domain simulation and model-based design to develop their world leading vehicles. Witness how JLR brings together the work of thousands of engineers, enabling all to become "Proud Creators of Modern Luxury".

Urenco provides safe, cost effective and reliable uranium enrichment services and fuel cycle products for power generation within a framework of high environmental, social responsibility and corporate governance standards.

Ensuring the safe medium-term storage of legacy waste in a controlled environment presents several unique challenges. These include reducing exposure to hazardous working environments and minimising costs associated with unplanned manual inspection and repairs. Predicting the expected failure time, or equivalently the remaining useful life (RUL) of a storage container requires a data-driven modelling and simulation approach, fully utilising inspection data which is often time consuming and costly to gather.

Discover how Urenco applies statistical modelling, Monte Carlo simulation and predictive maintenance algorithms to model the RUL of containers in a secure storage facility.

Innovation is at the heart of our products at Dyson. Behind the scenes, the development journey of a product relies on multiple design iterations, each of increasing maturity. This allows us to deliver consistent improvements and to learn more about our products and systems. In the past, this development followed a document-based approach, also known as a document centric workflow. 

Embracing a Model-Based Design workflow was essential to developing ever more complex and smarter products. This workflow allows our engineering and design teams to iterate faster and to take on user feedback early in the development process, whilst delivering our groundbreaking technologies. 

Model-Based Design and simulations are the enablers that accelerate our development pace. With this workflow, documents are replaced by a collection of interlinked models. These models encapsulate both requirements and design as well as testing and reports for coverage and verification.

Timely and efficient maintenance of wind turbines plays a crucial role in maintaining power grid security. Automated visual inspection and predictive maintenance facilitates the early detection of faults and anomalies, thereby reducing downtime of critical equipment and improving operational efficiency.

However, developing a fault detection algorithm may require analyzing vast amounts of data, which poses significant challenges to traditional image processing and computer vision techniques. Recent developments in deep learning and machine learning can be leveraged to accelerate and automate fault detection in wind turbines, thereby addressing these challenges.

Visual inspection for fault detection is used across a variety of industrial applications. Classical techniques from image processing and computer vision are often used to great effect, but deep learning has rapidly increased in importance in image analysis applications. Deep learning offers sophisticated image processing capabilities for developing smarter ways to identify and classify defects in images and videos.

In this talk, you’ll see an end-to-end workflow for developing an automated fault detection algorithm for identifying defects on wind turbine blades. Learn how front-end deep learning techniques, such as autoencoders for anomaly detection, can be applied to automate visual inspection algorithms, complementing classical techniques from image processing and computer vision.

Addressing climate impact requires a myriad of new technologies. With traditional methods, these technologies will not have the impact they deserve as the products will be too costly and too late. From electrical vehicles to hydrogen systems, modelling is now relied upon across the product lifecycle for conception, certification, and operation. 

This talk aims to walk through the development of a simplified propulsion system, focusing on establishing traceability, increasing automation, and the latest simulation capabilities in Simulink^®.

This session brings together a panel of senior women technical leaders to share their insights and career journeys across a wide variety of STEM disciplines. The discussion will focus on leadership style, approaches for tackling complex challenges, navigating career opportunities, and the importance of mentorship. All MATLAB EXPO attendees are welcome to attend.

In the 2009 MATLAB EXPO keynote, MathWorks identified the megatrend of “software in everything.” 15 years later, this has certainly come to pass. Indeed, industry is now moving beyond this point to software-centric products where the majority of value the customer gets from the product is dependent on the software. These changes have resulted in increased complexity. The panel will speak about their experience managing that complexity and transforming organisations that were built around physical products into the era of software first.

The discussion will include:

• The creation of software factories that develop, test and deliver in a very different way and managing the need for constant updates in the field.
• The comparison of in-house versus outsourced software development, including the challenges of integrating global teams.
• The adoption of agile methodologies, examining how they can coexist with the longer lifecycles typical of physical products and how Model-Based Design is applicable across these diverse development timelines.

With the rise in electrified mobility, battery systems are a central component in realising the future of transportation. Understanding the behaviour of the battery throughout its lifetime, from individual cell to pack level, is critical to the design of safe and performant airborne vehicles.

See how Vertical Aerospace engineers use MATLAB^® and Simulink^® products across the development of their battery system. This starts with easy and quick accessibility of raw experimental data so engineers can gather the understanding of how cells behave and age throughout their lifetime. This pipeline of experimental data enables efficient parameterization of battery cell models for use in simulation to explore dynamics and performance across a wide range of scenarios. Well-validated cell models enable various teams at Vertical Aerospace to scale up these individual cell simulation models to enable system-level powertrain and full aircraft analysis.

GE Vernova, a pioneering force in the energy sector, is at the forefront of revolutionizing power transmission through high- voltage direct current (HVDC) technology, supporting the rapid growth in renewable energy sources and developing a more flexible interconnected grid across borders. Model-Based Design plays a crucial role in the development and validation of the complex controllers that drive the power needs of our economies today and is a crucial tool in supporting GE Vernova in delivering the infrastructure needed for the global energy transition.

Adopting Model-Based Design with Simulink^® has significantly improved the speed and quality of GE Vernova's development processes, enabling better management of project complexity and scalability with a unified modelling and control system development platform for all projects.

In this talk, learn how GE Vernova uses MATLAB^® and Simulink products to integrate their simulation, validation, and deployment tools, with the ability to optimise the behaviour of both plant and controller, validate their models to grid requirements, and automatically test and deploy to hardware with automation pipelines.

Hear from innovative startups using MATLAB^® and Simulink^® to accelerate their development, and learn more about the MathWorks startup program.

The use of cloud technology is becoming increasingly important for engineers and scientists, enhancing efficiency and scalability. This trend extends beyond software development, as engineers across various industries are adopting the technology. MathWorks provides a wide range of solutions that can be integrated with cloud environments, allowing users to take advantage of the cloud's storage and computing power. This, in turn, improves the quality and speed of development processes.

In this session, we will explore how the cloud transforms MATLAB^® and Simulink^® workflows through different user profiles. Whether you are already familiar with cloud computing or looking to integrate it into your work, this session will offer perspectives on enhancing your development strategies.

The key topics covered in this session will include:

• Working with remote data from MATLAB and Simulink
• Running MATLAB and Simulink in the cloud
• Enhancing project collaboration and automation through DevOps practices
• Sharing code and models more effectively
• Leveraging cloud-based high-performance computing

Engineers focused on safety need to examine the impact of faults to assess the robustness of their systems. Comprehensive safety analyses, particularly the industry-standard failure mode and effects analysis (FMEA), are necessary activities to design safe systems. In this talk, learn about the advanced fault simulation capabilities in MATLAB^® and Simulink^® that are helping engineers perform these analyses and gain more detailed insights about their systems, faster.

Discover show how you can inject faults into a system model without needing any changes to the initial design. This technique is applicable to a variety of modeling environments and is particularly suited to handling faults that are either timed or conditionally triggered by the system’s behaviour.

You will also learn the strategies for establishing clear and formalized connections between system faults, associated hazards, and the logic for fault detection and mitigation. These strategies are crucial for creating a thorough safety analysis framework that can be integrated into the overall system design process.