Tesla Motors, a high-profile electric car manufacturer, was seeking ways to optimize its development cycle to expedite the production of high-quality vehicles. A significant challenge was the time-consuming process of preparing the finite element analysis (FEA) model, particularly the connector portion of its CAE model. The Model S sedan, for instance, had over 300 different fixings and more than 6,000 weld points, including welds, bolts, rivets, adhesives, and MIG welds. The most laborious task was recreating these connectors in the CAD model, which could take up to several days. This process was not only inefficient but also prone to errors, as there was a risk of overlooking a MIG weld or adhesive due to the lack of detail in the CAD file about the type of connector used, its mechanical properties, and the panels it was connecting.

In 2008, PWO Germany was tasked with the development and production of a new steel automotive cross car beam (CCB) for the dashboard of a new car. The challenge was to develop this component based on the CAD model, design space definition, and other pre-defined standards provided by the customer. The component had to meet various specifications related to modal analyses and dynamic loads, which were determined by the expected use of the component. For instance, the eigenfrequency of the cross car beam, when connected to the steering wheel, could not exceed a certain preset value to avoid undesirable vibrations within the vehicle at certain speeds. Other specifications were related to crash and vehicle safety. The challenge was to meet these often conflicting specifications while developing the component in a timely and cost-effective manner.

Assa Ashuach Studio, a London-based industrial research and product design consultancy, was faced with the challenge of designing a stool that was both light and economical. The stool needed to be customised to support a weight of 120 kg. The challenge was to determine how much material could be removed from the design space while still supporting this weight and achieving a unique design. The design and manufacturing process had to be efficient, reducing material waste and cost, without compromising on the quality of the product. The studio was also interested in exploring new design and production methods to achieve unique forms and aesthetic qualities.

The Hydraulic Systems Division of Eaton’s Aerospace Group, based in Jackson, Mississippi, is responsible for designing hydraulic components and systems for many of the world’s military and commercial aircraft. The division conducts virtual testing of many of its designs, including stress analysis, computational fluid dynamics, and dynamic simulation for hydraulic pumps, actuators, motors, and related components. However, the division faced a significant challenge in improving efficiency in meshing. Before 2002, the Analysis Group used a process built into a solver for use on finite-element models. This process was not designed for finite-element analysis and often failed to provide the quality mesh needed when dealing with complex hydraulic components. Meshing complex hydraulic component geometry required a great deal of effort and time, making the process inefficient and cumbersome.

The Durham University Electric Motorsport (DUEM) team, a group of undergraduate and postgraduate students, were faced with the challenge of reducing the weight and improving the performance of their Formula Student vehicle. The team participates in the highly competitive Formula Student competition, hosted annually by the Institute of Mechanical Engineering (IMechE) at the Silverstone Formula 1 track in the UK. The competition requires teams to demonstrate their technical, engineering, design, and manufacturing skills, reflecting the changes and demands of the industry while considering new developments in commercial car racing. The DUEM team aimed to apply the latest weight-saving technology to achieve a faster, more efficient car by optimizing an upright design for multiple load cases. The optimization of the upright design was a complex challenge, requiring design for multiple load cases including bump, cornering, braking, and acceleration loads. The conventional means of design iteration for many load cases by removing areas of low stress at each iteration was time-consuming and the final solution was not necessarily the most structurally efficient.

PSA Peugeot Citroën, a world-class automobile manufacturer, was facing a significant challenge in the development of engine components, specifically the exhaust manifold. The design of the exhaust manifold is crucial for the optimal performance of combustion engines, and it has to withstand harsh operational conditions. PSA conducts complex thermo mechanical calculations to determine the lifetime of the exhaust manifold. From these calculations, design changes are derived and proposed to the supplier of the component. However, the supplier often found it difficult to correctly interpret the design improvements suggested by the PSA CAE engineers. Furthermore, a full evaluation cycle of such a design change took about three weeks, with no guarantee that it represented the final design status after that time. This led to the situation where only a few design changes and evaluations were possible within the given development timeframe, making the design of the manifold a critical task in the engine development. PSA needed to change the overall development workflow to be faster and to be able to evaluate more design variants in the same time.

The Aircraft Carrier Alliance (ACA) faced a significant challenge in the concept and preliminary design phases of a naval ship project. The designers were often required to work with limited data on the major structural design drivers for the vessel. This often led to a largely subjective design approach, which could result in inefficiency and even structural problems being locked-in from the start. To rectify any issues, increased material use, weight, and unnecessary complexity, as well as high design and manufacture costs, could be introduced to the end product. The ACA sought to evaluate the potential of simulation-driven design under the unique requirements of naval ship design.

ÖBB Rail Cargo Group (ÖBB RCG), the freight transport sector of the Austrian Federal Railways, was faced with the challenge of staying competitive in the complex logistics industry. The demand for freight wagons was strong, and meeting customers' needs was a top priority. The company needed to invest in a modern fleet of wagons and locomotives. The trend towards lighter and more flexible wagons led ÖBB RCG to aim for a new, lighter, and more flexible wagon system. The design principles they wanted to adhere to were weight optimization, standardization, and modularization in production and maintenance, and the use of high-strength construction steel. To realize this project, ÖBB RCG collaborated with two major partners – voestalpine, a globally leading technology and capital goods group, and PJM, a provider of railway systems solutions.

CIKONI, an innovation-focused engineering company based in Stuttgart, Germany, was faced with the challenge of creating an integrated digital design workflow for Type IV composite pressure vessels (CPVs). The company aimed to develop a comprehensive digital design process and workflow for CPVs, particularly the state-of-the-art Type IV polymer-lined, carbon fiber overwrapped vessels used in vehicles, and reduce the need for extensive, expensive physical testing. The challenges identified with the design of composite pressure vessels were three-fold: complex material behavior, many constituents, and the need for fast results. For accurate simulation, filament winding paths, material anisotropy and nonlinear damage progression needed full consideration. Additionally, expensive testing for each material and process modification was required. Lastly, simple modeling and efficient computation were needed to reduce simulation cost.

The Research Designs and Standards Organisation (RDSO) was tasked with establishing Indian railways as a genuine supplier of Diesel locomotives for the South Asian and African market. The challenge was to develop a diesel locomotive that met performance, reliability, fuel economy, crashworthiness, and operator comfort demands. The locomotives needed to operate economically and safely for decades under harsh conditions with minimal downtime. Durability of components undergoing repeated fatigue cycles was a major concern, with most units logging more than 1 million miles during the first six years of operation and having a useful life of nearly 30 years. Some major components were expected to last more than 50 years in the used equipment market. Achieving these goals while shortening the development cycle was particularly challenging due to the significant time and cost factors associated with running physical tests on such large, complex machines. RDSO had been using simulation tools since 1990, but the time for pre-processing was too high due to limitations of computing machine and software.

Bental Motion Systems, a member of the Gevasol Group, has been designing and manufacturing advanced power and motion systems for demanding industries such as defense, aerospace, and semiconductors since 1983. The company produces a variety of end applications including motors, alternators, and electrical brakes. To meet increasing demands, Bental continues to advance its in-house capabilities in development, analysis and design, testing, and quality assurance. However, the company faced a challenge in accelerating the design of electric machines while reacting quickly to customer-specific requirements. The R&D team needed to extend its usage of the Altair software suite to cover more physics and gain flexibility in their approach depending on the project phase.

Crimson Racing, the University of Alabama’s Formula SAE team, has been participating in Formula SAE events across the United States for nearly two decades. Despite their long history, the team's most successful years have been the past five, thanks to a focus on understanding and justifying every component of their race cars. The team had made significant advancements, reducing the vehicle weight by nearly 200 pounds and advancing from a perennial 90th place to a Top 20 team in 2017. However, they set an ambitious goal to place in the top 10 at FSAE Michigan, which would require beating many of the best teams in the world. To achieve this, they decided to add a front and rear wing to their vehicle. This change, while significant for aerodynamics, also affected the structures of the vehicle, increasing loading, raising the center of gravity, and increasing the drag force which the powertrain system must overcome. The suspension team had to revalidate every load-bearing suspension component to ensure adequate strength and stiffness requirements would be met, a complex task when analyzing parts moving in three-dimensions.

Samsung R&D Institute India - Bangalore (SRI-B), the largest R&D centre outside Korea for Samsung Electronics, faced significant challenges in the mobile devices industry. The industry is fiercely competitive, with companies constantly being pushed to innovate their hardware design. The design cycles are becoming shorter, and cost margins are narrowing, leading to a greater emphasis on virtual testing using computer simulation. Traditionally, an analyst would use Finite Element Analysis (FEA) to iterate a design until a feasible solution is reached. However, due to the limitations of manually exploring the complete design space, the acquired solution is not always necessarily an optimal one. One of the critical tests to determine the reliability of a mobile device is the drop test, which often reveals weaknesses in the housing design.

Empire Cycles, in collaboration with Renishaw, aimed to design and manufacture the world's first metal 3D printed bicycle frame. The challenge was to leverage the freedom of additive manufacturing to create a bicycle frame that was not only innovative but also surpassed existing standards in terms of weight and strength. Chris Williams from Empire Cycles had been using Additive Manufacturing components in production for many years, but wanted the opportunity to test it out on a full bicycle product. The team at Renishaw thought that a standard simple part of the bicycle like the seat post would be the best fit for additive manufacturing and weight reduction, as this is a known entity and simple enough to validate and test.

CLAAS, a leading manufacturer of agricultural machinery, was facing the challenge of reducing production and serviceability costs of their harvester reel hub assembly system. The existing system, although successful and field-proven, was identified as a candidate for redesign to improve profitability and customer satisfaction. The primary objective of the redesign was to increase serviceability by making an individual reel hub easier to replace without compromising the rigidity of the existing assembly design. The incumbent design had numerous welded lap joints that provided enhanced stiffness, which was a critical factor to maintain in the new design. The challenge was to find a unique reinforcement bead pattern that would meet the redesign objectives while using the same material stock and package envelope.

Tallent Automotive Ltd, a leading designer, developer, and manufacturer of innovative chassis structural and suspension systems, faced a significant challenge. The company supplies to major automobile manufacturers like BMW, Ford, General Motors, Honda, Jaguar, Land Rover, Nissan, Porsche, Renault, Saab, and Volkswagen. With the growing demand for lightweight, fuel-efficient vehicles, Tallent Automotive needed a more automated method to produce minimum mass sheet metal chassis components. The new method had to consider performance targets and manufacturing constraints. The traditional design process of CAD followed by CAE verification was not efficient enough to meet these demands.

CEVA, a leading licensor of wireless connectivity and smart sensing technologies, faced a significant challenge in managing their engineering resources and speeding up their VLSI development flows. As an IP design and licensing company, CEVA's most critical metrics are time-to-market and engineering efficiency. The challenge was to allow the engineering team to work as if they have no constraints, enabling easy access to hardware compute servers, EDA licenses, and automated design flows without exceeding a project’s R&D budget. The team at CEVA selected the Altair Accelerator™ job scheduler for their VLSI workflows to address this challenge.

Samsung SDI, a global leader in the high technology and environmental battery industry, faced several challenges when transitioning to the electronic materials business. The company had to shift from digital display control circuits to battery control circuits, necessitating a new approach to electronic designs and related printed circuit board (PCB) manufacturing technologies. A robust solution for PCB design review and verification was required for both existing and new products. Additionally, after acquiring a significant player in the automotive battery pack business, Samsung SDI needed a solution that could establish and deploy PCB design review and verification where the design rules and user environment were centrally managed.

Annapurna Labs, a fabless chip start-up acquired by Amazon Web Services (AWS), was facing challenges in managing workloads on dedicated Amazon Elastic Compute Cloud (EC2) instances. The team could occasionally scale up by manually adding new On-Demand instances, but the process was not automated, leading to inefficiency, forgotten unused compute resources, and either under-scaling or excessive scaling. As a chip design company, time-to-market and engineering efficiency were critical metrics for them. The team needed a solution that could add structure and efficiency to scaling AWS compute resources, shorten time to results, and change the development model to Continuous Integration.

TEAMTAO, a collaboration of Newcastle University, SMD (Soil Machine Dynamics Ltd), and UK Research and Innovation, was competing in the Shell Ocean Discovery competition, a global challenge to advance deep-sea exploration using autonomous subsea drones. The goal was to develop underwater robots that could fully map 500 km2 of seafloor at a 4 km depth in less than 24 hours with no human intervention. TEAMTAO’s unique concept was to develop a swarm of these devices all communicating with each other and sharing information. The compact autonomous platform consisted of the BEMs (Bathypelagic Excursion Module), a swarm of vertically swimming AUVs and the surface vessel. It also had a 'vending machine' style autonomous surface catamaran that was responsible for the horizontal transit, data handling, communication, and recharging of the BEMs. The challenge was to test the devices in a range of different scenarios at deep depths without risking the prototype.

Sheet metal stamping is a crucial process in the automotive manufacturing industry, with a variety of tool, die, and process combinations used to create a diverse range of components. Traditionally, identifying the optimal stamping process for a specific part design has been a labor-intensive and time-consuming task, heavily reliant on the knowledge and skill level of the stamping engineer. Ford Mexico sought to address this issue by documenting successful metal stamping production runs over a five-year period. The goal was to capture in-house domain knowledge and best practices to expedite the selection of the best stamping process for future production runs. This would enable increased plant efficiency and part quality, reduction of scrap material, and the ability to rapidly train new personnel. However, the challenge lay in the growing design complexity, non-conventional material types, and numerous process combinations that could challenge even the most experienced process engineer, necessitating a labor and material intensive trial-and-error prove-out process.

Vierhout Engineering (VE), a professional independent engineering services provider, was approached by Universal Corrugated B.V. (UC) to analyze and simulate one of its machines. The machine was incredibly complex, and VE realized that traditional Finite Element Analysis (FEA) might not be sufficient for this project. The traditional FEA process required significant effort and expertise to prepare the models for analysis, especially for geometry simplification and meshing. The machine's complexity meant that each component or system had to be simplified and divided for analysis, a time-consuming process that often reached the hardware limits of the computers used. Large structural frames also had to be analyzed with simplified beams and sheet elements, a cumbersome, error-prone, and time-consuming process.

Valeo, a leading automotive supplier, was faced with the challenge of covering a broad range of simulation tasks for model preparation of glass fiber polymer composite parts. The company was focused on lightweight design with the primary aim of reducing CO2 emissions and achieving improved fuel consumption. The typical development process involved model generation and preparation, the actual solving, post-processing, and result interpretation. However, due to regulatory requirements for CO2 emissions and the overall need in the automotive industry for better fuel efficiency, it was becoming increasingly important to consider lightweight issues within the development of automotive parts. This drive for lightweight design required new and lighter materials in vehicles. The challenge was to make these processes as efficient as possible while keeping software investments low. For continuous improvement, Valeo validates its development processes each year, always on the lookout for additional efficient tools to handle the simulations involved in their development processes.

VR Steel, a company that designs, builds, and repairs fabricated mining equipment attachments, was faced with the challenge of optimizing dragline bucket performance and productivity for a wide range of media and mining conditions globally. They needed to develop a new, optimized bucket design that balanced efficiency, capacity, durability, and projected O&M costs. The company wanted to streamline the design process and provide their customers with design solutions that were guaranteed to fill easily and empty completely, operate at maximum capacity, boost wear protection, reduce operating costs, and improve overall efficiency.

VR Steel (Pty) Ltd, a company that designs, builds, and repairs fabricated mining equipment attachments, including truck load bodies, was faced with a significant challenge. The company aimed to reduce the mass of a truck load body while maintaining its structural integrity and increasing its performance. The challenge was not only to streamline the design process but also to reduce prototyping costs. VR Steel needed a simulation tool that could help them achieve these goals. Their customers also demanded proof that the new design would unload more quickly, lower operating costs, and withstand heavy use. The challenge was to find a solution that could meet all these requirements while also providing a competitive edge in the market.

Nemag BV, a manufacturer of grabs for handling bulk materials, faced a challenge in developing a new generation of grabs for iron ore that were faster and lighter. The traditional process of developing grabs involved building physical prototypes, which was expensive, time-consuming, and limiting. It was difficult to predict the performance of a new design, especially the interaction between the bulk material and the grab, which heavily influences the performance. The traditional methods were not sufficient to understand what happens inside the grab. Therefore, a virtual prototyping approach was developed at TU Delft to model iron ore pellets in interaction with grabs.

The case study revolves around the challenges faced by engineers in testing and prototyping complex mechatronic systems. The traditional approach of relying on physical prototypes is not only costly but also time-consuming. Moreover, it often comes too late in the design process. The situation is further complicated when the equipment is intended for high-risk and high-cost operations such as defense, offshore, or space. In such cases, engineers need to test feasibility, accessibility, and plan operations meticulously. Another challenge is the communication and demonstration of the value of complex machine operations, especially for off-highway and industrial equipment where access to equipment and worksites for demonstration or training is impractical.

The Western Sydney Solar Team was tasked with designing the most efficient and aerodynamic single-seat solar car possible, while ensuring driver safety and adhering to class rules. The team had a predetermined design of the solar car body shape that was optimized with the primary focus on reducing aerodynamic drag. However, they faced challenges in optimizing the monocoque chassis, bulkhead structure, and motor housing of the car within the existing design. They also had to adhere to strict design load cases set out in the class rules as well as minimum g-force strength requirements to ensure driver safety. Furthermore, they had to design and optimize the roll-hoop to safely accommodate the driver. The team was provided with a geometric model of the car that set out the chassis and structure, but no design existed for the roll-hoop.

AB Lundbergs Pressgjuteri, a die-casting company based in Vrigstad, Sweden, faced a significant challenge in their operations. The company was tasked with casting six identical details simultaneously, each round taking about a minute to cast. However, due to the details' thinness, the exact right amount of heat had to be applied to prevent any detail from freezing or hardening too soon. This precision was critical to meet the standard measurements required by their clients, including an international retail company for whom they made brochure holders. The challenge was further compounded by the need to explain the process, problems, and potential solutions to clients in a clear and understandable manner.

Porsche AG, a renowned automotive company, was faced with the challenge of improving the total design balance in e-motor development. The powertrain of electric vehicles had to be developed considering an increasing number of internal, customer, and legal requirements. Classical development strategies involved individual development routes for different requirements and different organizational structures responsible for fulfilling these requirements. This led to development taking place in several parallel disciplines, often resulting in negotiations and unfavorable compromises to reach a final acceptable design. Porsche aimed to adopt more integrated and holistic development strategies to better meet future requirements without significant sacrifices on target fulfillment. The challenge was to design optimization strategies that accounted for different requirements resulting from different physical phenomena simultaneously, i.e., multiphysics optimization.