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.

Laser Beam Melting (LBM) technology allows for the creation of complex metallic parts without material waste, finding applications in industries such as aerospace. However, the process is essentially a micro welding process, and thermo-mechanical phenomena play a significant role. The heat from the melting material must dissipate, and the force from the contraction of the weld paths must be compensated. To maintain temperature and keep the part attached to the build plate, additional support geometries are added to the part. This not only increases material usage but also necessitates additional post-processing. The process stability is heavily dependent on the support structure. If the supports are not strong enough or do not conduct heat effectively, the quality and shape of the part can deviate from the desired result. Cracking of supports during the process can lead to process abortion, potentially doubling the costs per part, especially for parts being printed for the first time.

DSA, an ocean engineering consultancy and software company, faced a significant challenge in creating high-quality hydrodynamic meshes and models for ship and marine structures. The task of creating high-quality meshes is a complex one in CAD software, as the mesh often isn't well conditioned for hydrodynamic solutions which require a closed surface for resolving hydrodynamic effects such as nonlinear hydrostatics and BEM solution. To build an accurate ship hydrodynamic model, ShipMo3D, one of DSA's software, requires the development of a mesh of the vessel hull. This could be achieved either through the creation of hull lines or through importing an OBJ mesh file created using third-party software. However, both these methods were time-consuming and often resulted in less than optimal meshes.

Trèves Products Services & Innovation, a leading Tier-1 supplier of noise, vibration, and harshness (NVH) reduction parts, was facing a challenge in reducing part design and lead time. The traditional approach required expensive and time-consuming physical testing with real parts to account for their multi-layer arrangement and varying thickness. The input parameters for these models also needed to be readily available. Furthermore, the models had to be comprehensive in scope and easy to implement. With the upcoming reduction in pass-by noise emission limits from 70 to 68 dB, expected in 2024, the ability to accurately predict noise levels became essential. The challenge was to replace physical testing with numerical modeling to meet customer expectations and regulatory requirements.

The shift towards e-mobility has put immense pressure on the automotive industry to develop more sustainable and affordable transportation solutions. This has led to a rush to electrify products and compete with e-vehicles that match the performance of internal combustion engine models. EVR Motors Ltd., an Israel-based company that designs and develops cost-effective radial flux Permanent Magnet (PM) electric machines, faced a unique challenge. For several decades, motors for electric vehicles have been optimized using the same topology, called Radial Flux Permanent Magnet Motor topology (RFPM). However, EVR chose to take a different approach. Instead of optimizing existing technology, they decided to invent a new topology and develop a completely new type of motor for the electric vehicle industry called the Trapezoid Stator RFPM topology. As the base of EVR topology is different from other well-known motor topologies, the use of multiphysics and optimization tools was highly important. Therefore, the team needed a reliable, robust simulation tool.

CEA Tech, a technology research unit for the French Alternative Energies and Atomic Energy Commission, is a global leader in miniaturization technologies. As a research and development center, they develop advanced technologies that require a robust computing infrastructure. They use various process design kits (PDKs) from multiple foundries for R&D designs, which include complex digital systems on a chip (SoCs), RF circuits, and analog and mixed-signal chips. EDA licenses are used throughout the design flow, with compute jobs varying in terms of run time and memory footprint. The design flows for circuits in advanced nodes are complex, making it critical to manage licenses and job scheduling to shorten the design cycle. CEA Tech needed to improve license utilization and ensure that licenses are freed quickly to be made available to queued jobs.

Bush Bohlman & Partners, a structural engineering design firm, was tasked with the structural analysis and timber design for the British Columbia Institute of Technology (BCIT) student plaza. The structure was to serve as a pedestrian and public transport user gateway for the institute, and needed to establish a strong campus identity with a biophilic design and demonstrable support for sustainable building practices. The hybrid mass timber structure consisted of a Cross-Laminated Timber (CLT) canopy, CLT columns, and steel columns. The pedestrian comfort walkway needed to meet sustainability, reliability, and structural design requirements. The structure involved a pitched roof, skylight openings in the roof CLT panels, and supporting columns constructed from CLT and hollow structural steel. The engineers needed to maintain a current structural model, apply local timber design codes, and analyze the complex two-way bending behaviour of the cantilevering roof panels and irregular column layout.

The automotive, heavy equipment, and aerospace industries face a significant challenge in verifying vehicle requirements, developing design parameters, and providing real-time project status to management. The traditional method of capturing requirements in a Word document is time-consuming and inefficient. Furthermore, the process of verifying these requirements using corporate fuel economy prediction software and cell equations is complex and requires a high level of expertise. Additionally, setting body bending and torsional mode natural frequency targets to meet program objectives is a critical task that requires precision and accuracy. The challenge also extends to the use of a coarse geometry model for dynamic finite element analysis, which requires the transmission of requirements and work requests to the CAE Team. Once completed, the results need to be returned and the status automatically updated, a process that can be prone to delays and inaccuracies.

Elastic couplings, frequently used in industries like automobile, power, and manufacturing, present a unique challenge due to their nonlinear characteristics, relative rotation, and large cycle number of the radial load. These peculiarities do not allow the usage of the superposition principle of loads, meaning that every possible combination of loads (axial force, radial force, and torsional torque) must be separately considered. This results in a large number of load cases and consequently a large number of strength assessments. The simple assessment of the superimposed stress states, resulting from a single unit load, would lead to false results, possibly showing a higher component strength than in reality, which could result in a failure of the part. Therefore, all load combinations must be simulated and subsequently assessed against the fatigue strength accordingly.

Mabe, a Mexico City-based home appliances manufacturer, recently launched a high-end washing machine that generates over 20 signals to measure various parameters such as water temperature, water levels, vibration, torque, noise, pressure, rotor position, etc. This smart, connected product allows Mabe's product team to analyze real-time streaming sensor data to understand in-service use-cases and predict potential failures. It also enables them to aggregate and analyze data collected from many in-service machines over long periods of time to inform next-generation design improvements, material selections, and supplier options for subassemblies and components. However, Mabe faced a challenge in efficiently and automatically managing the vast amount of data, including its velocity and complexity.

Unilever, a global leader in the consumer goods industry, was seeking ways to maintain its innovative edge in the male grooming market. The company was particularly focused on differentiating its Lynx (Axe) brand from competitors. The challenge was to adopt a simulation and analysis approach for designing a new deodorant packaging concept. However, Unilever lacked an in-house team of analysis engineers and needed a development partner to assist with the design and testing of the new can.

The Electric Storage Company, a Northern Ireland-based firm, manages electric power in households from renewable sources using battery storage and IoT technologies. Their clients range from large industrial operations like Belfast Harbor, Titanic Studios, and the Harland & Wolff shipyards to residential customers, including those living in public housing projects. The challenge lies in managing a variety of base load and intermittent renewable power sources. This requires the ability to ingest, process, and analyze high-frequency information from the grid and thousands of devices. The company needed real-time insight into energy markets, the grid, battery systems, and generation facilities, as well as customer-level power consumption patterns. Understanding consumption and generation trends was crucial to optimize power routing and battery storage and ensure that power sold back to the grid or on the open market fetched the best possible price.

The aerospace industry is constantly seeking ways to improve the design and manufacturing process of aircrafts. The challenge lies in reducing the weight of components and structures for greater fuel efficiency and passenger comfort. The adoption of advanced materials such as laminated composites is a key strategy in achieving these goals. However, the design and modelling process of these composites can be complex and time-consuming. Additionally, the industry faces the need for modern structural modelling and automated design processes, as well as the need for accurate stress, mechanism, and vulnerability simulation. The industry also needs to meet strict safety and performance requirements while achieving time efficiency, cost reduction, and quality improvement.

ACENTISS, a company that provides engineering services for structural design, stress and fatigue competencies for metallic and composite structures, was tasked with the development of ELIAS, an all-electric technology demonstrator airplane. The project, named EUROPAS, required the development of a full electric reconnaissance system, datalinks, and a ground control station. Additionally, ACENTISS had to design the structure of the wings and the landing gear. The challenge was to create a lightweight plane that could fly long distances, while also keeping development time and costs to a minimum. To achieve the optimum balance between weight, strength and performance, and to reduce design iterations with the real-world prototype, ACENTISS needed to leverage computer-aided engineering tools, particularly for the structural layout of the composite wings and the kinematics of the landing gear.