Bajaj Auto, the third largest motorcycle manufacturer and the world’s largest producer of three-wheelers, was facing challenges in managing and controlling its enterprise software assets. With software procurement becoming a rising cost of doing business, software inventory management, license utilization rates, and charge-back accounting became critically important for accurate capacity planning and budgeting. Bajaj Auto's senior management was struggling to 'right-size' their product lifecycle management (PLM) software investments against organizational productivity. The company found it difficult to consolidate the total number of licenses and understand the usage of PLM, CAD, CAE, CFD, and NVH software for capacity planning to support its R&D staff. The company also discovered that up to 25% of procured software was significantly underutilized or not utilized at all. The lack of visibility into distributed systems and minimal accounting for procured software assets further complicated the situation.

The engineers at [AB]structures, an Italian structural design and engineering company, were tasked with the challenge of developing three structurally optimized but unique racing yachts within a preset time frame. The yachts were to be used in the 2011 – 2012 edition of the Volvo Ocean Race. The challenge was further complicated by the Volvo Open70 Box Rule, which sets specific parameters for the yachts, such as the keel weight to be between 6.0-7.4 tons and the overall measured weight of the yacht to be no less than 14 tons. Each of the teams required different solutions from [AB]structures, pushing the design envelope and demanding innovative and efficient solutions.

Nippon Sharyo, a leading manufacturer of railroad cars in Japan, faced a complex challenge in enhancing the safety and comfort of their bullet trains. The aerodynamic pressures exerted on the trains, especially when entering and exiting tunnels or passing other trains, posed significant safety risks and discomfort to passengers. The pressure wave created when a train enters a tunnel could cause loud noise and vibration, and the collision of pressure waves when two trains pass each other in a tunnel could produce a force strong enough to push one train away from the other. If not properly managed, these forces could potentially derail the train or at least cause a jarring experience for passengers. Other factors such as unsteady loads when trains pass in open landscapes, the impact of crosswinds, noise from the door frame, and ensuring optimal airflow from heating and air conditioning systems also needed to be considered to maximize passenger safety and comfort.

In a bid to reduce carbon dioxide emissions and contribute to the prevention of global warming, the automobile industry has been working on improving vehicle body structures and engine efficiency. A significant part of this effort is the drive to make vehicle bodies lighter, thereby improving fuel efficiency. While metals like steel and aluminum make up most of a car's weight, there has been a growing trend to replace some of these materials with lighter plastic. However, plastic, which now accounts for about 9% of a car's weight, presents its own challenges. It is significantly lighter than metal and can be molded into complex shapes, but it also deforms easily under external force or high temperatures. Kanto Auto Works, a core member of the Toyota Group, was faced with the challenge of making plastic parts lighter while ensuring they maintained sufficient rigidity and heat resistance.

Mabe, a global company that designs, produces, and distributes appliances to over 70 countries, faced a challenge in improving the protection of its washer-dryer by optimizing packaging material. The company wanted to reduce potential transit damage to its products while avoiding the use of excessive packaging that would lead to significantly higher material and shipping costs. The challenge was to produce an optimized packaging design that took into account a variety of loading scenarios and alternative package designs, and to do so early in the design stage, before any physical testing of the packaging was performed. Mabe also wanted to transfer the analytical simulation techniques developed for the washer-dryer to packaging for other products in the future, allowing the company to optimize and accelerate its design efforts.

Sicma Aero Seat SA, a French manufacturer of airline passenger seats, faced a significant challenge in the design, manufacturing, and maintenance of its products. The company's seats, which range from simple to sophisticated models with complex electrical and electronic features, had to comply with stringent safety regulations. These regulations required the seats to withstand a crash impact 16 times the force of gravity, translating into tougher design and manufacturing constraints. Additionally, the seats had to appeal to passengers and adhere to various certification and safety regulations, including those related to crash impact. The company also had to meet customer specifications and use a combination of virtual and physical testing to meet appropriate regulations. The challenge was to improve their seating products, cut certification costs, and reduce product development and delivery cycles.

Automotive Original Equipment Manufacturers (OEMs) globally are grappling with the challenge of reducing computer aided engineering (CAE) cycle times. This is due to an increasing number of car variants, a surge in data volume, and intense competitive pressure. OPEL, in response to these challenges, identified the design process of engine mount systems as a potential area for process automation. The objective was to enable NVH engineers to generate input decks even without detailed load case information. The knowledge had to be captured and reused in a standardized workflow. Additionally, automatic optimization and robustness analysis of the mount parameters had to be integrated into the process to quickly improve the final product quality.

F.S. Fehrer Automotive GmbH, an international supplier for the automotive industry, was facing challenges in the development of their seating systems. The seat of a vehicle, being the direct and closest connection of the passenger with the automobile, has great demands placed on it. Factors such as ergonomics, vibration damping, durability features, and climatic comfort are important criteria in the development of a molded foam pad for seating. Fehrer was in search of simulation tools that could enhance their development process, deliver accurate and fast results, and provide access to a reliable and fast solver. The tools also needed to be easy to learn and affordable.

ABstructures, a company specializing in innovative design solutions for lightweight structures, was tasked with the challenge of developing a structurally optimized racing yacht within a preset time frame for the Volvo Ocean Race 2009. The challenge was compounded by the strict boundary conditions of the Volvo Open70 Rule, which defined parameters such as the keel weight to be between 6.0-7.4 tons and the overall weight of the yacht to be close to 14 tons. The company needed to design and optimize the carbon structures of the yacht to achieve fundamental structural improvements compared to the older-generation yachts that competed in the 2004 edition of the Volvo Ocean Race.

NASA's Orion Crew Module, designed for long-duration missions into deep space, required a clear understanding of the dynamic loads generated during water impact to maintain the spacecraft’s structural integrity and increase the safety of the crew. The water landing of a craft like the Orion Crew Module is a complex and changeable event, subject to the dynamics of the vehicle’s structure and sub-structures, such as its heat shield, as well as atmospheric and water conditions. Creating a computer simulation of this event is difficult and especially sensitive to such input variables as mesh density, boundary conditions and contact interfaces. To ensure that simulations reflect real-life conditions as accurately as possible, physical test data is needed to correlate to and anchor the finite element (FE) simulation models. The NASA Engineering and Safety Center (NESC) sought to establish a clear understanding of the specific modeling methods needed to perform dynamic simulations of the Orion Crew Module water landings.

Medtronic, a global leader in medical device manufacturing, was facing a significant challenge in the design and validation process of a new medical stent. The stent, an expandable mesh inserted into a patient's artery to keep it open, required meticulous design and rigorous testing. Traditional methods of computer-aided engineering (CAE) and virtual simulation were not fully utilized within the industry due to the slow verification process for often microscopic components. Medtronic was seeking a way to not only improve the design of the stent but also to speed up the validation process, ensuring a faster time-to-market and better performing products.

Esterline Advanced Sensors, a leading provider of aeronautic sensors, faced a significant challenge in the development of their products. Each sensor is a unique project for a specific customer, with individual requirements that often change during the development process. This necessitates multiple iterations on design changes and intensive simulations to ensure the final product meets the customer's needs. The sensors, composed of several sub-parts and different materials, grow into complex models when prepared for simulation. The efficiency and reliability of the simulation heavily depend on the mesh features and quality of these models. The challenge was to quickly incorporate required modifications into the current model, create models from scratch, and quickly adopt modifications for design variants, all while maintaining high quality and reducing calculation time.

Unatec, a company with over a decade of experience in energy solutions consulting, was grappling with the challenge of controlling costs and improving production for energy producers. The company recognized that uncontrolled costs and inaccurate predictions could significantly reduce profits, potentially leading to losses. The energy generation and management sector, if not optimized, can severely impact economic results. Profits can be dramatically diminished and losses can even be incurred if costs are not closely controlled or production is not predicted accurately. Furthermore, many countries have started to dramatically reduce economic subsidies for production and have introduced more regulations. In some cases, it is even mandatory for energy producers to optimize energy management to increase profit and avoid sanctions and penalties.

Unilever, a consumer goods giant, was faced with the challenge of reducing the environmental impact of their products. The company needed to find a way to minimize the material used in its packaging while ensuring that it remained strong enough to withstand transportation loads and a variety of use conditions. The challenge was to optimize Unilever’s packaging designs using advanced virtual simulation technology. However, at the time, Unilever did not employ many computer aided engineering (CAE) users, instead having an extremely talented team of CAD engineers at their disposal.

Boyacá, a company with 35 years of experience in newspaper delivery, was facing a significant challenge. The company needed to increase the productivity of its drivers and reduce delivery costs. The fulfillment of time schedules was crucial for customer satisfaction, and late deliveries could result in additional costs. Boyacá needed real-time information on arrival and departure times at each hub of the distribution chain to control costs with the lowest possible investment. The company uses several hundred trucks for delivery every day, making the task of tracking and optimizing delivery times a complex one.

Scania, a European heavy vehicles manufacturer, is renowned for its ability to deliver highly customized products. This unique selling proposition, however, presents a significant challenge for the company's computer aided engineering (CAE) departments. The engineers are tasked with rapidly verifying a multitude of different variants using finite element simulations. The entire virtual model assembly process, which includes positioning hundreds of components, creating contact definitions, and building part connections with pre-strained bolts, was a major goal for Scania to automate. This process was not only time-consuming but also prone to errors, thereby necessitating a solution that could streamline and automate the process.

In the aerospace industry, the overall weight of an aircraft is a critical design requirement due to the impact just a few kilograms can have on fuel efficiency and CO2 emissions. Heavier aircraft use more fuel during flight which leads to increased running costs for the airline carriers. Airbus, while designing the world’s largest passenger aircraft, the A380, aimed to ensure the design was as lightweight as possible while maintaining all performance standards. The challenge was to reduce the weight of the aircraft without compromising on the performance standards.

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 design a new deodorant packaging concept that would stand out in the market. However, Unilever lacked the necessary in-house expertise to adopt a simulation and analysis approach for the design and testing of the new can. They needed a development partner to assist with the design and testing of the new packaging concept.

The utility industry is faced with the challenge of managing vast amounts of operational data. This data, if properly analyzed and interpreted, can provide valuable insights that can enhance operational efficiency and customer service. However, the sheer volume of data and the complexity of utility operations make it difficult for utilities to effectively leverage this data. Furthermore, each utility has unique business needs, requiring a tailored approach to data analysis and reporting. The challenge, therefore, was to develop a solution that could integrate with the existing database schema of utilities, provide dynamic reports and dashboards, and be customizable to suit the unique needs of each utility.

Force Protection, Inc. (FPI), a South Carolina-based company, had developed a new class of military vehicle, the Buffalo, designed for clearing out land mines and Improvised Explosive Devices (IEDs). The Buffalo's pioneering design, with a monocoque hull designed to deflect blast away from personnel inside, became the basis of a new U.S. military vehicle design standard known as MRAP (Mine Resistant, Ambush Protected). However, as U.S. military involvement in the Middle East increased, the need for personnel transports that could withstand the kind of anti-insurgency war U.S. soldiers were fighting became apparent. The Army requested FPI to produce a smaller, more versatile version of the Buffalo, which was named the Cougar. This new vehicle had to meet a series of military, SAE, and NTSA standards, requiring documentable analyses to ensure compliance. FPI, however, lacked a formal in-house analysis capability.

Duco, a major subsea engineering design, manufacturing, and testing facility, faced significant challenges in improving their Computer-Aided Engineering (CAE) model generation and analysis procedures for their bespoke products. These products, known as subsea 'umbilicals', are complex structures designed to withstand extreme pressure, temperature conditions, and adverse weather in hydrocarbon fields at water depths beyond 3,000 meters. The umbilicals connect the topside platform or vessel with seabed equipment, including pumping stations with electricity and hydraulic pressure. Duco's challenge was to speed up the analysis time for these structures, which had to endure demanding fatigue load cases. They were also experiencing issues with mesh quality with their incumbent pre-processor, prompting the need for a change.

B/E Aerospace, a leading manufacturer of cabin interior products for commercial and private passenger aircraft, was faced with the challenge of designing lighter and safer seats for airline passengers. The rising fuel prices were forcing airlines to find inventive ways to reduce weight within an aircraft, which in turn would lower fuel costs and ultimately ticket prices. B/E Aerospace was tasked with not only reducing the weight of the seats but also ensuring that the components provide better passenger protection in emergencies. The design of these seats was completely market-driven, with airlines demanding comfort and features for their passengers, while also asking for lighter seats to combat the relentless increase in fuel costs. The challenge was to accommodate these demands within the constraints of safety certification.

Chrysler, a renowned automotive company, was facing a challenge in managing its growing Computer-Aided Engineering (CAE) server farm. Since the 1980s, Chrysler has been using computer simulation tools for designing cars and trucks. Over the years, the use of computer-aided engineering and finite element analysis expanded, leading to a significant increase in the processor count at Chrysler’s High-Performance Computing (HPC) center. By the late 1990s, Chrysler was building up its HPC capacity to meet the growing demand for CAE simulations by installing a number of servers. Initially, Chrysler used a competitor's product for workload management. However, in 2003, they acquired 384 PBS Professional licenses to manage clusters used exclusively for computational fluid dynamics (CFD) jobs. By 2008, the HPC center was operating 10 servers from a mix of vendors using a variety of Intel and AMD chips running Red Hat or SUSE Linux. The core count on the server farm had increased to 1,544.

CILEA, a technical consortium formed by ten universities in Italy’s Lombardy region, was faced with the challenge of managing a steep growth curve in demand for its high-performance computing (HPC) facilities. The consortium, which provides computing cycles for research, had to cope with a wide variety of disciplines, projects, and applications from its 400 registered users. These users, coming from government, industry, and academia, were driving the demand for CILEA’s facilities into a steep growth curve. The consortium responded by doubling its staff over three years and building up its HPC resources. However, managing these resources, which included a 208-blade HP cluster named Lagrange, two AMD Opteron clusters, and a 64-CPU HP Superdome SMP system, was a significant challenge. The consortium needed a workload manager that was robust, flexible, and had an excellent price/performance ratio.

The Scripps Clinic's Shiley Center for Orthopedic Research and Education (SCORE) was faced with the challenge of improving the understanding and design of orthopedic implants, specifically for shoulder arthroplasty. The existing implants, typically made of titanium alloy and lined with plastics, were not expected to last more than 20 years, making them unsuitable for patients under 65. Furthermore, patients often had concerns about the range of motion, strength recovery, and longevity of the new joint. The process of modeling replacements for the meniscus, a crescent-shaped knee cartilage, was also a complex and time-consuming task, requiring the team to start the modeling process from scratch each time they wanted to change the curvature or thickness.

Motorola, a global communications leader, is faced with the challenge of developing increasingly complex cell phones that support multiple data protocols and are built to withstand rugged use. The company is driven by shortened design cycles, increasing product complexity, and reduced profit margins. Design cycles that took 18 months in 1998 are now pushing toward a six-month goal to meet business-critical product launches and fixed ship dates. To maintain a healthy profit margin, Motorola must keep down the overall cost of producing the product. The company also needs to understand 'real-world' reliability well before next-generation cell phones hit the shelves. This requires capturing product-life behavior, predicting areas needing improvement, and generating high-quality products within a greatly reduced time frame.

Ford's Numerically Intensive Computing Department (NIC) had built a substantial heterogeneous High-Performance Computing (HPC) environment over the years, combining both capacity and capability. This environment included Beowulf clusters based on Xeon, Itanium, and Alpha processors, SGI Origin and Altix servers, IBMP650 capacity, and large SMP Cray systems. While this infrastructure enabled NIC to process compute-intensive jobs in a timely manner, it also resulted in a complex infrastructure of platforms and applications. Additionally, NIC faced complexity on the solver side, running many application versions, none of which ran on all architectures. The challenge was to find a solution that could efficiently manage this complex infrastructure and provide a simple tool for users.

Viessmann Werke GmbH, a leading manufacturer of household and industrial heating technology, was faced with acoustical issues during the development of a new generation of gas-fired heating boilers. The challenge was to reduce the noise levels by increasing the structural stiffness of the boiler cover. The initial approach involved integrating additional parts to increase the stiffness. However, this method was not optimal as it resulted in increased mass and more parts, leading to higher costs. An alternative approach was sought, which led to the exploration of optimum bead patterns using Altair OptiStruct. The bead pattern concept was preferred as it resulted in less mass, fewer parts, and ultimately, a lower total cost.

The Boeing Information Technology group, based in Bellevue, Washington, provides a wide range of computing services to the entire corporation. The Data Center, which houses the high-performance computing (HPC) systems, is the core of this campus. These HPC systems are accessed by all Boeing engineering departments, with the highest demand coming from engineers running aerodynamics and structural models, especially during the early stages of aircraft design. The HPC resources are primarily used for engineering studies and alterations to existing designs. The challenge was to find a reliable workload manager that could handle Boeing's distinct clusters and optimize several resources under one queue.

The Translational Genomics Research Institute (TGen) was in need of a vendor-supported solution that could provide flexible job scheduling on Saguaro, their 512-node production cluster. TGen's mission is to translate knowledge of the human genome into therapeutics and diagnostics, a task that requires massive computational resources. The institute had established its High Performance Biocomputing Center (HPBC) to provide these resources, but they needed a solution that could handle the scheduling of large jobs across multiple nodes while also running thousands of small serial jobs on a single node. The solution also needed to be easy to install and require little to no support.