Whether they call it smart manufacturing or Industry 4.0, Altair helps customers realize their factory of the future. We provide software and cloud solutions that integrate the enabling technologies of simulation, high-performance computing (HPC), and artificial intelligence (AI) to power a digital transformation in their production facilities and throughout their organization.
Altair’s customers span companies from discrete and process manufacturing to oil, gas, mining, and other industrial segments.
Industrial Internet of Things (IIoT) is increasing connectivity, generating data, and unlocking potential. Altair knows how to take full advantage of data to fuel innovation, drive new opportunities, and accelerate your smart manufacturing transformation.
Digital twins help organizations optimize performance, gain visibility of in-service life, know when and where to perform maintenance, and how to extend a product’s remaining useful life. We take a complete, open, and flexible approach that enables your digital transformation vision on your terms.
Altair provides software that goes beyond the creation of unique prototypes with a robust simulation toolchain to support production designs created for additive manufacturing (AM). AM isn’t just for rapid prototyping, research projects, and advanced engineering teams.
By extracting real value from their data, manufacturers can make accurate predictions about component life, replacement requirements, energy efficiency, utilization, and other factors that have direct impacts on production capacity, throughput, quality, sales, customer acceptance, and overall efficiency. Low cost sensors and new wireless connectivity tools enable manufacturers to employ digital analytics more effectively than ever before. With the right tools, they can gather, cleanse, process, and visualize massive amounts of data from disparate sources that cover all phases of the product life cycle, from product design to warranty claims. This guide explains some of the major challenges involved in applying data analytics to manufacturing processes and the benefits of developing optimized approaches to addressing those challenges.
Investment casting is a valued manufacturing process known for its ability to produce detailed components with accuracy, repeatability, and in a variety of different metals, waxes, and high-performance alloys. Producing high-quality casted components is less prone to common design errors when a simulation-driven approach is used, leading to easier, more accurate analysis and optimization during the design phase.
Any industry that produces bulk quantities of goods such as pharmaceuticals, food, chemicals, or cosmetics, is seeking to produce these products consistently while reducing cost factors like waste and down time. Due to the nature of process manufacturing, multiple ingredients are combined to be mixed, coated, or sorted, so understanding the behavior of these processes is of paramount importance for manufacturers. Through the use of simulation modeling and Smart Manufacturing principals, manufacturers are now able to optimize these processes, leading to greater productivity and profitability.
Product engineers are under consistent pressure to reduce the costs, improve the quality and increase the throughput of manufacturing processes. This fast-paced environment is not well suited for trial-and-error manufacturing engineering.
How are engineers responding to these challenges? Is simulation and simulation-driven design for manufacturing (SDfM) well established across the industry? When simulation is deployed, does it deliver on the promises of reducing costs while improving throughput and quality? And what are the barriers to the adoption of simulation during the early stages of product development?
In this 2021 survey report conducted by Engineering.com, we discuss those questions and discover: