2021 Survey Report: Technology Convergence for a Smarter, More Connected World: Market Trends to 2026

Write data-centric applications using the best programming languages for the job, mixing syntax from different languages inside a single program. Our code and no-code tools empower you to create, maintain and run models and programs using the languages of SAS, Python, R and SQL. Organizations that have invested many man-years in developing IP using SAS language use our tools to continue to maintain and run their existing SAS language programs without the need for any other third-party products. Request a demo today.

Reliability is a very broad term in the electronics world. It covers many different criteria, such as signal integrity, thermal management, environmental protection, power conversion and distribution, vibration, and many other electrical and mechanical considerations.This article, originally published by EE Times, explains the importance of reliability in PCB design and how software like Altair PollEx can help.

Realizing the true potential of self-service data transformation requires the ability to scale, automate, and govern across the organization. Altair® Monarch® Server is a centralized data management solution that automates bulk data processing and report distribution. It allows users to securely publish, collaborate, and share data preparation models, source data, and prepared datasets. See how Monarch Server can help you automate and streamline your data transformation and reporting capabilities at the enterprise level. Contact us to schedule a demo.

ATNA Industrial Solutions GmbH has accelerated the design and development process of its novel hydraulic press with the help of a new simulation tool, thus achieving its ambitious development goals.

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: • Top design priorities • Top benefits of SDfM • Top barriers to expanding and adopting SDfM • Risks to staying competitive in the market

Renishaw uses Altair signalAI to deliver advanced digital gauging with real-time melt-pool analytics. This AI-driven quality assurance process helps Renishaw identify manufacturing anomalies earlier, develop parts quicker, and realizes a stable production.

Examining your analytics system at regular intervals to get optimum performance is vital for your growing business. In order to ensure you get the most out of our technology and tools, Altair Data Analytics Services offers a technical health check. It covers full examination of the Altair Data Analytics product environment, related hardware and software configurations, the operating and networking environment, data backup and security, as well as can extend to any other bespoke criteria that you may want covered.

SmartWorks is an end-to-end platform that enables you to combine enterprise expertise with data and artificial intelligence (AI) to build analytics applications and scalable automation – with or without code. Develop AI-augmented analytics. See how with SmartWorks Analytics.

Knowledge Studio delivers explainable artificial intelligence (AI) and automates machine learning tasks to enable people to make fully informed decisions based on massive amounts of data. The software displays all the details of a model’s configuration so it is easy to understand how it generates predictions. Analysts who may not be familiar with modeling or AI processes can quickly uncover insights to help solve complicated problems. Data scientists can fine tune model parameters and develop highly sophisticated models using a drag-and-drop interface with no coding required.

Altair’s Data Analytics Assessment Service helps answer the tough questions: • What data do I have? • Can it be leveraged for analytics? • What other data do I need and how do I get it? • What ML technology can be used with my available data? • How do I get started?

The applications of computational fluid dynamics are broad, spanning multiple industries and requiring varying degrees of detail and analysis. For an analyst performing advanced computational fluid dynamics modelling or a design engineer quickly needing to understand fluid or thermal effects on a design proposal, Altair offers a complete set of tools to support each project.

Heavy equipment manufacturers want to design products that are durable and perform at their peak under a variety of conditions. To accomplish this, Altair provides an integrated multi-disciplinary simulation environment to virtually test and optimize equipment performance and therefore, help reduce design and development costs. Using simulation-driven design, studying the full dynamics of a product or system is possible, from motion analysis to complete lifecycle durability testing.

A key development goal of any machine-building project is to produce perfectly running, reliable machines that make high-quality products. By leveraging accurate virtual prototypes, seamless production can be ensured earlier in the development process to help assess and improve product profitability.

In this white paper, we have developed a numerical technique to accurately model the experimental near-field amplitude and phase spectra in near-field infrared nano-spectroscopy. Our numerical method using Altair Feko is especially useful for describing surface phonon-polaritons. Also, extension of our numerical technique to materials with anisotropic dielectric function and/or heterogeneous structure is possible in the future. This method is efficient to elucidate fundamental physical phenomena measured in near-field infrared nano-spectroscopy experiments on novel, complex materials.

Heavy mobile machines consist mostly of production equipment working almost twenty hours a day, year on year, in diverse harsh environments, undergoing extreme loads and overloads. Especially diggers and loaders such as hydraulic excavators, wheel loaders, and backhoes, cater to multiple applications with use cases such as digging, trenching, loading, lifting, breaking, and ripping. Many times, these machines undergo non-standard uses where the machine is subjected to unplanned forces and moments as in the case of self-loading on a trailer, or a bucket hitting a dump truck body. This paper highlights the workflow process and simulation-driven methods to integrate multi-physics with Altair’s industry-leading solutions. The latest generation of Altair simulation tools can capture a wider range of vehicle systems and environmental interactions.

Panopticon provides business users, analysts, traders, and engineers with the monitoring and analysis tools they need to conduct successful, profitable operations while maintaining a close eye on anomalies, trends, clusters, and outliers. They can make insightful, fully informed decisions based on massive amounts of fast-changing data. Panopticon is enterprise-class software you can deploy in the cloud (public or private) or on-premises. It connects directly to virtually any data source, including big data sources, SQL and NoSQL databases, flat files, and real-time message queues. Users can develop stream processing applications and design sophisticated visual user interfaces without writing a single line of code. This technical document provides a summary of the capabilities, implementation options, applications, and benefits of using Panopticon to support your operational requirements.

Radomes are used across multiple industries, including aerospace, defense, electronics, and telecommunications. When properly designed, the radome can actually enhance the performance of an antenna system. The proper selection of a radome for a given antenna can help improve the overall electromagnetic system performance by eliminating wind loading, allowing for all-weather operation, and providing shelter for installation and maintenance. Altair’s radome simulation solution helps to streamline the design of these complex components, ensuring performance while significantly reducing development time.

Industry 4.0 has led companies to investigate the automation of traditional manufacturing and industrial practices using modern smart technologies via Industrial Internet of Things (IIoT) making agricultural and mining equipment, trucks, and other heavy industrial assets smarter via effective connectivity solutions.

Reprint of the July 2021 cover feature in Microwave Journal Simulation-driven virtual prototyping is employed in the design of modern smart products to accelerate product development speed, ensure intrinsic product qualities and improve the decision-making process during development. It results in smart products that are more cost effective with higher quality and reliability.

The advancements in the fields of AI and ML, combined with the increased availability of robust simulation, testing, and field data sets has made engineering data science a critical component of the modern product development lifecycle, but in order to extract maximum value from these exciting tools, companies need a plan to store, manage, and utilize their data efficiently. They need data discipline

Simulation-driven design changed heavy equipment product development forever, enabling engineers to reduce design iterations and prototype testing. Increasing scientific computing power expanded the opportunity to apply analysis, making large design studies possible within the timing constraints of a program. Now engineering data science is transforming product development again. Augmented simulation features inside Altair® HyperWorks® are accelerating the design decision process with machine learning (ML). The power of ML-based AI-powered design combined with physics-based simulation-driven design leveraging the latest in high-performance computing is just being realized.

Information silos present a major challenge to Heavy Equipment OEMs. Poor integration of simulation models across the product life cycle, limited reuse of models between programs, and a variation of modeling maturity across various engineering disciplines result in lack of traceability and ultimately hampers development efficiency and product performance. Using system modeling and asset-centric data analytics solutions help develop and orchestrate coherent models to increase decision-making confidence and speed.

Smart connected devices are everywhere, in homes, in transportation, and at work. This means electronic system design (ESD) is having a greater influence on almost every type of product requiring new simulation tools to help achieve electronic, electrical, mechanical, thermal, and connectivity goals. New printed circuit board development opportunities also bring new production challenges for manufacturers, who must ensure process efficiency starting with identifying potential defects and optimizing for manufacturing in the design phase.

Learn how Altair AcuSolve™ performs with AMD EPYC™ 7003 series processors

Learn how Altair Radioss™ Performs with AMD EPYC™ 7003 Series Processors

How do industry leaders and today's young minds look at ethical AI? This article from Engineering.com poses some tough questions about the role AI will play in our future and how we can plan to deploy these powerful tools responsibly. The panel of industry leaders and up-and-coming engineers interviewed for this article include:

• James Scapa, chairman, founder and CEO of Altair
• Carsten Buchholz, capability lead of Structural Systems Design at Rolls-Royce
• Hod Lipson, a professor at Columbia University that researches Robotics, AI, Digital Design and Manufacturing
• John Estrada, a student that produced an AI model for drought stress assessments in plants
• Tienlan Sun, a student that produced an AI model to detect illnesses within the eyes

Fluid mechanics simulation is a critical tool for late-stage failure risk mitigation, as well as a driver of design insights throughout the product development process. Used across all levels of product design and validation, from design engineers seeking to understand fluid and thermal effects on a design proposal to analysts performing advanced aerodynamic modeling, Computational Fluid Dynamics (CFD) serves a broad array of applications and a range of users with varied levels of expertise. The sometimes complex and computationally intensive nature of CFD necessitates careful consideration of the software and hardware investments required to produce accurate solutions and scale them at the speed of a company’s development process.

Altair® Monarch® is a comprehensive, self-service data transformation and process automation solution. It connects directly to a wide range of structured and semi-structured data sources, including PDFs, text, complex spreadsheets, JSON, XML, big data sources, relational databases, and many others. Business users and analysts can extract, cleanse, and transform data into consistent, governed, and secure rows and columns without specialized knowledge or training, and without writing any code. The platform includes more than 80 pre-built data preparation functions which makes it easy to build new error-free workflows in minutes. Experience no-code, automated data transformation: Try Altair Monarch today, for free.

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.

This whitepaper outlines the best practices for migrating Electronic Design Automation (EDA) workloads to AWS using the I/O profiling and dependency analysis tool suite Breeze from Altair. Profiling the EDA tool on premises and in the cloud ensures that the AWS configuration is right sized for the application and that costs are optimized.

Electronic Medical Records (EMR) and Electronic Health Records (EHR) have greatly improved data access, but efficient Revenue Cycle Management still requires significant data preparation to meet operational demands and health IT standards. This can be time-consuming and delay revenue collection. Altair’s market leading data preparation tool Monarch enables healthcare professionals to save time, limit clerical errors, easily automate recurring processes in Revenue Cycle Management and collect revenue faster.

In collaborative engineering environments, handling large-size 3D CAD models with a high level of detail is becoming more and more challenging. Especially sharing of 3D CAD models between OEMs and suppliers as well as utilization in downstream processes require file size reduction for sufficient performance and IP (Intellectual Property) protection while maintaining the initial design intent. In this context, simplification of 3D geometry provides a valuable solution to companies through enveloping, defeaturing, and extraction of inner/outer surfaces. Lightweight CAD models enable the efficient sharing and communication of relevant 3D product information as the storage of redundant and confidential data is avoided. This is an important basis for efficient collaborative engineering in globally distributed development.

Medical stents are a lifeline for patients with cardiovascular illness and disease. Altair's solutions can speed up development time by satisfying the testing of variables virtually, allowing engineers to truly optimize the design and performance of medical stents.

The future of smart, connected product development is where data analytics, simulation, and high-performance computing converge to a unified discipline, sometimes referred to as Computational Science and Engineering. How far away is the future? When will broad adoption start? What does it mean for you? To answer these questions, CIMdata collaborated with Altair to survey business leaders, technologists, researchers, and the global development community for insights into our future smarter, more connected world.

Two- and three-wheeler vehicle manufacturers, whether they are existing OEMs, new EV start-ups, or suppliers serving this segment, all have the goal of shortening product development time and getting product to market faster. With Altair HyperWorks™, ride, durability, and vehicle dynamics simulations for two- and three-wheeled vehicles can now be seamlessly performed using an intuitive and easy to use GUI with built-in libraries for vehicle models, analyses, and predicting and optimizing vehicle behavior.

Speaker design and analysis, especially for a more complex product, system, or component, often requires building multiple simulation models. The loudspeaker development process involves multi-physics and multiple sources in parallel, to multiple simulation runs for prototyping, testing, and validation. This results in separate models for nonlinear analysis of strength, thermal analysis and stiffness, noise, vibration, and acoustics. Even though each model isn’t always built from scratch, typically the use of different solvers for each attribute will require that models need to be converted from one solver format to another. This practice is not only time consuming but frequently error prone resulting in an inefficient use of engineering time.

The Battery Production Group at the Institute for Machine Tools and Industrial Management at the Technical University of Munich (TUM) researches the production of innovative battery cells.

The core of the work is process development and the optimization of processes within battery production – from mixing, coating and calendering of the electrode materials to the formation of the final battery cells. All battery production steps are carried out in-house using the TUM’s electrode and battery production line.

TUM uses Altair EDEM software to simulate the calendering process for lithium-ion batteries.

As of today, the “classical” V diagram is very well known among more and more engineers. Nonetheless its usage – even partly – is far away from the potential that it offers. One reason might be, that its benefits are not really obvious for the end-users. With this presentation, we will bring a new view by “closing the old V” and transferring it to a “closed ∇ (Nabla) cycle”. The focus of this contribution is on the opportunities to significantly increase the effectiveness of the approach of model-based development (MBD) by re-using engineering efforts in multiple ways.

In order to reduce energy consumption, efficiency is a key criterion that designers seek to optimize their electric motors. Complementary to the electromagnetic analysis, a thermal characterization is essential to study from the first design phase how temperature influences the performance of the machine. To obtain results close to the real working conditions, the motor control and the current harmonics produced by the electrical converter and control algorithms cannot be ignored.

Reducing aircraft design and development time is critical for all aircraft manufacturers, from urban air mobility and electric aircraft startups to military to commercial OEMs. In order to fully understand and optimize the complex systems of systems required in modern aircraft, aerospace engineers leverage a simulation method called Model-based Systems Engineering (MBSE). MBSE allows the evaluation of various types of vehicle systems to determine which best meet the mission requirements.