Category: Blog

Part 1: What is Additive Manufacturing?

Additive Manufacturing (AM):

Additive Manufacturing (AM), commonly referred to as 3D printing is a manufacturing process to form 3D physical parts from CAD DATA. In AM process, hundreds or thousands of layers come together to form the physical 3-dimensional part by means of either binders or direct energy deposited on the material.

Due to very short lead time involved in the development of parts, the AM process used for manufacturing the prototypes rapidly is referred to as Rapid Prototyping. AM has gradually attained its importance in many industries like Aerospace, Healthcare etc. where use cases are proven for series or batch production also. This is only possible through high throughput and productivity of the latest systems that companies like EOS GmBH are manufacturing to yield the best of its productivity and optimized outcome. This brings down the ultimate cost of the parts produced through AM process.

Benefits of Industrial AM Process:

• Tool free technology to develop parts through only Digital Data.
• Short lead time to market.
• High performance materials engineered for different applications.
• High accuracy in first outcome.
• Design Flexibility at any time.
• High Repeatability with systems like EOS.
• Sustainability due to less environmental impact and sustainable material supply chain.
• Material reusability of highly efficient AM processes like SLS and DMLS.
• High strength of the printed materials in AM processes like SLS and DMLS.
• Reduced Physical inventory and practical possibility for JIT in supply chain.

Workflow of Industrial AM Process:

The Industrial AM process typically involves three stages –

• Pre-processing (Designing/ Data Preparation/ Build Simulation/ Build Optimization/ Slicing/ Programming for 3D printer or Parameter Assignment)
• Printing Process and
• Post Processing (Depowdering/ cleaning/ shot blasting/ Heat treatment/ support removal/ post machining etc.)

Classification of Industrial Additive Manufacturing:

Based on the raw material form, energy source used and technology workflow, the AM process is broadly classified into 7 Categories as follows:

1. VAT Photopolymerization
2. Material Jetting
3. Binder Jetting
4. Material Extrusion
5. Powder Bed Fusion
6. Sheet Lamination
7. Direct Energy Deposition

We shall discuss in detail about the above categories and subcategories of the AM processes in coming series.

Introduction to Business Process Management

Business process management (BPM) is a discipline that optimizes and manages an organization’s business processes via the use of tools, techniques, and methods. Analyzing, measuring, refining, and putting new processes into place are all part of BPM. BPM also considers how the processes tie in with the overall goals and strategy of the organization. It is a continuous cycle of improvement rather than an isolated event. Every piece of solution that is introduced to the company’s technological stack lessens the workload for managers, but it also makes the organization more complex. Optimizing operations involves enhancing efficiency and effectiveness in business processes.

Complexity and progress are frequently connected. This is particularly true about the improvements in technology. The good news is that technologies are becoming more accurate and effective even as they get increasingly complicated.

To make sure that businesses are utilizing their resources as efficiently as possible, business process management can be implemented in such scenarios.

 

What is Business Process & Why Companies need to Implement BPM

A business process is defined as a collection of business tasks and activities (that when performed by people or systems in a structured course) produce an outcome that contributes to the business goals.

 

The way businesses manage and enhance their processes is called business process management. BPM includes:

• Examining every procedure independently
• Considering how each step fits into the overall business plan

 

BPM Standard & its Importance in Business Process Management

Designing and mapping business processes in a business process model is done using the modelling standard BPMN 2.0. It is frequently used in business process management because it allows technical users to represent and implement complex processes in a way that is easily understood by business users, facilitating productive collaboration between the two groups. Using graphical representations of internal procedures, BPMN facilitates standard communication among users.

Dassault Systèmes’ 3DEXPERIENCE Platform is a comprehensive solution that combines engineering, quality, and regulatory compliance business processes. Organizations can configure forms and automate activities and KPIs to increase efficiency and standardization.

The Business Process Management roles on the 3DEXPERIENCE Platform enable organizations to simulate and optimize processes to identify and measure opportunities for improvement. Upon the definition of the business process, one can then test and deploy the process to ensure secure and scalable processes.

 

Business Process Management Roles on 3DEXPERIENCE Platform

Benefits of Business Process Management

Business Process Management on the 3DEXPERIENCE Platform enables process capitalization, instrumentation, and execution where one can:

• Maximize enterprise efficiency through Knowledge & know-how capturing and optimization.
• Increase process definition and configuration experience through a simplified user interface that enables to easily capture the enterprise processes.
• Improve the efficiency and traceability of enterprise business processes.
• Eliminate costly business process execution through secure compliance with regulations.

To get more information on how the 3DEXPERIENCE Platform drives Business Process Management, please reach out to us at marketing@edstechnologies.com

In the ever-evolving realm of engineering simulation, the need for sophisticated tools that automate and optimize the design process has reached a crucial point. SIMULIA Isight from Dassault Systèmes  is a potent simulation process automation and design optimization software. This blog post unfolds a strategic walkthrough, unravelling the indispensable steps to harness Isight’s prowess for impactful data analysis in engineering projects.

Defining the Simulation Process

It starts with meticulously evaluating the engineering objectives. Then, identify the specific simulations or analyses that Isight will automate or optimize.Understanding stress analysis, fluid flow simulation, and thermal studies is crucial for a successful workflow using SIMULIA Isight. Understanding stress analysis, fluid flow simulation, and thermal studies is crucial for a successful workflow using SIMULIA Isight.This can be demonstrated through a complex engineering problem involving hyperelastic materials such as a rubber bush, highlighting an optimization-based approach using parametric data analysis withIsight

Integrating Simulation Tools

Isight excels at integrating various simulation tools seamlessly into one unified environment. By establishing connections with specific tools such as Abaqus or other third-party software, this integration ensures a cohesive workflow. It enables smooth data transfer between these tools, ultimately boosting efficiency and accuracy in the overall process.

Creating a Workflow

Creating a logical workflow is key to making the most of Isight.This includes outlining the precise sequence Isight will follow to execute simulations seamlessly. It encompasses detailing the transfer of input information among various simulation tools to establish a streamlined and automated simulation procedure. Isight’s intuitive interface facilitates the visual design of workflows, making it accessible to both seasoned engineers and those new to simulation process automation.

Case Studies: Hyperelastic Material

Hyperelastic materials, also termed green elastic materials, possess the unique ability to undergo significant elastic deformations and revert to their original shape upon load removal. These materials, often described using a strain-energy density function like the neo-Hookean model, are used in fields such as biomechanics, rubber-like substances, and the mechanics of soft tissues.In engineering simulations, accurately modelling hyperelastic materials is vital for predicting responses to large deformations, making tools like Isight crucial for design optimization and simulation automation involving such materials.

Step 1: A parametric file was crafted in Abaqus, followed by analyses under diverse loading conditions such as axial, radial, conical, and torsional loads. All associated files, including CAE and ODB files, were consolidated in a single folder.

 

Step 2: Defining Design Variables – In projects geared towards optimization, pinpoint the design variables that Isight will manipulate to achieve desired outcomes. These variables could include material properties, geometric parameters, or any other factors influencing your simulation. Set constraints and allowable ranges, guiding Isight in its optimization process. In our case, geometrical parameters were defined rather than material inputs, as illustrated in the below snapshot of the DOE Editor windows with parameters defined.

 

Step 3: Setting Up Design of Experiments (DOE) – Efficiently navigate the parameter space by definingDesign of Experiments. Isight helps by letting you systematically change input values to check many scenarios.You can specify the number of simulations and the range of values for each variable, enabling Isight to navigate the design space. Different components can be aligned either parallelly or in series for data flow and execution. In our methodology, two Abaqus components were utilized for different loading conditions and physics, and Isight performed the Design of Experiment using optimal Latin hypercube methodology.

Step 4: Running Simulations – Withmeticulously designed workflow in place, execute the Isight workflow and witness the seamless automation unfold. Isight automates simulations with specified parameters, saving valuable time and reducing the likelihood of manual errors. Once the DOE Study is complete, all the results can be saved and further utilized for approximation studies.

Analyzing Results

Upon completion of simulations, Isight equips engineers with robust tools for result analysis. They can visualize data, generate plots, and extract meaningful insights from the simulation results. Isight’s post-processing capabilities empower engineers to delve deep into the system’s behaviour and performance.

 

 

Optimization

For projects focused on optimization, Isight automatically adjusts design variables to meet predefined objectives. Results can be reviewed, improvements can be assessed and iterated further if necessary.

Iterate and Refine

Isight’s flexibility allows for iterative refinement, enabling engineers to progressively enhance their simulation process.

Documentation and Reporting

A step often overlooked is comprehensive documentation. Isight enables the generation of detailed reports covering the simulation process, results, and any optimizations achieved. These reports serve as invaluable resources for communication with project stakeholders, offering a clear overview of the analysis methodology and outcomes.

By following these steps, unlock the full power of Isight, automating and optimizing your engineering simulations. This, in turn, drives efficiency and innovation in your projects. Stay tuned for more insights into the evolving landscape of simulation technology.

Introduction: Addressing Electric Vehicle Design Challenges

Designing electric vehicles (EVs) comes with unique challenges, from optimizing battery performance to ensuring efficient power distribution. However, most of these hurdles can be overcome with the right tools and technologies, paving the way for a more sustainable future. In partnership with Synopsys, EDS Technologies offers SaberRD, which addresses some specific design challenges EV manufacturers face. In this blog, we will discuss some challenges and explore key features that can address these challenges.

 

The Complexities of Electric Vehicle Design

Designing electric vehicles brings new challenges compared to traditional combustion-engine vehicles. The complexities lie in the powertrain and battery systems and other crucial components such as motor controllers, sensors, and charging infrastructure.

 

Driving Range

One of the primary concerns in EV design is range anxiety. EV manufacturers strive to extend the range of their vehicles to alleviate customer concerns about running out of power. Achieving a balance between range, battery size, and weight is a delicate task that requires advanced modellingand simulation tools.

 

Charging infrastructure

In the future, we expect improved charging infrastructure and faster chargers to make electric vehicles (EVs) competitive with gas cars. Long-distance travel poses a challenge due to sparse charging stations along routes. While expanding this infrastructure requires significant investment, daily recharging in home garages, workplaces, and commercial areas could eliminate the need for regular stops at filling stations for EV drivers.

 

Reliability

Ensuring the reliability of powertrain elements like the battery, motor, and power electronics while in use poses a significant challenge for engineers in powertrain design. These components are susceptible to various environmental stressors, including temperature fluctuations and mechanical impacts. Designers of automotive power ICs prioritize meticulous design and manufacturing of integrated power devices. The effectiveness of thermal management systems is crucial in ensuring the efficient and dependable operation of e-powertrain components. Suppliers and original equipment manufacturers (OEMs) must carefully consider material properties and the non-uniform distribution of current, voltage, magnetic flux, and component temperature. The performance of a single component can significantly affect the distribution of flux in others.

 

Introducing Synopsys SaberRD: The Solution to EV Design Challenges

The Saber® platform by Synopsys offers robust capabilities in design, modeling, and simulation to analyze and validate system interactions spanning various physical domains thoroughly. Saber encompasses an extensive array of models and utilities designed for simulating Hybrid Electric Vehicle (HEV) systems, encompassing:

• Motors (utilizing both analytical and Finite Element Analysis (FEA)-based models)
• Power devices such as IGBTs, MOSFETs, and BJTs
• Batteries, ultracapacitors, and charging systems
• Inverters, DC/DC converters, switches, speed controllers, and capacitors
• Mechanical components

 

Robust Design and Electric Vehicle Design Challenges

A comprehensive design approach, known as robust design, is critical in enhancing vehicle safety and reliability. This approach ensures that reliability concerns are integrated into the design process itself. Design teams rely on robust design methodologies to effectively handle and enhance complex system interactions, particularly when faced with operational and environmental variations. This makes such methods ideal for the development of hybrid and electric vehicles. The following outlines a typical flow of robust design.

Moreover, SaberRD provides advanced analytics and visualization tools that allow engineers to effectively interpret and communicate simulation results. This facilitates collaboration and decision-making throughout the design process.

• Simulate the complete system: Capture all the device effects and multi-domain interactions critical to power system design
• High accuracy results, faster: Robust simulation technology and distributed processing capabilities come standard with SaberRD
• Design for robustness and reliability: Built-in capability for analyzing effects of variation, parameter sensitivity, worst-case behaviours, faults and more

In conclusion, the key features and benefits of SaberRD position it as the ultimate solution for overcoming design challenges faced by the electric vehicle industry. In the next section, we will explore how SaberRD integrates seamlessly into the existing design workflow, making it easily accessible and adaptable for manufacturers.

 

Case Studies: Success Stories of Overcoming Design Challenges with SaberRD

One of the most compelling aspects of SaberRD is its proven track record in helping manufacturers overcome electric vehicle design challenges. In this section, we will delve into a few case studies that highlight the real-world benefits of using SaberRD.

Case Study 1: Optimizing Battery Performance

An electric vehicle manufacturer struggled to maximise their vehicles’ range while ensuring optimal battery performance. By utilizing SaberRD’s comprehensive modelling and simulation capabilities, engineers could analyse various factors accurately, such as battery capacity, voltage levels, and power distribution. With this information, they could fine-tune the battery system, resulting in vehicles that offered an extended range without compromising overall performance.

Case Study 2: Enhancing Vehicle Safety

Safety is paramount in the electric vehicle industry, and one manufacturer faced challenges in detecting and mitigating potential electrical faults. With SaberRD, engineers could simulate numerous safety scenarios and fault analyses, stress-test the electrical system, and identify potential weaknesses. By implementing necessary improvements, such as redundant safety features and enhanced insulation, the manufacturer significantly improved the overall safety of their electric vehicles.

Conclusion:  SaberRD for EV

In conclusion, SaberRD has proven to be a game-changer in the electric vehicle industry, enabling manufacturers to overcome various design challenges. Through case studies focused on optimizing battery performance and enhancing vehicle safety, we have seen the real-world benefits of utilizing SaberRD’s modelling and simulation capabilities.

By using SaberRD, manufacturers can design high-performance, safe, and sustainable electric vehicles. The seamless integration of SaberRD into the existing design workflow, with its user-friendly interface and compatibility with industry standards, makes it an invaluable tool for engineers.

 

In the rapidly evolving landscape of electric vehicles (EVs), EV manufacturers and EV infrastructure developers face the critical challenge of strategically selecting optimal locations for stores, charging infrastructure, and business planning and analytics. In this context, there is immense potential to harness location analytics’ transformative potential. By leveraging cutting-edge tools and techniques, such as strategic location analysis, network planning and optimization, demand forecasting and market analysis, environmental impact assessment, and asset management and maintenance, they can make informed decisions that drive success in the dynamic world of EVs. In this blog, we will explore the diverse aspects of location analytics and its role in empowering EV manufacturers and infrastructure developers to stay ahead of the curve, optimize their operations, and shape the future of sustainable transportation. 

EDS Technologies offers EV manufacturers and charging infrastructure developers a comprehensive range of solutions to optimize operations and drive the transition to sustainable transportation. 

 

• Strategic Location Analysis for EV Infrastructure: Site Selection and Planning: With Esri’s location analytics, Electric vehicle (EV) manufacturers and developers of charging infrastructure have access to advanced tools to assist them in site selection and planning. These solutions enable them to analyse spatial data, demographics, and traffic patterns, empowering them to make well-informed decisions about the optimal locations for showrooms, manufacturing plants, charging stations, and distribution centres. 

 

• Network Planning and Optimisation: By leveraging ESRI’s network analysis tools, companies can optimise the layout of their charging networks, identify coverage gaps, and ensure efficient connectivity to power grids. This collaboration helps reduce infrastructure costs, minimise range anxiety, and enhance the overall charging experience for EV users. 

 

• Demand Forecasting and Market Analysis: Accurate demand forecasting is critical for EV manufacturers and charging infrastructure developers to align their production and expansion plans with market trends. In collaboration with ESRI, EDS Technologies combines demographic data, consumer behavior patterns, and EV adoption rates to provide valuable insights into future EV demand at regional and local levels. These insights empower stakeholders to make data-driven decisions, prioritise investments, and align their offerings with market demand

 

• Environmental Impact Assessment: Sustainability is a key focus area in the EV industry, and GIS solutions can help companies address this through comprehensive environmental impact assessments. By integrating data on air quality, noise pollution, land use, and sensitive ecosystems, EV manufacturers and infrastructure developers can evaluate the potential environmental effects of their projects. This collaboration allows companies to mitigate risks, ensure regulation compliance, and promote sustainable development practices. 

 

• Asset Management and Maintenance: Geospatial solutions can assist companies in effectively managing their growing EV fleets or networks of charging stations. Through ESRI’s GIS software, companies can get asset tracking capabilities, predictive analytics, and real-time monitoring tools that enable stakeholders to monitor EVs’ performance, health, utilisation and charging infrastructure. These analytics also help optimise maintenance schedules, minimise downtime, and maximise asset longevity. 

 

• Data Visualisation and Communication: Effective communication and collaboration are essential for successful EV manufacturing and charging infrastructure development. Companies can use these applications to create interactive maps, data visualizations, and dashboards that simplify complex information and facilitate stakeholder engagement. These tools enable manufacturers and developers to effectively communicate their plans, engage with communities, and gain public support for their initiatives. 

 

EDS Technologies Pvt Ltd is a partner of ESRI India. ESRI is a global leader in geographic information system (GIS) software. EDS Technologies provides comprehensive geospatial solutions and expertise to EV manufacturers and charging infrastructure developers. With a deep understanding of the industry and access to ESRI’s powerful software suite, EDS Technologies empowers companies to leverage the full potential of GIS technology in their operations. In this blog post, we will explore how EV manufacturers and charging infrastructure developers can benefit from these GIS solutions to streamline their processes and drive the transition to sustainable transportation. By using EDS Technologies solutions, companies can harness the full potential of ESRI software and drive their success in the rapidly evolving EV industry.