How to Optimize the Automotive Manufacturing Process

Manufacturing automobiles is a complex process involving multiple stages that convert raw materials into finished products. The impressive estimated global sale volume of 70.8 million cars in 2023 (source: statista) shows that the automotive industry rebounded in a V-shaped recovery trend after COVID-19. Optimizing the manufacturing process is crucial to remain competitive in the rapidly advancing automotive industry. This article will delve into the automotive manufacturing process' key stages, identify optimization opportunities and highlight the role of artificial intelligence in the car manufacturing process.

Main Stages of the Production Process

Firstly, let's review the main stages of the automotive manufacturing process.

Material Selection and Acquisition

When selecting materials, automotive industry manufacturers must consider factors like durability, cost-effectiveness, sustainability, and regulatory compliance. Optimizing this stage involves adopting innovative materials, such as lightweight alloys or composite materials, enhancing fuel efficiency without compromising safety or performance.

Design and Production

During design and production, engineers develop the blueprint of the car body for the vehicle and create prototypes for testing. This stage is critical as it lays the foundation for the manufacturing process.

Optimization opportunities in this stage include implementing computer-aided design (CAD) software, virtual reality, engineering simulation with CAE and 3D printing technologies.

These advancements allow faster design iterations, improved accuracy, and reduced costs. Additionally, incorporating collaborative platforms such as PLM (Product Lifecycle Management) enables better communication and collaboration among teams involved in the design car production process.

The above stages are somehow "state of the art" in the car manufacturing process but do not fully reflect the latest advancements, mainly due to AI, leading to data-driven decisions such as generative design supported by AI. We will review them in the next section.

Latest Advances: AI in Industry 4.0 and Industry 5.0

Industry 4.0 and 5.0 represent significant advancements in the automotive sector.

  1. Industry 4.0 utilizes AI to create smart factories, optimizing manufacturing processes through data analytics and predictive maintenance.
  2. Industry 5.0 builds upon this same manufacturing innovation by emphasizing the collaboration between humans and AI-powered robots, enabling higher levels of automation while leveraging human creativity, problem-solving skills, and adaptability.

These advancements are reshaping the automotive manufacturing industry, increasing efficiency, productivity, and innovation.

Industry 4.0

In Industry 4.0, AI is crucial in handling and analyzing massive volumes of data generated by various sensors, devices, and machines. AI algorithms can identify patterns, detect anomalies, and derive insights from this data.

Predictive Maintenance

Predictive maintenance is a key application of artificial intelligence in the automotive industry that significantly benefits manufacturers. Car manufacturers can implement a proactive approach to maintenance with AI. AI can help to accurately predict potential failures or maintenance needs of machines and equipment. This allows to reduce downtime, optimize maintenance schedules, and maximize the lifespan of the equipment.

An example of predictive maintenance in the automotive industry is using machine learning algorithms to analyze sensor data collected from various vehicle components, such as the engine, transmission, and brakes.

These algorithms can detect patterns and anomalies in the data, enabling early identification of potential failures.

By detecting and addressing issues in their early stages, manufacturers can prevent unexpected breakdowns, minimize production delays, and reduce the costs associated with emergency repairs. Conversely, if the equipment is in good condition, the system can extend the maintenance interval, reducing unnecessary downtime and maintenance costs.

Conversely, if the equipment is in good condition, the system can extend the maintenance interval, reducing unnecessary downtime and maintenance costs.

A final aspect of predictive maintenance is leveraging historical data and machine learning algorithms to predict component failure rates and optimize spare parts inventory.

Optimizing the Production Line Schedule

Moreover, AI facilitates real-time decision-making in Industry 4.0.

AI algorithms can adjust production line plans dynamically by considering various factors, such as machine performance, supply chain conditions, and customer demands.

This real-time optimization helps manufacturers to improve efficiency, reduce costs, and respond swiftly to changing market demands.

Industry 5.0

While Industry 4.0 introduced the concept of smart factories and AI-driven automation, Industry 5.0 built upon this foundation by emphasizing the collaboration between humans and robots in manufacturing. In Industry 5.0, AI-powered robots and machines work alongside human workers, augmenting their capabilities and enhancing overall productivity.

By leveraging AI technologies, robots in Industry 5.0 can perform complex tasks with precision and efficiency. These robots are equipped with advanced perception systems, machine learning algorithms, and natural language processing capabilities, enabling them to adapt to dynamic environments and interact with human workers.

Robots can handle repetitive, mundane, or physically demanding tasks, allowing human workers to focus on more creative problem-solving activities.

The collaboration between humans and robots in Industry 5.0 allows for a more flexible and adaptable manufacturing process. Human workers can contribute their cognitive skills, critical thinking abilities, and creativity to address complex challenges that require human intuition and judgment.

This human-robot collaboration also enables the rapid reconfiguration of production lines to accommodate changing product specifications or customer demands, ensuring high customization, improved quality control, and flexibility.

Achieving Efficiency and Innovation

As consumer demands evolve, the automotive industry constantly seeks to improve its production systems and processes to meet market needs while maintaining safety, quality standards, and cost-effectiveness.

We will explore the importance of an efficient automotive manufacturing process and how it impacts the overall success of the automotive industry.

The automotive components manufacturing process involves various stages, from procuring raw materials to the assembly process of the automotive components.

One critical aspect is the assembly process, where a more efficient production process and assembly lines are crucial. Implementing a moving assembly line revolutionized the industry. This enhanced moving assembly line process enabled mass production and increased productivity. The conventional production line approach significantly reduced production time, making producing vehicles on a larger scale possible.

However, with new technologies and market demands, the automotive industry requires even more efficient and flexible production lines and assembly processes. To stay competitive, manufacturers must explore innovative methods that streamline operations while maintaining high-quality standards.

One approach is the integration of advanced automation and robotics technologies. By leveraging these technologies, manufacturers can automate repetitive tasks, increase precision, and reduce the risk of errors, resulting in a more efficient and cost-effective automotive production line and process.

Optimizing the Workflow

Efficiency is not only achieved through technology but also by optimizing the workflow of the automotive manufacturing process. An efficient automotive manufacturing process requires effective coordination between various stages of impacted automotive manufacturing process workflow and processes, such as sourcing and managing raw materials, assembly line operations, and the production of automotive components.

By mapping out the automotive manufacturing process workflow and identifying potential bottlenecks, manufacturers can implement solutions to streamline operations and maximize efficiency.

Furthermore, an efficient rapid manufacturing process is crucial in responding to market demands and reducing lead times. By embracing agile manufacturing principles, manufacturers can quickly adapt to changes, introduce new models, and address customer preferences. This flexibility allows for a more dynamic and responsive automotive industry.

Sustainability

Moreover, the need for sustainability has also driven the pursuit of efficiency in automotive manufacturing processes. Manufacturers are increasingly exploring eco-friendly materials, more fuel efficient models and production processes, and implementing greener practices to minimize environmental impact. The automotive industry can meet regulatory requirements and appeal to environmentally conscious consumers by adopting sustainable production and assembly line methods.

An efficient automotive production line and process is key to success as the automotive manufacturing industry constantly evolves. Automakers can achieve a more efficient and sustainable automotive manufacturing process by embracing advanced technologies, optimizing workflows, and adopting agile manufacturing principles.

Enhancing Car Manufacturing Processes through Optimization Opportunities

The automotive industry continually evolves, and manufacturers always seek ways to improve manufacturing processes. By revolutionizing manufacturing methods and adopting new technologies and lean manufacturing principles, automotive companies aim to produce safe and reliable vehicles while reducing production costs and improving quality control.

Advanced Manufacturing Methods

One area of optimization lies in the car-making process utilizing advanced methods. Automotive companies can utilize computer-aided design (CAD) to streamline car-making, creating virtual models of car bodies and components and facilitating precise production methods.

By integrating CAD with their other production systems and engineering systems, carmakers can reduce errors and minimize delays, ensuring a smoother transition to the next production stage.

An example is a CAD representation that is the reference for a built prototype for a preliminary wind tunnel test and virtual simulations.

The Industry 4.0 approach leverages the creation of a digital twin, a virtual replica of the physical product. This promotes transitioning from concept to production by simulating and optimizing various design aspects before committing to physical production.

Automotive engineers can identify and address potential issues, refine the design, and enhance performance in a cost-effective and time-efficient manner. The virtual design enables rapid iterations and provides valuable insights into product behaviour and performance.

By employing this approach, manufacturers can minimize errors, reduce wastage, and optimize the production process, improving quality, productivity, and customer satisfaction.

Furthermore, the digital twin is a valuable tool throughout the product's lifecycle, facilitating maintenance, monitoring, and even predicting performance and failure, enabling proactive measures and enhancing overall operational efficiency.

Wind tunnel testing is the physical process while CFD simulation (virtual aerodynamics simulation) could represent its digital twin

Lean Manufacturing: methods & benefits

The adoption of lean manufacturing principles enhances production volume while maintaining high-quality standards. By eliminating waste, optimizing inventory management, and streamlining production processes, manufacturers can improve efficiency, reduce costs, and increase their competitiveness in the automotive market. The continuous pursuit of lean practices enables companies to adapt and respond effectively to changing market demands, making them more agile and resilient in an increasingly competitive industry.

Lean manufacturing is a proven approach that can bring about substantial optimization opportunities for automotive manufacturers. By embracing lean principles, manufacturers can continuously analyze their production processes, identify areas for improvement, and implement strategies to enhance efficiency, productivity, and quality.

Historia del Lean Manufacturing by Andrés Felipe (historia-biografia.com)

JIT

One key aspect of lean manufacturing is just-in-time (JIT) inventory management. Instead of stockpiling large quantities of inventory, manufacturers strive to have the right raw materials and components delivered at the precise moment needed in production. This reduces inventory carrying costs, minimizes waste, and improves cash flow. For example, Toyota's production system, known as the Toyota Production System (TPS), is based on the principles of JIT, where suppliers deliver parts in small batches precisely timed to meet the production requirements. This lean strategy allows manufacturers to optimize their inventory levels, reduce storage space, and respond more effectively to fluctuations in demand.

SMED

Another aspect of lean manufacturing is the focus on efficient and flexible production line and setups. By implementing strategies such as single-piece flow, cellular manufacturing, and quick changeover (SMED - Single Minute Exchange of Die), manufacturers can eliminate bottlenecks, reduce lead times, and increase the overall flow and efficiency of the production line and process.

For instance, by arranging workstations in a logical sequence and minimizing movement between stations, manufacturers can achieve a smoother and faster production flow, eliminating unnecessary waste and improving productivity. Additionally, reducing the time required to switch between different products or setups through SMED techniques allows for greater flexibility and responsiveness to customer demands.

Benefits of Lean Manufacturing

Implementing lean manufacturing principles optimises production processes and contributes to maintaining high-quality standards. By focusing on waste reduction and continuous improvement, manufacturers can identify defects, errors, and inefficiencies in the production process and take corrective actions promptly.

This emphasis on quality control helps minimize defects, rework, and scrap, resulting in improved product quality, customer satisfaction, and reduced warranty claims and returns costs.

Robotics and Automation

In addition to process optimization, implementing new technologies can lead to substantial improvements. Automotive manufacturers can enhance efficiency and productivity by adopting cutting-edge technologies like robotics, automation, and modular production lines.

Automated and modular production line lines enable a precise and consistent assembly line, reducing human errors and increasing production speed. Integrating new manufacturing technologies also improves quality control tests, ensuring each vehicle meets stringent safety and reliability standards.

The Human Factor in Car Manufacturing

Collaboration and knowledge-sharing within the industry are also essential for optimizing the car manufacturing process. By sharing best practices and innovations, automotive companies can collectively drive improvements across the sector. Collaborative efforts may involve joint research and development projects to explore new methods and techniques to support more efficient mass production.

Moreover, manufacturers should prioritize investing in their workforce by providing training and upskilling opportunities. Equipping employees with the necessary knowledge and skills to operate advanced manufacturing technologies fosters a culture of innovation and continuous improvement.

Skilled employees are better equipped to identify optimization opportunities and contribute to the overall efficiency of the car manufacturing process.

Challenges and Solutions in Car Manufacturing: 3D Printing

We cannot talk about innovation in manufacturing without hinting at the emergence of 3D printing, also known as additive manufacturing.

Additive manufacturing has greatly impacted the automotive manufacturing process. This innovative technology has revolutionized conventional manufacturing techniques, providing automotive engineers with new opportunities and greater design flexibility.

One significant advantage of 3D printing in automotive manufacturing is its ability to produce complex geometries and intricate parts with high precision. The traditional car manufacturing process often requires multiple steps and assembly processes to create intricate components. With 3D printing, engineers can directly fabricate these parts, reducing the need for assembly and enhancing efficiency.

Moreover, 3D printing enables the mass production of lightweight structures, which is essential for improving fuel efficiency and reducing vehicle weight. By utilizing advanced materials, such as carbon fibre-reinforced polymers, in the 3D printing process, automotive engineers can create components that are not only lightweight but also possess outstanding strength.

Furthermore, 3D printing enables on-demand, efficient rapid manufacturing process, minimizing the need for large-scale production runs and reducing inventory costs.

By employing 3D printing for low-volume production or customized parts, automotive manufacturers can respond to customer demands more efficiently and economically.

Will a full car be manufactured with additive manufacturing? An article explores the possibility of designing a car with AI.

Key Takeaways

In conclusion, car manufacturing is a dynamic and highly competitive sector requiring continuous optimisation.

This article has delved into the key stages of the car manufacturing process and identified numerous opportunities for improvement and efficiency gains.

One significant area for optimization is the supply chain.

Manufacturers can reduce lead times, minimize inventory holding costs, and enhance responsiveness by streamlining the supply chain. For instance, implementing advanced logistics systems, such as real-time tracking and data analytics, enables manufacturers to optimize transportation routes, minimize delays, and ensure timely delivery of components and materials. This lean approach to supply chain management allows for improved coordination, reduced waste, and increased operational efficiency.

Another avenue for optimization is the implementation of advanced robotics and automation.

By integrating robotics into automotive manufacturing processes, manufacturers can enhance precision, speed, and consistency. For example, robotic arms can perform complex tasks such as welding, painting, and assembly more accurately and efficiently than manual labor. Automation also enables manufacturers to achieve greater process control, reduce human error, and improve safety conditions. Additionally, collaborative robots (cobots) can work alongside human workers, augmenting their capabilities and increasing overall productivity.

Furthermore, the article emphasizes the critical role of artificial intelligence (AI) in car manufacturing.

AI-powered technologies like machine learning and predictive analytics offer valuable insights and capabilities. For instance, machine learning algorithms can analyze large datasets to identify patterns and optimize various aspects of the manufacturing process. On the other hand, predictive analytics enable manufacturers to forecast maintenance needs, prevent breakdowns, and optimize equipment performance. By leveraging AI, manufacturers can achieve higher accuracy, precision, and safety levels, leading to improved product safety and quality standards and customer satisfaction.

By optimizing manufacturing processes and embracing AI technologies, car manufacturers benefit their industry and set an example for other sectors. The successful implementation of intelligent manufacturing practices showcases the potential for transformation and increased competitiveness for major manufacturers. These practices highlight the importance of continuous process improvement, efficiency gains, and the adoption of innovative technologies. Ultimately, by staying at the forefront of intelligent manufacturing, car manufacturers can adapt to changing market dynamics, enhance their competitive edge, and contribute to the overall advancement of the manufacturing industry.

About the author
About the author
About the author
Anthony Massobrio
Anthony has been a CFD expert since 1990, working initially as a senior researcher, then moved to Engineering, acting also as technical director in a challenging Automotive Tier 1 supplier environment. Since 2001, Anthony has worked in Software & Engineering Consultancy as a Sales Engineer and manager. In 2020, Anthony fell in love with AI and has worked since then in the field of “AI for CAE” at Neural Concept and as an independent contributor.
About the author
About the author
Anthony Massobrio
Anthony has been a CFD expert since 1990, working initially as a senior researcher, then moved to Engineering, acting also as technical director in a challenging Automotive Tier 1 supplier environment. Since 2001, Anthony has worked in Software & Engineering Consultancy as a Sales Engineer and manager. In 2020, Anthony fell in love with AI and has worked since then in the field of “AI for CAE” at Neural Concept and as an independent contributor.
About the author
Anthony Massobrio
Anthony has been a CFD expert since 1990, working initially as a senior researcher, then moved to Engineering, acting also as technical director in a challenging Automotive Tier 1 supplier environment. Since 2001, Anthony has worked in Software & Engineering Consultancy as a Sales Engineer and manager. In 2020, Anthony fell in love with AI and has worked since then in the field of “AI for CAE” at Neural Concept and as an independent contributor.
About the author
Anthony Massobrio
Anthony has been a CFD expert since 1990, working initially as a senior researcher, then moved to Engineering, acting also as technical director in a challenging Automotive Tier 1 supplier environment. Since 2001, Anthony has worked in Software & Engineering Consultancy as a Sales Engineer and manager. In 2020, Anthony fell in love with AI and has worked since then in the field of “AI for CAE” at Neural Concept and as an independent contributor.
About the author
Anthony Massobrio
Anthony has been a CFD expert since 1990, working initially as a senior researcher, then moved to Engineering, acting also as technical director in a challenging Automotive Tier 1 supplier environment. Since 2001, Anthony has worked in Software & Engineering Consultancy as a Sales Engineer and manager. In 2020, Anthony fell in love with AI and has worked since then in the field of “AI for CAE” at Neural Concept and as an independent contributor.
About the author
Anthony Massobrio
Anthony has been a CFD expert since 1990, working initially as a senior researcher, then moved to Engineering, acting also as technical director in a challenging Automotive Tier 1 supplier environment. Since 2001, Anthony has worked in Software & Engineering Consultancy as a Sales Engineer and manager. In 2020, Anthony fell in love with AI and has worked since then in the field of “AI for CAE” at Neural Concept and as an independent contributor.
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About the author
About the author
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About the author
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About the author
About the author
About the author
About the author
About the author
About the author
Anthony Massobrio
Anthony has been a CFD expert since 1990, working initially as a senior researcher, then moved to Engineering, acting also as technical director in a challenging Automotive Tier 1 supplier environment. Since 2001, Anthony has worked in Software & Engineering Consultancy as a Sales Engineer and manager. In 2020, Anthony fell in love with AI and has worked since then in the field of “AI for CAE” at Neural Concept and as an independent contributor.
About the author
About the author
About the author
About the author
About the author
About the author
About the author
About the author
About the author
About the author
Anthony Massobrio
Anthony has been a CFD expert since 1990, working initially as a senior researcher, then moved to Engineering, acting also as technical director in a challenging Automotive Tier 1 supplier environment. Since 2001, Anthony has worked in Software & Engineering Consultancy as a Sales Engineer and manager. In 2020, Anthony fell in love with AI and has worked since then in the field of “AI for CAE” at Neural Concept and as an independent contributor.
About the author
About the author
About the author
About the author
Anthony Massobrio
Anthony has been a CFD expert since 1990, working initially as a senior researcher, then moved to Engineering, acting also as technical director in a challenging Automotive Tier 1 supplier environment. Since 2001, Anthony has worked in Software & Engineering Consultancy as a Sales Engineer and manager. In 2020, Anthony fell in love with AI and has worked since then in the field of “AI for CAE” at Neural Concept and as an independent contributor.
About the author
About the author
About the author
About the author
About the author
About the author
About the author
About the author
About the author
About the author
About the author
About the author
About the author
About the author
About the author
Anthony Massobrio
Anthony has been a CFD expert since 1990, working initially as a senior researcher, then moved to Engineering, acting also as technical director in a challenging Automotive Tier 1 supplier environment. Since 2001, Anthony has worked in Software & Engineering Consultancy as a Sales Engineer and manager. In 2020, Anthony fell in love with AI and has worked since then in the field of “AI for CAE” at Neural Concept and as an independent contributor.
About the author
Anthony Massobrio
Anthony has been a CFD expert since 1990, working initially as a senior researcher, then moved to Engineering, acting also as technical director in a challenging Automotive Tier 1 supplier environment. Since 2001, Anthony has worked in Software & Engineering Consultancy as a Sales Engineer and manager. In 2020, Anthony fell in love with AI and has worked since then in the field of “AI for CAE” at Neural Concept and as an independent contributor.
About the author
Anthony Massobrio
Anthony has been a CFD expert since 1990, working initially as a senior researcher, then moved to Engineering, acting also as technical director in a challenging Automotive Tier 1 supplier environment. Since 2001, Anthony has worked in Software & Engineering Consultancy as a Sales Engineer and manager. In 2020, Anthony fell in love with AI and has worked since then in the field of “AI for CAE” at Neural Concept and as an independent contributor.
About the author
Anthony Massobrio
Anthony has been a CFD expert since 1990, working initially as a senior researcher, then moved to Engineering, acting also as technical director in a challenging Automotive Tier 1 supplier environment. Since 2001, Anthony has worked in Software & Engineering Consultancy as a Sales Engineer and manager. In 2020, Anthony fell in love with AI and has worked since then in the field of “AI for CAE” at Neural Concept and as an independent contributor.
About the author
Anthony Massobrio
Anthony has been a CFD expert since 1990, working initially as a senior researcher, then moved to Engineering, acting also as technical director in a challenging Automotive Tier 1 supplier environment. Since 2001, Anthony has worked in Software & Engineering Consultancy as a Sales Engineer and manager. In 2020, Anthony fell in love with AI and has worked since then in the field of “AI for CAE” at Neural Concept and as an independent contributor.
About the author
Anthony Massobrio
Anthony has been a CFD expert since 1990, working initially as a senior researcher, then moved to Engineering, acting also as technical director in a challenging Automotive Tier 1 supplier environment. Since 2001, Anthony has worked in Software & Engineering Consultancy as a Sales Engineer and manager. In 2020, Anthony fell in love with AI and has worked since then in the field of “AI for CAE” at Neural Concept and as an independent contributor.
About the author
Anthony Massobrio
Anthony has been a CFD expert since 1990, working initially as a senior researcher, then moved to Engineering, acting also as technical director in a challenging Automotive Tier 1 supplier environment. Since 2001, Anthony has worked in Software & Engineering Consultancy as a Sales Engineer and manager. In 2020, Anthony fell in love with AI and has worked since then in the field of “AI for CAE” at Neural Concept and as an independent contributor.
About the author
Anthony Massobrio
Anthony has been a CFD expert since 1990, working initially as a senior researcher, then moved to Engineering, acting also as technical director in a challenging Automotive Tier 1 supplier environment. Since 2001, Anthony has worked in Software & Engineering Consultancy as a Sales Engineer and manager. In 2020, Anthony fell in love with AI and has worked since then in the field of “AI for CAE” at Neural Concept and as an independent contributor.
About the author
About the author
Anthony Massobrio
Anthony has been a CFD expert since 1990, working initially as a senior researcher, then moved to Engineering, acting also as technical director in a challenging Automotive Tier 1 supplier environment. Since 2001, Anthony has worked in Software & Engineering Consultancy as a Sales Engineer and manager. In 2020, Anthony fell in love with AI and has worked since then in the field of “AI for CAE” at Neural Concept and as an independent contributor.
About the author
Anthony Massobrio
Anthony has been a CFD expert since 1990, working initially as a senior researcher, then moved to Engineering, acting also as technical director in a challenging Automotive Tier 1 supplier environment. Since 2001, Anthony has worked in Software & Engineering Consultancy as a Sales Engineer and manager. In 2020, Anthony fell in love with AI and has worked since then in the field of “AI for CAE” at Neural Concept and as an independent contributor.
About the author
Anthony Massobrio
Anthony has been a CFD expert since 1990, working initially as a senior researcher, then moved to Engineering, acting also as technical director in a challenging Automotive Tier 1 supplier environment. Since 2001, Anthony has worked in Software & Engineering Consultancy as a Sales Engineer and manager. In 2020, Anthony fell in love with AI and has worked since then in the field of “AI for CAE” at Neural Concept and as an independent contributor.
About the author
Anthony Massobrio
Anthony has been a CFD expert since 1990, working initially as a senior researcher, then moved to Engineering, acting also as technical director in a challenging Automotive Tier 1 supplier environment. Since 2001, Anthony has worked in Software & Engineering Consultancy as a Sales Engineer and manager. In 2020, Anthony fell in love with AI and has worked since then in the field of “AI for CAE” at Neural Concept and as an independent contributor.
About the author
About the author
Anthony Massobrio
Anthony has been a CFD expert since 1990, working initially as a senior researcher, then moved to Engineering, acting also as technical director in a challenging Automotive Tier 1 supplier environment. Since 2001, Anthony has worked in Software & Engineering Consultancy as a Sales Engineer and manager. In 2020, Anthony fell in love with AI and has worked since then in the field of “AI for CAE” at Neural Concept and as an independent contributor.
About the author
Anthony Massobrio
Anthony has been a CFD expert since 1990, working initially as a senior researcher, then moved to Engineering, acting also as technical director in a challenging Automotive Tier 1 supplier environment. Since 2001, Anthony has worked in Software & Engineering Consultancy as a Sales Engineer and manager. In 2020, Anthony fell in love with AI and has worked since then in the field of “AI for CAE” at Neural Concept and as an independent contributor.
About the author
Anthony Massobrio
Anthony has been a CFD expert since 1990, working initially as a senior researcher, then moved to Engineering, acting also as technical director in a challenging Automotive Tier 1 supplier environment. Since 2001, Anthony has worked in Software & Engineering Consultancy as a Sales Engineer and manager. In 2020, Anthony fell in love with AI and has worked since then in the field of “AI for CAE” at Neural Concept and as an independent contributor.
About the author
Anthony Massobrio
Anthony has been a CFD expert since 1990, working initially as a senior researcher, then moved to Engineering, acting also as technical director in a challenging Automotive Tier 1 supplier environment. Since 2001, Anthony has worked in Software & Engineering Consultancy as a Sales Engineer and manager. In 2020, Anthony fell in love with AI and has worked since then in the field of “AI for CAE” at Neural Concept and as an independent contributor.
About the author
About the author
Anthony Massobrio
Anthony has been a CFD expert since 1990, working initially as a senior researcher, then moved to Engineering, acting also as technical director in a challenging Automotive Tier 1 supplier environment. Since 2001, Anthony has worked in Software & Engineering Consultancy as a Sales Engineer and manager. In 2020, Anthony fell in love with AI and has worked since then in the field of “AI for CAE” at Neural Concept and as an independent contributor.
About the author
About the author
Anthony Massobrio
Anthony has been a CFD expert since 1990, working initially as a senior researcher, then moved to Engineering, acting also as technical director in a challenging Automotive Tier 1 supplier environment. Since 2001, Anthony has worked in Software & Engineering Consultancy as a Sales Engineer and manager. In 2020, Anthony fell in love with AI and has worked since then in the field of “AI for CAE” at Neural Concept and as an independent contributor.
About the author
Anthony Massobrio
Anthony has been a CFD expert since 1990, working initially as a senior researcher, then moved to Engineering, acting also as technical director in a challenging Automotive Tier 1 supplier environment. Since 2001, Anthony has worked in Software & Engineering Consultancy as a Sales Engineer and manager. In 2020, Anthony fell in love with AI and has worked since then in the field of “AI for CAE” at Neural Concept and as an independent contributor.
About the author
Anthony Massobrio
Anthony has been a CFD expert since 1990, working initially as a senior researcher, then moved to Engineering, acting also as technical director in a challenging Automotive Tier 1 supplier environment. Since 2001, Anthony has worked in Software & Engineering Consultancy as a Sales Engineer and manager. In 2020, Anthony fell in love with AI and has worked since then in the field of “AI for CAE” at Neural Concept and as an independent contributor.
About the author
Anthony Massobrio
Anthony has been a CFD expert since 1990, working initially as a senior researcher, then moved to Engineering, acting also as technical director in a challenging Automotive Tier 1 supplier environment. Since 2001, Anthony has worked in Software & Engineering Consultancy as a Sales Engineer and manager. In 2020, Anthony fell in love with AI and has worked since then in the field of “AI for CAE” at Neural Concept and as an independent contributor.
About the author
Anthony Massobrio
Anthony has been a CFD expert since 1990, working initially as a senior researcher, then moved to Engineering, acting also as technical director in a challenging Automotive Tier 1 supplier environment. Since 2001, Anthony has worked in Software & Engineering Consultancy as a Sales Engineer and manager. In 2020, Anthony fell in love with AI and has worked since then in the field of “AI for CAE” at Neural Concept and as an independent contributor.
About the author
Anthony Massobrio
Anthony has been a CFD expert since 1990, working initially as a senior researcher, then moved to Engineering, acting also as technical director in a challenging Automotive Tier 1 supplier environment. Since 2001, Anthony has worked in Software & Engineering Consultancy as a Sales Engineer and manager. In 2020, Anthony fell in love with AI and has worked since then in the field of “AI for CAE” at Neural Concept and as an independent contributor.
About the author
Anthony Massobrio
Anthony has been a CFD expert since 1990, working initially as a senior researcher, then moved to Engineering, acting also as technical director in a challenging Automotive Tier 1 supplier environment. Since 2001, Anthony has worked in Software & Engineering Consultancy as a Sales Engineer and manager. In 2020, Anthony fell in love with AI and has worked since then in the field of “AI for CAE” at Neural Concept and as an independent contributor.
About the author
Anthony Massobrio
Anthony has been a CFD expert since 1990, working initially as a senior researcher, then moved to Engineering, acting also as technical director in a challenging Automotive Tier 1 supplier environment. Since 2001, Anthony has worked in Software & Engineering Consultancy as a Sales Engineer and manager. In 2020, Anthony fell in love with AI and has worked since then in the field of “AI for CAE” at Neural Concept and as an independent contributor.
About the author
Anthony Massobrio
Anthony has been a CFD expert since 1990, working initially as a senior researcher, then moved to Engineering, acting also as technical director in a challenging Automotive Tier 1 supplier environment. Since 2001, Anthony has worked in Software & Engineering Consultancy as a Sales Engineer and manager. In 2020, Anthony fell in love with AI and has worked since then in the field of “AI for CAE” at Neural Concept and as an independent contributor.
About the author
Anthony Massobrio
Anthony has been a CFD expert since 1990, working initially as a senior researcher, then moved to Engineering, acting also as technical director in a challenging Automotive Tier 1 supplier environment. Since 2001, Anthony has worked in Software & Engineering Consultancy as a Sales Engineer and manager. In 2020, Anthony fell in love with AI and has worked since then in the field of “AI for CAE” at Neural Concept and as an independent contributor.
About the author
Anthony Massobrio
Anthony has been a CFD expert since 1990, working initially as a senior researcher, then moved to Engineering, acting also as technical director in a challenging Automotive Tier 1 supplier environment. Since 2001, Anthony has worked in Software & Engineering Consultancy as a Sales Engineer and manager. In 2020, Anthony fell in love with AI and has worked since then in the field of “AI for CAE” at Neural Concept and as an independent contributor.
About the author
Anthony Massobrio
Anthony has been a CFD expert since 1990, working initially as a senior researcher, then moved to Engineering, acting also as technical director in a challenging Automotive Tier 1 supplier environment. Since 2001, Anthony has worked in Software & Engineering Consultancy as a Sales Engineer and manager. In 2020, Anthony fell in love with AI and has worked since then in the field of “AI for CAE” at Neural Concept and as an independent contributor.
About the author
Anthony Massobrio
Anthony has been a CFD expert since 1990, working initially as a senior researcher, then moved to Engineering, acting also as technical director in a challenging Automotive Tier 1 supplier environment. Since 2001, Anthony has worked in Software & Engineering Consultancy as a Sales Engineer and manager. In 2020, Anthony fell in love with AI and has worked since then in the field of “AI for CAE” at Neural Concept and as an independent contributor.
About the author
Anthony Massobrio
Anthony has been a CFD expert since 1990, working initially as a senior researcher, then moved to Engineering, acting also as technical director in a challenging Automotive Tier 1 supplier environment. Since 2001, Anthony has worked in Software & Engineering Consultancy as a Sales Engineer and manager. In 2020, Anthony fell in love with AI and has worked since then in the field of “AI for CAE” at Neural Concept and as an independent contributor.
About the author
About the author
Anthony Massobrio
Anthony has been a CFD expert since 1990, working initially as a senior researcher, then moved to Engineering, acting also as technical director in a challenging Automotive Tier 1 supplier environment. Since 2001, Anthony has worked in Software & Engineering Consultancy as a Sales Engineer and manager. In 2020, Anthony fell in love with AI and has worked since then in the field of “AI for CAE” at Neural Concept and as an independent contributor.
About the author
Thomas von Tschammer
Thomas joined Neural Concept in the company's early days in 2018, following his master’s degree in mechanical engineering with a specialization in Neuroprosthetics. He is now Director of Operations, leading the Application Engineering team, and working closely with large companies to deploy AI-based workflow in their engineering design processes.
About the author
Anthony Massobrio
Anthony has been a CFD expert since 1990, working initially as a senior researcher, then moved to Engineering, acting also as technical director in a challenging Automotive Tier 1 supplier environment. Since 2001, Anthony has worked in Software & Engineering Consultancy as a Sales Engineer and manager. In 2020, Anthony fell in love with AI and has worked since then in the field of “AI for CAE” at Neural Concept and as an independent contributor.
About the author
Philipp Egolf
Philipp is responsible for the product development around the NCS platform. He has numerous years of experience in the Artificial Intelligence and data analytics environment with a background in Mechanical Engineering, the development of product visions and strategies and Human Centered Design Thinking.
About the author
Thomas von Tschammer
Thomas joined Neural Concept in the company's early days in 2018, following his master’s degree in mechanical engineering with a specialization in Neuroprosthetics. He is now Director of Operations, leading the Application Engineering team, and working closely with large companies to deploy AI-based workflow in their engineering design processes.
About the author
Anthony Massobrio
Anthony has been a CFD expert since 1990, working initially as a senior researcher, then moved to Engineering, acting also as technical director in a challenging Automotive Tier 1 supplier environment. Since 2001, Anthony has worked in Software & Engineering Consultancy as a Sales Engineer and manager. In 2020, Anthony fell in love with AI and has worked since then in the field of “AI for CAE” at Neural Concept and as an independent contributor.
About the author
Anthony Massobrio
Anthony has been a CFD expert since 1990, working initially as a senior researcher, then moved to Engineering, acting also as technical director in a challenging Automotive Tier 1 supplier environment. Since 2001, Anthony has worked in Software & Engineering Consultancy as a Sales Engineer and manager. In 2020, Anthony fell in love with AI and has worked since then in the field of “AI for CAE” at Neural Concept and as an independent contributor.
About the author
Anthony Massobrio
Anthony has been a CFD expert since 1990, working initially as a senior researcher, then moved to Engineering, acting also as technical director in a challenging Automotive Tier 1 supplier environment. Since 2001, Anthony has worked in Software & Engineering Consultancy as a Sales Engineer and manager. In 2020, Anthony fell in love with AI and has worked since then in the field of “AI for CAE” at Neural Concept and as an independent contributor.
About the author
Anthony Massobrio
Anthony has been a CFD expert since 1990, working initially as a senior researcher, then moved to Engineering, acting also as technical director in a challenging Automotive Tier 1 supplier environment. Since 2001, Anthony has worked in Software & Engineering Consultancy as a Sales Engineer and manager. In 2020, Anthony fell in love with AI and has worked since then in the field of “AI for CAE” at Neural Concept and as an independent contributor.
About the author
Anthony Massobrio
Anthony has been a CFD expert since 1990, working initially as a senior researcher, then moved to Engineering, acting also as technical director in a challenging Automotive Tier 1 supplier environment. Since 2001, Anthony has worked in Software & Engineering Consultancy as a Sales Engineer and manager. In 2020, Anthony fell in love with AI and has worked since then in the field of “AI for CAE” at Neural Concept and as an independent contributor.
About the author
About the author
Anthony Massobrio
Anthony has been a CFD expert since 1990, working initially as a senior researcher, then moved to Engineering, acting also as technical director in a challenging Automotive Tier 1 supplier environment. Since 2001, Anthony has worked in Software & Engineering Consultancy as a Sales Engineer and manager. In 2020, Anthony fell in love with AI and has worked since then in the field of “AI for CAE” at Neural Concept and as an independent contributor.