The (Rocket) Science of Quality

What do the space program and a quiet running car ventilation fan have in common? Plenty: the same physics, research and guiding principles that launch rockets into space are now ensuring the quality of manufactured parts.

While beauty may be in the eyes of the beholder, quality, on the other hand, must be nonnegotiable. With market share, reputations and contracts hanging in the balance, there is no room for interpretive subjectivity of what is or is not acceptable. It is therefore critical that manufacturers ensure that their parts/products meet specific quality metrics, tolerances and specifications before reaching the customer.

Fortunately, quality inspection test systems are allowing them to do just this.  read the entire article in Manufacturing News.

The Expanding of AI and Engineering Simulation

Artificial intelligence (AI) is profoundly transforming engineering simulation, enhancing speed, precision, and scope. The integration of AI is enabling engineers to tackle complex problems more efficiently, opening up new possibilities and improving workflows across industries.

1. Accelerating Simulation Processes

AI accelerates simulation processes by optimizing time-consuming computations. Traditionally, engineering simulations require finite element analysis (FEA), computational fluid dynamics (CFD), or other complex mathematical models that demand substantial computational power and time. Deep learning and machine learning models, especially in areas like surrogate modeling, can streamline these tasks. Surrogate models are trained on large datasets from simulations and experiments to approximate the output of traditional simulation models with a fraction of the time and computational resources. For instance, by employing neural networks to learn the behavior of complex systems, AI allows engineers to predict outcomes without needing to re-run full simulations. This is beneficial in industries with time constraints, where accelerated testing speeds up the research and development process, fostering innovation.

2. Enhancing Accuracy

Minor miscalculations can lead to flawed designs and AI can improve the accuracy of simulations by analyzing and correcting potential errors that may arise during traditional modeling processes. These systems are well-suited for detecting patterns, spotting anomalies, and learning from past mistakes, which means they can help engineers create more accurate models.

Machine learning algorithms can also integrate diverse datasets, taking multiple variables into account that human engineers may overlook or find challenging to incorporate. The result is a more comprehensive model that better predicts real-world outcomes. Furthermore, AI’s capacity to minimize human error is particularly useful in fields where safety is paramount, such as aerospace engineering and civil infrastructure.

3. Optimizing Design

Another impact that AI is having on engineering simulation is in optimizing design and predicting how changes in one variable will affect others. Advanced A algorithms can analyze data from multiple simulation iterations, identify trends, and provide insights that guide design optimization. For example, in automotive applications, AI can simulate the effects of various materials, shapes, and manufacturing techniques on vehicle safety, aerodynamics, and efficiency. AI models can even predict maintenance needs and lifespan based on simulations, allowing for more efficient resource allocation and maintenance schedules. This predictive capability supports the engineering goal of creating designs that are both effective and cost-efficient.

4. Real-Time Feedback

With advancements in real-time data processing, AI can provide real-time feedback and adapt simulations based on incoming data. This capability is crucial in environments where conditions may change rapidly, such as in automated manufacturing or autonomous vehicle testing. Adaptive simulations powered by AI can modify parameters in real-time, allowing for a more dynamic understanding of system behaviors under evolving conditions. This leads to a more interactive simulation experience, enabling engineers to test hypotheses on the fly and adjust based on real-world feedback, ultimately leading to better-informed decision-making and greater adaptability.

5. Democratizing Access to Complex Simulations

AI-driven tools are making advanced simulation technologies more accessible to a broader range of users who may not have the resources for traditional high-complexity simulations. Machine learning models can simplify the user experience, allowing engineers with less simulation experience to create accurate models by handling some of the complex computations behind the scenes. Moreover, cloud-based AI simulation platforms enable remote access to powerful modeling capabilities, further broadening accessibility and enabling collaboration across locations.

Reshaping Simulation

AI is fundamentally reshaping engineering simulation by accelerating processes, enhancing accuracy, optimizing design, enabling adaptive simulations, and democratizing access to advanced modeling tools. These changes are fostering a new era of innovation and efficiency in engineering, with AI’s capabilities allowing engineers to push the boundaries of what is possible.

The ongoing integration of AI in engineering simulation promises even more sophisticated and insightful tools, ultimately transforming how engineers approach design and problem-solving across industries.

Go here to learn more about how AI is having a growing impact on engineering simulation and product development.

Plasma/oxyfuel system with 3D scanning automates challenging dome cutting operations

With more than 70 employees, Waterford Tank and Fabrication manufactures above-ground storage tanks and custom ASME pressure vessels in Beverly, Ohio. The company’s 90,000-sq.-ft. fabrication facility houses equipment including a plasma table; combination plasma/oxyfuel table; large, medium, and vertical ring rollers; a press brake; and 10 overhead cranes.

Waterford has a steady stream of work, but the volume of these jobs, coupled with complex fabrications and a limited ability to process thicker metals, had become a roadblock to growth.

Read the full article in The Fabricator.

Rolling in Productivity

Despite their relatively simple design, pressure vessels and tanks can present some complex fabrication challenges. Charged with storing liquids and gasses (often hazardous or corrosive) under sometimes demanding conditions, there can be no questions surrounding the structural integrity of these tanks. Consequently, manufacturing these impenetrable chambers requires that metal be formed, cut, and welded to exact specifications.

Because pressure vessels must withstand intense forces and high temperatures, their construction is guided by stringent safety, environmental, and regulatory requirements. This includes standards such as the ASME Boiler and Pressure Vessel Code. Compliance involves extensive documentation, regular inspections, and adherence to strict fabrication standards. Depending on their usage, tanks are constructed from a variety of material types, with the most common being stainless steel, carbon steel, and specialized alloys. Material selection is nothing short of critical as the wrong type or thickness can lead to premature wear, leaks, or even a catastrophic failure.

Read the article here.

Presenting with Purpose

Each year, Fabtech offers a unique opportunity to see a literal arena full of machine tools representing all types, sizes and brands. And this year is no different. While at the show, there will be a lot to see, including the equipment on exhibit from Cincinnati Inc. (CI). With more than 125 years under its belt, CI is proving that you don’t have to be the largest rock to make a big splash.

I sat down recently with Matt Garbarino, business unit leader for new machinery sales, Bryant Downey, business unit leader for software, and Nikki Stenzel, marketing manager, to learn more about what Fabtech attendees can expect to see at the CI booth, No. 13085. One thing I quickly learned was that the company has a passion that extends far beyond equipment and software.

Read it here.

Ready or Not, Manufacturers will Soon be Held to Rigid Sustainability Standards

By enabling manufacturers to incorporate sustainability best practices into the early upstream product development stages, engineers can advance innovation while helping to mitigate the industry’s environmental footprint.

ccording to the United States Census Bureau, data from the International Database puts the global population at about 8 billion and rising. With this growth comes an increased demand for products. Unfortunately, as manufacturing output intensifies, so does its effect on the environment.

Common significant environmental footprints in discrete manufacturing include:

• Material Consumption: The current demand alone exceeds 1.75 of Earth’s capacity.
• Energy Consumption: 54% of global energy consumption is by manufacturing and production sectors.
• Waste (Hazardous and Non-Hazardous): Only 18% of e-waste and 6% of discarded plastic is recycled. Although aluminum can be infinitely recycled, 7 million tons are not recycled each year.

In response, forward-thinking manufacturers are emphasizing a shift towards more sustainable practices. In addition to social awareness, such initiatives are generally driven by a confluence of business factors, including demand, regulatory requirements, economic benefits, and the broader shift towards a circular economy.

Read the entire article here in Digital Engineering 24/7.

Unlocking the Full Potential of Simulation Results

The manufacturing industry’s movement towards zero physical prototype testing and the consequential shift towards increased digital testing represent a historic turning point in the simulation world. This transition highlights the critical need to embrace and implement new classes of tools to support the management and sharing of simulation results data. Foremost among these tools are Simulation Process and Data Management (SPDM) and Rapid Results Review™ (RRR).

Simulation Process and Data Management

Simulation Process and Data Management, refers to a comprehensive approach to managing simulation processes and their associated data throughout their lifecycle. It involves organizing, storing, and retrieving simulation data, ensuring version control, traceability, and data integrity.

SPDM facilitates collaboration among team members, streamlines workflows, and enhances productivity in simulation-based projects. By centralizing simulation data and automating processes, SPDM optimizes decision-making, reduces errors, and enhances the efficiency of engineering and research endeavors.

SPDM is playing an increasingly important role in modern product development and engineering. Through SPDM, many companies have realized measurable and sustainable gains in product development time, quality, and cost. As industries strive for innovation, agility, and cost-effectiveness, the significance of SPDM cannot be overstated.

Rapid Results Review

While SPDM handles a wide range of simulation data and processes, the integration of Rapid Results Review technology emerges as a vital component of every successful SPDM installation and its adoption. RRR contributes to shortening product development cycles, improving product performance, and minimizing time-to-market. All within the SPDM framework.

Read the entire article here.

Seven Ways to Grow Profits Without Adding Customers That Companies Often Overlook

Because the bottom line is critical to any “for profit” company, business owners and management are constantly looking for ways to improve. The key is to advance profitability without relying solely on sales.  How? Look around — profitability boosters can be found throughout the average plastics processor’s operation. Technology in the form of automation, for example, provides the foundation to become more efficient, cost conscious, and less wasteful. And there are plenty more opportunities. In fact, here are seven often overlooked areas where you can enhance profitability.

Read the entire article here in Plastics Today magazine.

Bringing CAE Reporting into the Digital Era

Does today’s product development process match current market demands or is it just a replica of the way we’ve “always done it”? Looking in from the outside, product development can often appear to be a sequential process on a one-way street running from design to production with a side trip for analysis. However, there are multiple touchpoints and feedback loops within and between these stages.

One of the most critical, yet often overlooked and underdeveloped, areas of collaboration is between the CAE analyst and design teams. More than an inconvenience, effects of this gap can ripple throughout the organization, causing delays, excessive costs and bad decisions.

Read the entire Machine Design story here.

Smart Approach

One of the biggest mistakes a small to mid-size fabricator makes has nothing to do with equipment, personnel or partnerships. Rather, the error lies in dismissing automation as beyond what they need or can afford. Automation positions manufacturers for long-term success in an increasingly digital world. Reducing manual or repetitive efforts frees up skilled workers to focus on higher value tasks, minimizes errors, improves product quality and grows profitability through increased production capacity.

So, with these advantages and more, why do some fabricators shy away from automation?

Read more here.