Not programming press brakes offline yet?

What’s that noise coming from your shop floor? That’s the sound of your equipment running, parts bending, and money being made—and fabricators who have adopted offline programming are hearing a lot more of it these days.

Your press brake operation has been doing things the same way for as long as you can remember. The good news is the process seems to be relatively efficient and profitable. The not-so-good news is that machine-based programming robs you of production.

You likely invest heavily in your press brake department, and you want those machines to work all day. The minute a job is done, the next program should be loading. That simply isn’t practical when programming on the machine’s console. By many estimates, traditional on-machine programming cuts a press brake’s throughput potential by half.

A growing number of fabricators are finding the answer in offline programming. Unfortunately, adopting this approach isn’t as easy as flipping a switch. A smooth transition hinges on a willingness to change perceptions and challenge the status quo.

Read the entire article in The Fabricator here.

Fiber-Powered Production

Next time you’re cruising down the interstate, take a moment to appreciate the engineering behind that fully loaded tractor-trailer beside you. Every mile, immense payloads and relentless torsional forces push intermodal chassis to their limits, testing both design and craftsmanship. That’s why durability isn’t just a feature, it’s a necessity.

With robust construction that lowers maintenance costs, reduces risk, and ensures compliance with the toughest safety and environmental standards, it’s no wonder more Intermodal Equipment Providers (IEPs), chassis pools, truckers, and transportation companies trust Jansteel trailers to go the distance.

Expanding into New Markets

Since beginning operations in Israel in 2004, Jansteel has established itself as a cornerstone of the region’s trucking industry. With a reputation for superior metal fabrication and exceptional craftsmanship, the family-owned company quickly rose to become the nation’s leading manufacturer of chassis and trailers.

In 2020, Jansteel expanded its operations to the United States with an eye on bringing its tradition of excellence to the North American trucking industry.

Today, Miami-based Jansteel USA, Inc. boasts capabilities spanning metal cutting, assembly, powder coating, welding, and painting. The facility manufactures chassis and an expansive range of trailers. Key to success is the ability to produce this equipment without relying on parts from overseas. This strategic move has not only unlocked the potential of new markets but is also solidifying Jansteel’s international presence while creating over 100 new jobs within the local community.

Following in his father’s footsteps, Jansteel USA CEO, Moshe Jan put the company’s success into perspective.

“In Israel, we produced chassis and a full range of trailer types. In the U.S., the market is so big that we can focus on chassis and just two or three trailer types. Back home, we were manufacturing about 40 trailers a month. Here we reach that number in just over two days. This is why we came to America, for the opportunity to grow.”

To keep pace with rising demand, Jansteel continues to invest in its people, equipment, and technology. In 2024, the company took steps to upgrade plasma cutting and bending operations with advanced fiber laser cutting technology. This would prove critical in helping Jansteel further expand its trailer lineup to meet the evolving needs of the industry it serves.

Read the entire article here in Shop Floor Lasers Magazine.

Offline Programming

How long does it take to program your press brake for the next job? Two, three, five minutes? While that might seem trivial, every minute that your press brake sits idle is lost revenue – likely a lot of it. And those minutes add up to a staggering amount at the end of the week, month, or year.

For a growing number of fabricators, regardless of size, the answer lies in offline programming. Unlike traditional at-the-machine programming, offline programming involves creating press brake bending programs on a computer, separate from the machine’s physical location.

Read the entire post here.

Scenario Modeling

The business world is bursting with what-if scenarios. One needs to look back no further than the 2020 pandemic to understand that companies must plan for a variety of situations. What if we don’t get that expected contract? What if certain regulations are suddenly expanded or eased? What if a hurricane threatens our plant?

Several approaches used for both immediate and long-term planning help companies set expectations, budgets, production targets and staffing requirements while preparing for business challenges.

Time Series Analysis predicts future business performance based on historical data patterns. By analyzing trends, seasonality, and cyclic behaviors in data, companies can forecast future sales, demand or financial metrics.

The Delphi Method gathers insights from a panel of experts to predict future events or trends. Independent forecasts are aggregated and iterated upon until a consensus is reached.

Regression Analysis models quantify relationships between variables and forecast future outcomes by analyzing how independent variables affect dependent ones. This highly mathematical method works best when there are established causal relationships.

Insights gained from such methods provide the framework to forecast growth while developing contingency. However, none can offer reliable answers in the face of shifting variables. Consequently, a growing number of manufacturers are adopting a more dynamic approach.

Read the entire article here in Industry Week magazine.

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.