To keep up with rising product complexity, engineers need more powerful systems engineering tools that offer enhanced modeling capabilities and leverage the power of generative AI. Siemens and IBM announced last year that we are collaborating to accelerate sustainable product development and operations. Since then, the two companies have partnered to provide standard systems engineering solutions through the integration of IBM Engineering Systems Design Rhapsody with Siemens Teamcenter, Polarion and Capital. By working together, we have updated the interface of our systems engineering tools and developed prescriptive templates for engineers to seamlessly adopt the solutions. Siemens and IBM are now collaborating to augment the product development and operation optimization capabilities enabling engineers to build with IBM’s AI and data platform, IBM watsonx. This helps provide access to relevant information and tools throughout the engineering process.

The joint team is continuously extending and innovating the solutions using a digital thread approach, providing leading-edge digital tools that enable organizations to create, maintain and capitalize on digital threads. These digital threads seamlessly connect data sources across the product and service lifecycle. As a result, organizations enjoy greater accessibility to important product information and can address the challenges associated with designing next-generation products based on actual data from manufacturing and operations.

Digital threads connect every aspect of the product lifecycle

Digital threads are the essential link to a product’s mechanical, electrical, electronics and software design. This includes manufacturing and other downstream operations, such as maintenance, service and end-of-life management. Digital threads are becoming the essential and mandatory technology to cope with regulatory compliance and maintenance requirements and are implemented and defined during product design. Product-related information can flow seamlessly between cross-functional teams, breaking down data silos and communication barriers that impede collaboration and put product quality at risk. Engineers and other stakeholders work from a single source of truth to coordinate work more efficiently without worrying that information is lost or outdated. As a result, stakeholders can make well-informed decisions throughout the product development process.

The digital threads and digital twins of physical assets, fleets or factories ensure accurate contextualized data flow and optimized service processes from engineering to operations. With increasing requirements and more regulations from the EU, as well as in other countries, the need for monitoring and management of the product lifecycle has become even more important.

The new combined engineering solution from Siemens and IBM can provide data visibility and support traceability throughout the product lifecycle, from early design and manufacturing to operations, maintenance, updates and end-of-life management. This can help companies make informed decisions earlier in the design and provides an engineering process to help drive improvements in cost, performance and sustainability.

GenAI-enhanced digital threads can automate and transform workflows for companies and bring complex and more sustainable products to market faster

Systems engineering is a very complex process that requires engineers with unique skill sets. When bringing GenAI into our systems engineering solutions, the technology can help automate the creation of system models. Engineers can also then use natural language processing to operate faster. Instead of manually typing, drawing and curating the design by coding, engineers can instead verbally instruct the system and software on the task they want to perform.

There will be a process to develop the knowledge base that trains the model, but over time it will be able to assist the engineers with recommendations and speed up the design process. Then the next step will be to generate software codes automatically using GenAI technology, leveraging the extensive knowledge base that has been built into your system. In reality, this helps to democratize systems engineering and make it accessible to more people with a broader skill set. There has always been a shortage of specialized experts in the marketplace, and this approach can help broaden the potential pool of engineers that companies can hire for systems engineering jobs, accelerating the product development process and shortening time to market.

IBM’s AI and data platform, IBM watsonx securely enables engineers to use large language models (LLMs) and other foundation models in a truly open environment, avoiding vendor lock-in based on development in IBM Research. This open approach enables engineers to design highly complex products with confidence and spend more time focusing on key differentiators such as quality and sustainability.

Siemens and IBM are also collaborating on developing a SysML v2-based solution with an associated migration path for businesses to transition to the next generation Systems Lifecycle Management solutions. SysML defines a modern modular standard for the specification, analysis, design, verification and validation of a broad range of systems and systems-of-systems. Service lifecycle management can assist in maximizing business value for product serviceability by connecting service engineering and maintenance to facilitate new collaborative processes between OEM and operators.

Systems engineering is being adopted by nearly every industry as a more holistic, collaborative and efficient approach is required in the market

Most people know systems engineering from aerospace and automotive industries; they are indeed the early adopters of the systems engineering approach. However, today the application of systems engineering extends beyond these industries into a wider range of sectors that have electronics and software embedded in their products. These industries require a holistic, collaborative and efficient approach to designing complex electromechanical systems.

Electronics

The integration of electronics into a wide range of products and industries is fueling significant growth and innovation around the world. As technology continues to evolve, we can expect to see even greater convergence of electronics with other emerging technologies. For electronics designers and manufacturers, they need a solution that unifies electrical, mechanical and software domains on a single platform. This can provide a comprehensive system view that encourages innovation and accelerates development cycles. They also need a smart manufacturing strategy to enable businesses to connect and streamline processes from customer desire, engineering and production to service.

Aerospace

As the early adopter of systems engineering, organizations in this industry are developing cutting-edge platforms and systems with exceptional performance goals. Governments are transforming infrastructure and security systems for new aircraft and technology. Companies need innovation, facilitated by collaborative, synchronized program management across the product lifecycle and value chain. Multidisciplinary design and optimization provide a comprehensive design solution that integrates critical aspects of product development, including mechanical, electrical and software design. That way when requirements change, all aspects of the design can adapt simultaneously, significantly speeding up and reducing the impact of change.

Automotive

Software and systems engineering accelerates the development of electric vehicles (EV), advanced driver-assistance systems (ADAS), interaction with the vehicle for maintenance and usability and autonomous vehicle (AV) feature deployment. It does so by utilizing methodologies, processes and tools that manage the rapid increase of software and electronics while providing mechanical system alignment. As vehicle software becomes increasingly interconnected and integrated across multiple domain systems, combining advanced software and systems engineering are required to ensure software and hardware interoperability. This approach will help deliver vehicle performance, compliance, safety and cybersecurity while meeting challenging cost and timing targets.

Design and manufacture sustainable and complex products faster

Companies today face more pressure than ever to deliver sustainable and quality products on short timelines. At the same time, rising product complexity is making it harder to coordinate cross-domain engineering and manufacturing work with other functional departments. Siemens and IBM’s joint solution for systems engineering and asset lifecycle management helps manufacturers realize continuous integration across domains from concept through operation.

For additional information about current Siemens and IBM joint offerings visit our respective websites at the Siemens + IBM Partnership Page.

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It’s easy to forget the technology that supports the food industry when you look at a meal on a plate. After all, a lot of food preparation is still done at home, or by a local restaurant. But what about the ingredients? They must come from somewhere and they need to be processed into a consistent, high-quality product usable by chefs, home cooks and fast-food operators. In truth, the amount of engineering behind the foods we eat is enormous.

Blendhub is well versed in the hidden complexity behind the food industry. The company aims to streamline food production into easy, repeatable processes to ensure a product has the same quality and consistency regardless of where it is made, who makes it and the local ingredients available.

“The founding principle,” as Henrik Stamm Kristensen, founder and chief moonshot officer at Blendhub, puts it, “was there are trillions of recipes available online from Google search to cookbook uploads and individual blogs, all together containing millions of different food ingredients. We set out to connect the dots and ‘kill the black box’ – read transparency – by identification of every single ingredient and its functionality in the final food product.”

To make this dream a reality, Blendhub couldn’t just worry about its own workflows, products and equipment; it also had to keep a close eye on suppliers from around the world. Even a simple ingredient, like milk, can have different qualities, material properties, compositions, allergens and tastes due to local regulations, animal feeds, climates, livestock and more.

Using Siemens Digital Industries Software’s Xcelerator portfolio of solutions for digital transformation, the company was able to digitally transform its own and other food producers’ product lifecycle, create a central, cloud-based repository of supplier data and scale it to the point where anyone could take a food product idea to market launch anywhere in less than 3 months’ lead time. And the best part is, Blendhub and Siemens are sharing this technology with the world.

Who is Blendhub?

At the end of the day, Blendhub offers hungry consumers, and food and drink companies, powder-based food ingredient solutions or powdered food products. Think of just-add-liquid meals like dry pancake batter: Add water, dairy or vegetable milk, eggs (if you’re feeling ambitious) and the powder to a bowl, then mix, cook and eat. Blendhub may have been the company contracted by a given brand to produce the powdered mix.

What really sets Blendhub apart from its competitors is its extreme flexibility and localization. Traditionally, a company might spend years and millions of dollars to open a new food facility. In fact, Stamm Kristensen laments the first time he opened a food production facility in Spain. “It was a turning point,” he says. “We did the same thing most other food producers do. We went out to the market, we looked for hardware, blending equipment, you know, all the equipment to build a facility. It took a little more than two years, and we understood that the final factory was not replicable … it does not make sense!”

After what Stamm Kristensen describes as, “all that hassle,” he called in his engineering team with a mission: build a blending and packaging factory that can fit in a 40 ft container. It must be easily transported, cleaned, recommissioned, validated, certified, switched to a new product and installed in any room with the right size to house it. With this equipment, Blendhub could now make its products where the customers and/or ingredients were located.

The next time Blendhub needed a new facility, all Stamm Kristensen and his team needed was to find a factory building for rent large enough to fit the container, a quality control lab and a food formulation and reformulation lab. The first facility of its kind opened in India in less than nine months and cut the cost of specific food recipes by 30%. Better yet, Blendhub now had a replication model to deploy anywhere on a narrow budget.

But to capture big name customers like Unilever and PepsiCo, who Stamm Kristensen says his facilities are approved by, this replication model needed to be taken a step further. It needed to ensure that wherever the facility was, its recipes and final products were consistent. After all, a globally branded food product is supposed to taste the same wherever you are, so the solutions created by Blendhub must be the same as well. To ensure this level of consistency, Blendhub needed exceptional and instant quality control and a digital transformation.

Blendhub’s digital transformation reimagines the food industry

Stamm Kristensen notes that the first step was to digitize the quality and production equipment as the hardware wasn’t cloud-based. Next, Blendhub created software to run and communicate with its equipment. The idea was to have the software control not only the recipe and ingredients, but also the operations of the equipment.

To ensure quality, Blendhub started using near-infrared spectroscopy to assess the quality of its products and the products of its suppliers. But due to insufficient software quality, they created their own ChemoMetric Brain platform. For example, a potential supplier might send Blendhub a sample of their whey powder. Blendhub can then run those samples through the spectroscopy machine both before and after mixing it into a product. They can then assess the homogeneity of the blend and how the finished product performs to see if it meets specification. By repeating this process, Blendhub started to produce a library of its ingredients, product compositions and performance based on spectroscopy data. These results now act like fingerprints to check anything that goes in or out of a facility.

Stamm Kristensen adds, “If we can digitize the suppliers that we have approved ourselves, and if we can digitize the outcome — the blended powder-based solutions that we supply to our customers — then what if we actually could digitize [any] formulation that is made by anyone in the world?”

This concept then became the crux of Blendhub’s food-as-a-service model.

Food-as-a-Service?

The idea of food-as-a-service, at least to Blendhub, is to enable different food formulators, ingredient suppliers and experts to participate in a project to digitize the whole powder blending lifecycle. Suppliers can input their own spectroscopy data and then others can assess their product’s quality. Participants can then customize recipes and compositions, based on all of this collected data, to create recipes and shared value.

For an example, Stamm Kristensen considered a retired food formulation expert with a wide range of industry knowledge. That expert is likely to still experiment with new recipes on their own as a hobby or a means to make money on the side. They can use Blendhub’s repository of data to customize their own recipes. The company could then offer this recipe, as a product, to a customer. Everyone down from the suppliers to the expert wins, as Blendhub ensures they receive a margin of the formulations’ profits.

“We can show that with these freelance formulators, with these ingredients suppliers, we are now creating a participation model where everyone [creating and participating are] taking advantage of that shared value,” says Stamm Kristensen. “So, this is … why we have turned our business model into a Food-as-a-Service model where we invite many other people and organizations to participate.”

Blendhub’s partnership with Siemens

To bring its digital transformation and food-as-a-service model to reality, Blendhub approached Siemens Digital Industries Software. Tools like Siemens Opcenter, for manufacturing operations management (MOM), and Totally Integrated Automation (TIA), for monitoring and controlling production in real time, were used to bring data from differing equipment into the Siemens ecosystem. But perhaps the most influential result from this partnership is how Blendhub is exploring the use of Teamcenter X, Siemens’ cloud-based Product Lifecycle Management (PLM) solution designed to provide organizations with a scalable, flexible and easy-to-deploy PLM platform to manage product data and processes throughout the entire product lifecycle, from design and development to manufacturing and maintenance.

Stamm Kristensen says, “This is where Blendhub and I came and said, ‘what if we can start using Teamcenter X and start utilizing some very useful capabilities for multiple users, companies and people to connect on one single platform?’” The idea is to use Teamcenter X as the backbone for Blendhub’s library and food-as-a-service platform vision. Its users can then access the data and produce a recipe on the database that anyone can use. As a result, everyone benefits by accessing the same single source of truth.

For years, Siemens has been connecting suppliers from all industries with OEMs via its Teamcenter software. Blendhub is a recent example of a small or medium business making full use of Siemens’ solutions in an effort to achieve sustainable success..

“Most companies are only thinking about their own problems internally, but we look beyond that and say, ‘how can we bring our internal solutions to the utilization of many of the other small and medium enterprises around the world?’” Stamm Kristensen says. “And that is exactly the same reason why with Siemens, we are pushing the boundaries to start prototyping what we could do with Teamcenter.”

Visit Siemens to learn more about how Siemens’ digital transformation technologies that can impact the food and beverage industries.

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The Cremina classic lever-operated espresso machine. We like the “Swiss” red one pictured here. (Right) The Cremina modeled in Solid Edge. (Image: Felix Wey/ Schätti AG Metallwarenfabrik.)

Thomas Schätti and his brothers, all mechanical engineers, run multiple family businesses from their headquarters in Glarus, Switzerland under the family name, Schätti AG Metallwarenfabrik. Jos Schätti is the eldest and president of Schätti, and Stefan Schätti is COO. They were introduced to Olympia Express, makers of espresso coffee grinders, which appealed to Thomas Schätti on several levels. Schätti had always loved the mechanical aspects of mechanical engineering, and also loved the aesthetics of industrial design, having studied both subjects. Top that off with his love of espresso, and it seemed like a no-brainer for the brothers to invest in Olympia Express in 2011 and install Thomas as CEO to run it.

The Schätti brothers were exposed to business and mechanical engineering at an early age as their grandfather ran a sheet metal business in the 1940’s, which their father eventually took over. When asked why they became mechanical engineers, Schätti said they were “conditioned” by the family business as they grew up learning the trade by working on machines and doing stamping, milling, painting and welding. “We were conditioned, but we were also technically interested, and it suited us,” said Schätti.

The Schätti brothers took over the family business together in the early 1990’s, which Schätti said was tough at times; as you can imagine, the three brothers occasionally butted heads.

Today the family business is 90 years old, and they continue to pride themselves on family tradition and quality. The core business continues to revolve around design and manufacturing of products made from sheet metal, including electrical household appliances, components and devices for ventilation technology, as well as fittings and mechanisms for furniture, white goods and mechanical and apparatus engineering. They also currently design and manufacture the Olympia Express machines, since taking over the brand in 2011.

The Olympia Express brand goes all the way back to 1928, started by Italian Luigi Bresaola who ran the Olympia Café in the border town of Italy in Switzerland. “He was technically very gifted,” said Schätti. “He was northern Italian from Trieste, which is one of the most important places for coffee as well. He started a coffee bar [in Switzerland] and he was not happy with the coffee machine, so he started to design his own coffee machines.”

After making his machines available to cafes and restaurants under the name Olympia Express, he started offering espresso machines for home use.

Today the Schätti brothers design and manufacture the Olympia Express machines in house as they continue to combine the company’s passion for Italian espresso and the old tradition of Swiss craftsmanship. They make machines that are built to last, as the tanks are made out of chrome steel. We’re talking built to last for decades, as “50-year-old Olympias” are still a highly sought after machine and often kept in the family and passed down from generation to generation.

Olympia Express uses Solid Edge from Siemens, and Schätti said when they took over the company the previous owners had designed in 2D, so the data was not very useful to them. They remodeled all the parts of the machine in Solid Edge and made new models as well as spare parts. Essentially, they started fresh and built a complete data engineering set. Since then, they’ve made various design iterations and improvements to the machines.

Schätti said overall they have kept the analog look of the machine. He said while some companies might focus on innovation and progression and changing the look, Olympia Express has stuck to the traditional appearance of their machines while also increasing the choice of materials to provide the highest quality product possible.

Though Schätti’s combined businesses have around 12 employees in the engineering department, Olympia Express only requires one engineer. Schätti said Solid Edge is extremely easy to learn and includes helpful tutorials within the interface. They have also developed an in-house tutorial for their draftsman interns, typically ages 15 to 16, where they cover the fundamentals of Solid Edge, enabling them to model a small mechanism and produce a drawing within three days.

To illustrate how easy it is to learn Solid Edge, Schätti uses his daughter as an example. She was able to design and 3D print a tamper base, pictured below.

He said one of the benefits 3D modeling with Solid Edge provides is that it speeds up the design process and reduces the number of prototypes. They can easily model and quickly 3D-print a prototype to get a better feel of the components in various materials.

Since they use a lot of sheet metal in the machines, having a tool like Solid Edge that includes a module for sheet metal was very important to the company.

They also use Teamcenter for design review and to manage design revisions. “It becomes even more important to be able to maintain the data than for the engineer to create it,” said Schätti.

He said they also use the rendering capabilities for internal communications. In addition, they sometimes service machines that are 50 or 60 years old, so they are very fond of the exploded views capability in Solid Edge. With exploded views, they can provide documentation on how to assemble and also how to service the machines so the servicing department can see which spare parts they need and how to replace them. “That’s where Solid Edge has proven very helpful, as well: making exploded views to create documentation on how to replace parts and how to assemble them initially,” he said.

These high-tech machines may not be for everyone as they command a hefty price. They start around US $3,000. They offer three machines (available in three colors) and one of the most sought after is the Olympia Express Cremina. The New York Times wrote the “Cremina 67, a lever-operated machine designed in 1967, is ‘the best Espresso machine in the world.’”

In addition, Olympia Express offers an updated version, the Cremina SL, and the Maximatic semiautomatic machine that provides espresso in just a few steps. Lastly, they offer the Moca espresso grinder.

Despite the name and logo, Schätti said Olympia Express is more in the “slow foods” category. “It’s more of a celebration to make coffee and make an espresso as it takes time to prepare it. And the quality of course, it’s really good. It’s like the small machines can really make coffee like the quality of a barista machine in an Italian coffee bar,” said Schätti. “The size is just a fraction of the professional machine, but it is built like a professional machine. The materials are the same as in the big machines the baristas have. It’s like having a home barista.”

About the price, Schätti said if coffee is important to you, you will spend a lot of money on a coffee machine if it’s the right one for you. He often justifies it to his mountain biking friends saying it’s similar to how they spend five or six grand on a mountain bike.

He said the Olympia Express machines are definitely on the wish list of many serious coffee lovers. Most must save up to make the purchase.

Schätti also has a wish list for Solid Edge. What Schätti said he’d like to see in Solid Edge is the ability to test temperature stability better. “Temperature stability is a very, very, very important point and temperature control is a very important thing in coffeemaking and maintaining a stable temperature. We are lucky that we inherited machines that can hold a temperature. But if you want to design new machines you must in fact reach the same quality level and simulating temperature distribution and flow would be really helpful. It’s on our wish list.”

Speaking of wish lists, the Olympia Express machine is on ours at engineering.com.

Visit Siemens to learn more about the Solid Edge for Startups program.

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Written by: Dale Tutt and Jim Thompson, Siemens Digital Industries Software

The medical device and pharmaceutical industries are emerging from a period of unprecedented challenge and upheaval. Supply chain challenges and growing complexity have impacted the industry at a time when speed and agility have become critical in the delivery of new therapies, devices and drugs. Meanwhile, the management of risk and protection of patient safety and privacy have remained paramount despite shortening timelines.

This disruption, however, has sparked a wave of innovation and ingenuity in the design and production of medical devices and pharmaceuticals. The addition of digital elements, electronics and software to the life sciences industry has powered the creation of smarter and cheaper medical devices and accelerated the development of new drugs. The ongoing digitalization in the delivery of healthcare is also laying the foundation for a shift in how care is delivered, where home is becoming the new hospital.

Medical device and pharmaceutical trends in the post-pandemic era

The pandemic highlighted the significant built-in risk associated with highly global supply chains; which had become the norm across industries. The pandemic also prioritized condensing already shrinking development cycles. Disruptions to semiconductor production also hampered the production of various devices, vehicles and equipment. This impacted nearly every industry as computing and electronics approach ubiquity.

Meanwhile, the rapid development of the COVID diagnostic tests and vaccines demonstrated to the industry that faster timelines can be achieved within the current regulatory framework, catalyzing device manufacturers and pharmaceutical companies to search for better means of managing the complexities of drug and device development to minimize development cycles.

Shifting care from hospital to home

Methods of delivering care have also undergone some upheaval in recent years. Hospital beds are in high demand as many populations age and require increased care. With limited space and growing costs in traditional hospital and clinical settings, the ability to deliver high quality care remotely and to support patients outside the confines of the hospital is becoming crucial.

This requires increasingly intelligent, robust and safe medical devices that can be distributed to patients for use in their homes or on the go. For device manufacturers, the result is increased complexity in the design, engineering and regulatory clearance of new devices to ensure safety, efficacy and ease-of-use by untrained users. For example, smart glucose monitors are now available that can be worn or implanted, helping diabetes patients manage their condition more easily and reduce episodic emergency clinical care. The smart device continuously monitors blood glucose levels, displaying this information for the patient to use in tracking their blood sugar and its responses to diet, exercise, stress and other factors.

The age of software-defined care

Software is an increasingly central piece of the delivery of modern therapies, and this will only heighten in the future. Software is everywhere in life sciences and healthcare. It is used in the design, production, operations, delivery and management of devices and drugs. Software is also being used increasingly as a medical device itself. The integration of software into such a multitude of processes has enabled remarkable advancements in the technology of medicine, aiding in the diagnosis and treatment of disease, the management of chronic conditions and the organization and security of patient data. Yet, the growing application of software and digitalization in the medical space incurs some challenges.

All this software, including updates whether used by a medical provider or by a patient, must undergo rigorous certification and risk assessment to ensure patient safety and efficacy. Furthermore, smart medical devices, software as a medical device and even wellness devices such as a smart watch all produce or manage highly sensitive patient data. Manufacturers must therefore adopt rigorous data security and risk management protocols with the same attention and investment paid to traditional innovation pathways for medical products and therapies.

Digitalization fosters improvement and innovation

Digitalization and digital twins are being adopted by the medical industry for their ability to improve underlying engineering, design and data management processes. This becomes particularly important as devices become more complex, smart and software-defined. Medical devices are an especially good fit for advancing the digitalization of design, engineering, testing and production as many are discrete-manufactured products, created in the same way as cars or smartphones — two examples of industries that are viewed as leaders in digitalization. The comprehensive digital twin of a new medical device enables engineers to simulate and predict multiple aspects of device performance, such as heating or power consumption, to ensure reliability and safety. Likewise, digitalization is a boon to the development of surgical robotics that are highly precise and robust, enabling surgeons to perform delicate tasks with confidence.

Due to the potential advantages digital twins can offer, digitalization is top of mind for medical device and pharmaceutical companies. Yet, the necessity for safety and minimizing risks, and the high regulatory standards with which new devices and drugs must comply, have prevented these industries from embracing digitalization on the same timeline as others, such as the automotive and consumer electronics industries. For manufacturers of medical devices and drugs, the potential benefits of a new technology or methodology must be sufficiently evaluated and proven to displace a legacy process due to the importance of preserving product quality and patient safety.

So, looking to the future, how can engineers and designers expect digitalization and the digital twin to advance in the medical device and pharmaceutical industries to further adoption?

The evolution of digitalization in the delivery of new therapies

Broadly, continued investment in digitalization will open new opportunities for the application of the digital twin, automation, artificial intelligence (AI) and the industrial metaverse with respect to the development of medical devices, implants and pharmaceuticals. The application of these technologies will be crucial for increasing the productivity of healthcare systems and improving the remote delivery of care. As space in hospitals becomes increasingly limited, especially for aging populations, the ability to provide effective care whether in the hospital or at the home will be vital.

The pharmaceutical industry is already taking advantage of AI to analyze drug performance to better understand how the body absorbs different medications. The regulatory approval of a new pharmaceutical requires multiple stages of testing in both laboratory and clinical settings. These trials typically produce large data sets on the drug’s efficacy, side effects, risks and patient data. AI is being used to examine extremely large data sets, looking at biomarkers to characterize the complex interactions between individual anatomy, genetics and the chemistry of the drug being administered. By considering results from multiple studies involving several drugs, biologists and physicians can use the power of AI to uncover interactions that may not be obvious in any individual study, resulting in drugs that are safer and more effective.

Looking further into the future, the industrial metaverse may be applied to the delivery of healthcare to reduce the time patients spend in care facilities, costs and improve condition diagnosis. A typical doctor visit may transition to a remote consultation in which the physician can examine a digital twin of some part of the patient’s anatomy, helping both the provider and patient better understand the patient’s specific disease and treatment options.

Furthermore, the work already being done with AI and pharmaceutical development may enable physicians to customize a drug or therapy to the patient’s anatomy, genetics and condition, accentuating health benefits and mitigating side effects. Routine wellness visits may also be more effective at catching conditions early, preventing lengthy and expensive hospital stays and improving patient outcomes.

A digital future for medical devices and pharmaceuticals

As medical device and pharmaceutical manufacturers emerge from a disruptive and uniquely challenging period, they face a future of growing complexity, speed and innovation. Medical device makers are managing the development of devices that are smarter, increasingly complex and more user friendly. This places additional strain on traditional design and engineering methods. Meanwhile, the need for speed of innovation in both device and pharmaceutical spaces has elevated, driving manufacturers to seek process improvements that can accelerate development cycles while preserving safety, efficacy and data security.

Digitalization and the digital twin are relatively nascent in the medical device and pharmaceutical industries. Yet, with a commitment to digitalization and the application of powerful technologies like the digital twin, AI and the industrial metaverse, manufacturers of medical devices and pharmaceuticals can build a foundation for transformative capabilities that will enable them to develop new generations of devices and therapeutic drugs. These advanced therapies will contribute to a system of care that is more productive, accessible and effective.

About the Authors

Dale Tutt is Vice President of Industry Strategy at Siemens Digital Industries Software. Dale leads a team of experts to develop and execute industry-specific product and marketing strategies in collaboration with the global product, sales, and business development teams. With over 5 years of experience in this role, combined with extensive experience in the aerospace and defense industry, Dale has a deep understanding of the challenges and opportunities facing companies as they embark on their digital transformation journeys. Connect with Dale on LinkedIn.

Jim Thompson is the Senior Director of Digital Strategy for the Medical Device and Pharmaceutical Industries at Siemens Digital Industries Software. Jim has three decades of experience in product lifecycle management and solutions development. His current role focuses on strategy and solution management for the Medical Device and Pharmaceutical industries. Connect with Jim on LinkedIn.

The post How digitalization in medical devices and pharmaceuticals sparks innovation appeared first on Engineering.com.

Written by Todd Tuthill, Vice President for Aerospace and Defense Strategy and Marketing, Siemens Digital Industries Software.

The enormous breakthroughs artificial intelligence (AI) has had in the past couple years are common knowledge at this point. AI itself is nothing new, but recent advances in hardware and GPU technology have enabled the operation of more sophisticated machine learning models that can handle larger amounts of data and make better predictions, pushing AI past the hype threshold into a legitimate tool to do business with.

These advancements cannot be understated as there is a massive demand for AI, opening numerous opportunities across industries.

Aerospace and defense (A&D) is not only an industry that can benefit from AI, but also one that needs it. Despite the immense growth the A&D industry is expected to profit from in the coming years, a growing worldwide workforce shortage threatens to hinder this progress, exacerbated by increased product complexity from the integration of new technologies. If A&D companies wish to stay in business in the future, they will find AI to be a necessary component in accelerating their digital transformation journeys and producing the next generation of aircraft and spacecraft.

Expecting turbulence

There is a lot to look forward to in the realm of aerospace. For instance:

• Companies are researching different forms of sustainable propulsion.
• Engineers are designing the next generation of defense aircraft.
• The United States is poised to return to the Moon and land humans on Mars.

The future of aerospace has never looked more exciting.

Yet these ambitious goals rely on new technologies, and with these new technologies comes increased product complexity. Sustainable propulsion systems for commercial aircraft and enhanced networking capabilities for drones — for example — present new design considerations that must be integrated within the same or shorter design cycles. Additionally, as product complexity increases, so does tool complexity, as new powerful software is developed to design and validate everything from the smallest microchips to wing shapes. All these considerations and tools will take engineers years to learn, and even longer to become experts in.

This comes at an inopportune time as the industry struggles to overcome a worsening workforce shortage that is spanning the globe. The Boston Consulting Group predicts that by 2030, one out of three engineering positions may go unfilled due to a lack of required skillsets. The A&D industry is expected to create all these incredible products and innovations, but it lacks the engineers to bring them to fruition.

Transforming engineering with AI

AI has the potential to counteract the worst effects of the workforce shortage and growing product complexity. At an individual level, it gives engineers new ways to do their work, transforming how they interact with tools and enabling them to gain knowledge and experience faster.

Many industries are already integrating AI copilot systems into their tools, which engineers can utilize, through conversation, to make their jobs easier. By simply asking questions with natural language, engineers can have the copilot automate workflows and clear mundane tasks, as well as quickly access the copilot’s library of specialized knowledge to better understand the software tool. This lessens the need to have an expert on hand to guide newly hired engineers.

Companies can take a step even further by integrating AI directly into design tools. Not only would the AI be able to learn from expert users of the software tool, but it could also use those experts’ workflows to streamline the use of the tool itself. This enables the AI to develop a set of best design practices to help engineers with everything from component placements to wing shape optimization. With AI helping develop better workflows, engineers will be in a better position to navigate product complexity.

All these applications culminate in multiplying the impact of engineers, allowing them to focus on higher-level engineering and critical thinking as AI handles the mundane work. Not only would this reduce the intensity of the workforce shortage, but it would also create a more attractive working environment to draw in new engineers.

Addressing trust

Despite the excitement surrounding AI, some people are still bound to be skeptical of the technology. There are those concerned about AI being unable to effectively do work that has long been done by humans and the results it generates, while others are concerned with AI’s ability to keep proprietary data secure. The latter is especially important in the A&D industry, as many programs are data sensitive or outright classified.

While these concerns are valid, they are not so different from when previous technological innovations changed how work is done. Therefore, they can be addressed. Efforts can be made to reduce the black box obscuring how an AI comes to its conclusions, as well as educate users to better understand how AI functions and where it could be best applied. Regarding proprietary data, instead of drawing on public information from the Internet, like ChatGPT, the AI of an aerospace company can be run locally. This way it only learns and accesses data from the company’s secure and proprietary data lake.

AI in digital transformation

The capabilities described earlier in this article are just the tip of the iceberg. At a higher level, AI can be the key component to help accelerate companies’ digital transformation journeys to levels once thought impossible.  

Most companies in A&D have already begun their digital transformations, making inroads in configuring model-based workflows and data archiving, as well as connecting data across engineering domains and increasing traceability. With AI, however, companies can go even further. Automating mundane tasks and streamlining engineers’ workflows with copilots and tool assistants is just the beginning. AI is already being used to generate component designs, write support documents, find optimized solutions and perform many other tasks that we once thought only humans could do. Right now, these capabilities are limited to single engineering domains, but with every leap in AI technology, they grow closer to applying to full multi-domain physics models.

As products increase in complexity and the aerospace workforce gets tighter, AI is positioned to enhance the work of human engineers and enable the A&D industry to overcome its obstacles. By the time 2030 approaches, AI will have dramatically altered the way A&D does engineering, and there will be two types of companies: those who have gone out of business and those who embraced AI.

About the Author

Todd Tuthill is the Vice President for Aerospace and Defense Strategy and Marketing at Siemens Digital Industries Software. Todd’s engineering background is in systems design with functional engineering and program leadership roles and a strong vision for digital transformation. His 30+ aerospace leadership career spans McDonnell Douglas/Boeing, Moog, Raytheon, and Siemens. His experience encompasses all aspects of A&D programs, including design, model-based systems engineering, software engineering, lean product development, supplier/partner management and program management. In his role at Siemens, he is a passionate advocate for the advancement of digital transformation across the A&D industry.

The post Why aerospace needs artificial intelligence appeared first on Engineering.com.

Written by Nand Kochhar, vice president of Automotive and Transportation for Siemens Digital Industries Software.

The U.S. autonomous car market size is estimated to reach $37.56 billion by 2029, growing at a CAGR of 20.5% between 2024 and 2029. However, the widespread implementation of automated vehicles (AVs) in the real world (Figure 1) depends on the verification and validation (V&V) for designing, manufacturing and of course, operation. Hence, AVs must safely and reliably drive on roads in all weather and traffic conditions on urban, suburban and back-country roads.

To continue the march towards autonomy, companies must transform the methods with which vehicles are developed and put into the market. While great opportunity exists in the future, companies face several impediments to supplying connected, automated and software-defined vehicles to the world.

Building AVs is a particularly complex process because the entire vehicle is a system of mechanical, electrical, electronic, network and software systems. State-of-the-art components from each of these domains are required to create the most sophisticated vehicles ever produced.

Thus, the V&V of AV safety, reliability and performance in all traffic scenarios is a daunting task. Projections indicate AV platforms will need to complete the equivalent of billions of miles of testing to ensure their safety and reliability. And, because the vehicle involves interconnected and interdependent systems, the complexity compounds.

Connecting real world and simulation data via digitalization

The development of advanced driver assistance systems and AVs is a data-driven engineering process. Numerous measurements are generated, analyzed and incorporated back into the design at each step in the lifecycle. Translating the raw data gathered into engineering insights that drive improvements and optimizations is where competitive advantages are won and lost.

Companies can successfully address the complexities of these challenges by using a mixed-reality, digitalized approach to the development, building, verification and validation of their vehicles and driving systems.

Real-world data collection is critical to providing accurate V&V. Typically, the information collected from a physical test is immense. Data-collection software can perform an initial analysis to distinguish what is pertinent to the testing objective at hand. This enables teams to make well-informed decisions on data storage and processing priority.

Essential hardware elements, sensors, actuators, controllers or complete autonomous driving systems need to be tested. Hardware components are verified and validated using simulators to mimic on-road driving scenarios with varying environments, traffic and road conditions.

Hardware-in-the-loop simulation software can help with the testing of sensor systems. These solutions can test camera-based perception systems used for advanced driver assistance systems by integrating the actual camera sensor into the testing environment. This helps increase simulation fidelity because the system is processing real sensor data. Camera projection boxes, as well as camera injection setups, allow engineers to test the camera-based perception systems under challenging conditions.

This information becomes more powerful when converted into the virtual domain. Real-world tests enrich and inform simulated vehicle environments and driving dynamics. Scenarios captured during real-world testing can be imported and recreated in a simulation solution (Figure 2). Within the simulation environment, engineers can change parameters of the scenario (such as weather conditions or vehicle speeds) so that they can interrogate all facets of system performance in different driving environments.

Using data from physical testing and simulation, AV engineers can quickly identify on-road edge cases and assess vehicle behavior in all driving scenarios. As the AV is an integrated system, its development platform also needs to be integrated to test and retest the operation of the vehicle in realistic virtual scenarios throughout the design process. By implementing both design and simulation on one platform, test results and simulation data can be readily reincorporated into the vehicle design. This produces a closed-loop feedback system that improves not only the design but also operation and physical characteristics of the vehicle.

When this approach is used, a comprehensive digital twin of the AV then can be created. This empowers an efficient closed-loop AV development lifecycle that spans from design to verification and validation and even through to in-field maintenance.

Encountering unsafe scenarios in a virtual environment, not on the road

High-fidelity simulations using a comprehensive vehicle digital twin also provide a virtual environment for identifying unknown unsafe scenarios. Engineers can combine the knowledge from known real-world situations with mathematical prediction and simulation methods to uncover possible alternative critical scenarios. They can discover and analyze these scenarios more efficiently in a virtual environment, reducing the number of unknown-unsafe scenarios and the risk incurred when deploying AVs.

As stringent regulations are adopted by governments that focus on road safety, they will likely guide the future of virtual vehicle testing and simulation technology standards to help streamline consistency and acceptance of AV certification.

Collaboration is key to building confidence

In the United States and worldwide, standards were developed for vehicle certification. As regulations matured, confidence in the products was built. The engineering environment for AVs also needs to build that confidence, to prove the connection between physical testing and virtual testing so that the authorities can confidently approve standards that will benefit everyone, manufacturers and customers alike.

Three areas are crucially important to fully autonomous vehicles being introduced successfully: public acceptance, technology and regulations. The automotive and transportation industries have a challenging task ahead of them to address the needs of all three areas.

Standards should help balance out this tension between technology and regulations. They would help guide companies, like Siemens, that develop tools for AV manufacturing companies. These tools could then help ensure that the standards are in alignment with the technology that they are developing and vice versa. Standards, and the verification and validation they call for, may be driving the speed with which we will see AVs become common.

The process of designing, building, testing and scaling autonomous cars is complex and time-consuming. As such, advancement must rely heavily on collaboration and partnerships, which will drive innovation, improve functionality and ensure safety for everyone on the road.

About the Author

Nand Kochhar is the vice president of Automotive and Transportation for Siemens Digital Industries Software. He joined Siemens in 2020 after nearly 30 years with Ford Motor Company, where he most recently served as Global Safety Systems Chief Engineer. In this capacity, Kochhar was responsible for vehicle safety performance of all Ford and Lincoln brand products globally. He also served as Executive Technical Leader, CAE and as a member of Ford’s Technology Advisory Board. Kochhar’s tenure at Ford also included executive engineering leadership across a range of disciplines including in product development, manufacturing, digitalization, simulation technology development and implementation.   

The post Digitalized verification and validation paves the way for automated vehicles appeared first on Engineering.com.

Bob Schuster is no stranger to the automotive industry. The GM veteran saw ‘the writing on the wall’ and decided it was time to make it on his own. Though already a manufacturing expert, Bob quickly trained up on Siemens technology, acquired CNC equipment — and Schuster Mechanical LLC was born. His success in the automotive field, and now adjacent industries, continues to this day.

“I’m small and attentive,” says Schuster. “Jobs that I landed were due to my reputation. I will collaborate with the assigning engineer and make sure the job is completed to their satisfaction. I’m not done until they are happy.”

But this level of success, especially for an individual, does not come unexpectedly. Schuster says that much of what he does is made possible using Siemens Zel X, because it enables him to foster and grow close relationships with his clients.

Schuster Mechanical’s secret to success is helping the “big guys”

Schuster Mechanical takes on the important, but small, jobs that big CNC outlets do not want. “They want volume,” Schuster says. “They can’t do smaller stuff like I can.” However, large manufacturers often need one-off replacements for old machinery. This important but underserved niche is where Schuster Mechanical flourishes.

As a one-man-show, its Schuster’s skills, flexibility and adaptability that separates his shop from the rest. If customers call him to a production facility to help design a tool, replace a broken part or make minor changes to a line, he shows up when needed. “Afterall, you can’t stop production,” he says. “I will see the existing design and propose a new one.”

Schuster’s close, attentive and accurate services do not come cheap. But his skill, work and adaptability speak for themselves. “Right now, there is a shortage of available shops,” says Schuster. “But you can’t do any job at the door. You need to be well suited … [its about] having a good relationship and getting the work you like. I’m not doing precision, ultra precision [or volume] work. I’m doing the other work. You have to match the work at the door to your capabilities.”

When makers match work to their capabilities it goes beyond their personal skills; it also boils down to the tools they use. To overcome most of those capability challenges, Schuster has turned to Zel X.

What Schuster Mechanical makes and the challenges it faces

Schuster mostly makes new grippers or effectors and installs them to legacy equipment. These parts must be custom designed to grab, mount and move parts during manufacturing and assembly.

Often customers only need one part; however, this does not minimize its importance as it may be used to make hundreds of thousands of products a day. These new parts could replace ones at the end of their lifecycle or adapt equipment to make new products — or even multiple products.

“My job is to build the fixture and it’s important for me to design it properly and deliver it on time,” he says. This accuracy and time sensitivity is key. If the part is not ready on time, then it may not be available for installation during a plant’s scheduled maintenance. As a result, the customer could lose millions of dollars waiting for the part. Additionally, if the part does not work as designed, equipment may fail, or products may come out of spec. This would also cost customers millions as they try to fix the issue on the fly.

Another challenge Schuster faced when making new parts for old equipment is that the reference data you need is often inexact, incomplete or non-existent. Sometimes the equipment he adapts could have reference manuals hundreds of pages long and he only needs to extract a few details to make the part. However, if the customer made prior changes to the equipment, that reference manual may be out of date.

Sometimes, the only way to get the information Schuster needs is to see and access the current installation in person. However, accessing the part can be hard and dangerous. During early development, Schuster explains, he must “find a window, maybe 20 minutes, to get in there and take it apart, take pictures, put it back together and take all that data to build my improved part.”

He also often crawls into the equipment a second time to install his new part. During installation, he has “been in [situations where] I thought I had time to finish a project and I was fabricating on the fly … suddenly I was told this line has to run. I had minutes to get it going and fortunately I landed on my feet, and it worked.”

How Schuster Mechanical confronts development cycle hiccups

It is of course best to avoid challenges like the ones noted above. Though issues will arise with any project, Schuster and his customers can foresee and address most of them early in development using better means of communication.

“I address these challenges by being honest with the customer,” says Schuster. “When I look at the data and there is a misunderstanding … I call the engineer right away and verify.” He notes that after one of these moments of honesty, the customer involved ordered eight new parts the very next day. “Pointing out the error made them happy; they trusted me.”

Schuster also uses Zel X to bridge communication gaps with customers and peers. “Zel X makes collaboration instantaneous. [With email you] needed to export CAD, describe it in PDF and the person on the other end needs to interpret that. That’s a time-consuming process. With Zel X, I still need to do some of the same steps … but instead of an email, the data updates and shares. We can communicate on the phone while looking at the same data and make decisions faster.”

In fact, this improved form of communication has enabled Schuster to reduce on-site visits. “I get to design much sooner,” he says. “I have the ability to do a quick design review and get started. These were done in person before. Now this happens much less.”

Zel X also has tools that stakeholders can use to markup, comment and revise data. As a result, Schuster is up to date on what the customer is up to, and his customers knows where he is with a project. Thus, the design process runs smoothly without in-person interactions. “The markup tools are built-in and we are able to talk back and forth and steps are recorded. Misunderstandings were honest before, but now you can see it written so we understand and finish much faster.”

When things do go wrong, Zel X is also helpful. It enables Schuster’s customers to keep him aware about how his parts are running. “The sooner I know it’s successful the better,” he says. “I need feedback on any concerns right away. Zel X is the way to do that. [With it, customers can] communicate with me like in the review process. If something was overlooked — sometimes by one or both of us — it’s usually very simple to punch out these little details. It’s easier to correct these faster [in Zel X] than with email.”

What else does Schuster Mechanical do with Zel X?

Another big challenge machine shops face is ensuring that a customer’s data is secure, tracible, accessible and available in a way that fosters collaboration between stakeholders. It has built-in tools for collaboration. When I put data into it, its more secure than it was before.”

Schuster also uses features in the software for quoting, restricting data access (based on a user’s credentials) and storing information safely on the cloud. If he or any stakeholder needs to look up data on the system, they must use two-step authentication. This ensures users only see the data they have permissions to see.

“It’s a step in the right direction and long overdue, like 20 years overdue,” he says. “The methods we shared things with in the past weren’t good.  Almost all shops can do the work effectively, but customers need to be comfortable their data is in good hands. They trust Siemens to be a good steward of their data, and I think they are. That’s a good thing for everybody.”

As for Zel X’s quoting abilities, Schuster says, “The quoting process marches along much more efficiently and quickly. It can shorten the quoting process and make it more comfortable and safer for both parties … Everything is recorded.

To learn more about how Zel X, click here

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One of the biggest challenges faced by legacy industrial companies is the transition into a digital age. Effectively digitizing your products and business can be a big hurdle, especially for small- and medium-sized businesses.

But Italian industrial furnace company Gadda Group has done just that, taking their more than 45-year-old family business into a more digitized world. Key to that transition has been the company’s use of Siemens’ Solid Edge and Teamcenter software mixed with an Industry 4.0 approach.

From garage to factory

Founded in 1978 by Rocco Vincenzo Adorisio, Gadda Group—which is still a family-owned business—has been producing industrial furnaces for more than 45 years. It had a humble beginning.

“My father started in a garage to produce furnaces,” Rocco’s son Stefano Adorisio told Engineering.com. “In 2010, me and my two brothers joined the company. Since then, we have grown a lot and guided the company into the digital era.”

Stefano is now an owner, proposal engineer and project manager at Gadda. He works alongside his brother Andrea Adorisio, a production manager, and his brother Simone Adorisio, general manager. They are continuing their family legacy of designing, manufacturing and installing industrial furnaces, while also making sure their products remain cutting edge. Gadda also manufactures many pieces of equipment needed to support a furnace operation, including automatic loading machines and quenching tanks.

Today Gadda has 50 employees, including engineers, production workmen and technical support, with more than 6,000 square meters of production area in the Italian provinces of Turin and Milan. The company has completed more than 600 projects for more than 400 companies in over 20 countries.

Making custom furnaces with Solid Edge

Gadda does not take on a large number of projects, typically only producing around 30 units a year.

“We do not have a catalog. We have only references. So, every piece of equipment is tailor made for every single customer,” Stefano Adorisio says.

Gadda’s furnaces can heat parts up to 1,300° C inside of variously sized chambers, each designed specifically for a customer’s needs. The company’s clients represent a variety of industries including aerospace, automotive, and oil and gas, all needing to heat treat materials ranging from steel to titanium alloy.

Two of Gadda’s custom furnaces have already debuted this year for Italian customers. The Bogie Hearth Furnaces will be used for heating large ingots up to 1,300° C and for forging. The larger of the two furnaces includes a 450-ton capacity and 11 pairs of flat flame regenerative burners. Gadda focused on ease of maintenance and safety in these designs.

Customization for each client requires a high level of design work, which for Gadda takes place in Siemens’ Solid Edge CAD software. Adorisio says that typically half of each project is constructed from standard parts and designs from other projects, while the other half is tailor made for each customer. It typically takes Gadda around one year to complete a furnace from when the order is placed to when the furnace is commissioned.

Adopting Solid Edge as the company’s design software has enabled the business to scale while taking this custom design approach. Gadda first explored using Solid Edge back in 2000 when a young engineer recommended that the organization purchase a single license of the software.

Gadda never looked back. Today the company has ten licenses of Solid Edge thanks to its partnership with Italian Siemens reseller Novasystem. All of Gadda’s complex, custom industrial furnace models now come to life in Solid Edge. The engineering team relies on simulation tools within Solid Edge, as well as the XpresRoute tool to simplify the piping and routing design process.

Gadda also adopted Siemens’ product lifecycle management (PLM) software, Teamcenter, after encountering issues with their previous system of design management.

“When two to three people were working on the same project, it was difficult to define who would do some parts and who would do other parts,” Adorisio recalls.

The company switched to Teamcenter in 2019 and saw immediate improvements. This software helped elevate the Gadda team’s collaboration and was an important asset for Gadda during the COVID-19 pandemic, when many of their employees worked remotely.

“With Teamcenter, it is very easy because of their system to check in and check out parts,” Adorisio says. “Everyone knows who is making some modifications to the project, and it also is easy to work at home.”

Firing up Industry 4.0

Being part of the business for decades, Gadda has continued to innovate, pushing their designs to ensure their products fit in with the evolving Industry 4.0 world and the modern smart factory.

“Industry 4.0 has become a standard for us because every customer today needs good automatization and a robust system to communicate with the equipment,” Adorisio says.

Gadda has incorporated many sensors into their industrial furnaces that can assist with predictive maintenance and improve safety, especially in their automated systems. Automation is even helping to reduce human error and safety risks for operators, who now play a more supervisory role, with things like heat-treatment recipes able to be programmed into the system remotely.

“I think that new sensors, new PLCs and new communication can help our equipment to reach higher performance in terms of efficiency and in terms of productivity. This was a step made together with all stakeholders: our customer, our supplier and ourselves,” Adorisio says.

The Italian government has also been a driving factor in pushing companies towards the Industry 4.0 approach and beyond. Italy launched Industria 4.0 in 2016, a national strategy for digitizing industry and encouraging new investment from domestic and international organizations.

Now, Italy and Gadda are both looking at the next step beyond Industry 4.0 and what it means for the country and company.

“In Italy, we are speaking about Industry 5.0, which includes artificial intelligence,” Adorisio explains. “I think that in the next five years, some of that new technology will also be part for our equipment.”

Thanks to modern design software and tools, this family-owned business plans to evolve and stay at the cutting edge of their industry.

Want to learn more about how you can adopt Solid Edge and Teamcenter in your business? Visit the Siemens website here.

The post Industry 4.0 heats up with Gadda’s industrial furnaces appeared first on Engineering.com.

Traditional scanning electron microscopes (SEMs) are large, expensive and complex pieces of lab equipment. To use, maintain and repair them would require specialized knowledge and skills few companies and research outlets have. This didn’t sit well with Semplor, makers of NANOS — an easy-to-use SEM the size of a desktop computer.

Making SEM available to “anybody, anywhere in the world, that’s our goal,” says Emile Asselbergs, CEO and co-owner of Semplor. “Like a modern [cellphone,] you don’t need a training course to use it. It’s easy, fast and doesn’t break.”

The Netherlands-based company achieved this paradigm shift by rethinking SEM technology and designing the NANOS with completely new parts, methodologies and workflows. In other words, they redesigned SEM from the ground up. However, as a small startup, Semplor didn’t have the budget for most engineering design software.

“With Enginia we were in contact about the Solid Edge Startup bundle,” said Asselbergs. “In this period, we were in touch with Enginia about the possibilities of the Solid Edge license, and their customer service helped with the installation and use of [the] Solid Edge Standard Parts Library.”

With this software Semplor made something as complex as an SEM into a machine that looks right at home in any startup, SME, makerspace, big-name research lab and everywhere in between.

SEM experts think the equipment is too complex

Asselbergs explains that traditional SEM equipment can be hard to maintain. “You open them up and they are large, complex, with lots of circuit boards. It needs a lot of maintenance.”

While working in the SEM field, Asselbergs and a few colleagues realized that the equipment doesn’t have to be this complicated. “We’ve been thinking about how to ideally design a table-top SEM. We didn’t use the things of the past or things we didn’t like; instead, we made a new concept,” he says “Organizations have difficulty changing mindsets. That is what we love to do.”

Asselbergs’ colleagues soon became co-founders with a shared goal: to use their combined 200 years of experience with SEM to democratize the field. They understood the common user pain points and wanted to build something better. “It’s what people need these days; when you have a problem, you want to solve it now.”

Aside from the physical design of the NANOS, its software user interface also plays a big role in simplifying SEM. The UI has a lot of automatic functions to optimize brightness, contrast and illumination. It also guides the user through the process so that those new to SEM can catch on quickly. However, it also contains many of the power-user features used by seasoned veterans in the field.

An example of how the NANOS democratizes SEM can be seen with how it deals with living samples. These samples contain a lot of water and are sensitive to the beam of electrons. As a result, they will shrivel in the high vacuum and sustain damage from the beam. Traditional equipment overcomes this challenge by coating living samples in gold, platinum and other expensive materials. Aside from the added expense, this process also complicates the assessment of these sample.

Newer SEMs have an option to operate at low vacuums, which ensures that living samples don’t shrivel and the charge they experience is neutralized. But Asselbergs says this feature is an expensive add-on for traditional SEM offerings. For the NANOS, it comes standard without added expense. This is in part thanks to how the equipment was designed.

“We don’t use vacuum gages, just good calculations,” says Asselbergs. “By the pump power and RPM, we know the vacuum level. Measuring gages cost money and can break, so that’s something we don’t want to use.”

Simplifying SEM for the masses while maintaining functionality

Scrapping the vacuum gage demonstrates the strategy Semplor used when designing the NANOS: If it’s not there, it can’t break or take up space. This enabled the design team to reduce the size of the SEM while also improving on its reliability.

This philosophy, Asselbergs explains sets the NANOS apart from other tabletop SEM devices. “They are basically low-end systems and look like a large microscope shrunk into a smaller one. They are very traditional when you open them up.”

He admits that some aspects of the NANOS are similar to other SEMs. “Some things are physics, you can’t change that. But [the NANOS has] all new systems with today’s technology. All software and electronics are from the last three years.”

Asselbergs team produced many calculations and design permutations, early in development, to optimize the NANOS. For instance, a material might be well accepted by other SEM manufacturers for a given application, but Semplor asked: would another lighter, smaller or less expensive one work just as well?

This process of testing the assumptions of the SEM industry was then applied to all other aspects of the NANOS. Could it get comparable magnifications with fewer lenses? Can an off-the-shelf camera be used to navigate a sample? Could the number of cable connections be reduced by using one PCB to control the whole system?

“The mechanics are completely redesigned,” says Asselbergs. “The electro column is assembled more like the engine of a car [than traditional SEM]. It’s not stapled cylinder segments. It’s much simpler and works beautifully.”

Simplifying the traditional SEM design doesn’t mean the NANOS is short on advanced features and capabilities. In fact, it is the opposite, and the redesign enabled Semplor to develop new features and future proof the final product.

For instance, the NANOS contains an eucentric stage that keeps the sample in focus as its tilted. Thanks to this stage every sensor currently aimed at the sample will remain aligned and focused; all that changes as the sample tilts is the spot they are pointed to. In more traditional equipment, tilting the sample would require the user to change SEM settings to refocus the sample.

As for future proofing the NANOS design, Asselbergs says, “We designed a system that has a lot of space in the column to add more sensors that can aim at the same focal point as the other sensors and equipment. So, we can make it a more high-end system. You need to design for the future from the start.”

The role of engineering software in designing the NANOS

The main design team on the NANOS consisted of one physicist and one mechanical engineer. However, these individuals were far from alone when developing the equipment. They received help from Siemens, Enginia and even Semplor’s manufacturing partners.

“The system was designed and engineered with the people that would manufacture the system,” says Asselbergs. “We knew what they had in terms of manufacturing machines and based on that knowledge we designed the system for them to manufacture and assemble.”

Solid Edge was used to track the design, manufacturing and building logistics. This ensured all stakeholders, internal and external, were aligned. “We do nothing on paper,” says Asselbergs. “You talk to many suppliers and can have a meeting five minutes long without being in the same physical spot. Many suppliers have CAM systems to operate machine millings and lathes and it’s been my goal to work with those suppliers without making 2D drawings with tolerances.”

The 3D models made in Solid Edge also helped Semplor ensure that the NANOS was easy to maintain. For instance, designers were able to ensure that parts could be easily accessed and changed out. “It helps if you have a good 3D model of your system to assess if parts are easily accessible,” says Asselbergs. “We knew the system before we built it. If a PCB breaks, users untighten four bolts and a few connectors, put in the new PCB and send the old one in for a refund. You can replay this maintenance in Solid Edge to make sure it works, is easy and is optimized.”

Solid Edge didn’t just simplify the maintenance, logistics, prototyping and manufacturing of the NANOS, it also reduced the number of physical prototypes needed via simulations. Part stiffness, modal vibrations and other mechanical assessments were done using Solid Edge. Meanwhile, many of the field calculations and electron beam simulations were made using a separate academic software.

 “A lot of simulations were done before parts were made,” says Asselbergs. “We looked at 10 different setups to optimize the design.” Regarding Solid Edge, Siemens and Enginia specifically, Asselbergs adds, “they helped us design the system to work on the first go. We’re very happy with it.”

This partnership is bound to continue. Since Semplor’s SEM design is designed to handle more sensors, it will need to optimize those setups as they are developed. What future capabilities the NANOS will have is a mystery — for now. But no doubt the work to design it will continue within Solid Edge and with the help of Siemens and Engina.

To learn how Solid Edge can help the development of your product, visit Siemens.

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Brazilian company ZEMA has been a staple in the grinding machine industry since 1953, shortly after the first machines surfaced. This certainly says something about the company as they have a long-standing presence, specializing in the design and production of CNC grinding machines.

ZEMA FLEXA corundum grinding machine. (Image: ZEMA.)

ZEMA, owned by the JUNKER Group, manufactures CNC grinding machines for the automotive industry as well as for diverse industrial sectors, such as grinding components for the aerospace industry, agriculture and steel industries, among others. Their machines consist of more than 5,000 components, so designing and manufacturing them is no small task. Currently, Zema has more than 35,000 Solid Edge drawings being managed on the Teamcenter platform. ZEMA uses Siemens’ Solid Edge for 3D design and Teamcenter for collaboration and data management, in addition to other solutions.

ZEMA’s engineering team designs all the components for the CNC grinding machines, including the casted parts such as the machine bed and column and their casting mold, the manufactured steel parts and sheet metal parts, while outsourcing some commercial components to suppliers.

CNC and Solid Edge for manufacturing planes, trains and automobiles

The first NC machines date back to the 1940s. John T. Parsons is credited with inventing the first NC machine in 1949 with help from aircraft engineer Frank L. Stulen, which was used to machine helicopter blades using mathematically developed aero foil shapes. A group of researchers from Massachusetts Institute of Technology then developed the first CNC machine in 1952.

John Parsons with Frank L. Stulen and the first NC machine. (Image: The Wood Temple.)

Today CNC continues to be a popular manufacturing process to help manufacture components for planes, trains and automobiles.

“ZEMA transitioned from using 2D drawings generated from AutoCAD to Solid Edge in 2010,” says Edward Coltri, engineering general manager at ZEMA.

Coltri was in a different position with ZEMA at the time, and his colleague says it took the design team about three months to get up and running with Solid Edge with the help from their local reseller, PLMX. They were surprised how quickly it went.

Coltri says PLMX was the primary reason that ZEMA chose Solid Edge, in addition to the capabilities of the software, and was very supportive through the transition period. He says the feedback from the design team is that the learning curve for Solid Edge was quick, and that “Solid Edge is easy and quick to work with, and with the updates, it keeps getting better with each version.”

Over the years, ZEMA has released various models of their machines, and their customers regularly come back to negotiate with ZEMA to retrofit their machines. Because it is an older machine, the original drawings were created in a different format than Solid Edge. The migration to the new Teamcenter solution made it easier to manage this legacy data.

The company has been using Teamcenter since 2022, and last year were able to incorporate all the data from one of their latest machine designs into Teamcenter. Coltri says originally it took about eight months to use Teamcenter to its full potential.

Complete 3D model in Solid Edge of a ZEMA machine, including all subgroups. (Image: ZEMA.)

“With Solid Edge, we are able to easily convert a drawing and provide a 3D model, which is one advantage of the software,” Coltri says.

It’s been their go-to tool, not only for collaborating internally, but also for when external suppliers send neutral formats as these can be read by Solid Edge and stored in Teamcenter for easy review.

“Solid Edge data can be easily exchanged with other software from our suppliers,” says Coltri. “Teamcenter is on the desktop and the data is coming from a local main server. Other features we appreciate are the interface between CAD and CAM, and checking for interference between machine groups. We also use it for virtual reality, video creation and simulation.”

Teamcenter is also integrated with their shop floor to aid in producing the parts and in the assembly of the machines. Clashes between parts are caught by Solid Edge.

Cast iron assembly groups for the machine spindle grinding unit, managed in Teamcenter. (Image: ZEMA.)

With Teamcenter, the ZEMA team can easily create a bill of materials and put that into their enterprise resource planning (ERP) system.

Coltri says they are currently working with PLMX to integrate set drawings and lists of materials with external systems, and with the automatic loading of information into the company’s ERP system.

Overall, he says, “we are very happy with the software from Siemens. And we have very good support from PLMX.”

ZEMA at the Sao Paulo headquarters with Edward Coltri and design team members Dirk Huber, Erica Taira, Thais Hachul, Richard Runnells, Dan Staples and Georgia Berardi. (Image: ZEMA.)

Griding machines for many applications

If you’re interested in grinding machines, ZEMA offers a full range of options. The company is based in São Paulo, Brazil, and currently has around 105 employees. They typically produce about 25 machines per year. They use the JUNKER Group’s international distribution and service network, and operate mainly for automotive and tool customers.

Their corundum grinding machines fulfill the requirements of series production for a wide range of different workpieces. The CNC grinding machines grind elements such as flanges and journals on crankshafts, as well as gear, turbocharger and cardan shafts with the utmost precision and reliability.

ZEMA produces NUMERIKA and KARGO brands. See here for more information on ZEMA’s grinding machines.

Learn more about Solid Edge from Siemens.

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