Tag Archives: Siemens

Updates from Siemens

Digitalizing Energy
By John Lusty – Digitalization is transforming the global Energy & Utilities (E&U) industry, and the most exciting part is that it’s happening so differently in each industry sector depending on their unique plans and priorities. That’s because each organization has a slightly different digital legacy and is executing a different business model that is making them a leader in their respective sectors of the market. It’s also because E&U businesses are inherently non-uniform due to mergers and acquisitions, project mindsets, boom and bust business cycles, breakthroughs in technology, and sudden societal or geopolitical shifts that ripple through the global energy economy at the speed of light.

This blog is the first in a new series from Siemens Digital Industries Software, where we’ll discuss trends in digitalization that relate to the Energy & Utilities industry.  At Siemens, we have the privilege of working closely with industry leaders and people from an extensive range of manufacturing sectors with different degrees of digital maturity.  That lets us see what’s working great as well as some things that didn’t go quite as planned.

We’re also the software business unit within Siemens AG, a mega-enterprise of close to 400,000 colleagues that acts as a massive internal customer for our solutions. People usually look at us a little differently, knowing that as a global engineering and manufacturing organization that relies extensively on our software solutions, we truly have “skin in the game” as our supplier.

Much work has been done across the E&U industry to assemble and apply the “digital twin” of assets, projects and facilities to be more efficient, profitable, and operationally excellent. In this blog, we’ll review examples of excellence in these areas and speak with some of the people who made them happen. more>

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Updates from Siemens

The best reason to adopt cloud innovation software
By Blake Snodgrass – The decision on cloud timing varies based on each company’s scenario. The first step in the transition is to understand what your company’s goals are in the first place. The change driver may be reaching the limits of an existing solution, requiring new capabilities to support digital transformation, consolidating acquisitions, or choosing to modernize IT infrastructure. The impetus for moving to the cloud helps set the right objectives.

The cloud should not be the driver, in the same way that the goal of a software implementation should never be to “go live” with the software. There has to be some tangible business value. For product innovation and engineering software, what better reason could there be than to improve product innovation and engineering performance? The cloud is a means to an end. The real value is helping manufacturers improve the pace and level of innovation.

Improving product innovation and engineering is the bread and butter of CAD, CAE, PLM, and other engineering solutions. These solutions help provide the capabilities engineers and designers need to innovate efficiently. They offer collaboration capabilities that enable product development teams to work together so they can move faster and avoid introducing errors from disjointed processes. They also help coordinate processes and manage product development projects to ensure that projects are executed effectively.

Perhaps that’s old school, and clearly, on-premise solutions can deliver most of these benefits. But the cloud offers some special help here, as well. Today’s engineering teams are working with increased complexity and disruption, adopting new materials, systems-oriented designs, advanced manufacturing methods, and more. To remain efficient, they need to not only innovate their products – they need to innovate their innovation and engineering processes.

How does the cloud help? Traditional software deployments lock in processes and capabilities until the next upgrade cycle. With the cloud, innovations, functionality, and techniques developed by the software vendor can be made available on an ongoing basis. Access to new features allows engineering teams to take advantage of new software capabilities faster. more>

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Updates from Siemens

The Changing Face of Simulation
By Joy LePree – Simulation software and its capabilities have come a long way in recent years. The latest versions include easier-to-use and more advanced features, increased computing speeds and simplified integration with other simulation programs, as well as data analytics and Industry 4.0 technologies. These modern features allow today’s simulation tools to be employed in a variety of applications throughout the lifecycle of a plant.

As a result, chemical processors are using simulation not only for design and optimization tasks, but also for other challenges, such as increasing safety and avoiding operational risk, achieving sustainability goals and training employees.

While simulation has become the de facto method for designing and optimizing processes in the chemical process industries (CPI), for many years, users didn’t apply the technology to other types of analysis, such as overall profitability, safety issues or smaller engineering problems, because it took too long to get an answer or because the simulators were too difficult to set up and use. As a result, some software providers have built solutions with lower-fidelity models that are easier to build and use. Meanwhile, other providers have taken steps to increase speed of calculations and simplify the use of rigorous process simulators.

Another change Chemstations has made is to increase the computing speed of its rigorous process simulator by taking advantage of parallel processing, which uses all available computing cores. “This means that instead of using just one core of the user’s computer, we can spread the workload across as many cores as are available, which will speed the process considerably,” explains Brown. While the initial intent of the improved calculation time was to allow faster execution of large optimization projects, the increased speed opens the door for simulation of smaller-scale projects and “what-if” studies. more>

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Updates from Siemens

Rocket Lab to use Siemens software to explore new frontiers of space
Siemens – Rocket Lab plans to implement Siemens hi-tech industrial software to help digitally manage the lifecycle needs of the business. The software is from the Xcelerator portfolio, which is from Siemens Digital Industries Software and includes Teamcenter®, the world’s most widely used digital lifecycle management software, and NX™ software for computer-aided design (CAD) and manufacturing.

This announcement comes as Rocket Lab prepares to integrate all its design, engineering and production systems to establish an end-to-end digital thread that enables increased transparency and efficiency across various offices.

Speaking on the decision, Rocket Lab’s Vice President of Global Operations, Shaun O’Donnell, said: “As we’ve grown, so has our production capacity and the platforms associated with various products and processes. Using Teamcenter, we’ll be able to combine various aspects of data related to the same part, assembly and system to maintain a single source of truth across the life cycle of the product. Also, as we grow, NX will give our designers increased performance and stability to cope with larger assemblies.”

“Investing in the right digital platforms that allow us to easily scale with growth is critical to the sustainability of our business. With offices around the world, we rely heavily on the access of relevant information that impacts the efficiencies of our production processes,” said Mr. O’Donnell. more>

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Updates from Siemens

Artificial intelligence development is changing how industry works
By StevenH – Many industries are going to benefit from artificial intelligence development. It’s hard to say which ones in the long term will find the highest level of success, but we can already see significant benefits in a host of industries.

At its core, artificial intelligence is a tool that can acquire, organize and analyze vast amounts of data to create and parameterize models to recognize patterns and make predictions. AI is delivering many benefits and its continued use is the key to making a business more competitive. By automating some of the repetitive, basic tasks, a company can increase productivity, reduce mistakes and enable quicker, better decisions. In insurance, for example, companies are using AI to automate claims processing. The entertainment industry uses AI to optimize streaming services and suggest content based on an individual’s previous choices and comparing it to the choices of others.

If you’re a business or a company wondering about what to do about AI, whether to use it or even when to use it, then the answer is, Yes. Businesses must think about using AI. Artificial intelligence is a practical tool, and just like banks use it to prevent fraud or healthcare uses its algorithms to scan X rays, companies should look to solve problems and challenges with AI.

In engineering and manufacturing, artificial intelligence is already enhancing the scheduling in a factory by improving downtime and conducting predictive maintenance scheduling. Artificial intelligence saves companies money by reducing costs, for example by collecting data from running machines in the factory and feed it into training for predictive maintenance AI models.

Manufacturers can use these models to detect signs that maintenance is needed, such as changes in vibration signals which might indicate there is a developing problem. They can then schedule a maintenance session at the downtime of their choosing, perhaps overnight on a Saturday where there could be minimal or no loss of production. Naturally, it’s more economical to perform maintenance at the company’s discretion than having an expensive machine offline for several days, while possibly waiting for delivery of replacement parts from somewhere on the other side of the world. more>

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Updates from Siemens

Why noise is one of the biggest problems with electric cars
By Steven Dom – Imagine your company is engineering the next line of electric vehicles. You create technical specifications that reduce range anxiety, you’ve perfected the colors that pop and entice customers to buy and with battery technology advancement, you’ve priced it right.

But there are problems with electric cars.

Because the electric vehicle engine emits no noise, pedestrians are more likely to be struck by an electric vehicle. A study by the National Highway Traffic Safety Administration indicated that hybrid and electric vehicles are 57 percent more likely to cause accidents with cyclists, and 37 percent more likely to cause an accident with pedestrians, than a standard internal combustion engine vehicle.

Countries are requiring the quietest cars emit a sound to warn those around the vehicle of its presence.

Now, imagine after creating the ideal electric vehicle, the customers reject it based on the noise it emits. What if your vehicle’s noise is too strange or annoying?

This is just one of the many perils facing the quiet electric vehicle.

The goal of successfully getting an electric vehicle to market, one that a consumer would be interested in and enjoying, was about improving range. In a world lacking in electric vehicle infrastructure, solving range anxiety would allow customers to feel more comfortable driving the electric vehicles to-and-from work and longer trips beyond.

Engineers focused on vehicle architecture including the number of motors driving the wheels, managing the HVAC system’s energy consumption and finding ways to reduce weight, such as using thinner panels and less sound deadening components to provide better mileage. Without the roar of a combustion engine, there was no need to reduce noise. more>

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Updates from Siemens

Electrolux implements worldwide 3D factory and material flow planning
Siemens – Based in Stockholm, Sweden, Electrolux AB sells appliances for household and commer­cial use in 150 countries around the world. With around 58,000 employees and 46 pro­duction sites, the company develops and manufactures products of numerous brands: in addition to Electrolux, the top brands Grand Cuisine, AEG, Zanussi, Frigidaire and Westinghouse enjoy a particularly high reputation.

In 1996, the German AEG brand was acquired from Daimler Benz, together with several divi­sions and locations of the group. This is how the factory in Rothenburg ob der Tauber, founded in 1964, came to Electrolux, which today produces 600,000 stoves and 1,400,000 cooking ranges per year for the European market.

We attach great impor­tance to implementing in detail the essential product characteristics of each brand in development and production,” reports Bernd Ebert, director of Global Manufacturing Engineering − Food Preparation at Electrolux. Based in Rothenburg, Ebert ensures that all Electrolux cooking appliance factories imple­ment uniform processes and systems.

As part of a comprehensive digitalization strategy covering all areas, 11 digital manu­facturing projects are on the agenda of the Swedish global corporation. Ebert has assumed responsibility for two global proj­ects with the highest priority. They aim to create “digital twins” of all manufacturing sites: In the virtual manufacturing project, an advanced planning tool was selected and introduced for early design verification to develop products that are production- and assembly-friendly. For example, assembly sequences and movements will be planned and optimized three-dimensionally to pre­vent collisions. The prerequisite for this is the development of three-dimensional fac­tory layouts, which is the focus of the sec­ond project, 3D factory layout. The layouts will be created using a standard factory planning tool that can simulate both the plant and the material flow on the basis of 2D data in order to optimize capacity and efficiency.

Software selection began in 2014, when only a few had powerful software for 3D factory planning. A small, specialist team led by Ebert worked closely with the company’s IT department in Stockholm. Starting in 2015, Teamcenter from Siemens PLM Software was deployed there as a strategi­cally important product development plat­form for product lifecycle management (PLM) at Electrolux.

Discussions about Siemens’ future strategy led to an offer to test a pre-release version of the 3D layout software Line Designer in an early adopter program. more>

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Updates from Siemens

Essentra Components Achieves Cost Savings Up To 10%
By Emilia Maier – Essentra Components is a global leader in manufacturing and distributing plastic injection molded, vinyl dip molded and metal items.

The company is focused on being a low-cost producer, so they can secure revenue growth at attractive margins, and facilitate continuous improvement programs with tight cost controls and productivity gains, serving to reduce conversion costs.

With the integrated calculation system for component and tool costs from Siemens, Essentra Components delivers cost-effective, high-quality products in response to customer needs. Essentra is using the global costing solution in the bidding phase to deliver fast and accurate costs worldwide.

“Quote generation is done today within one hour, as opposed to five hours before we had Teamcenter product cost management, so we save 80% of our time,” Derek Bean, Manager, Divisional Engineering Solutions Essentra Components.

The cost estimators at Essentra consolidate and verify the cost results in terms of plausibility, competitiveness, opportunities and risks with the help of the Profitability Analysis module in Teamcenter Product Cost Management. more>

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Updates from Siemens

Spaceport America Cup Student Competition Soars to 30,000 Feet, Now with Siemens Software Partnering
Siemens commitment to workforce development
By Chris Penny – Siemens Digital Industries Software’s academic partnering staff recently attended the Spaceport America Cup (SA Cup) for the first time as a sponsor. We are very excited to be working with these teams to provide software and training grants to help team excel in the design and manufacturing of their rockets. Leigh Anderson from the global academic team and Chris Penny from the US academic team met with virtually every team of 120 teams from 14 countries, and Chris gave two workshops on Siemens software featuring demonstrations in STAR-CCM+ for aerodynamic analysis.

We selected this competition to sponsor due to the sophistication of the student challenge, the opportunity to engage with and support these students, and the high level of industry support (many of which use Siemens software).

A great example of how this competition prepares students for the workforce could be seen when James Ferrese (University of Washington) who led the development of an advanced plasma actuator payload obtained on-the-spot job offers from Raytheon and Northrup Grumman after their design presentation. more>

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Updates from Siemens

Siemens Case Study: Lean Digital Factory Project

By Gunter Beitinger – In October 2017, Siemens launched their Lean Digital Factory (LDF) program. Combining a group of experts from different business functions and technology units, its purpose is to define a conceptual holistic digital transformation roadmap for all factories of the operating company Digital Industries (DI).

To fully capture the value of using big data in manufacturing, the plants of DI needed to have a flexible data architecture which enabled different internal and external users to extract maximum value from the data ecosystem. Here, the Industrial Edge layer comes into the picture, which processes data close to the sensors and data source (figure).

The Industrial Edge and data lake concept will enable a more powerful solution than any other data storage and utilization concept:

  • The MDP will be a colossal storage area for all manufacturing data and will be tremendously powerful for all user levels
  • The MDP data platform is a centralized and indexed aggregation of distributed organized datasets
  • Big data will be stored in the MDP independently of its later use, this means as raw data
  • In combination with Industrial Edge, the MDP is the pre-requisite for effective and scalable cloud computing and machine learning
  • The Industrial Edge is used in this architecture for multiple purposes like data ingestion, pre-preparation, security-gate, real-time decisions.
  • Highly integrated, but module and service-based ecosystem functionalities.

In DI, it can be challenging to harness the potential of digitalization at full scale due to installed proprietary software solutions, customized processes, standardized interfaces and mixed technologies. However, at Siemens, this doesn’t mean that we ran a large standardization program before leveraging the possibilities of data analytics and predictive maintenance in our plants.

To get rubber on the road at large scale, we required an architectural concept which allowed us to develop applications, scale up and transfer solutions from plant to plant, from engineering to shop floor as well as supplier to customer and reuse identified process insights from one application to another. more>

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