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Smart engineering’s competitive advantages

Siemens Enthusiast Siemens Enthusiast
Siemens Enthusiast

In today’s highly lean environment, where there is little room for optimization in production lines, smart engineering provides a critical opportunity for OEMs. By adopting this differentiator, OEMs can increase manufacturing efficiency, improve products, reduce costs and get products to market faster.

 

PLM software is essential to smart engineering and smart machines. It enables OEMs to increase speed and accuracy during the design process, achieve equipment durability quickly, and bring real-time field information into product refreshes and new product development. Thus, a full-featured PLM solution is required to unite the data, integrate OEM disciplines, monitor project requirements, share project progress and implement the holistic potential of smart engineering.

 

Rapidly design high-value products

From a traditional standpoint, validating heavy equipment design can be a process that takes anywhere from three to nine months. This timeframe for heavy equipment tests encompasses an extensive instrumentation process to place test sensors into the equipment and then record the results. The tests include an exhaustive set of use cases that get more complicated with the addition of each automation and electrification technology. Engineers need to perform the experimental analysis in the field and then come back to the drawing board to resolve issues at hand.

 

The heavy equipment simulator streamlines the data through smart engineering. As the test is conducted, the information from the sensors is available and visible instantaneously to design engineers. Furthermore, design engineers can communicate with field engineers while they are testing, regardless of location. A design engineer may be based in the U.S., while a field engineer might be working on a machine in China. This continuous flow of information provides the opportunity to work together through a live system, thereby accelerating the process and reducing the time required for field tests by 30 percent.

 

Additionally, strategically placed sensors connected to the right software provide the opportunity for minimalistic simulation that yields a comprehensive conclusion, because the software optimizes the collected data with analytical intelligence. As a result, manufacturers can quickly deliver products that relieve specific user pain points or resolve existing inefficiencies.


For example, a pump responsible for hydraulic pressure that controls an excavator arm may overheat in the field, prompting the supplier to test the pump under different conditions. The offending pump is replaced in the excavator, and its design is modified for the next generation of products.

 

Alternatively, a machine designed to have a load capacity of 20 tons may only require a capacity of 10 or 12 tons because of the information it’s continuously provided through sensors. Rather than combing through logs of service engineer feedback to find these changed requirements, the information provided through the software makes this discovery simple. As a result, manufacturers might decide to design a machine with a lower capacity at a significant cost reduction that could be passed on to buyers of the next generation of products.

 

Kapp Niles, a producer of industrial equipment used in the machining of gears and shafts, has cut validation time from three weeks on a real machine in the factory to three days on a virtual machine in the office. The machine to be replaced through virtual commissioning remains in production, eliminating downtime and revenue loss, while the new machine is tested in a simulation environment. At Kapp Niles, Siemens PLM technology enables engineers to work faster on capital equipment, whether expiring or new, to achieve optimum efficiency.

 

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Achieving equipment durability at a competitive pace

One of the critical metrics for assessing the value of heavy machinery equipment is durability. While always a goal of manufacturers, achieved durability traditionally involves time-intensive practices, such as testing sensor placement for the collection of necessary data and sifting through unnecessary data to identify best practices and leverageable learning.

 

Through smart engineering, manufacturers can achieve reliable durability, eliminate most assumptions and move products to market at a faster rate.

 

Dana Advanced Engineering achieved this by developing an integrated powertrain design using Siemens software. The software’s simulation capabilities enabled the company to meet durability, adaptability, energy-efficiency and cost concerns without multiplying time in the test or vehicle labs.

 

Instead, Dana used model-based systems engineering simulation in all phases of the development cycle. This included prototype testing, as well as front-end loader integration testing in an experimental environment.

 

This simulation sped up design evaluation, effective integration, controls development and performance testing by:

 

• Dropping modification evaluation from more than one or two weeks down to one day
• Requiring fewer physical testing loops
• Debugging controls in simulation
• Reducing damage to system hardware

 

Real-time data from different parts of the world accelerates innovation

Another time-sensitive challenge to innovation involves accommodating design to address global variability. The soil in China is different than it is in India. Crops are more substantial in Ireland than in the Benelux. Some Asian countries harvest sorghum Sudangrass hybrids, a very thick type of crop almost like bamboo.

 

Adaptive innovations are necessary to gather data and address the diverse technical design needs of different parts of the world.

 

Siemens PLM technology provides a fast, straightforward setup to collect data on a global level. Data can flow back to design engineers, allowing them to iterate on a design faster, with trustworthy requirements based on actual use locations. Animations in simulation software mimic the stresses and strains, flexibility and other performance factors of equipment based on real data points. This collection and flow of data is key to optimizing and expediting the design process.

 

Overall, the efficiency and precision available through smart engineering leads to increased productivity for OEMs, resulting in lower costs and the opportunity to get products to market faster. Rapid innovation introductions, advanced functionality and optimized in-field equipment performance, give OEMs a trifecta of advantages over their competitors.

 

This concludes our series on smart engineering in the heavy equipment industry. 

 

About the author
Rahul Garg is the vice president for industrial machinery and heavy equipment industry at Siemens PLM Software, responsible for global business development. He and his team are responsible for identifying and delivering strategic initiatives and developing solutions for the industry, working closely with industry-leading customers and providing thought leadership on new, emerging issues facing the machinery industry. Rahul’s experience and insights are derived from a 25 year career of delivering software-based solutions for product engineering and manufacturing innovation for the global manufacturing industry. He has held leadership positions in multiple areas, including research and development, program management, sales and P&L management, having focused exclusively on the industrial machinery and heavy equipment industry since 2007.