Aerospace & Defense
Innovation and collaborative, synchronized program management for new programs
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A tough and urgent issue for the heavy equipment industry is energy management, including fuel consumption, emission reduction, powertrain downsizing, hybrid and electrical alternatives, and overall thermal optimization.
Help your customers be more productive by delivering heavy equipment that can withstand higher loads while reducing downtime.
Improve product operability and efficiency, and help your heavy equipment customers save operational cost. Siemens PLM Software’s portfolio helps you during all stages of the development cycle.
Optimize noise and vibration performance to increase the comfort and safety of operators, passengers and bystanders, and to comply with market-mandatory regulations.
In the mechatronic evolution, mechanical, performance engineering and software development departments need to share more real-time information and knowledge to optimize the entire mechatronic system.
The new norm for heavy equipment manufacturers is how to address the massive, constantly increasing level of complexity in machine design while improving the engineering process – a tricky balance. Electrification, hybridization and mechatronics are important market differentiators, but these individual systems must work seamlessly together. And they are not suited for every market. Manufacturers must design a variety of customized machines faster and more efficiently to meet local requirements.
The arrival of Big Data and the Internet of Things means that heavy equipment is no longer just a simple machine – it is a smart machine. Manufacturers must work closely with other industries, partners and customers to understand and succeed in implementing smart infrastructures in a global engineering operation. Sharing know-how while designing innovative and high-performance equipment quickly and accurately is a critical success factor. Improving the engineering process is a way to achieve this.
Implementing our solutions enables manufacturers to efficiently control multiple aspects of the engineering process by developing digital twins and implementing predictive engineering analytics.