Thought Leadership

Intelligence performance engineering addresses machine complexity with digitalization and simulation

By Blake Snodgrass

In an article by Rahul Garg, vice-president for the industrial machinery and mid-market program at Siemens Digital Industries Software, he explains how machine builders compete to respond to customer demand for increasing machine customization and complexity. Intelligent Performance Engineering (IPE) assists in solving these challenges by developing new engineering practices that align with the growing intricacies of new machine introductions.

Rahul Garg
Rahul Garg, Vice-president, Industrial Machinery and Heavy Equipment of Siemens Digital Industries Software

>Read the article.

Machine complexity requires digitalization

As technologies rapidly advance, companies are trying to adapt their processes by staying competitive in an Industry 4.0 world where customers desire machines that meet complete specifications and fulfilling performance requirements. Therefore, it is essential to differentiate a product from global competition in today’s landscape by serving customers rapidly and economically.

These goals are a mainstay of manufacturing, with ever-changing technologies propelling companies to consider and evaluate the best methods to meet customers’ needs and challenges using digitalization.

So, there is an ongoing need to address the growing demands of flexibility and complexity. However, this goal is not achieved without evaluating machine behaviors that provide data back into the model. IPE provides the ability to confirm that innovative machine designs are delivered as provided via a digital thread to support consistency and high performance.

IPE is an innovation that offers essential design parameters (including personalization), global competition and simulation while adopting practices to ensure safety, reliability and cost-effectiveness. Also, IPE provides improved integration between designers, analysts, and live data, enabling original equipment manufacturers (OEMs) to adopt practices that will enhance engineering speed while delivering optimum performance. Therefore, implementing Intelligent Performance Engineering in combination with a digital thread balances a customer’s needs to improve machine reliability and performance and evaluate, verify, and test designs.

Simulation measures performance

Traditional machine test occurs with multiple physical prototypes, taking considerable time and cost. However, simulation occurs upfront in machine-building to help corporations deliver machines with a faster cycle rate, advanced reliability, and constricted delivery schedules.

IPE simulation and testing competently address the essential needs of modern machines. A necessary facet of designing new industrial equipment or modifying existing designs is verifying and testing performance before it gets to the customer. Therefore, OEMs must adopt a collection of digital simulation and analysis tools to comprehend the designs that affect the performance and failure of a component, device or machine. It’s better to find possible problems up front in the design process rather than address machine issues in the development cycle – saving time and cost.

There are some manual handoffs between the design and simulation processes in traditional processes. Engineers use design-level simulation to provide a baseline design assessment leading to advanced simulation. As companies deliver machines with faster cycle rates and compressed delivery schedules, engineering teams must perform simulations early in the design phase instead of testing multiple physical prototypes. So, the objective is to work efficiently with simulation and testing.

Learn more in Rahul’s article.

Siemens Digital Industries Software drives the transformation to enable a digital enterprise where engineering, manufacturing, and electronics design meet tomorrow.

Xcelerator is a comprehensive, integrated portfolio of software, services and an application development platform. The portfolio accelerates the transformation of businesses into digital enterprises. It unlocks a powerful industrial network effect – essential requirements to leverage complexity as a competitive advantage, no matter the industry or company, to transition seamlessly to create tomorrow’s complex, efficient machines.

Related links:
Listen to IPE podcast01 from this series.

About the Author

Rahul Garg is vice president for the industrial machinery and mid-market program at Siemens Digital Industries Software, responsible for global business development. He and his team deliver strategic initiatives and develop solutions, working with industry-leading customers to provide thought leadership on new, emerging issues in the machinery industry. Rahul’s 25-year career includes delivering software-based solutions for product engineering and manufacturing innovation globally. He has held leadership positions in research and development, program management, sales and P&L management, focusing on industrial machinery and heavy equipment since 2007.

Leave a Reply

This article first appeared on the Siemens Digital Industries Software blog at