Siemens Digital Industries Software submitted this post.
By Rahul Garg, Vice President for Industrial Machinery & SMB Program, Siemens Digital Industries Software
Digital transformation is enabling machine builders to address evolving customer requirements for increasingly customized products. Machines and equipment are becoming more complex as they become smarter, lighter and more customized to specific end-user needs. To effectively address these challenges and thrive in a competitive global landscape, industrial machinery companies are adopting advanced design and simulation practices through intelligent performance engineering (IPE).
Complexity Impacting Machine Building
Myriad pressures are driving machine builders to consider and adopt new design, simulation and testing methods. Customers are demanding that machines be built to specific, customized requirements. Moreover, global competition in the industrial equipment and machinery landscape requires differentiating their product, while serving customers faster and more economically than their competitors.
Advances in technology are fueling this process, prompting companies to consider and evaluate how to meet customer needs and discover how digitalization can assist that process. With all these demands, complexity is increasing, pushing the limits of the established machine-building design process. Addressing the growing demands of flexibility and complexity requires quickly evaluating machine behaviors and performance and providing information back into the machine model and development process.
For years, engineers have depended on design-level simulation to provide a baseline assessment of the design. But these basic simulations do not always reflect the interdependency of electromagnetic interference, structural loads, heat and vibration inclusively. This is becoming more of an issue with smarter equipment, which increases the complication of wiring, electronics and software. The designer may run a basic analysis to prove a design is safe, but cannot explore the various engineering trade-offs' in performance results. Consequently, designers tend to be overly cautions, resulting in added weight, cost or reduced performance to meet safety requirements.
That is why more advanced simulations now require handing the design off to simulation experts. But these simulation experts are not familiar with the design criteria and goals and often cannot identify issues at a granular level. Hence, delays in the process from the handoff between teams can mean the risk of analyzing an outdated design.
Even with advanced simulation, the design team must wait until the physical prototype testing phase to genuinely examine and validate all aspects of the machine's multi-domain performance. Finding and fixing problems at the prototype stage is expensive and time-consuming and often leads to cost overruns and slipped schedules.
A New Approach: Intelligent Performance Engineering
As enterprises attempt to deliver machines with faster cycle rates and compressed delivery schedules, teams feel pressure to perform further simulation upfront rather than waiting for the simulation experts' handoff to test the physical prototype. Fortunately, an approach is emerging that is easy to adopt and helps facilitate digital transformation and an increasing need for higher performance in machine building, which Siemens Digital Industries Software calls Intelligent Performance Engineering (IPE).
This approach incorporates advanced digital simulation and analysis tools to help machine builders analyze how specific design choices will impact the performance and failure modes for a component, assembly or the complete machine. Intelligent Performance Engineering improves reliability and addresses risk by enabling machine builders to construct a set of highly accurate models that help predict product behavior during every lifecycle phase of a machine. IPE’s principal goal is to promote a continuous connected digital thread to share information between simulation, design and production, thus enabling machine builders to evaluate the capabilities and limitations of advanced machines early in the design cycle.
IPE contains the following three differentiators:
- Multi-physics simulation and testing balances multi-attributes of a model to arrive at an optimal design by combining a broad range of physics and disciplines under one umbrella.
- Integrated design and simulation enable machine builders to produce personalized and differentiated customer products that are safe, cost-effective and well-performing by allowing designers and simulation engineers to use the same models in one system and keep the simulation data in sync with the design while maximizing reuse.
- Closed-loop validation validates virtual simulations and leverages physical prototypes and real-world data by capturing and testing the relationship between the production operation and the original requirements and design.
These key differentiators enable machine builders to create a comprehensive digital twin allowing teams to evaluate the capability and limitation of product performance and variations most efficiently. Adopting Intelligent Performance Engineering practices enables better integration between designers, analysts and live data, improving equipment performance while ensuring safety, reliability and cost-effectiveness.
Multiphysics Simulation and Testing: Promoting Collaboration
Multi-physics simulation brings a broad range of physics and disciplines together, portraying a model's many attributes and making them available to design engineers. It promotes better collaboration between domain experts, addressing critical interrelations that were traditionally addressed one at a time. Instead of each expert focusing on their area, multi-physics simulation and testing empowers them to work together. As a result, during the virtual simulation—as in the real world—the machine functions across all the environments, collaborating simultaneously.
For example, different simulation capabilities are needed for thermal and stress analysis. In the design phase, several factors must be considered as early as possible and simultaneously: fluid forces, thermo-mechanical loads and electromagnetic radiation. A designer needs to examine both the stress and thermal effects to determine if over-temperature can impact the product's reliability. These types of interactions can impact product performance, safety and longevity. Isolating and examining these forces does not always accurately predict end production behavior. Therefore, it is vital to consider all the loads simultaneously during the simulation.
Having multi-physics capabilities within an integrated design and simulation environment also enables machine builders to easily create a complete system simulation machine model with drag and drop capabilities. This enables them to move the necessary components from a resource library into a simulation model to customize a machine and witness the overall machine design impact.
This approach guarantees production performance without significantly impacting design schedules. Now it is possible to perform detailed what-if analyses in the conceptual design phase, to quickly ascertain whether a design change will deliver the required customized result. For example, it assesses the impact of increasing the production speed and throughput rate on efficient energy consumption.
Furthermore, with the system simulation approach, by interfacing industrial automation devices it is possible to evaluate the impact of new control strategies to integrate system simulation models with the test environment, complementing physical measurements with virtual sensors data.
These collaborations extend beyond the final machine. Multi-physics simulation can help equipment manufacturers and their broader supplier network to evaluate complete machine performance with component changes in the context of the overall machine or equipment specifications. Subsequently, a comprehensive digital twin is built, which is fully validated by tests based on real-life behavior, and performs analysis from the smaller components level up to the entire machine—evaluating all the relevant explicit characteristics.
In the future, we see these system models also being used as an ‘executable’ digital twin, which can help monitor and control the behavior of the machine as its being used in production.
Integrated Design and Simulation: Streamlining Customization
Equipment manufacturers face many challenges when responding to the increasing demand for more flexible and customized equipment. Integrated design and simulation provide the vital capability to produce differentiated customer products, ensuring that added product or part variations are safe, cost-effective and well-performing.
An integrated design and simulation process enables performance engineering to be addressed from the front-end product design to the commissioning process, ensuring that the design and engineering models are consistent, and that all data is in sync. Consequently, each variant can be validated quickly through multi-physics simulation and testing before customer delivery.
As customization needs keep proliferating, creating a physical prototype for every variant is less and less feasible. Therefore, it is essential to test these variants in a simulated environment. An integrated design and simulation approach enables a dramatic reduction in the number of physical prototypes, allowing design and simulation engineers to use a primary model concept across their respective tools, keeping simulation data in sync with the design.
Also, this approach can leverage libraries of components built over time to facilitate simulating various what-if scenarios in the early design phase, building your corporate knowledge-base and maximizing reuse.
Closed-loop Validation: Syncing Virtual Simulation and Physical Operation
It is crucial to validate that simulations align with the machine’s real-world operation. Closed-loop validation broadens testing beyond the testbed and prototype stage into the customers' actual operation, integrating real-world machine operations into the simulation environment. With the advent of IoT-related capabilities, this closed-loop process truly enables the highest level of customer care and continuous innovation.
As machine usage data becomes available, it is merged back into the verification analysis information. This process creates a closed-loop validation, determining that the data from customer use, physical testing and front-end simulation and design is all in sync. This confirms that the machine's virtual model accurately replicates the physical world's machine operation behavior.
Once this closed-loop validation is in place, the design team can confidently explore machine behavior in a virtual environment. For example, measuring the impact of various operators when the end-user exceeds the machine's throughput rate instead of keeping it at its recommended speed. It can also evaluate different operating conditions, such as excessive particulate matter in the factory environment or the impact of various humidity levels on machine performance. Equally important, this real-world data can apply to designing next-generation solutions.
Navigating Complexity with Intelligent Performance Engineering
Leading industrial equipment manufacturers and machine builders are increasingly challenged to balance productivity with accuracy, reliability and efficiency. Digital transformation can help them innovate in response to changing customer demands and stay ahead of global competition. IPE unlocks insights to drive innovation while meeting faster cycle rates and constricted delivery schedules.
IPE delivers these attributes by supporting multi-domain simulation upfront. This fosters an integrated design and simulation approach to support custom variants and enable closed-loop validation. Real-world performance validates and enriches the virtual simulation. All are made possible by a connected digital thread that automates sharing information between design teams, analysts, production test teams and service engineers.
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