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Simulation Lifecycle Management is important for manufacturing

CIMdata has published a new paper about Simulation Lifecycle Management (SLM).

To help design and perfect today’s more complex products, simulation and analysis (S&A) is becoming increasingly important to manufacturing enterprises of all sizes.

Broader, deeper, and more effective simulation is needed to properly analyse the complex products being designed and developed and validate that they meet functional and regulatory requirements.

S&A tools and methodologies must be used more effectively throughout the product development process to improve designs and reduce the cost of prototyping and physical testing. This is driving increased investments in simulation and the need to better manage S&A tools, data, and processes.

Because of the increased need for and importance of simulation, companies now recognise that S&A information is valuable intellectual property (IP) that needs to be captured, shared, and leveraged throughout the product lifecycle.

New approaches are transforming product-related S&A into a visible and accessible component of the product development process, across the full product lifecycle and across extended enterprises; not just maintaining them as a domain for specialists.

We call this approach to managing S&A information and processes, and integrating it within the full product lifecycle, Simulation Lifecycle Management (SLM). SLM is the enterprise’s gateway to simulation tools, processes, and data.

This paper provides a perspective on simulation lifecycle management: the pressures that motivate its use; SLM’s role; its value and future; and how one company, Dassault Systèmes, is developing and delivering advanced SLM solutions for product development companies.

Download the paper Simulation Lifecycle Management.

To bring simulation data and processes into the enterprise lifecycle, leading-edge companies are implementing programs to get their simulation data under control and to better manage their simulation processes and knowledge.

These companies seek to include the analysis of intellectual property as part of their product lifecycle management (PLM) implementation. However, bringing simulation into the enterprise is much more than managing simulation data.

As traditional PLM solutions routinely capture the form and fit of product designs through digital mockup (DMU), simulation lifecycle management complements PLM by associating behavioral simulation data and processes with the DMU; in essence offering behavioral-digital mockup (B-DMU).

In doing so, this then provides a single source of truth for all design and S&A information and processes.

A major objective of SLM is to transform simulation from a specialty operation to an enterprise product development enabler that spans many segments of the product lifecycle. To do this, SLM should provide technology in four foundational areas:
· Simulation and test data management
· Simulation and test process management
· Decision support
· Enterprise collaboration

These factors illustrate that SLM has evolved from just managing simulation results files (essentially providing S&A data vaulting) to being a process- and context-driven management environment.

With SLM, simulation is no longer decoupled from the product lifecycle. Simulation data and processes can be linked with requirements, parts, the BOM and other elements in the PLM process.

Verification and validation of the design becomes more than a check in a box. Users can navigate to the exact simulation results that drove design decisions.

SLM helps make it straightforward to see the genesis of the design – why certain designs were selected in favor of others. This exposure of simulation to the enterprise PLM provides a critical bridge between design and engineering.

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