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Maintenance Aware Design Ecosystem (MADE)

Maintenance Aware Design Ecosystem (MADE) identifies and mitigates technical risk, and optimizes design for complex engineering systems.

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Schematic created in MADe, which stands for Maintenance Aware Design environment

Why MADE?

Access MADE from PHM Technology for model-based reliability, availability, maintainability and safety (RAMS) analysis.

Tackle increased system complexity
Traditional manual methods of risk identification and mitigation are no longer practical or realistic in the face of increasingly complex engineering systems. The platform uses a digital twin to help identify and mitigate technical risk, optimize the design process, increase availability and promote continuous engineering innovation for complex engineering systems.

Overcome a distributed organization structure
Design organizations need to leverage technology to ensure that data, analysis methods, and processes are consistent, reliable, and efficient when used in a distributed work environment.​

Capture digital domain knowledge
It is critical to capture the knowledge and experience of your team, so it isn't lost as people leave. A model-based RAMS solution can help with this by integrating domain knowledge into the model.

Support digital transformation
Digital transformation will not automatically lead to increased RAMS unless all aspects of the process are digitized. Any analog steps in the process will limit the potential benefits of digital transformation.​ A model-based approach to RAMS can lead to demonstrable cost, schedule, and technical benefits for your organization.​

Learn more about Maintenance Aware Design Ecosystem

Airplane in a hangar

Discover more about our comprehensive reliability, availability, maintainability and safety platform (RAMS).

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WEBINAR

Spacecraft safety and mission assurance

In this webinar, learn how a digital risk twin supports spacecraft safety and mission assurance.

A spacecraft in space.

MADE capabilities

Digital risk twin

Build a digital risk twin of your system to enable safe, reliable and cost-effective performance and operation. Having a model-based digital risk twin enables you to carry out analysis earlier, where it has the greatest impact – avoid making expensive changes to mitigate risk later on in the design cycle. ​

Use MADE to build an extensible and reusable visual representation of your product based on a standardized taxonomy of functions and failures to ensure consistency across an organization and facilitate knowledge capture and transfer. Leverage and combine quantitative simulation results of a 1D performance twin with the qualitative result of the digital risk twin to drive design changes and increase operational availability.

Aircraft systems technical diagram.

Safety and risk assessment

Analyze and understand the critical nature of functional risks in a design configuration, and establish and document the potential impact of failures on operations and the cost of ownership. Define critical parameters for component functions to support the automated generation of a range of safety and risk assessments that are required for the design and support of safety or mission-critical equipment, including FMECA and functional fault tree analysis.​

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A woman wearing PPE gear is standing in a factory.​

Design for reliability, availability and maintainability

Focus on design for reliability and provide a model-based solution that combines capabilities for reliability allocation, reliability block diagrams, and reliability and availability analysis with multiple failure distribution methodologies. Enable your engineers to generate design and service recommendations at each stage of the product lifecycle based on simulation analysis that can be aligned with the specific design state or operational configuration.​

Read about design for reliability, availability and maintainability

A jet is taking off on a runway.

Prognostics and health management

Design and validate the diagnostic requirements for condition-based maintenance (CBM) of complex systems in an integrated analysis solution. With sustainment as the major cost contributor for complex systems, effectively build a maintenance process that is crucial to optimize platform availability, total cost of ownership, and future redesign activities. Ensure the accuracy of the budget estimation for a proposal by generating data to support a range of specific metrics to enhance the bid (for example, maintenance cost per operating hour, mean time between maintenance (MTBM), etc.).​

Engineer using a Simcenter advanced vibration testing equipment.