Eigendauer

Eigendauer offers specialized engineering services for mechanical component root cause analysis and Design for Additive Manufacturing (DfAM). Their proprietary MIP platform uses digital twins and AI to simulate manufacturing processes, reducing waste and improving component durability.

Updated 2 months ago

Funding

Funding not disclosed

Funding rounds are not available yet.

Founders

Founder details are not available yet.

Product

Problem

Mechanical components such as bearings, gears, and shafts are susceptible to failure, leading to operational disruptions and increased maintenance costs. Identifying the precise root cause of these failures is critical for optimizing component lifespan and ensuring system reliability. Furthermore, traditional component design often results in suboptimal weight and functionality, limiting performance and efficiency.

Solution

Eigendauer provides specialized engineering services focused on root cause analysis (RCA) for mechanical components, enabling clients to pinpoint failure origins and inform data-driven decision-making. The company also offers Design for Additive Manufacturing (DfAM) expertise to develop optimized, lightweight components with enhanced functionalities. Eigendauer's proprietary MIP platform leverages digital twin technology and artificial intelligence to simulate manufacturing processes, thereby reducing material waste and improving component durability. This integrated approach addresses both failure analysis and advanced design optimization for mechanical systems.

Target Audience

Eigendauer serves industries such as aerospace, wind energy, and automotive, targeting engineering departments and product development teams responsible for mechanical component integrity and performance.

Features

Root Cause Analysis (RCA) for mechanical components including bearings, gears, and shafts, adhering to IEC 62740:2015 standards.
Design for Additive Manufacturing (DfAM) services for creating optimized, lightweight components with novel functionalities.
Manufacturing process simulation using digital twin and AI to predict and mitigate residual stresses and distortions.
MIP (Manufacturing Interaction Platform) for simulating manufacturing chains and controlling process parameters.
Analysis of component design, manufacturing, assembly, and application factors contributing to failure events.
Focus on reducing operational costs and time by addressing the fundamental causes of component failure.