RapidMiner

RapidMiner

Synthesize and Optimize Your Current Systems

RapidMiner

RapidMiner is a product of Altair

RapidMiner is a comprehensive data science platform that empowers users to build and deploy advanced analytics solutions. It provides a visual workflow designer, enabling both technical and non-technical users to easily create machine learning models.

RapidMiner supports the entire data science lifecycle, from data preparation to model deployment and monitoring.

RapidMiner

Main benefits

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  Visual Workflow Design

Simplifies the creation of complex analytics workflows through a drag-and-drop interface. Reduces the need for extensive coding, making data science accessible to a wider range of users.

  Comprehensive Data Science Lifecycle Support

Covers all stages of the data science process, including data preparation, model building, and deployment. Provides a unified platform for end-to-end analytics.

  Wide Range of Algorithms and Techniques

Offers a vast library of machine learning algorithms and statistical techniques. Enables users to build diverse and sophisticated models.

  Flexible Deployment Options

Supports deployment of models on-premises, in the cloud, or as embedded solutions. Provides scalability and adaptability to various deployment needs.

  Automation and Efficiency

Automates repetitive data science tasks. Increases the efficiency of the data science workflow.

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Insights

CASE STUDY

Optimization of the SLM/DMLS process to manufacture an aerodynamic Formula 1 part

This paper presents the RENAULT F1 Team’s AM process for an aerodynamic insert in titanium Ti6Al4V. Production was optimized by identifying the best orientation for the parts and the best positioning for the support structures in the melting chamber, in addition to using the ANSYS Additive Print module, a simulation software useful for predicting the distortion of a part and for developing a new, 3D, compensated model that guarantees the best “as-built” quality.

automotive additive-manufacturing optimization

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CASE STUDY

Flexible factory design and reconfiguration using digital simulation models

The text discusses the importance of digital simulation models in modern factory design and reconfiguration, particularly in response to shorter product lifecycles and increased customization demands. Traditional design methods often lead to inefficiencies and high costs, making digital simulation essential for creating flexible and adaptable production systems. The article highlights a case study involving a furniture assembly factory, where a manufacturer needed to efficiently handle a variety of custom kitchen cabinet orders. The system integrator was tasked with designing a robotic assembly line that could maintain production efficiency despite the high variety of products.

industry4 SIMUL8

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CASE STUDY

Filming the Bloodhound Super Sonic Car Land Speed Record

Using CAE to optimise the design of a prototype for a super sonic filming drone

This detailed technical case study describes how the students arrived at a supersonic aircraft drone prototype using MATLAB and modeFRONTIER in order to reduce the time and costs of numerical and wind-tunnel testing.

automotive modefrontier optimization

CASE STUDY

Development and optimization of crash brackets for ECE R29 regulation compliance

IVECO uses modeFRONTIER to simulate results to pass type-approval tests

This paper presents the main steps taken in the development phase of the IVECO cab suspension brackets to comply with the new ECE R29 crash regulation for Heavy Commercial Vehicles (HVC).

modefrontier optimization automotive

CASE STUDY

The design optimization of a small axial turbine with millions of configurations

The case for computerized optimization over manual design interventions

In this article, we show that the main turbine characteristics, such as efficiency and exit flow angle, can be sufficiently improved using parametric optimization.

modefrontier energy optimization