🔷 Core Technology and Differentiation

Product Overview and Development Process

SmartSIM is a Python-based, independently developed design analysis software that leverages simulation and test data. Optimized for small and medium-sized enterprises (SMEs), it features a user-friendly interface and automated report generation, enabling non-experts to perform advanced data-driven analysis.

⦁ Development Stages

Technical (Quality) Aspects

Functionality and Performance

● SmartSIM

• Developed entirely in Python, SmartSIM incorporates its own analysis logic, automated report generation, and data preprocessing functions, such as automatic conversion of parameter study results from SolidWorks.

• Supports various advanced analysis methods:

  • Linear correlation analysis and sensitivity analysis

  • Constraint-based design space exploration and automatic derivation of input parameter ranges

  • Metamodeling techniques (Kriging, MLS, Polynomial) for predicting output values based on input changes

  • Scenario generation using Latin Hypercube Sampling (LHS)

• Offers a user-friendly interface built with Python TTK, making it intuitive and easy to use for non-experts.

● Competing Products (Ansys optiSLang, Dassault Systems Isight, ESTECO ModeFRONTIER)

• These foreign commercial products provide powerful and complex high-end features but often come with very high licensing and maintenance costs.

• Key features include:

  • Fully integrated optimization environments with support for advanced analysis algorithms (metamodeling, design optimization, etc.)

  • Primarily designed for expert users, making the UI complex and less accessible for non-specialists

  • Automation features for simulation process management are included

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Quality and Reliability

● SmartSIM

• Focuses on delivering practical, field-oriented analysis results tailored to SME environments

• Capable of analyzing data under various real-world design constraints

• Ensures consistency and clarity through automated report generation, and incorporates user feedback into regular updates for continual improvement

● Competing Products

• Designed for global enterprise use, offering high technical reliability and precision

• However, their complexity and high cost create barriers for adoption by SMEs and non-expert users

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🔷 Technological Competitiveness

Technological Independence and Innovation

● SmartSIM

• All core functions are developed independently in Python, with no reliance on external simulation engines

• Includes scenario generation, data transformation, constraint-based design optimization, input range extraction, and predictive modeling—all implemented with proprietary algorithms

• Capable of custom feature development based on client requirements

• Python-based architecture makes it highly adaptable and easy to integrate with additional algorithms or modules

● Competing Products

• Comprehensive platforms that support a wide range of advanced analysis and optimization functions

• Backed by strong global brand recognition and customer support infrastructure

• However, their complexity and high cost limit usability and accessibility, especially for SMEs or use cases requiring lightweight, customizable solutions

Product Features and Core Technologies

Differentiation from Competitors

Technological Competitiveness and Scalability

• Independent Technology: All key modules—LHS scenario generation, SolidWorks parameter conversion, sensitivity/correlation analysis, constraint-based design optimization, and metamodeling (Kriging, MLS, Polynomial)—were developed in-house.

• Future Expandability: Currently integrating with open-source simulators such as CARLA, AirSim, and Gazebo for use in autonomous driving, robotics, and drone applications.

• Development Roadmap:

  • Expand metamodel options and improve accuracy through residual evaluations

  • Implement deep learning-based scenario generation and automatic technical report creation using LLMs (Large Language Models)

Price Competitiveness

● SmartSIM

• Offers affordable, SME-oriented licensing: more cost-effective than commercial solutions, with flexible pricing and payment options to reduce adoption barriers

• Reduces Total Cost of Ownership (TCO): since all functions are self-developed, maintenance and feature upgrades are cost-efficient

● Competing Products

• Require high upfront investment and ongoing maintenance costs

• Users often need to purchase entire software suites, even when only a portion of the features are required, leading to higher cost burdens