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IT R&D Team

IT연구개발팀

주요 협력 기관

  • 한국생산기술연구원
  • 대구기계부품연구원

IT R&D team development culture

Code review using GitHub PR (pull request)
– Smooth communication within the team through healthy feedback and discussions
– Improve the team’s overall development ability by learning each other’s technologies and solutions

Documentation and information sharing using confluence
– Effective and convenient information sharing through centralized document management
– Easy collaboration as multiple people can edit documents at the same time

Schedule and issue management using Jira
– Visualize real-time project progress to understand overall progress
– Strengthen collaboration by clearly defining roles for each team member and separating each task.

project manager

Define the project’s goals and scope, set a work schedule, and track and manage project progress. This helps coordinate team members’ work and ensure project schedules are met.

front-end

We develop web screens for various monitoring screens used in production sites and a back office that displays production status and analysis contents.

Back-end

We store and process collected data in the cloud and develop various analysis logic and RestfulAPI.

Edge system development

Machine data is collected in real time, first processed, and transmitted to the cloud.

data analysis

We analyze large amounts of diverse data generated from machines, discover insights, and conduct research to apply them to artificial intelligence.

system engineer

Dedicated to Barofactory service field installation, issue tracking, and customer response

technology stack

Edge system development

– Go, Rust, Python
– FOCAS, OPC UA

Our edge system developers have studied modern programming languages ​​Go, Rust, and Python in depth and utilize a variety of technology stacks to efficiently collect, process, and control data in the edge environment. They take into account the characteristics of each language and appropriately utilize Go’s outstanding performance and stability, Rust’s safety and memory management, and Python’s various libraries and productivity. In addition, considering integration with FOCAS and OPC UA, we select a language appropriate for the edge system to ensure integration and interoperability between systems. This ensures excellent performance and stability in data processing and control in the edge environment and meets business requirements.

backend

– Node, Nest, Java
– RDB(mysql)
– GCP
– Docker, websocket, MQ(message Queue)
– RestfulAPI

Our backend developers choose Node.js, Nest.js, and Java to maximize scalability and performance, and leverage RDB (mysql) to ensure data consistency. It provides stability and various services through Google Cloud Platform (GCP), and uses Docker, Websocket, and MQ (Message Queue) to streamline the development and deployment process and implement real-time communication and event-based architecture. It also supports efficient communication with clients through Restful API and maintains compatibility across various platforms and devices.

front end

– React, Next.js, JavaScript, TypeScript
– Styled-components or Tailwindcss
– Docker
– GCP Deploy, CICD

Our front-end development team chooses React, Next.js, JavaScript, and TypeScript to improve development efficiency and user experience, and implement flexible and reusable UI styling through Styled-components or Tailwind CSS. Additionally, we use Docker to efficiently manage the development and deployment environment, increase stability and development speed through GCP Deploy and CI/CD technology, and help developers develop and deploy more quickly.

data analyst

– Python, R, TensorFlow, PyTorch

At our company, our data analysts use Python, R, TensorFlow, and PyTorch to process data, visualize, perform statistical analysis, and build deep learning models. Python has a variety of libraries and a rich ecosystem and is used for a variety of tasks, while R is specialized in statistical analysis and data visualization. TensorFlow and PyTorch are used to build and train deep learning models, respectively, through which data analysts derive useful insights and contribute to business decisions.

system engineer

– Ubuntu, RHEL, GCP, Proxmox, Hyper-v, VMware
– VNC, RDP, SSH, FileServer
– Network skill

Our company’s system engineers build and manage a flexible and stable in-house IT infrastructure utilizing a variety of operating systems and virtualization platforms, including Ubuntu, RHEL, GCP, Proxmox, Hyper-V, and VMware. In addition, it plays a very important role in the company’s core business, which is responsible for building a company system for Barofactory service, and establishing and maintaining the related machine tools and communication environment after installation.

R&D Performance

Self-solution

  • Barofactory v1.0: SaaS-based production status monitoring and analysis service. Among commercial services from multiple companies.

  • Baro Factory v2.0 development in progress

barofactory

Government R&D tasks

  • Development of a service platform for smart manufacturing that implements the digital twin of machine tools (2020 ~ 2022, completed)

  • Development of a solution to support the establishment of automatic production planning (Advanced Planning and Scheduling) through AI algorithms based on big data built in the cloud through the collection and analysis of manufacturing data (2020 ~ 2022, completed)

Smart factory construction performance

  • Two smart workshop technology distribution projects underway (2023)

  • One data voucher support project underway (2023)