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  • Nutraceuticals/Cosmetics
  • Nutraceuticals/Cosmetics
  • Nutraceuticals/Cosmetics

    임픽스의 발자취를 소개합니다.

    AI autonomous manufacturing in the health functional food/cosmetics industry

    The health functional food and cosmetics industry has high demands from consumers and certification organizations for food safety standards, quantitative formulation of chemical ingredients, and in-process hygiene/quality/traceability management. In order to improve the precision of raw material formulation and production hygiene management, AI autonomous control systems that can perform real-time analysis of formulation conditions and automatic control of environmental standards are required.
    At the same time production history management, hygiene standard certification, history tracking for consumer quality satisfaction, recipe management, expertise in quality monitoring are required.

    Required expertise: Recipe-based equipment operation and hygiene control, production history, expiration date, lot tracking management, integrated management of process hygiene and certifications such as HACCP and ISO

    BEST PRACTICE

    Nutraceuticals

    CKD Healthcare Smart Factory

    Pain Point

    • Eliminate inefficient managers' work process of managing/sharing planned, production, and inventory volumes based on handwritten logbooks
    • Improve efficiency by aggregating production rates and quantities in production management
    • Production planning based on production status monitoring and integrated management enables accurate delivery forecast and emergency response preparation
    • Improve product quality by applying a LOT number management system that minimizes missing data and errors


    Implementation Goals
    • Implement a smart input process that verifies raw material conformity and prevents misplacement through QR code-based LOT and aging management and IoT-linked weighing system from raw material receipt to weighing and packaging.
    • Implemente real-time monitoring of the entire process and CPS system through QR code-based input material management and LOT tracking by process, real-time data collection, and automatic yield calculation.
    • Robotic packaging and palletizing, AGV-based automated warehouse linkage, and traceability system to build a smart logistics system that enables automation and consumer tracking from packaging to shipping.

    Adopted Technology

    MES (Manufacturing Execution System)

    A manufacturing execution system that manages all production processes on the manufacturing floor
    It is a manufacturing site system that focuses on real-time monitoring of manufacturing facilities, production management, status identification, and defect management.
    It accurately records all production processes at the manufacturing site, from raw material input to process to product production, and provides optimized information to improve production efficiency.

    • Automatically record manufacturing facility baseline information, real-time tags, and facility Process Value (PV) values
    • Real-time aggregation of production status by line and process
    • Improve production control precision with plan-versus-actual analysis
    • Use as a foundation system for unmanned and automated operations

    Real-time monitoring

    Real-time facility and production monitoring with 3D video and status boards
    Intuitively monitor operational status across your processes with autoplay 3D video and status boards for each machine.

    • Real-time, facility-specific health monitoring
    • Analyze production performance against instructions by period
    • Automatically update production start-end and field call information

    Process control and e-documentation

    공정, 설비, 생산데이터의 자동 수집, 기록 및 관리를 통하여
    자료의 신뢰성 및 활용성을 확보합니다.

    • Increase the credibility and usability of documents
    • Check work status and set values by process
    • Going paperless throughout the process

    Facilities Management

    Integrated monitoring of pre-production processes and equipment lifecycle management
    By establishing a process management system that can monitor and integrate the pre-production process in real time, we quantify the manpower, equipment status, and labor on the production line to support systematic productivity improvement and quality control..

    • Monitoring cumulative operating data of major parts by facility
    • Manage equipment failure repair history
    • Monitor utilization by process line

    LOT Tracking

    Manage all product LOT Tracking
    Manage identities responsible for tracking and analyzing production LOT units, from the receipt of raw materials to the production of the products they go into.

    • LOT matching of inputed raw materials for all products by management of incoming, weighed raw materials
    • LOT tracking and facility utilization information collection by matching facility utilization by process
    • Check production, process, and quality data for all products
    • Tracking LOT of complete products

    BEST PRACTICE

    Cosmetics

    COSMAX Production Records Management System

    Pain Point

    • Solving the problem of inefficient work process in which the person in charge manages/shares the planned amount, production amount, and inventory amount based on handwritten records every day
    • Improve efficiency by aggregating production speed and quantity in terms of production management
    • Establishment of production plan based on production status monitoring and integrated management enables accurate delivery forecast and preparation for emergency response
    • By introducing a management system that minimizes data loss and errors, we aim to improve quality by tracking production data and enhancing reliability.


    Implementation Goals
    • Real-time process data collection
    • Real-time process deviation detection, alarm generation, and alarm system establishment
    • Production data tracking management and analsys-based implementation
    • Facility inspection cycle and optimal control through facility history management

    Adopted Technology

    N-POP (Next generation-Point of Production)

    Management system from a production perspective through automatic input of equipment and process values
    N-POP is a system that automatically collects and records various data generated on site based on production plans and work instructions.
    Key information (performance, equipment operation status, production status by process) can be analyzed and viewed in real time, improving both operational efficiency and production quality.

    • Automatic recording of manufacturing facility baseline information, real-time tags, SP (Preset) values, and PV (Process Value) values of facilities
    • Real-time aggregation of production status by line and process
    • Improved production management precision through plan-performance comparison analysis
    • Can be used as a base system for unmanned and intelligentization

    Real-time monitoring

    Real-time facility and production monitoring with 3D imaging and status boards
    Intuitively monitor operational status across your processes with autoplay 3D video and status boards for each machine.

    • Real-time status monitoring by detailed equipment
    • Analyze production performance against instructions over time
    • Automatically update production start-stop and field call information

    Process management

    Process management system based on early detection of equipment abnormalities and predictive maintenance
    A facility diagnostic system is established to detect and manage facility abnormalities in advance by collecting facility operation information and quality data in real time. This will improve facility operating rates and ensure reliability based on predictive maintenance.

    • Check work status and setting values by facility
    • Call the person in charge of Teamz and collect historical data
    • Improve facility utilization and secure quality stability

    Real-time data collection/analysis

    Visualization analysis function based on equipment-specific and process-specific data
    It automatically collects various data from the field and provides real-time analysis results in tables and graphs to support efficient insight extraction.

    • Check the status of tasks and settings through real-time data visualization by facility
    • Call the person in charge of Teamz and collect historical data

    Facility management

    Integrated monitoring of pre-production processes and equipment life cycle management
    This is a process management system that enables real-time monitoring and integrated management of the entire production process. It supports systematic productivity improvement and quality control by quantifying the number of personnel on the packaging line, SOPs, and equipment status.

    • Monitoring of accumulated operation data of major parts by equipment
    • Manage history of equipment repairs

    USE CASE

    Starting with the construction of a smart factory in 2019,
    IMPIX has created best practices optimized for SMEs
    through various AX(AI Transformation) projects.

    건강기능식품·화장품
    AI 기반 화장품 제조 공정 스마트공장 구축 실증 사례

    AI 기반 화장품 제조 공정 스마트공장 구축 실증 사례

    AI를 이용하여 화장품 제조 공정의 공정·품질 예측 및 자동화를 수행하는 임픽스의 인공지능 솔루션입니다.

    


    1. Pain Point 

    산업 특성 측면

    - ODM 중심의 화장품 제조 산업의 글로벌 경쟁력 강화를 위한 품질 및 수율 제고 필요

    - 다양한 제품군과 짧은 제품 라이프사이클로 인한 공정 관리 및 품질 관리 어려움

    - 공정 불량 및 고객 클레임 발생 시 전체 공정 데이터 추적의 어려움으로 인한 원인 규명 지연


    데이터 및 시스템 측면

    - 수작업 및 부분 자동화 기반의 공정 및 품질 데이터 관리로 인한 신뢰도 부족

    - 공정 조건 및 설비 상태와 품질 데이터 간 상관관계 분석 기반의 품질 예측 체계 부재

    - 공정·설비 데이터를 실시간으로 수집, 시각화, 예측·분석할 수 있는 AI 기반 시스템 부재


    설비 및 인프라 측면

    - 공정별 설비 상태 및 품질 결과를 연계하여 실시간 모니터링하고 품질 이슈를 사전에 감지할 수 있는 시스템 부재

    - 생산 완료 이후 불량 확인으로 인한 매몰 비용 및 납기 지연 문제 발생

    - 스마트공장 고도화를 위한 통합 관제 및 실시간 분석 인프라 필요


    2. AI Solution 

    A2LAB 및 One Way Platform 기반 AI 공정·품질 예측 및 분석 솔루션 적용



    3. 구축 목표

    세부 목표

    - AI 기반 데이터 분석을 통한 공정·품질 예측 및 자동화 체계 구축

    - 실시간 공정 모니터링 및 불량 예측을 통한 수율 개선 및 품질 향상

    - 스마트 HACCP Factory 구축을 통한 데이터 기반 의사결정 체계 마련

    - 제조·포장 공정 전반의 표준화 및 작업 가이드 자동 제공을 통한 불량 감소

     


    4. 구축 내용

    데이터 통합 관리 기술 적용

    - 제조 공정 및 설비 데이터, 품질 데이터, ERP·MES 데이터를 실시간 수집 및 통합 관리

    - 수집 데이터의 정합성 검증 및 전처리, 시계열 라벨링 기반 학습용 데이터셋 구축


    AI 알고리즘 기술 적용

    - 의사결정나무 및 LSTM 기반 공정·품질 예측 모델 적용

    - 공정 데이터와 품질 데이터 간 상관관계 분석 및 주요 변수 도출

    - AI 기반 실시간 불량 예측 및 작업 가이드 제공


    공정 품질 예측 및 시뮬레이션 적용

    - 실시간 모니터링 및 이상 감지 기반 품질 예측 및 공정 이탈 방지

    - 디지털트윈 및 시뮬레이션 기반 설비 세팅 전 품질 예측 시뮬레이션 제공

    - AI 분석 결과의 스마트공장 대시보드 시각화 및 작업 현장 적용



    5. 구축 효과

    제조공정 불량률 감소 

    - 도입 전 1.7%

    - 도입 후 1.0% 


    충포장공정 원불 폐기율 감소 

    - 도입 전 3.4%

    - 도입 후 2.0%