Deep Focus, Clear Insight

Count What
Matters!

HearIMLab listens to the voice of data.
We discover core values within complex manufacturing process data,
and predict the future of your business.

Why HearIMLab?

We go beyond simple data analysis to understand the context of the industrial site.

๐Ÿง

Deep Focus

We do not sway over superficial numerical changes. We dig into the root causes considering the physical/chemical mechanisms of the process.

๐Ÿ’ก

Clear Insight

We make complex Black-box models Explainable. We provide clear insights that field engineers can understand and trust.

๐ŸŽฏ

Optimal Control

We break through the limits of process efficiency through data-driven mathematical optimization algorithms, not trial & error.

Business Impact

Process Optimization Efficiency 92%
Defect Detection Accuracy 98.5%
Report Automation 100%

Interactive Solutions

Simulate the core analysis solutions provided by HearIMLab.

๐Ÿ› ๏ธ

Process Condition Optimization

Analyzes correlations between various process variables to find the conditions that yield the best yield.

Key Metrics

Live Simulation Data

Core Technology

From strategic approach to implementation technology stack, we introduce HearIMLab's integrated solution capabilities.

๐Ÿง 

Advanced Algorithms

Applying latest deep learning (Transformer, Autoencoder) and mathematical optimization algorithms.

๐Ÿญ

Domain Expertise

Interpreting physical meaning of data and selecting optimal methodology based on rich manufacturing field experience.

โ™พ๏ธ

Sustainable Lifecycle

Data pipeline and lifecycle management for continuous value creation of models.

๐Ÿ

Python & AI Stack

Structured/Unstructured AI modeling utilizing PyTorch, TensorFlow.

๐Ÿ“Š

R & Statistics

Rigorous statistical hypothesis testing, DOE, SPC execution.

โ˜๏ธ

MLOps & Serving

Monitoring and retraining pipeline construction for stable deployment and continuous utilization.

Key Project Experience

We have successfully performed projects in various industrial fields over the past 10 years.

์ปจ์„คํŒ… (2026)

Smart Factory (ERP, MES) Implementation

(์ฃผ)ํ”ผํ‹ฐ์”จ

ํ’ˆ์งˆ์˜ˆ์ธก (2025)

Missing Value Imputation & Quality Prediction

(์ฃผ)์”จ์—์Šค์— 

์ตœ์ ํ™” (2025)

Factory Layout Optimization Design

(์ฃผ)ํ”ผํ‹ฐ์”จ

์ด์ƒํƒ์ง€ (2024)

Gas Supply Anomaly Detection

(์ฃผ)์ง„์†”๋ฃจ์…˜

Start Your Journey

Leave your name, company name, contact information, etc. for faster consultation.

support@HearIMLab.com

Project History (Recent 10 Years)

์ตœ๊ทผ 10๋…„๊ฐ„ ์ˆ˜ํ–‰ํ•œ ์ฃผ์š” ํ”„๋กœ์ ํŠธ ์ด๋ ฅ์ž…๋‹ˆ๋‹ค.

์ตœ์ ํ™”

Factory Layout Optimization Design

๊ณต๊ฐ„ ์ œ์•ฝ์„ ๊ณ ๋ คํ•œ ์ตœ์  ๋ฐฐ์น˜

(์ฃผ)ํ”ผํ‹ฐ์”จ 2025
ํ’ˆ์งˆ์˜ˆ์ธก

Missing Value Imputation & Quality Prediction

๊ณ ๋น„์šฉ ๋ฐ์ดํ„ฐ ์ทจํ•ฉ ๊ตฌ์กฐ ๊ฐœ์„ 

(์ฃผ)์”จ์—์Šค์—  2025
์ตœ์ ํ™”

Initial Product Stabilization & CTQ Discovery

๊ณต์ •์กฐ๊ฑด ์ œ์‹œ

์œจ์ดŒํ™”ํ•™(์ฃผ) 2021
ํ’ˆ์งˆ์˜ˆ์ธก

Real-time Quality Prediction System

์‹ค์‹œ๊ฐ„ ์ œ์กฐ๊ณต์ •์ •๋ณด ํ™œ์šฉ ๋”ฅ๋Ÿฌ๋‹

์˜ค์‚ฐ๋Œ€ํ•™๊ต 2021
์ตœ์ ํ™”

Printing Process Job Sequencing

์ƒ‰์ƒ ๋ฐ ์ƒ‰๋„ ์œ ์‚ฌ์„ฑ ํ‰๊ฐ€

์˜ค์‚ฐ๋Œ€ํ•™๊ต 2020
์ด์ƒํƒ์ง€

Gas Supply Anomaly Detection

์‹ค์‹œ๊ฐ„ ์•Œ๊ณ ๋ฆฌ์ฆ˜ ๊ฐœ๋ฐœ

(์ฃผ)์ง„์†”๋ฃจ์…˜ 2024
์•ˆ์ „์ง„๋‹จ

Daesan Complex Facility Safety Diagnosis

์ข…ํ•ฉ์•ˆ์ „์ง„๋‹จ ์‹œํ–‰

HDํ˜„๋Œ€์˜ค์ผ๋ฑ…ํฌ ์™ธ 2021
์ปจ์„คํŒ…

Smart Factory (ERP, MES) Implementation

์‹œ์Šคํ…œ ๊ตฌ์ถ• ์ปจ์„คํŒ…

(์ฃผ)ํ”ผํ‹ฐ์”จ 2026
๊ธฐ์ˆ ๊ต์œก

EV Future Outlook & SW Utilization

ํ˜„๋Œ€์ฐจ EV์‚ฌ์—…์žฅ ์ง์› ๊ต์œก

(์ฃผ)ํ˜„๋Œ€์ž๋™์ฐจ 2025
์ปจ์„คํŒ…

KOSDAQ Listing Tech Evaluation Support

๊ธฐ์ˆ ํ‰๊ฐ€ ์ „๋žต ์ˆ˜๋ฆฝ

UDMTEK 2022
๊ธฐ์ˆ ๊ต์œก

4th Ind. Rev. & Kia's Future

์ „์‚ฌ์› ๋Œ€์ƒ ๊ต์œก

๊ธฐ์•„ 2020
์ปจ์„คํŒ…

System Replacement QA (ERP/MES)

ERP/MES/APS/WMS

์œจ์ดŒํ™”ํ•™(์ฃผ) 2019
์—ฐ๊ตฌ์šฉ์—ญ

Smart Factory Level Diagnosis Model

์ค‘์†Œ๊ธฐ์—… ๋Œ€์ƒ

ํ•œ์–‘๋Œ€/์ง€์‹์„œ๋น„์Šค์—ฐ๊ตฌ์†Œ 2018
์—ฐ๊ตฌ์šฉ์—ญ

Consulting Methodology Development

์Šค๋งˆํŠธ ํŒฉํ† ๋ฆฌ ์ปจ์„คํŒ…

ํ•œ์–‘๋Œ€/์ง€์‹์„œ๋น„์Šค์—ฐ๊ตฌ์†Œ 2017
์ปจ์„คํŒ…

ํฌ๋ผ์šฐ๋“œ ํŽ€๋”ฉ ์ด๊ด„

์Šคํƒ€ํŠธ์—… ์ง€์›

๋ธŒ๋ฆด๋ฆฌ์–ธ์ธ  2017
์—ฐ๊ตฌ์šฉ์—ญ

ํ•€ํ…Œํฌ ๋””๋ฐ”์ด์Šค ์‚ฌ์šฉ์„ฑ ๊ฐœ์„ 

์ผ๋ณธ ํ•€ํ…Œํฌ ์‹œ์žฅ ์ง„์ถœ

๋ธŒ๋ฆด๋ฆฌ์–ธ์ธ  2016