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The Urgent Need for AI Adoption and Digital Transformation

We support our clients' sustainable growth by delivering the most effective solutions.
With smart factory adoption at just 19.5% and AI adoption at only 0.1%, digital transformation has become an urgent business imperative.

Many Factories, but How Many Are Smart?

163,000 Small and Mid-Sized Manufacturers Nationwide

Only 19.5% are smart factories, equivalent to roughly two out of every ten

Eight out of Ten Factories Have Yet to Begin DX

Most factories still rely on handwritten records, individually managed spreadsheets, and verbal instructions

Most DX Adopters Remain at a Basic Level

As many as 75.5% of smart factories operate at only a basic level

Current AI Adoption Stands at Just 0.1%

Although 99.9% of companies have yet to adopt AI, many expect DX and AX to deliver significant productivity gains

Source: 2024 Smart Manufacturing Innovation Survey Results

The Digital Transformation Gap

Share of Analog Factories in 2024

"We plan to build an ecosystem that advances Digital Transformation (DX) and AI Transformation (AX) in manufacturing."
<Soon-jae Kwon, Director of Manufacturing Innovation, Ministry of SMEs and Startups>

Source: 2024 Smart Manufacturing Innovation Survey Results

During an on-site assessment for an AX project at a leading Korean heavy-industry company (Company D),
we identified the following challenges.

Operational Reality at a Leading Heavy-Industry Company

Given the company's scale and position in heavy industry, we expected at least a basic level of digitalization. In reality, its operations still depended on handwritten documents and non-standardized processes, with virtually no digital transformation in place.

Key Challenges

1 All maintenance records managed on paper

2 Inconsistent record formats across workers

3 An average of 30 minutes required to retrieve historical records

4 No capability for pattern analysis or predictive maintenance

Implementation Process

Data Collection

Digitize Paper Records

Data Standardization

Build an Integrated Database

Pattern Analysis

Apply AI Models

Predictive Maintenance

Establish a Proactive Response System

Conventional Approach	A2Tec Solution
All Maintenance Records Managed on Paper Risk of damage or loss, with no search capability	Mobile-Based Digital Maintenance Records Real-time recordkeeping from any location
Different Record Formats Used by Each Worker No standardization and no meaningful data comparison	Standardized Data Collection and Analysis Consistent formats enable reliable data comparison
Average of 30 Minutes to Retrieve Historical Records Manual searches through paper documents required	Real-Time Record Retrieval in Under Five Seconds Fast searches by keyword, equipment, or date
No Pattern Analysis or Predictive Maintenance Maintenance limited to reactive responses after failures	AI-Powered Predictive Maintenance Failure prediction and preventive maintenance

1 Minimized Reliance on Manual Labor

2 Reduced Labor Disruption Risk

3 A Sustainable Operating System