ZEROCKZEROCK for Makers

Drawings. Inspection records. 30 years of expertise.
All preserved by AI, for the next generation

Japan's manufacturing workforce has shrunk by 1.57 million in 20 years. ZEROCK turns veteran knowledge into AI-powered assets and accelerates technology transfer.

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Knowledge Challenges in Manufacturing

1

Finding past drawings takes 30+ minutes each time, with no way to know if similar designs already exist

2

Veteran engineers approaching retirement, but tacit knowledge (sound, vibration, touch-based judgment) cannot be formalized

3

Embedded software testing depends on specific QA engineers, with test case creation alone taking days

4

No way to cross-search past defect records and corrective action history for root cause investigation

5

Manual linking between drawings and specifications leads to frequent tracking gaps during design changes

6

Previous AI/DX tools failed due to data preparation barriers. 'AI doesn't work' sentiment lingers on the shop floor

1.57M

Workers lost from manufacturing in Japan over the past 20 years. The 2025 problem makes knowledge transfer even more critical

Source: METI Manufacturing White Paper 2024

A day in the life of a technical manager with ZEROCK

08:00

Quality anomaly detected before shift starts

AI auto-detected outliers in yesterday's inspection data and sent a Slack alert overnight.

Scheduled Automation + Slack
09:00

Similar drawings found in 30 seconds

"Pull up every past drawing similar to this part." Similar drawings ranked by relevance in 30 seconds.

AI Knowledge Base / GraphRAG
10:00

Veteran know-how, always accessible

"What machining conditions did veteran Tanaka use for this material?" Instant answers from past knowledge with conditions and precautions.

AI Knowledge Base (Tech Transfer)
13:00

Design change impact, auto-traced

"Part A's material changed—trace the impact across all assemblies." Related drawings, processes, and inspection criteria auto-traced.

Smart Agent + GraphRAG
15:00

Meeting action items auto-registered

Meeting AI extracts quality improvement actions and auto-registers TODOs on each person's calendar.

Meeting AI + Calendar
17:00

Estimate accuracy within 5%, based on past data

"Generate a rough estimate for these specs, referencing similar past projects." High-accuracy estimate exported to Excel.

Smart Agent + Excel Export

Skills built for manufacturing

AI Similar Drawing Search

30min → 30sec

Tech Transfer Knowledge Base

70% shorter onboarding

Quality Anomaly Auto-Detection

Scheduled runs

Design Change Impact Analysis

GraphRAG

Manufacturing Meeting Notes

Meeting AI

Estimation AI Assistant

±5% accuracy

Quality Traceability

Days → hours

Before and After Implementation

Before
After
Impact
30 min/search
30 sec/search
98% reduction
Drawing search
3 years (OJT)
6 months
80% shorter
Knowledge transfer
2 weeks/model
3 days/model
78% reduction
Embedded SW testing
3-5 days
2-3 hours
90% shorter
Defect investigation
2 days (manual)
10 min (auto)
99% reduction
Design change review
Half day/item
30 min/item
88% reduction
Cost estimation

Manufacturing Implementation Results

Automotive Parts Manufacturer (1,200 employees)

1,200 employees, 45 in engineering

Drawing search time reduced by 95%

We loaded 30 years of 150,000 drawings into ZEROCK. What used to take designers 30 minutes to find now appears instantly with a text search. Since defect history is linked, we've stopped repeating the same mistakes. TIMEWELL engineers completed data migration in 2 weeks. Almost zero burden on our team.

Design Department Director

Before

30 min/search

After

30 sec/search

Electronics Manufacturer (500 employees)

500 employees, 12 in QA

Embedded software testing reduced by 65%

With IoT product variations increasing, manual testing reached its limits. ZEROCK's Agent Mode auto-generates test cases from specs, letting our QA engineers focus on critical edge cases.

Quality Assurance Manager

Before

2 weeks/model

After

3 days/model

Precision Parts Manufacturer (380 employees)

We decided to adopt ZEROCK ahead of 3 veteran engineers retiring. We had failed with an AI chatbot before, so we were skeptical—but seeing the search demo with our actual drawings convinced us. Within 2 months, drawing search was no longer person-dependent, and junior engineers' design review quality improved.

Manufacturing Technology Director

Manufacturing ROI Simulation

Monthly cost reduction for a manufacturer with 10 engineers

Current Monthly Cost

Drawing search (3×/day × 30min × 10 people)150 hrs/mo
Engineer training (OJT hours)80 hrs/mo
Embedded SW testing (2 models)160 hrs/mo
Defect investigation40 hrs/mo
Total hours
430 hrs/month

* Calculated at ¥5,000/hr × 10 engineers (custom estimates available for your team size)

After ZEROCK

Drawing search (30sec × 10 people)2.5 hrs/mo
Engineer training (AI-assisted)20 hrs/mo
Embedded SW testing (automated)56 hrs/mo
Defect investigation (AI search)4 hrs/mo
Total hours
82.5 hrs/month

347.5 hours/month saved

ZEROCK費用

¥300,000* Includes implementation support, data migration, and ongoing support. No hidden fees

Monthly cost savings

¥1,437,500

ROI 379%

Payback period: ~3 months

AI活用準備度診断

10問・3分で、貴社のAI導入準備状況を可視化

無料で診断する

Turn veteran expertise into
everyone's advantage

Start a 7-day free trial and see how ZEROCK accelerates technology transfer on your shop floor.

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