The tire
inspection market was valued at USD 1.42 billion in 2025 and is projected
to grow at approximately 5.7% CAGR from 2026 to 2035, reaching USD 2.41 billion
by 2035. The market includes automated and manual systems that assess tire
condition, dimensions, internal construction, pressure, and visible defects.
Market growth is driven by vehicle safety regulations,
increasing tire-production volumes, evolving electric-vehicle tire
requirements, and Industry 4.0 adoption in tire manufacturing. These trends are
increasing demand for more consistent, traceable, and production-integrated
inspection processes.
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Automated tire inspection systems are gaining importance
where production consistency and defect containment are critical. Robotic
handling and automatic defect recognition help move inspection from a discrete
task to a controlled production step.
Camera-based inspection is widely used for surface, marking,
code, and geometry-related information. Its commercial advantage is deployment
flexibility across manufacturing, service, fleet, and retail inspection
settings.
Asia Pacific held approximately 26.4% of the tire inspection
market in 2025 and is projected to grow at approximately 7.7% CAGR through
2035. The region benefits from expanding tire production capacity,
export-oriented quality requirements, and the need for scalable inspection
systems.
AMETEK Micro-Poise held approximately 18–22% market share in
2025. The company competes through its X-ray, uniformity, handling, and
defect-recognition capabilities for tire-production applications.
Some of the major players in this market are A&D
Technology, Comet (YXLON), Erhardt+Leimer, MESNAC, Micro-Epsilon, Mitsubishi
Heavy Industries, MTS Systems Corporation, Nikon Corporation, Technip Energies
N.V., Blue Star Engineering & Electronics, CyXplus SA, Dandong Aolong
Radiative Instrument Group, Mabri.Vision, Numetrix Technologies, Parth Systems
India, TMSI, Anyline, ProovStation, and UVeye.
Table of Contents
Chapter 1. Methodology & Scope
1.1 Research approach
1.2 Quality Commitments
1.2.1 GMI AI policy & data integrity commitment
1.2.1.1 Source consistency protocol
1.3 Research Trail & Confidence Scoring
1.3.1 Research Trail Components
1.3.2 Scoring Components
1.4 Data Collection
1.4.1 Partial list of primary sources
1.5 Data mining sources
1.5.1 Paid sources
1.5.1.1 Sources, by region
1.6 Base estimates and calculations
1.6.1 Base year calculation
1.7 Forecast model
1.7.1 Quantified market impact analysis
1.7.1.1 Mathematical impact of growth parameters on forecast
1.8 Research transparency addendum
1.8.1 Source attribution framework
1.8.2 Quality assurance metrics
1.8.3 Our commitment to trust
Chapter 2. Executive Summary
2.1 Industry 360° synopsis
2.2 Key market trends
2.2.1 System
2.2.2 Technology
2.2.3 Inspection
2.2.4 Application
2.2.5 End Use
2.3 TAM Analysis, 2026-2035
2.4 CXO perspectives: Strategic imperatives
Chapter 3. Industry Insights
3.1 Industry ecosystem analysis
3.1.1 Supplier landscape
3.1.1.1 Raw material suppliers
3.1.1.2 Component suppliers
3.1.1.3 Manufacturers
3.1.1.4 Service providers
3.1.1.5 Distribution channel
3.1.1.6 End Use
3.1.2 Cost structure
3.1.3 Profit margin
3.1.4 Value addition at each stage
3.1.5 Vertical integration trends
3.1.6 Disruptors
3.2 Industry impact forces
3.2.1 Growth drivers
3.2.1.1 Stringent vehicle safety regulations
3.2.1.2 Rising tire production volumes globally
3.2.1.3 Growth of electric vehicle tire requirements
3.2.1.4 Industry 4.0 adoption in tire manufacturing
3.2.2 Industry pitfalls & challenges
3.2.2.1 High capital cost of X-ray systems
3.2.2.2 Technical complexity & integration challenges
3.2.3 Market opportunities
3.2.3.1 AI-powered automatic defect recognition
3.2.3.2 Integration of X-ray with vision systems
3.2.3.3 Mobile and drive-through inspection solutions
3.2.3.4 Real-time data analytics & cloud connectivity
3.3 Growth potential analysis
3.4 Pricing Analysis (Driven by Primary Research)
3.4.1 Historical Price Trend Analysis
3.4.2 Pricing Strategy by Player Type (Premium / Value / Cost-plus)
3.5 Regulatory landscape
3.5.1 North America
3.5.1.1 U.S.: National Highway Traffic Safety Administration (NHTSA)
3.5.1.2 U.S.: Tire Safety Standards (FMVSS)
3.5.1.3 Canada: Motor Vehicle Tire Safety Regulations (SOR /2013-198)
3.5.2 Europe
3.5.2.1 German Road Traffic Licensing Regulations
3.5.2.2 UK: Ministry of Transport (MOT) Test
3.5.2.3 EU Tire Labeling Regulation
3.5.2.4 REACH Compliance & Sustainable Material Standards
3.5.3 Asia-Pacific
3.5.3.1 Japan Low Rolling Resistance Tires Certification
3.5.3.2 Malaysia: JPJ Puspakom Mandatory Tread Depth
3.5.3.3 Australia: HVNL Defect Management
3.5.3.4 China Tire Quality Certification Standards
3.5.4 Latin America
3.5.4.1 Brazil INMETRO Tire Labeling Program
3.5.4.2 Mexico NOM Tire Safety Regulations
3.5.5 Middle East & Africa
3.5.5.1 GCC Tire Quality & Import Regulations
3.5.5.2 South Africa Tire Safety Compliance Standards
3.6 Technology and Innovation landscape
3.6.1 Current technologies
3.6.2 Emerging technologies
3.7 Porter’s analysis
3.8 PESTEL analysis
3.9 Patent analysis (Driven by Primary Research)
3.10 Impact of AI & generative AI on the market
3.10.1 AI-Driven Disruption of Existing Business Models
3.10.2 Automated design optimization
3.10.3 Supply chain AI for demand forecasting
3.10.4 GenAI use cases & adoption roadmap by segment
3.10.5 Risks, Limitations & Regulatory Considerations
3.11 Forecast assumptions & scenario analysis (Driven by Primary Research)
3.11.1 Base Case — key macro & industry variables driving CAGR
3.11.2 Optimistic Scenarios — Favorable Macro and Industry Tailwinds
3.11.3 Pessimistic Scenario — Macroeconomic slowdown or industry headwinds
3.12 Sustainability and environmental aspects
3.12.1 Sustainable practices
3.12.2 Waste reduction strategies
3.12.3 Energy efficiency in production
3.12.4 Eco-friendly Initiatives
3.12.5 Carbon footprint considerations
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