세계의 상용차(CV) 예지보전 산업(북미, 유럽, 인도, 2024-2029년)

Prognostics is Driving Growth by Increasing Operational Efficiency and Reducing Maintenance Costs

The commercial vehicle industry is undergoing a major transformation, fueled by rapid technological advancements and rising demand for efficiency, safety, and sustainability. A standout innovation in this shift is prognostics, which is the ability to predict vehicle health and performance based on real-time data. This study takes a deep dive into prognostics in commercial vehicles, the ecosystem, key participants, and their market share. It also identifies key trends and case studies and highlights the potential of prognostics to revolutionize maintenance practices, enhance operational efficiency, and drive cost savings. The focus of this study is on commercial vehicles that weigh more than 3.5 tons in North America, Europe, and India. By including both developed and developing markets, the study provides a comprehensive view of the opportunities and challenges in these regions.

Prognostics in commercial vehicles leverages data analytics, artificial intelligence (AI), and machine learning (ML) algorithms to forecast vehicle component failures and maintenance needs before they occur. The study kicks off by defining prognostics, listing some common ML approaches used, outlining the scope of prognostics regarding commercial vehicle applications with a 5-year timeline, and highlighting the sharp contrast of this predictive approach with traditional reactive and preventive maintenance practices.

The growth opportunity in prognostics for commercial vehicles lies in its potential to significantly reduce maintenance and operational costs, as traditional maintenance strategies often lead to inefficiencies and excessive downtime. As commercial vehicles become more sophisticated, vehicle data availability is at its peak. This data is extracted from the vehicle through 2 primary routes-diagnostics tools and telematics, which become the sources to feed prognostics' ML algorithms. After touching upon these data sources, the study moves on to classify different categoric participants of the predictive maintenance ecosystem that leverage these data channels to offer prognostics services. The study also discusses the inter-relationships between these participants and their functions, identifies new start-ups, emerging leaders, and dominant companies, and throws light on the on-ground scenario by drawing meaningful insights by mapping key companies against each other.

The integration of prognostics systems with other emerging technologies, such as telematics and autonomous driving, amplifies its potential benefits. Considering these innovations, this study maps key trends with their impact on the industry against certainty and discusses the top 3 trends of 2024 (digital twins, OTA updates, and advances in ML, each of which is elaborated along with a case study).

Despite its promise, the widespread adoption of prognostics in commercial vehicles faces several challenges. A key growth restraint in prognostics-high false positives in bumper-to-bumper solutions, which has kept fleet owners and OEMs from widespread adoption-is discussed. False positives have restricted prognostics to a niche and made it an application-specific market. Here lies another notable opportunity in the AI and ML domains for analytics and data science companies to develop accurate algorithms that can reduce these false positives, increasing the solution's adoption across a wider user base.

In conclusion, the study estimates market size, installed base, and penetration of prognostics as of 2023, across the North American, European, and Indian commercial vehicle markets. In addition, it offers a 5-year forecast until 2029 for revenues and estimated market bases across the regions of study.

Prognostics represents a transformative opportunity for the commercial vehicle industry, offering significant advantages. As technology evolves, the adoption of prognostics systems will become increasingly prevalent. Prognostics is reshaping the maintenance ecosystem through strategic partnerships and mergers and acquisitions among dedicated prognostics companies, telematic service providers, and OEMs, driving the next wave of innovation in fleet management.

Table of Contents

Transformation in CV Predictive Maintenance

• Why Is It Increasingly Difficult to Grow?
• The Strategic Imperative 8™
• The Impact of the Top 3 Strategic Imperatives on the CV Maintenance Industry

Aims, Objectives, and Scope

• Aims and Objectives
• Research Methodology
• Scope

Growth Environment

• Competitive Environment
• Key Findings
• Growth Drivers
• Growth Restraints
• Definition of Prognostics
• Approaches to Implementing Prognostics Models
• Scope of Prognostics in CVs

Prognostics Solutions in CV Maintenance

• Data Channels for Prognostics in CV Maintenance
• Prognostics in CV Maintenance
• Channels to Offer Prognostics Solutions in CVs
• Prognostics in CV Maintenance through Telematics Data
• Applications of Prognostics in CV Maintenance

Prognostics Ecosystem in Commercial Vehicles

• Value Addition for Fleet Owners through Prognostics Services
• Prognostics in the Value Chain
• Global*: OEMs in Prognostics-Available Solutions
• Global: Dedicated Prognostics and Diagnostics Tool Companies
• Comparison of Key Ecosystem Participants, 2023

Trends and Case Studies

• Key Trends in Prognostics
• Trend: Digital Twin and Sensor Fusion
• Case Study: Intangles-A Digital Twin Company
• Trend: OTA Updates
• Case Study: Volvo Trucks Uptime Center-OTA Updates
• Trend: Deep Learning and AI in CV Maintenance
• Case Study: CerebrumX

Regional Analysis

• Regional Analysis: North America
• Regional Analysis: Europe
• Regional Analysis: India
• Prognostics Solution Providers' Share
• Revenue Share Analysis

Growth Generator

• Growth Metrics
• Revenue Forecast Considerations
• Revenue Forecast by Region
• Units Forecast by Region
• Revenue Forecast Scenario Analysis
• Installed Base Forecast
• Pricing Trends and Forecast Analysis
• Key Growth Driver: Partnerships between TSPs and Prognostics Companies
• Key Growth Restraint: Slower Adoption Because of High False Positives

Best Practices Recognition

• Best Practices Recognition: Pitstop
• Best Practices Recognition: Intangles
• Best Practices Recognition: CerebrumX

Growth Opportunity Universe

• Growth Opportunity 1: Prognostics-as-a-service (PaaS)
• Growth Opportunity 2: Inventory Automation
• Growth Opportunity 3: Developments in Machine Learning and AI

Next Steps

• Benefits and Impacts of Growth Opportunities
• Next Steps
• List of Exhibits
• Legal Disclaimer