The Internet of Things (IoT) and Industry 4.0 are mega-trends that are rapidly changing the global trucking industry, with North America and Europe being at the helm of it. From curtailing road safety issues to improving diagnostics capabilities of fleets, these trends are making trucking a more effective business. By applying diagnostic and prognostic techniques to vehicle data, companies can reveal how vehicles and their systems are currently performing (diagnostics) and how they will perform in the future - will they be able to produce when they need to be (prognostics). Prognostics and Health Management/Monitoring (PHM) are methods to assess the health condition and reliability of systems for the purpose of maximising operational reliability and safety. In the commercial vehicle segment, PHM systems are useful for predictive maintenance, product improvement, warranty claim optimization, Over-the-air (OTA) updates, dealer optimization and so on.
The usage of PHM systems will have an impact on trucks OEMs, Tier-1 Suppliers and fleet operators in terms of reducing unnecessary expenses and improving efficiency. However, establishing significant benefits for all value chain participants remains a challenge, as not all value chain participants have established the monetary benefits of converting unstructured data to useful information. Apart from this, there are some common challenges that the industry as a whole is facing. Challenges such as shortage of budget, poor connectivity, low quality and quantity of data, and lack of dedicated sensors are pulling back the implementation of PHM system currently.
With storage of data getting cheaper, bandwidth ever-increasing and the cost of sensors steadily coming down whilst their ability is increasing, doing things with vehicle data beyond basic analytics is becoming increasingly viable and adoption of PHM system is expected to grow in the future. The prognostics market in NA and EU put together is expected to experience a compound annual growth rate (CAGR) of 130.5% between 2018 and 2025. The scope of PHM systems are currently restricted to tire, engine, transmission and emission. With electrification of trucks picking up pace, predictive maintenance, scheduling of battery recharge and replacement of batteries will drive the adoption of prognostics in the mid-term. The advent of autonomous trucks and platooning is expected to thrust the implementation of Artificial Intelligence and Machine Learning based prognostics in the long term.
Key Issues Addressed
- What are the challenges that the CV industry is facing in adopting prognostics solutions?
- What are the effects of prognostics and use cases for stake holders such as OEMs, Tier 1 Suppliers and Telematics providers?
- What is the current status of stakeholders’ telematics based CV diagnostics solutions in North America and Europe?
- By how much is the prognostics market expected to grow from 2018 to 2025?
- What are the growth opportunities available for Prognostics solution developers in 2019 and what are the strategic imperatives to be taken?
1. EXECUTIVE SUMMARY
- Key Findings
- Fleet Manager Prognostics Technology Survey Summary
- Integration of Remote and Prognostics Data
- Importance of Prognostics in CV Industry
- Challenges in Deploying Prognostics Systems in the Short term
- The Paradigm Shift Towards Being Predictive
2. RESEARCH SCOPE, DEFINITIONS, AND METHODOLOGY
- Research Scope
- Research Methodology
- Key Questions this Study will Answer
3. PROGNOSTICS AND ITS USE CASES
- Types of Prognostic Solutions
- Components Monitored and Potential Failures
- Maintenance Scheduling Strategies in CV Telematics
- Evolution of Prognostic Solutions in Connected Trucks Ecosystem
- Use Cases of Prognostics - Predictive Maintenance
- Use Cases of Prognostics - SOTA and FOTA
- Use Cases of Prognostics - Warranty Claim Optimization
4. COMMERCIAL VEHICLE PROGNOSTICS ECOSYSTEM
- Commercial Vehicle Prognostics Stakeholders
- Prognostics Solution Providers Benchmarking
- OEM Business Model Canvas
- Tier-1 Supplier Business Model Canvas
- Telematics Service Providers Business Model Canvas
- Select Truck OEMs Diagnostics Solutions
- Select Tier-1 Suppliers Diagnostics Solutions
- Select TSPs and Analytics Companies Diagnostics Solutions
5. CASE STUDIES
- OEM - Navistar’s Predictive Maintenance Technology
- Tier 1 Supplier - ZF’s Predictive Maintenance Technology
- Analytics Company - Progress’ Predictive Maintenance Technology
6. MARKET MEASUREMENT AND MARKET ANALYSIS
- Prognostics Installed Base - Forecasting
- Segment Wise Contribution
- Prognostics Packaging and Pricing Strategy
- Prognostics Service Revenue Analysis
7. GROWTH OPPORTUNITIES AND COMPANIES TO ACTION
- Growth Opportunity - Technology and Partnerships
- Strategic Imperatives
- The Last Word - 3 Big Predictions
- Legal Disclaimer