Strategic Overview of Quantum Computing Applications in the Automotive Industry

Strategic Overview of Quantum Computing Applications in the Automotive Industry

New Product Development Initiatives to Focus on Process Optimization and Advanced Materials Research

RELEASE DATE
29-Sep-2023
REGION
Global
Deliverable Type
Market Research
Research Code: PF30-01-00-00-00
SKU: AU_2023_174
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Strategic Overview of Quantum Computing Applications in the Automotive Industry
Published on: 29-Sep-2023 | SKU: AU_2023_174

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This analytics highlights quantum computing innovation in the automotive industry and the significance of integrating this technology in supply chain, materials research, vehicle design, vehicle testing, assembly, manufacturing, retail, after-sales, and vehicle-in-motion. Simulations integrated with quantum computing processors analyze multiple pre-production scenarios substantially faster; they are more accurate and have a shorter turnaround time, helping automakers stay ahead of the competition. Quantum computing also helps simulate complex molecular properties and battery material reactions and behaviors at the quantum level and can enable OEMs to design low-cost batteries with new, sustainable materials. The technology can help optimize traffic management and vehicle routing. BMW, VW, Toyota, Hyundai, Daimler, and Ford are piloting (in partnership) quantum computing for select use cases. Though the proof-of-concept (Poc) for a smaller set of variables looked promising, the future plan will involve scaling up the infrastructure, qubits quality, and using complex sets of parameters. Identifying the right use case is critical before investing in quantum research. OEMs should partner with professional services experts that can help with problem identification through proof-of-concept development and eventually integration into day-to-day production processes. However, huge investment costs and existing pertinent technologies (to digitize the automotive value chain) are currently hindering quantum adoption among OEMs. Right use case identification, coupled with a hybrid quantum-classical computing model, will enable OEMs to achieve the best of both worlds. This analytics presents the overall scope of quantum computing and the current challenges hindering quantum momentum in the automotive industry. It analyzes OEM partnerships and key use cases.

Author: Dorothy Amy

Why is it Increasingly Difficult to Grow?

The Strategic Imperative 8™

The Impact of the Top 3 Strategic Imperatives on the Automotive Quantum Computing Industry

Growth Opportunities Fuel the Growth Pipeline Engine™

Scope of Analysis

Growth Drivers

Growth Restraints

Key Findings

Classical Bits vs. Qubits

Classical vs. Quantum Computers

Quantum Computing Methods

How can Quantum Computing Transform Industry Verticals?

Quantum Computing Domains

Quantum Computing Across the Automotive Value Chain

Stakeholder Overview

Automotive Partnerships in Quantum Computing

Current Challenges to Using Quantum Computing in the Automotive Industry

Hybrid Operating Model of the Future

Use Case Segmentation

Quantum Simulations for Automotive Product Design

Quantum Simulation in Product Design—Automotive Partnerships

Quantum Simulation to Revolutionize F1 Racing

Quantum Chemistry for EV Battery Design

Case Study—Ford’s Exploration of EV Battery Materials Using Quantum Simulations

Other OEM Initiatives—EV Battery & Fuel Cell Design

Automotive OEMs Exploring Quantum in Product Design Phase

Quantum Computing in Product Design—Key Takeaways

Use Case Segmentation

Quantum Computing in Manufacturing

Quantum Computing in Process Optimization

Case Study—BMW’s Use of Quantum Computing for Robot Path Optimization

Quantum-based Machine Learning for Predictive System Maintenance

Quantum Digital Twins

Partnerships for Quantum Computing in Automotive Manufacturing

Automotive OEMs & Tier I Suppliers exploring Quantum Computing in Manufacturing

Quantum in Manufacturing—Key Takeaways

Use Case Segmentation

Quantum Computing Use Case Analysis in Retail & Aftersales

Quantum Computing for Vehicle In-Motion Use Cases

Case Study—Quantum Computing for Traffic and Route Optimization

Quantum Cryptography for Future Vehicle Security

Automotive OEMs Exploring Quantum Computing in Retail, Aftersales, & Vehicle In-Motion

Quantum in Retail, Aftersales and Vehicle In-Motion—Key Takeaways

Use Case Segmentation

How can Quantum Computing Revolutionize the Supply Chain?

Case Study—Fujitsu and Toyota Optimize Supply Chain Logistics

Case Study—BMW and Honeywell Optimize Supplier Management

Impact Analysis of Quantum Computing in Supply Chain Use Cases

Growth Opportunity 1—Advanced Materials Research

Growth Opportunity 1—Advanced Materials Research (continued)

Growth Opportunity 2—Vehicle Design Simulations

Growth Opportunity 2—Vehicle Design Simulations (continued)

Growth Opportunity 3—Real Time Traffic Route and Fleet Optimization through Quantum Computing

Growth Opportunity 3—Real Time Traffic Route and Fleet Optimization through Quantum Computing (continued)

List of Exhibits

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This analytics highlights quantum computing innovation in the automotive industry and the significance of integrating this technology in supply chain, materials research, vehicle design, vehicle testing, assembly, manufacturing, retail, after-sales, and vehicle-in-motion. Simulations integrated with quantum computing processors analyze multiple pre-production scenarios substantially faster; they are more accurate and have a shorter turnaround time, helping automakers stay ahead of the competition. Quantum computing also helps simulate complex molecular properties and battery material reactions and behaviors at the quantum level and can enable OEMs to design low-cost batteries with new, sustainable materials. The technology can help optimize traffic management and vehicle routing. BMW, VW, Toyota, Hyundai, Daimler, and Ford are piloting (in partnership) quantum computing for select use cases. Though the proof-of-concept (Poc) for a smaller set of variables looked promising, the future plan will involve scaling up the infrastructure, qubits quality, and using complex sets of parameters. Identifying the right use case is critical before investing in quantum research. OEMs should partner with professional services experts that can help with problem identification through proof-of-concept development and eventually integration into day-to-day production processes. However, huge investment costs and existing pertinent technologies (to digitize the automotive value chain) are currently hindering quantum adoption among OEMs. Right use case identification, coupled with a hybrid quantum-classical computing model, will enable OEMs to achieve the best of both worlds. This analytics presents the overall scope of quantum computing and the current challenges hindering quantum momentum in the automotive industry. It analyzes OEM partnerships and key use cases. Author: Dorothy Amy
More Information
Deliverable Type Market Research
Author Dorothy Amy
Industries Automotive
No Index No
Is Prebook No
Keyword 1 Quantum Computing For Autonomous Vehicles
Keyword 2 Automotive Quantum Solutions
Keyword 3 Quantum Computing In Manufacturing
Podcast No
WIP Number PF30-01-00-00-00