2024-2028 年全球人工智慧品质成长机会

Global Quality AI Growth Opportunities, 2024-2028

出版日期: 2024年07月17日 | 出版商:

Frost & Sullivan | 英文 68 Pages | 商品交期: 最快1-2个工作天内

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简介目录

品质人工智慧可确保公司的生产力、效率、收入成长和成本效益

本研究检验了人工智慧 (AI) 在品管中日益增长的应用。人工智慧的快速发展导致其在品管的所有领域中得到应用，从预测品质分析和企业品管系统 (EQMS) 的成长中可以看出。随着竞争的加剧，主动避免品质问题而不是依赖被动方法变得至关重要。人工智慧驱动的预测品管工具可以在生产过程的早期预防品质问题，确保减少浪费并提高整体产品品质。机器学习 (ML)、自然语言处理 (NLP) 和 EQMS 解决方案中的高级分析等数位技术可推动用户采用，从而实现明智的业务决策、创新和提高生产力。不确定的投资收益(ROI) 和缺乏对这些技术的认识是挑战，但供应商现在透过强调越来越多的实际用例来应对。然而，如果无法取得干净、可靠的资料，人工智慧在品管方面的潜力就无法实现。因此，在开始人工智慧计划之前製定强大的资料策略对于成功至关重要。

本研究分析了促进和抑制人工智慧在品管中应用的因素。我们还重点介绍了主要用户案例并介绍了影响该领域的公司。基准年为2023年，预测期间为2024年至2028年。

This study examines the increasing use of artificial intelligence (AI) in quality management. The rapid advancement of AI has led to its use across sectors, particularly quality management, as is evident in the growth of predictive quality analytics and enterprise quality management systems (EQMS). With increasing competitive intensity, it has become essential to proactively avoid quality issues instead of relying on reactive approaches. AI-driven predictive quality management tools can preempt quality issues early in the production process, ensuring waste reduction and enhancing overall product quality. Digital technologies such as machine learning (ML), natural language processing (NLP), and advanced analytics in EQMS solutions drive user adoption and result in informed business decisions, innovation, and heightened productivity. While the unclear return on investment (RoI) and a lack of awareness about these technologies present challenges, vendors are now responding by highlighting the increasing number of practical use cases. However, the full potential of AI in quality management cannot be unlocked without access to clean, reliable data. Therefore, formulating a strong data strategy before embarking on AI projects will be imperative to success.

This study analyzes the factors driving and restraining the use of AI in quality management. It also highlights key user cases and profiles the companies impacting this space. The base year is 2023, and the forecast period is from 2024 to 2028.

Strategic Imperatives

Why is it Increasingly Difficult to Grow?
The Strategic Imperative 8™
The Impact of the Top 3 Strategic Imperatives on the Quality AI Industry
Growth Opportunities Fuel the Growth Pipeline Engine™

Ecosystem

AI in Quality-An Introduction

Growth Generator

Growth Drivers
Growth Restraints
AI in Quality-The Transition
AI Revolution in Quality Management

Growth Opportunities-AI in Predictive Quality

The Business Case for Predictive Quality
The Business Case for AI in Predictive Quality
AI in Predictive Quality (case study)
AI-enabled Systems and Machine Vision for Quality Control
Case Studies

Growth Opportunities-AI Use Cases

AI Use Cases and Manufacturing Value Chain
AI in Quality Control in Heavy Industries
Market Opportunity

Growth Opportunities-Autonomous AI

Autonomous AI Decisions

Growth Opportunities-Operationalizing AI and Data Strategy

Roadmap to Operationalize AI
Data Strategy in AI
Generative AI and Predictive AI

Growth Opportunities-Sustainability and ESG

Sustainability and ESG

Growth Opportunities-AI in EQMS

AI in EQMS
The Business Case for AI in EQMS
The Challenges for AI in EQMS
The Benefits of AI in EQMS
AI in EQMS-Application Areas
AI in Quality and Safety

AI in Quality-Companies to Action

Companies
AI in EQMS-ComplianceQuest
AI in EQMS-IQVIA
AI in EQMS-ETQ
AI in EQMS-Honeywell (Sparta Systems)

Growth Opportunity Universe

Growth Opportunity 1: Predictive Quality Management in EV Component Manufacturing
Growth Opportunity 2: Stricter Quality Control for the Aviation and Transportation Sectors
List of Exhibits
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