2024-2028 年全球人工智慧品質成長機會

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個工作天內

價格

簡介目錄

品質人工智慧可確保公司的生產力、效率、收入成長和成本效益

本研究檢驗了人工智慧 (AI) 在品管中日益成長的應用。人工智慧的快速發展導致其在品管的所有領域中得到應用，從預測品質分析和企業品管系統 (EQMS) 的成長中可以看出。隨著競爭的加劇，主動避免品質問題而不是依賴被動方法變得至關重要。人工智慧驅動的預測品管工具可以在生產過程的早期預防品質問題，確保減少浪費並提高整體產品品質。機器學習 (ML)、自然語言處理 (NLP) 和 EQMS 解決方案中的高級分析等數位技術可推動用戶採用，從而實現明智的業務決策、創新和提高生產力。不確定的投資收益(ROI) 和缺乏對這些技術的認知是挑戰，但供應商現在透過強調越來越多的實際用例來應對。然而，如果無法取得乾淨、可靠的資料，人工智慧在品管方面的潛力就無法實現。因此，在開始人工智慧計劃之前製定強大的資料策略對於成功至關重要。

本研究分析了促進和抑制人工智慧在品管中應用的因素。我們還重點介紹了主要用戶案例並介紹了影響該領域的公司。基準年為2023年，預測期間為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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