查看購物車
  • Simplified Chinese
  • English
  • Japanese
  • Korean
封面
市場調查報告書
商品編碼
1525343

全球基於人工智慧的化學製造市場研究（按人工智慧技術按應用、最終用途產業和區域預測 2022-2032）

Global AI-based Chemical Manufacturing Market Study by AI Technology By Application, By End-use Industry and Regional Forecasts 2022-2032
出版日期: | 出版商: Bizwit Research & Consulting LLP | 英文 285 Pages | 商品交期: 2-3個工作天內

價格
簡介目錄

2023年全球以人工智慧為基礎的化學品製造市場價值約為24.6億美元，預計在2024年至2032年的預測期內將實現28.87%的顯著年複合成長率（CAGR）。製造利用人工智慧最佳化和創新化學工業的製程。透過整合人工智慧，製造商可以提高化學品生產的效率、精度和安全性。人工智慧演算法分析生產各階段的大量資料，以預測結果、最佳化反應條件並提高產量。該技術還可以在潛在問題出現之前識別它們，從而減少停機時間和維護成本。此外，人工智慧透過模擬分子相互作用並預測其特性來幫助發現新材料和化學品，從而顯著加快研發過程。

全球基於人工智慧的化學品製造市場受到對先進製造流程開發的日益關注的推動，這極大地推動了基於人工智慧的化學品製造市場的動態。人工智慧技術利用機器學習（ML）演算法，能夠預測化學品的特性和行為，從而增強製造流程並加快化學領域最佳化解決方案的開發。此外，針對基於人工智慧的化學基礎模型的資金激增進一步推動基於人工智慧的化學製造業的進步。這些基礎模型擅長解決化學製造中的各種複雜問題，進而促進產業成長。然而，高昂的初始投資成本、技術複雜性和整合問題將阻礙 2024-2032 年預測期內市場的整體需求。

全球基於人工智慧的化學製造市場研究涵蓋的關鍵區域包括亞太地區、北美、歐洲、拉丁美洲和世界其他地區。 2023年，北美主導市場，佔最大佔有率。這種主導地位歸因於該地區各行業較早採用人工智慧。陶氏化學公司等許多化學公司正在利用機器學習和預測分析來開發適合個人客戶需求的客製化聚氨酯產品。此外，化學產業研究活動的快速成長正在提升北美的市場佔有率，而人工智慧在加速流程和產品開發階段之間的創新方面發揮著至關重要的作用。此外，預計亞太地區的市場在 2024 年至 2032 年的預測期內將以最快的速度發展。

目錄

第 1 章：全球基於人工智慧的化學品製造市場執行摘要

  • 全球以人工智慧為基礎的化學品製造市場規模及預測（2022-2032）
  • 區域概要
  • 分部摘要
    • 透過人工智慧技術
    • 按申請
    • 按最終用途行業
  • 主要趨勢
  • 經濟衰退的影響
  • 分析師推薦與結論

第 2 章：全球基於人工智慧的化學製造市場定義和研究假設

  • 研究目的
  • 市場定義
  • 研究假設
    • 包含與排除
    • 限制
    • 供給側分析
      • 可用性
      • 基礎設施
      • 監管環境
      • 市場競爭
      • 經濟可行性（消費者的角度）
    • 需求面分析
      • 監理框架
      • 技術進步
      • 環境考慮
      • 消費者意識和接受度
  • 估算方法
  • 研究涵蓋的年份
  • 貨幣兌換率

第 3 章：全球基於人工智慧的化學品製造市場動態

  • 市場促進因素
    • 日益關注先進製造流程的開發
    • 基於人工智慧的化學基礎模型的資金激增
  • 市場挑戰
    • 初始投資成本高
    • 技術複雜性和整合問題
  • 市場機會
    • 新興市場的擴張
    • 人工智慧技術的進步

第 4 章：全球基於人工智慧的化學製造市場產業分析

  • 波特的五力模型
    • 供應商的議價能力
    • 買家的議價能力
    • 新進入者的威脅
    • 替代品的威脅
    • 競爭競爭
    • 波特五力模型的未來方法
    • 波特的五力影響分析
  • PESTEL分析
    • 政治的
    • 經濟
    • 社會的
    • 技術性
    • 環境的
    • 合法的
  • 頂級投資機會
  • 最佳制勝策略
  • 顛覆性趨勢
  • 產業專家視角
  • 分析師推薦與結論

第 5 章：全球基於人工智慧的化學製造市場規模與預測：按人工智慧技術 - 2022-2032

  • 細分儀表板
  • 全球基於人工智慧的化學製造市場：2022年和2032年人工智慧技術收入趨勢分析
    • 機器學習
    • 深度學習
    • 自然語言處理
    • 預測分析
    • 最佳化演算法
    • 監理合規軟體
    • 其他

第 6 章：全球基於人工智慧的化學製造市場規模與預測：按應用分類 - 2022-2032

  • 細分儀表板
  • 全球基於人工智慧的化學製造市場：2022 年和 2032 年應用收入趨勢分析
    • 流程最佳化
    • 產品開發
    • 品質管制
    • 供應鏈管理
    • 安全和法規合規性

第 7 章：全球基於人工智慧的化學製造市場規模和預測：按最終用途產業 - 2022-2032

  • 細分儀表板
  • 全球基於人工智慧的化學品製造市場：2022 年和 2032 年最終用途產業收入趨勢分析
    • 藥品
    • 特種化學品
    • 石化產品
    • 農業化學品
    • 聚合物和塑膠
    • 其他

第 8 章：全球基於人工智慧的化學製造市場規模與預測：按地區 - 2022-2032

  • 北美洲
    • 美國
    • 加拿大
  • 歐洲
    • 英國
    • 德國
    • 法國
    • 西班牙
    • 義大利
    • 歐洲其他地區
  • 亞太
    • 中國
    • 印度
    • 日本
    • 澳洲
    • 韓國
    • 亞太地區其他地區
  • 拉丁美洲
    • 巴西
    • 墨西哥
    • 拉丁美洲其他地區
  • 中東和非洲
    • 沙烏地阿拉伯
    • 南非
    • 中東和非洲其他地區

第 9 章：競爭情報

  • 重點企業SWOT分析
  • 頂級市場策略
  • 公司簡介
    • IBM Corporation
      • 關鍵訊息
      • 概述
      • 財務（視數據可用性而定）
      • 產品概要
      • 市場策略
    • Cognex Corporation
    • Honeywell International Inc.
    • Emerson Electric Co.
    • Rockwell Automation, Inc.
    • Mitsubishi Electric Corporation
    • ABB
    • Google DeepMind
    • Siemens AG
    • BASF SE

第 10 章：研究過程

  • 研究過程
    • 資料探勘
    • 分析
    • 市場預測
    • 驗證
    • 出版
  • 研究屬性
簡介目錄

Global AI-based Chemical Manufacturing Market was valued at approximately USD 2.46 billion in 2023 and is projected to achieve a remarkable compound annual growth rate (CAGR) of 28.87% over the forecast period from 2024 to 2032. AI-based chemical manufacturing leverages artificial intelligence to optimize and innovate processes in the chemical industry. By integrating AI, manufacturers can enhance the efficiency, precision, and safety of chemical production. AI algorithms analyze vast amounts of data from various stages of production to predict outcomes, optimize reaction conditions, and improve yield. This technology can also identify potential issues before they arise, reducing downtime and maintenance costs. Additionally, AI aids in the discovery of new materials and chemicals by simulating molecular interactions and predicting their properties, significantly accelerating the research and development process.

The Global AI-based Chemical Manufacturing Market is driven by increasing focus on the development of advanced manufacturing processes is significantly driving the dynamics of the AI-based chemical manufacturing market. AI technology, leveraging Machine Learning (ML) algorithms, has the capability to predict the properties and behaviors of chemicals, thereby enhancing manufacturing processes and expediting the development of optimized solutions in the chemical sector. Moreover, surge in funding directed toward AI-based chemistry foundation models is further propelling the advancement of the AI-based chemical manufacturing industry. These foundation models are adept at addressing a wide array of complex issues in chemical manufacturing, thus boosting industry growth. However, high initial investment costs and technical complexity and integration issues is going to impede the overall demand for the market during the forecast period 2024-2032.

The key regions considered for the Global AI-based Chemical Manufacturing Market study includes Asia Pacific, North America, Europe, Latin America, and Rest of the World. In 2023, North America dominated the market holding the largest share. This dominance is attributed to the early adoption of AI across various industries within the region. Numerous chemical companies, such as Dow, are employing ML and predictive analytics to develop customized polyurethane products tailored to individual customer needs. Additionally, the rapid growth in research activities within the chemical sector is bolstering the market share in North America, with AI playing a crucial role in accelerating innovation between process and product development stages. Furthermore, the market in Asia Pacific is anticipated to develop at the fastest rate over the forecast period 2024-2032.

Major market players included in this report are:

  • IBM Corporation
  • Cognex Corporation
  • Honeywell International Inc.
  • Emerson Electric Co.
  • Rockwell Automation, Inc.
  • Mitsubishi Electric Corporation
  • ABB
  • Google DeepMind
  • Siemens AG
  • BASF SE

The detailed segments and sub-segment of the market are explained below:

By AI Technology

  • Machine Learning
  • Deep Learning
  • Natural Language Processing
  • Predictive Analytics
  • Optimization Algorithm
  • Regulatory Compliance Software
  • Others

By Application

  • Process Optimization
  • Product Development
  • Quality Control
  • Supply Chain Management
  • Safety and Regulatory Compliance

By End-use Industry

  • Pharmaceuticals
  • Specialty Chemicals
  • Petrochemicals
  • Agrochemicals
  • Polymers and Plastics
  • Others

By Region:

  • North America
  • U.S.
  • Canada
  • Europe
  • UK
  • Germany
  • France
  • Spain
  • Italy
  • ROE
  • Asia Pacific
  • China
  • India
  • Japan
  • Australia
  • South Korea
  • RoAPAC
  • Latin America
  • Brazil
  • Mexico
  • Middle East & Africa
  • Saudi Arabia
  • South Africa
  • RoMEA

Years considered for the study are as follows:

  • Historical year - 2022
  • Base year - 2023
  • Forecast period - 2024 to 2032

Key Takeaways:

  • Market Estimates & Forecast for 10 years from 2022 to 2032.
  • Annualized revenues and regional level analysis for each market segment.
  • Detailed analysis of geographical landscape with Country level analysis of major regions.
  • Competitive landscape with information on major players in the market.
  • Analysis of key business strategies and recommendations on future market approach.
  • Analysis of competitive structure of the market.
  • Demand side and supply side analysis of the market

Table of Contents

Chapter 1. Global AI-based Chemical Manufacturing Market Executive Summary

  • 1.1. Global AI-based Chemical Manufacturing Market Size & Forecast (2022- 2032)
  • 1.2. Regional Summary
  • 1.3. Segmental Summary
    • 1.3.1. By AI Technology
    • 1.3.2. By Application
    • 1.3.3. By End-use Industry
  • 1.4. Key Trends
  • 1.5. Recession Impact
  • 1.6. Analyst Recommendation & Conclusion

Chapter 2. Global AI-based Chemical Manufacturing Market Definition and Research Assumptions

  • 2.1. Research Objective
  • 2.2. Market Definition
  • 2.3. Research Assumptions
    • 2.3.1. Inclusion & Exclusion
    • 2.3.2. Limitations
    • 2.3.3. Supply Side Analysis
      • 2.3.3.1. Availability
      • 2.3.3.2. Infrastructure
      • 2.3.3.3. Regulatory Environment
      • 2.3.3.4. Market Competition
      • 2.3.3.5. Economic Viability (Consumer's Perspective)
    • 2.3.4. Demand Side Analysis
      • 2.3.4.1. Regulatory frameworks
      • 2.3.4.2. Technological Advancements
      • 2.3.4.3. Environmental Considerations
      • 2.3.4.4. Consumer Awareness & Acceptance
  • 2.4. Estimation Methodology
  • 2.5. Years Considered for the Study
  • 2.6. Currency Conversion Rates

Chapter 3. Global AI-based Chemical Manufacturing Market Dynamics

  • 3.1. Market Drivers
    • 3.1.1. Rise in Focus on Development of Advanced Manufacturing Processes
    • 3.1.2. Surge in Funding for AI-based Chemistry Foundation Models
  • 3.2. Market Challenges
    • 3.2.1. High Initial Investment Costs
    • 3.2.2. Technical Complexity and Integration Issues
  • 3.3. Market Opportunities
    • 3.3.1. Expansion in Emerging Markets
    • 3.3.2. Advances in AI Technology

Chapter 4. Global AI-based Chemical Manufacturing Market Industry Analysis

  • 4.1. Porter's 5 Force Model
    • 4.1.1. Bargaining Power of Suppliers
    • 4.1.2. Bargaining Power of Buyers
    • 4.1.3. Threat of New Entrants
    • 4.1.4. Threat of Substitutes
    • 4.1.5. Competitive Rivalry
    • 4.1.6. Futuristic Approach to Porter's 5 Force Model
    • 4.1.7. Porter's 5 Force Impact Analysis
  • 4.2. PESTEL Analysis
    • 4.2.1. Political
    • 4.2.2. Economical
    • 4.2.3. Social
    • 4.2.4. Technological
    • 4.2.5. Environmental
    • 4.2.6. Legal
  • 4.3. Top investment opportunity
  • 4.4. Top winning strategies
  • 4.5. Disruptive Trends
  • 4.6. Industry Expert Perspective
  • 4.7. Analyst Recommendation & Conclusion

Chapter 5. Global AI-based Chemical Manufacturing Market Size & Forecasts by AI Technology 2022-2032

  • 5.1. Segment Dashboard
  • 5.2. Global AI-based Chemical Manufacturing Market: AI Technology Revenue Trend Analysis, 2022 & 2032 (USD Billion)
    • 5.2.1. Machine Learning
    • 5.2.2. Deep Learning
    • 5.2.3. Natural Language Processing
    • 5.2.4. Predictive Analytics
    • 5.2.5. Optimization Algorithm
    • 5.2.6. Regulatory Compliance Software
    • 5.2.7. Others

Chapter 6. Global AI-based Chemical Manufacturing Market Size & Forecasts by Application 2022-2032

  • 6.1. Segment Dashboard
  • 6.2. Global AI-based Chemical Manufacturing Market: Application Revenue Trend Analysis, 2022 & 2032 (USD Billion)
    • 6.2.1. Process Optimization
    • 6.2.2. Product Development
    • 6.2.3. Quality Control
    • 6.2.4. Supply Chain Management
    • 6.2.5. Safety and Regulatory Compliance

Chapter 7. Global AI-based Chemical Manufacturing Market Size & Forecasts by End-use Industry 2022-2032

  • 7.1. Segment Dashboard
  • 7.2. Global AI-based Chemical Manufacturing Market: End-use Industry Revenue Trend Analysis, 2022 & 2032 (USD Billion)
    • 7.2.1. Pharmaceuticals
    • 7.2.2. Specialty Chemicals
    • 7.2.3. Petrochemicals
    • 7.2.4. Agrochemicals
    • 7.2.5. Polymers and Plastics
    • 7.2.6. Others

Chapter 8. Global AI-based Chemical Manufacturing Market Size & Forecasts by Region 2022-2032

  • 8.1. North America AI-based Chemical Manufacturing Market
    • 8.1.1. U.S. AI-based Chemical Manufacturing Market
      • 8.1.1.1. AI Technology breakdown size & forecasts, 2022-2032
      • 8.1.1.2. Application breakdown size & forecasts, 2022-2032
    • 8.1.2. Canada AI-based Chemical Manufacturing Market
  • 8.2. Europe AI-based Chemical Manufacturing Market
    • 8.2.1. UK AI-based Chemical Manufacturing Market
    • 8.2.2. Germany AI-based Chemical Manufacturing Market
    • 8.2.3. France AI-based Chemical Manufacturing Market
    • 8.2.4. Spain AI-based Chemical Manufacturing Market
    • 8.2.5. Italy AI-based Chemical Manufacturing Market
    • 8.2.6. Rest of Europe AI-based Chemical Manufacturing Market
  • 8.3. Asia-Pacific AI-based Chemical Manufacturing Market
    • 8.3.1. China AI-based Chemical Manufacturing Market
    • 8.3.2. India AI-based Chemical Manufacturing Market
    • 8.3.3. Japan AI-based Chemical Manufacturing Market
    • 8.3.4. Australia AI-based Chemical Manufacturing Market
    • 8.3.5. South Korea AI-based Chemical Manufacturing Market
    • 8.3.6. Rest of Asia Pacific AI-based Chemical Manufacturing Market
  • 8.4. Latin America AI-based Chemical Manufacturing Market
    • 8.4.1. Brazil AI-based Chemical Manufacturing Market
    • 8.4.2. Mexico AI-based Chemical Manufacturing Market
    • 8.4.3. Rest of Latin America AI-based Chemical Manufacturing Market
  • 8.5. Middle East & Africa AI-based Chemical Manufacturing Market
    • 8.5.1. Saudi Arabia AI-based Chemical Manufacturing Market
    • 8.5.2. South Africa AI-based Chemical Manufacturing Market
    • 8.5.3. Rest of Middle East & Africa AI-based Chemical Manufacturing Market

Chapter 9. Competitive Intelligence

  • 9.1. Key Company SWOT Analysis
  • 9.2. Top Market Strategies
  • 9.3. Company Profiles
    • 9.3.1. IBM Corporation
      • 9.3.1.1. Key Information
      • 9.3.1.2. Overview
      • 9.3.1.3. Financial (Subject to Data Availability)
      • 9.3.1.4. Product Summary
      • 9.3.1.5. Market Strategies
    • 9.3.2. Cognex Corporation
    • 9.3.3. Honeywell International Inc.
    • 9.3.4. Emerson Electric Co.
    • 9.3.5. Rockwell Automation, Inc.
    • 9.3.6. Mitsubishi Electric Corporation
    • 9.3.7. ABB
    • 9.3.8. Google DeepMind
    • 9.3.9. Siemens AG
    • 9.3.10. BASF SE

Chapter 10. Research Process

  • 10.1. Research Process
    • 10.1.1. Data Mining
    • 10.1.2. Analysis
    • 10.1.3. Market Estimation
    • 10.1.4. Validation
    • 10.1.5. Publishing
  • 10.2. Research Attributes