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市场调查报告书
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1525343

全球基于人工智慧的化学製造市场研究（按人工智慧技术按应用、最终用途产业和区域预测 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个工作天内

价格
简介目录

2023年全球以人工智慧为基础的化学品製造市场价值约为24.6亿美元，预计在2024年至2032年的预测期内将实现28.87%的显着年复合成长率（CAGR）。製造利用人工智慧优化和创新化学工业的製程。透过整合人工智慧，製造商可以提高化学品生产的效率、精度和安全性。人工智慧演算法分析生产各阶段的大量资料，以预测结果、优化反应条件并提高产量。该技术还可以在潜在问题出现之前识别它们，从而减少停机时间和维护成本。此外，人工智慧透过模拟分子相互作用并预测其特性来帮助发现新材料和化学品，从而显着加快研发过程。

全球基于人工智慧的化学品製造市场受到对先进製造流程开发的日益关注的推动，这极大地推动了基于人工智慧的化学品製造市场的动态。人工智慧技术利用机器学习（ML）演算法，能够预测化学品的特性和行为，从而增强製造流程并加快化学领域优化解决方案的开发。此外，针对基于人工智慧的化学基础模型的资金激增进一步推动基于人工智慧的化学製造业的进步。这些基础模型擅长解决化学製造中的各种复杂问题，进而促进产业成长。然而，高昂的初始投资成本、技术复杂性和整合问题将阻碍 2024-2032 年预测期内市场的整体需求。

全球基于人工智慧的化学製造市场研究考虑的关键区域包括亚太地区、北美、欧洲、拉丁美洲和世界其他地区。 2023年，北美主导市场，占最大份额。这种主导地位归因于该地区各行业较早采用人工智慧。陶氏化学公司等许多化学公司正在利用机器学习和预测分析来开发适合个人客户需求的客製化聚氨酯产品。此外，化学产业研究活动的快速成长正在提升北美的市场份额，而人工智慧在加速流程和产品开发阶段之间的创新方面发挥着至关重要的作用。此外，预计亚太地区的市场在 2024 年至 2032 年的预测期内将以最快的速度发展。

目录

第 1 章：全球基于人工智慧的化学品製造市场执行摘要

  • 全球以人工智慧为基础的化学品製造市场规模及预测（2022-2032）
  • 区域概要
  • 分部摘要
    • 透过人工智慧技术
    • 按申请
    • 按最终用途行业
  • 主要趋势
  • 经济衰退的影响
  • 分析师推荐与结论

第 2 章：全球基于人工智慧的化学製造市场定义和研究假设

  • 研究目的
  • 市场定义
  • 研究假设
    • 包含与排除
    • 限制
    • 供给侧分析
      • 可用性
      • 基础设施
      • 监管环境
      • 市场竞争
      • 经济可行性（消费者的角度）
    • 需求面分析
      • 监理框架
      • 技术进步
      • 环境考虑
      • 消费者意识和接受度
  • 估算方法
  • 研究考虑的年份
  • 货币兑换率

第 3 章：全球基于人工智慧的化学品製造市场动态

  • 市场驱动因素
    • 日益关注先进製造流程的开发
    • 基于人工智慧的化学基础模型的资金激增
  • 市场挑战
    • 初始投资成本高
    • 技术复杂性和整合问题
  • 市场机会
    • 新兴市场的扩张
    • 人工智慧技术的进步

第 4 章：全球基于人工智慧的化学製造市场产业分析

  • 波特的五力模型
    • 供应商的议价能力
    • 买家的议价能力
    • 新进入者的威胁
    • 替代品的威胁
    • 竞争竞争
    • 波特五力模型的未来方法
    • 波特的五力影响分析
  • PESTEL分析
    • 政治的
    • 经济
    • 社会的
    • 技术性
    • 环境的
    • 合法的
  • 顶级投资机会
  • 最佳制胜策略
  • 颠覆性趋势
  • 产业专家视角
  • 分析师推荐与结论

第 5 章：全球基于人工智慧的化学製造市场规模与预测：按人工智慧技术 - 2022-2032

  • 细分仪表板
  • 全球基于人工智慧的化学製造市场：2022年和2032年人工智慧技术收入趋势分析
    • 机器学习
    • 深度学习
    • 自然语言处理
    • 预测分析
    • 最佳化演算法
    • 监理合规软体
    • 其他的

第 6 章：全球基于人工智慧的化学製造市场规模与预测：按应用分类 - 2022-2032

  • 细分仪表板
  • 全球基于人工智慧的化学製造市场：2022 年和 2032 年应用收入趋势分析
    • 流程优化
    • 产品开发
    • 品质管制
    • 供应链管理
    • 安全和法规合规性

第 7 章：全球基于人工智慧的化学製造市场规模和预测：按最终用途产业 - 2022-2032

  • 细分仪表板
  • 全球基于人工智慧的化学品製造市场：2022 年和 2032 年最终用途产业收入趋势分析
    • 药品
    • 特种化学品
    • 石化产品
    • 农业化学品
    • 聚合物和塑料
    • 其他的

第 8 章：全球基于人工智慧的化学製造市场规模与预测：按地区 - 2022-2032

  • 北美洲
    • 我们
    • 加拿大
  • 欧洲
    • 英国
    • 德国
    • 法国
    • 西班牙
    • 义大利
    • 欧洲其他地区
  • 亚太
    • 中国
    • 印度
    • 日本
    • 澳洲
    • 韩国
    • 亚太地区其他地区
  • 拉丁美洲
    • 巴西
    • 墨西哥
    • 拉丁美洲其他地区
  • 中东和非洲
    • 沙乌地阿拉伯
    • 南非
    • 中东和非洲其他地区

第 9 章：竞争情报

  • 重点企业SWOT分析
  • 顶级市场策略
  • 公司简介
    • IBM Corporation
      • 关键讯息
      • 概述
      • 财务（视数据可用性而定）
      • 产品概要
      • 市场策略
    • Cognex Corporation
    • Honeywell International Inc.
    • Emerson Electric Co.
    • Rockwell Automation, Inc.
    • Mitsubishi Electric Corporation
    • ABB
    • Google DeepMind
    • Siemens AG
    • BASF SE

第 10 章：研究过程

  • 研究过程
    • 资料探勘
    • 分析
    • 市场预测
    • 验证
    • 出版
  • 研究属性
简介目录

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