Continuous advancements in machine learning algorithms and
big data analytics empower chemical manufacturers to extract
valuable insights from large datasets. This capability
enhances decision-making processes and supports innovative product
development.
WILMINGTON, Del., July 10, 2024 /PRNewswire/ -- The AI-based
chemical manufacturing market was projected to attain
US$ 2.4 billion in 2023. It is
likely to garner a 28.8% CAGR from 2024 to 2034, and by
2034, the market is expected to attain US$ 37.6 billion. AI plays a crucial role in
ensuring safety and regulatory compliance within chemical
manufacturing processes. AI-powered systems can detect anomalies,
predict potential hazards, and maintain strict adherence to
environmental and safety standards.
Digital twin technology, which creates virtual models of
physical assets or processes, is increasingly applied in chemical
manufacturing. AI-driven digital twins simulate operations, predict
outcomes, and optimize performance, contributing to enhanced
productivity and reduced downtime.
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AI-based Chemical Manufacturing Report Scope:
Report
Coverage
|
Details
|
Forecast
Period
|
2024-2034
|
Base
Year
|
2020–2022
|
Size in
2023
|
US$ 2.4 Bn
|
Forecast (Value) in
2032
|
US$ 37.6 Bn
|
Growth Rate
(CAGR)
|
28.8 %
|
No. of
Pages
|
389
Pages
|
Segments
covered
|
By AI Technology, By
Application, By End-use
|
The following companies are well known participants in the
AI-based chemical manufacturing market:
- Google DeepMind
- Siemens AG
- BASF SE
- IBM Corporation
- Cognex Corporation
- Honeywell International Inc.
- Emerson Electric Co.
- Rockwell Automation, Inc.
- Mitsubishi Electric Corporation
- ABB
Integration of AI with Internet of Things (IoT) devices under
Industry 4.0 initiatives enhances connectivity and data exchange
across manufacturing operations. This connectivity enables
real-time monitoring, predictive maintenance, and improved
operational efficiency. Increased investments in research and
development aimed at AI applications in chemical manufacturing are
driving innovation and the development of new technologies,
processes, and products.
AI-powered predictive maintenance algorithms help in reducing
downtime by forecasting equipment failures before they occur, thus
optimizing asset reliability and improving overall operational
efficiency. AI enables real-time monitoring and analysis of
production processes, helping to maintain consistent product
quality and ensure adherence to stringent quality standards.
Integration of AR and VR with AI enhances training, maintenance,
and troubleshooting processes within chemical manufacturing
facilities, improving workforce productivity and reducing training
time.
Key Findings of the Market Report
- Blockchain applications in supply chain management can enhance
transparency, traceability, and security across the chemical
manufacturing value chain, ensuring compliance with regulations and
reducing the risk of counterfeit products.
- AI-powered collaborative robots work alongside human operators
in tasks such as handling hazardous materials, assembly, and
packaging, enhancing workplace safety and productivity.
- Accelerated adoption of digital transformation strategies by
chemical manufacturers, leveraging AI, cloud computing, and big
data analytics to streamline operations and drive innovation.
- With increased connectivity and digitization, there is a
heightened focus on cybersecurity measures to protect sensitive
data, intellectual property, and operational technologies from
cyber threats.
Market Trends for AI-based Chemical Manufacturing
- By AI technology, the machine learning segment is expected to
boost the growth of the AI-based chemical manufacturing
market.
- Machine learning algorithms analyze large volumes of process
data to optimize manufacturing processes, improve efficiency, and
reduce operational costs.
- Machine learning models predict equipment failures and
maintenance needs, minimizing downtime and enhancing asset
reliability.
- Machine learning enables real-time monitoring and analysis of
production variables, ensuring consistent product quality and
compliance with quality standards.
- Machine learning facilitates rapid prototyping and iterative
design processes, accelerating the development of new products with
enhanced properties.
- On the basis of application, the process optimization segment
is anticipated to augment the market growth.
- AI-driven process optimization algorithms analyze real-time
data to identify inefficiencies, streamline operations, and reduce
production costs.
Global Market for AI-based Chemical Manufacturing: Regional
Outlook
North America
- North America, particularly
the United States, is at the
forefront of technological innovation, with significant investments
in AI, machine learning, and data analytics. These advancements
drive the adoption of AI in chemical manufacturing for process
optimization, predictive maintenance, and product innovation.
- Continued investments in research and development foster
innovation in AI technologies tailored for chemical manufacturing
applications. Academic institutions, research centers, and industry
collaborations contribute to the development of cutting-edge AI
solutions.
Asia Pacific
- Industry 4.0 initiatives and digital transformation strategies
are gaining momentum across Asia
Pacific. AI, IoT, and big data analytics are integrated into
manufacturing operations to improve efficiency, agility, and
decision-making capabilities.
- Asia Pacific countries are
investing in developing a skilled workforce proficient in AI and
digital technologies. Training programs and partnerships between
academia and industry support the adoption and utilization of AI in
chemical manufacturing.
AI-based Chemical Manufacturing Market: Key Players
The AI-based chemical manufacturing market is characterized by a
diverse ecosystem of players, each contributing unique capabilities
and expertise to drive innovation, efficiency, and sustainability
in the chemical industry. The competitive landscape continues to
evolve as companies seek to leverage AI to address complex
challenges and capitalize on emerging opportunities in the global
market.
Key Developments
- In 2024, Cognex Corporation introduced the In-Sight®
L38 3D Vision System, integrating AI alongside 2D and 3D vision
technologies to address diverse inspection and measurement
needs.
- In 2023, IBM launched the IBM Storage Scale System 6000, a
cloud-scale global data platform tailored to address the growing
demands of data-intensive workloads and AI applications. This marks
the latest addition to IBM's Storage for Data and AI
portfolio.
AI-based Chemical Manufacturing Market Segmentation
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
- Latin America
- Europe
- Asia Pacific
- Middle East & Africa
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