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 [https://www.transparencymarketresearch.com/ai-based-chemical-manufacturing-market.html] 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.
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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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