The global smart manufacturing market is projected to exhibit a significant growth, at a CAGR of around 12.8%, during the forecast period. The rising adoption of AI industrial robots is witnessed in developed countries and certainly seems to be predictable due to the rise in production demands. This includes continued adaptation to the proliferation of automation and IoT, increased resource efficiency, and need for safer and more simplified robotic technologies to work in collaboration with humans. According to IFR (International Federation of Robotics), around one million industrial robots are currently working in industrial units across the globe. Many global institutions and organizations have taken several initiatives for the adoption of AI in the manufacturing sector.

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The manufacturing industry incorporates substantial activities from the past few years, certainly aiming new advancements based on AI. This includes standardized schemes and establishment of ecosystems that engage both the IT and manufacturing industries together, along with the introduction of IIC (Industrial Internet Consortium) in the US, led by General Electric Co., and the introduction of government-led Industry 4.0 initiative in Germany. Several global companies are adopting autonomous decentralized systems to enhance production process. For instance, Hitachi, a Japanese multinational conglomerate, is working to offer numerous innovative manufacturing solutions to industries, based on the “symbiotic autonomous decentralization” model for forming new business and achieving overall optimization of activities by connecting different systems together.

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One of the other crucial elements of AI that is expected to gaining popularity and application in manufacturing control systems and pattern recognition is fuzzy logic or fuzzy models. The fuzzy logic was introduced in 1965 and is based on the mathematical theory of fuzzy sets, which is a generalization of the classical set theory. Tools based on fuzzy logic enable inclusion of imperfect information and uncertainties in decision making models, which makes them perfectly compatible for manufacturing decisions. A few instances are the automatic transmission of Lexus automobile, a washing machine that automatically adjusts the washing cycle for load size, fabric type and amount of dirt, and avoice-controlled helicopter that follows commands such as forward, up, left, right:hover, and land. This fuzzy logic is expected to offer growth opportunity to the global smart manufacturing market during the forecast period.

Global Smart Manufacturing Market-Segmentation

By Component

Hardware
Software & Services

By Technology

Programmable Logic Controller (PLC)
Supervisory Controller and Data Acquisition (SCADA)
Machine Vision
Distributed Control System (DCS)
Product Lifecycle Management (PLM)
Others (3D Printing)

By End-Use Industry

Healthcare
Automotive
Aerospace & Defense
Oil & Gas
Food & Beverages
Others (Metals and Mining)

Global Smart Manufacturing Market– Segment by Region

North America

United States
Canada

Europe

Germany
UK
France
Spain
Italy
Rest of Europe

Asia-Pacific

China
Japan
India
Rest of Asia-Pacific

Rest of the World

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