“Artificial Intelligence in the Manufacturing Market”
[270 Pages Report] The Artificial Intelligence in Manufacturing market size is expected to reach USD 16.3 billion by 2027, from USD 2.3 billion in 2022, growing at a CAGR of 47.9% from 2022 to 2027.
According to a research report “Artificial Intelligence in Manufacturing Market by Offer (Hardware, Software and Services), Industry, Application, Technology (Machine Learning, Natural Language Processing, Contextual Computing, Computer Vision) and Region – Global Forecast to 2027” published by MarketsandMarkets, the global Artificial Intelligence in Manufacturing market size is expected to grow from USD 2.3 billion in 2022 to USD 16.3 billion by 2027, and is expected to grow at a CAGR of 47.9% 2022 to 2027.
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Browse 195 market data tables and 58 figures spread over 270 pages and a detailed table of contents at “Artificial Intelligence in Manufacturing Market and Region – Global Forecast to 2027” View Detailed TOC Here – https://www.marketsandmarkets.com/Market-Reports/artificial-intelligence-manufacturing-market-72679105.html
Major factors contributing to the growth of artificial intelligence in manufacturing market include improved computational power of AI chipsets and increase in venture capital investment in manufacturing space. ‘IA. However, increasing venture capital investment in the AI manufacturing space is hampering the growth of artificial intelligence in the manufacturing market. The limited availability of skilled labour, especially in developing countries, represents a huge challenge for the industry. However, the growing focus on improving the operational efficiency of manufacturing plants is the biggest opportunity in the market, with Asia-Pacific having the highest market share and CAGR for the forecast period. .
Development of sophisticated hardware and software sensors to drive the growth of context-aware computing segment
By using context awareness technology, a control system called Manufacturing Execution System (MES) is designed to manage and monitor the work in a factory, which is based on the dynamic and complex production process in the manufacturing plant. The context-aware architecture further establishes the dynamic interaction properties of the system and guides the tasks of specifying and abstracting objects in machine language. This technology provides computing environments with the ability to learn and adopt context by sensing through different sensors and automatically provides feedback to the user. This service makes the operator attentive, reactive and predictive. In the manufacturing plant, the production quantity fluctuates depending on many uncertain factors, including internal and external factors such as random orders, sudden equipment failure, supply change, and restriction of the execution time. Context-aware technology finds custom solutions and organizes machines accordingly for the problems mentioned above. Siemens (Germany) and General Motors (USA) are using context awareness technology in their factories. Additionally, the distribution of contextual information can provide substantial value to industries. It provides task-relevant information or services to users in a manufacturing shop, improving decision-making through contextual recommendations.
Asia-Pacific shows the highest CAGR during the forecast period
APAC is likely to be the largest contributor in terms of market size and growth rate in the overall AI in manufacturing market over the forecast period. This APAC market is divided into China, Japan, South Korea, India, and Rest of APAC (RoAPAC). RoAPAC includes Singapore, Malaysia, Thailand, Australia and New Zealand. Among all APAC countries, China held the largest share of AI in the manufacturing market in 2021.
APAC, led by China, Japan and South Korea, is considered the largest market for industrial robots. Industrial robots generate a huge amount of data. This data is used in deep learning algorithms to further train the robots. This would act as one of the major drivers for AI in the manufacturing market in APAC. APAC is also considered to have the largest number of manufacturing plants in the world. There are some dark factories in China, where only robots operate without any human intervention. Implementing AI can make robots smarter, reduce machine downtime and increase productivity.
Advancements in Deep Learning and Supervised Learning Industry to Drive Growth of AI in Machine Learning Manufacturing Market
Machine learning (ML) allows systems to automatically improve their performance with experience. ML helps develop a computer program/algorithm that can access data and use it to train without human intervention. ML is adopted to process large volumes of data. Time previously spent analyzing charts and spreadsheets is now being used to find smart ways to automate data analysis. ML includes various technologies, such as deep learning, supervised learning, unsupervised learning, and reinforcement learning.
Extensive use of big data in production planning to fuel market growth
Production planning is a process that combines and transforms various resources used in the production system of a manufacturing plant. The AI system performs the interrelated operational activities involved in the manufacturing processes. The deep learning based algorithm uses many functions such as Program Evaluation Review Technique (PERT)/Critical Path Method (CPM) to optimize production scheduling under various conditions. The use of AI in production planning leads to the standardization of the sequence of products and processes, dedicated machines for special purposes having higher production capacities and production rates, faster short production cycle, perfectly balanced production lines, faster material flow and easy material handling.
Key Players Operating in Artificial Intelligence in Manufacturing Market NVIDIA (US), IBM (US), Intel (US), Siemens (Germany), General Electric (US), Google (United States), Microsoft Corporation (United States) and Micron Technology (United States). The players in this market have adopted various strategies to expand their global presence and increase their market shares.
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