AI in Manufacturing Market Business Opportunities, Latest Innovations, Top Players and Forecast | COVID-19 Effects

Artificial Intelligence (AI) in Manufacturing Market: by Component (Software, Service, Hardware (Network, Processor (ASIC, FPGA, GPU)), by Technology (Deep Learning, NLP), by Application (Robot, Quality Control), by Vertical (Automobile, Pharmaceutical)

Artificial intelligence has transformed the way people operate, and there is no doubt about this. Right from Netflix recommendations, advertising to healthcare, AI enhances people’s daily lives directly by offering a customized, efficient, and fast experience. Not only this, artificial intelligence appears to be the answer, as well as promises to revolutionize the manufacturing sector. AI is an amazing present. With constant shifts in consumer expectations and needs, most industries rely on AI to increase efficiency to better cater to customer demands. AI in Manufacturing Industry is estimated to reach USD 14.77 billion by 2024 at a 47.09% CAGR during the forecast period 2019–2024. 

Pivotal Role of AI in the Manufacturing Sector 

AI in Manufacturing Industry is widely used in different sectors for the following reasons,

Round the Clock Production- Human beings being biological organisms, need regular maintenance such as sleep and food. For production facilities to continue working 24/7, it is essential to introduce shifts, utilizing three workers every 24 hours. On the contrary, robots neither feel hungry nor get tired and can work 24/7. This, in turn, expands the production capabilities that are essential to cater to the needs of the customers worldwide. Besides, robots are highly efficient in most areas like the assembly line and the packing picking departments. The best part, robots can help to cut down turn-round times in most parts of business operations.

Quality Control- Artificial intelligence is immensely useful to perform predictive maintenance on equipment and machinery. Using sensors for operating conditions and tracking performance, machines can learn to predict failures and malfunctions and take action to remedy these before they occur. It will, in turn, lead to faster feedback, assisting companies in eradicating unplanned downtimes. A sensor can also help in detecting microscopic defects, scan the same at resolutions beyond human vision, thus enhancing productivity and increasing the number of goods that pass quality control. Artificial intelligence helps in speeding up most routine processes and improving accuracy to a great extent. This will prevent the need for in-process inspection and quality control by human beings that is often fallible and time-consuming.

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Safety- Humans are fallible and susceptible to making errors, particularly when they are distracted or tired. Accidents and errors occur in the factory, processing environment, or construction area, a tendency that can be eradicated by robotic assistance and AI. Remote access control indicates cutting down human resources, particularly when the work needs superhuman effort or is dangerous. Regular working environments too will reduce industrial accidents and result in an improvement in safety overall. Further, higher advanced sensory equipment integrated with the IIoT devices helps make the installation of barriers and safety guards a more effective and simpler measure for protecting human lives.

Optimize Supply Change- When artificial intelligence is used in the supply chain, there is increased data and transparency. It is used for improving customer service and manufacturing processes. Data from several devices are gathered and analyzed in real-time for an in-depth insight such as a possible challenge. The manufacturer then can take informed industry-related decisions. Artificial intelligence helps minimize time and cost that may be invested in shipping and warehousing during a mishap. AI solutions and tools can help schedule factory activities, supply and demand gaps, and avoid under or over production.

Improved Generative-Design Process- Through AI, manufacturers can make improved means to design their products. The designer with generative designs can easily input product details. These details comprise the material type, time, budget, and appropriate production methods. The designer can also input every possible constraint. The details using an artificial intelligence algorithm can be processed for meeting a list of probable product options. An appropriate solution will then be tested to suffice manufacturing conditions. A key factor that makes the generative design have the upper hand is it eliminates the human bias design option. It also proposes more ideal performance demands.

Real-time Monitoring- This is a key perk of AI in manufacturing because it offers a detailed picture of inefficiencies that are taking place in the manufacturing process and what causes the bottleneck. The capability to pinpoint the exact process that needs improvement enables businesses to promptly address the issue, resulting in cost and time savings.

Customer Management- The applications of AI for manufacturing boost productivity, business performance, and sales. The smart artificial intelligence apps for manufacturing can right away understand customer problems and offer personalized solutions. AI solutions and service in customer services offers a plethora of benefits namely,

(a) Make an informed decision through customer data

(b) Improved relations using customer relationship management (CRM)

(c) Personalized experience 

(d) Quick response time

Detect Errors- A manufacturer can use an automated visual inspection tool to look for defects on the production line. Different visual inspection equipment like machine vision cameras can detect faults accurately and quickly than human eyes. For instance, a visual inspection camera can find a flaw easily in a complex, small item such as a mobile phone. The attached artificial intelligence systems will alert workers regarding the flaw before this reaches an unhappy consumer.

Lower Operational Costs- Most companies are considering introducing artificial intelligence into the manufacturing sector with trepidation, as this needs a massive amount of investment. The ROI, on the contrary, is essential and increases with time. The moment intelligent machines start taking over the day-to-day activities of factory floors, a business will benefit due to considerably reduced operations costs, with predictive maintenance assisting additionally for reducing machine downtime. Consumers these days are boosting their need for customized, personalized, and unique products while continuing to expect the best value. Following advances such as IIoT connected devices and 3D printing, it has become cheaper and simpler to meet these needs and utilize augmented or virtual reality techniques, indicating that the entire production process will be cost-effective. Integrating CAD and machine learning indicates that the system can be designed and tested in virtual models before putting them into production, reducing the trial-and-error machine testing cost.

Quick Decision Making- As IIoT is coupled with AR or VR and cloud computing, organizations can share simulations, exchange critical information in real-time, or confer on the production activity, regardless of geographical location. The data collected from beacons and sensors help determine consumer activity, enabling organizations to anticipate future needs and make quick decisions on production and speed up the exchange between suppliers and manufacturers. 

With all these perks and much more, it will not be an exaggeration to state that artificial intelligence is indeed the future of the manufacturing sector.

Regional Analysis

Market Research Future (MRFR) study has covered some key countries in the regional analysis of artificial intelligence (AI) in the manufacturing market—North America, Europe, Asia-Pacific, the Middle East Africa, and South America in the rest of the world.

Artificial intelligence in the manufacturing market is currently led by the Asia-Pacific region as the primary economic countries such as India, China, the Philippines, and South Korea are the major manufacturing centers of electronics, semiconductors, pharmaceuticals, and energy power. Further, the escalating adoption of robots in manufacturing processes is anticipated to aid the region is leading the market throughout the forecast period. 

The region of North America is the second highest contributor to the artificial intelligence market. The US is the first adopter of new technologies for applications such as process planning, factory automation, production scheduling, and engineering design.

Artificial intelligence (AI) in the manufacturing market in Europe is also estimated to gain high momentum during the projected period owing to the mounting adoption of industry 4.0 and robotics by the automotive and aerospace industry.

Top Market Players

Market Research Future has well-known some of the key players in the global artificial intelligence (AI) in the manufacturing market are IBM Corporation, Nvidia Corporation, Intel, Inc., General Electric company, Siemens AG, Microsoft Corporation, Google, Inc., Bosch, Amazon Web Services, Cisco Systems, Rockwell Automation, Foxconn, SAP SE, and others.

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AI in Manufacturing Market Research Report: Information by Technology (Hall Effect, Magneto Resistive, Variable Reluctance), By Application (Automotive, Industrial, Aerospace Defense, Consumer Electronics) and Region (North America, Europe, Asia-Pacific, Middle East Africa, and South America)—Forecast till 2030

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