Artificial Intelligence (AI) in manufacturing is defined as a simulation of human intelligence used to communicate with the machines, extract the data from the field, analyze that data, and perform the required task. From material movement to machinery inspection and self-diagnostics, which are usually operated by human labor or robot with the help of human intelligence, the AI-based system would perform in lesser time, cost, and human intervention

COMPETITIVE LEADERSHIP MAPPING TERMINOLOGY

The Artificial Intelligence in Manufacturing vendors are placed into 4 categories based on their performance and reviews in each criterion: “visionary leaders,” “innovators,” “dynamic differentiators,” and “emerging companies". Among all the Artificial Intelligence in Manufacturing vendors, the top 25 have been evaluated, including Alphabet Inc.(US), Microsoft Corporation (US), Omron Adept Technologies (US)DataRPM (US), General Vision, Inc. (US),Sight Machine (US), and AIBrain (US) and other companies.

VISIONARY LEADERS

Visionary leaders are the leading market players in terms of new developments such as product launches, innovative technologies, and adoption of growth strategies. This quadrant receives high scores for the most evaluation criteria. They have a strong service portfolio, a robust market presence, and effective business strategies across the world. The AI in manufacturing market is moderately dominated by Tier 1 players. These players have a broad product offering that caters to most of the regions globally. Visionary leaders primarily focus on acquiring the leading market position through their strong financial capabilities and their well-established brand equity. NVIDIA Corporation (US), Siemens AG (Germany), IBM Corporation (US), Intel Corporation (US), General Electric Company (US), Alphabet Inc. (US), and Microsoft Corporation (US) are the major Visionary leaders in the AI in manufacturing market.

INNOVATORS

Innovators demonstrate substantial product innovations compared with their competitors. They have a focused service portfolio. However, they do not have effective growth strategies for their overall business, and their geographical presence is low. The AI in manufacturing market depends on innovators to some extent as they require moderate capital investment for the designing and manufacturing products, and it is not very difficult for new players to enter this market. Moreover, there is a high demand for these products; therefore, new players can make steady profits. Major innovators in the AI in manufacturing market are AIBrain Inc. (US), Kespry, Inc. (US), SkyMind, Inc. (US), CloudMinds Technologies (US), Citrine Informatics (US), and Arimo, Inc. (US).

DYNAMIC Differentiators

Dynamic differentiators are established vendors with effective business strategies and market presence. However, they have a weak service portfolio. They focus on a specific type of technology related to the product. There have been many companies in the AI in manufacturing market since the past decade that is largely dependent on their competitive R&D activities. DataRPM (US), Sight Machine (US), General Vision, Inc. (US), Preferred Networks, Inc. (Japan), and Rockwell Automation, Inc. (US) are the major dynamic differentiators in the AI in manufacturing market.

EMERGING COMPANIES

Emerging companies have niche service offerings and are gaining traction in the market. They do not have effective business strategies compared with other established players. They might be new entrants in the market and require more time before gaining significant traction in the market. The emerging companies do not have a wider market presence. The AI in manufacturing market poses a moderate threat to new entrants in establishing their footprints, as there are many players who are providing AI products in the manufacturing market to diverse clientele groups globally. Some of the emerging players are Vicarious, Inc. (US), Ubtech Robotics Corp. (China), Tamr, Inc. (US), Krtkl, Inc.(US), Darktrace (UK), DataRobot (US), and Omron Adept Technologies, Inc. (US).

TOP VENDORS
In Artificial Intelligence in Manufacturing

  1. INTEL CORPORATION
    0 Reviews
    4.4
  2. NVIDIA CORPORATION
    0 Reviews
    4.4
  3. GOOGLE INC
    0 Reviews
    3.9

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KEY BUYING CRITERIA

Product Maturity
Strategic Maturity
Most IMPORTANT
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Breadth and Depth of Product Offerings
4.95
4.00
4.00
Product Features and Functionality
4.95
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3.10
Scalability
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4.00
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4.00
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TOP VENDORS

  • The company has designed Deep Learning Inference Accelerator (DLIA), integrated hardware, software frameworks, and libraries such as Intel Math Kernel Library for Deep Neural Networks (MKL-DNN) and Caffe, which simplifies the neural-network acceleration for image processing applications. Intel Corporation spends more than 20% of its revenue on R&D activities, every year. With such high investments in R&D, the company has a vast product offering for AI hardware and platform, with the latest technological advancements. Intel is using their existing business channel to reach into the market. This in turn, gives the opportunity to scale their product more. These factors earn Intel Corporation a very high rating for its product strategies.

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    4.4
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  • NVIDIA Corporation has designed an AI supercomputer—NVIDIA DGX Station for easy experimentation at the office, lab, or workspace. This integrated hardware and software solution helps the user to research more on deep learning for various purposes in manufacturing. This solution reduces both the expenditure and time, as well as has a computing capacity of four server racks. NVIDIA Corporation is one of the leading providers of deep learning hardware. The company also provides AI platforms, which is using in manufacturing plant. In addition the company’s continuous technological advancements have resulted in its very high rating.

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    4.4
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  • BUYER
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    3.9
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  • This Predix platform is used for Industrial IoT app development purpose. This is divided into three segments—Edge Connectivity and Insight, Cloud Application Services, and Apps Visibility and Insight. The Edge Connectivity and Insight connect the assets, gateways, controller, sensors with Edge Analytics, whereas the Cloud Application Services provide Digital Twin Modeling and Analytics Platform. The Predix Apps is an industrial intelligence dashboard, which provides prediction analysis and conditions of assets, operations, and business. GE Digital covers aviation, chemicals, food and beverages, healthcare, industrial manufacturing, intelligent environments, oil and gas, power and utilities, transportation. The company’s digital twin solution provides a wide range of solutions for predictive maintenance and machinery inspection in the manufacturing sector. Considering all these factors, GE has been rated very high.

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    3.8
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  • This technology provides the intelligence to see, hear, recognize faces, detect emotions, interpret language, infer intent, and prescribe and automate outcomes. Microsoft Corporation has a moderate number of products in the AI in manufacturing market. The company invests around 12% of its revenue on R&D activities, every year.

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    3.6
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  • Siemens AG offers Intelligent Data Analysis, a machine learning technology that used to optimize industrial facilities. This technology is also used in energy distribution, electric motors, and rail technology. Moreover, the company’s AI-based technology improves the operation of wind turbines by adjusting the position of the rotors to change the direction of the wind to get the highest amount of yield from a wind farm. The company’ industrial operating system “MindSphere” provides intelligent data analysis with regard to predictive maintenance. The software’s ability to analyze operating data and sensor measurements allows it to spot anomalies in facilities and automation systems. Furthermore, Siemens AG provides smart boxes, which contain sensors and a communications interface for data transfer. By analyzing the data, the artificial intelligence systems can draw conclusions on the machine’s condition and detect irregularities in order to provide predictive maintenance. This system also improves the reliability of power grids by making them smarter and providing the devices that control and monitor electrical networks with artificial intelligence. This enables the devices to classify and localize disruptions in the grid.Siemens AG developed a Simulation Environment for Neural Networks (SENN), which helps in predictive analysis. The company has developed another AI-based system called Gas Turbine Autonomous Control Optimizer or GT-ACO, which is used to optimize the operations and control the combustion in gas turbines. Siemens AG has also developed a Quadcopter, called Flying Inspector, which is eventually an unmanned vehicle driven by a small engine block with a high-resolution camera and laser technology that scans the walls, machines, and other architectural structures. The machine collects the data and creates precise 3D models. The inbuilt AI technology in the machine detects the defects, faults where human inspection is difficult due to factors such as position, heat, and chemicals. Moreover, Siemens AG has developed driverless intelligent forklifts, which is used for material movement in the manufacturing industry. The company’s wide range of customized solutions for the AI in manufacturing market caters to various industries such as energy and power, chemicals and automotive. The company’s continuous technological advancements to increase the features of each solution have earned it a very high rating.

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    3.5
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  • Furthermore, the platform provides predicting asset failures, reduces maintenance costs, optimizes inventory and resources, predicts quality issues, forecasts warranty and insurance claims, and manages risks in a better way. As the company offers software-based solutions in major applications such as predictive maintenance and machine inspection and covers most of the major end-user industries.

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    3.3
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  • This is utilized for machine learning and voice/recognition applications in AI software for manufacturing. General Vision “breadth of offering” is moderately high as they are providing hardware for faster calculations, which is required for deep learning technology. Thereby, it is rated high among the hardware providers in the AI in manufacturing market.

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    2.7
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  • The Sight Machine Platform is used for various application in the manufacturing industry, which includes machinery inspection, prediction maintenance, and field service. Moreover, this platform provides customized solutions, which indicates high scalability, thereby resulting in the company’s high rating for overall product strategies

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    2.6
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  • BUYER
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    2.4
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    2.2
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