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Top 20 Manufacturing AI Solutions for Optimization, PdM & more

Top 20 Manufacturing AI Solutions for Optimization, PdM & moreTop 20 Manufacturing AI Solutions for Optimization, PdM & more

Manufacturing companies can reduce their maintenance costs or customize product designs by adopting manufacturing AI solutions in manufacturing plants. Nearly half (49%) of respondents from the automotive and manufacturing sectors believe that AI will be crucial to manufacturing success in the next five years.

While the benefits are clear, navigating the manufacturing AI landscape poses a unique challenge in choosing the right tool for specific needs.

In this article, we will explore the top 20 manufacturing AI solutions within each relevant category. Our aim is to provide insights that will assist companies in navigating the complexities of selecting the most suitable tools for their needs.

Selecting top 20 manufacturing AI software

ToolsTypes# of employeesYear founded
AWSBig Tech100-500k2006
General ElectricsBig Tech100-500k1892
Google Cloud AI in ManufacturingBig Tech100-500k2008
IBM Watson for ManufacturingBig Tech100-500k1911
Microsoft Azure AI for ManufacturingBig Tech100-500k1975
SKF GroupBig Tech100-500k1907
Oracle Manufacturing CloudBig Tech100-500k1977
AuguryScaleups100-5002011
AvevaScaleups5,000-10,0001967
C3 AIScaleups1,000-5,0002009
DataRobotScaleups500-1,0002012
RescaleScaleups100-5002011
Cogniac CorporationStart-ups50-1002015
FalkonryStart-ups50-1002012
Fero labsStart-ups10-502015
MachineMetricsStart-ups10-502014
Narrative WaveStart-ups10-502014
PredictronicsStart-ups50-1002013
Sight MachineStart-ups10-502011
VantiStart-ups10-502019

While identifying the top manufacture AI tools, we took into account two factors:

  • Pure players: Our attention was on those who specialize exclusively in creating and offering advanced AI systems designed for manufacturing processes.
  • Number of employees: We assess the employee numbers to classify the tools into categories such as scale-ups, startups, and big tech providers based on their size.

We typically take into account reviews on B2B platforms but manufacturing AI is almost exclusively used by large enterprises and these businesses tend to leave fewer reviews. Therefore, we couldn’t rely on review data in this list.

Big Tech’s manufacturing AI solutions

Big Tech Manufacturing AI vendors represent industry giants with extensive resources and global reach. These established players leverage their vast technological infrastructure to provide comprehensive AI solutions for manufacturing. Their offerings encompass a wide range of applications, from predictive maintenance and quality control to supply chain optimization, driving innovation and efficiency across the manufacturing landscape.

1.) AWS Industrial solutions

AWS, a subsidiary of Amazon, offers a comprehensive suite of cloud services, including AI solutions tailored for the manufacturing sector. Their platform provides scalable and flexible solutions, enabling manufacturers to leverage advanced analytics, machine learning, and IoT for improved operational efficiency and innovation.

Key features

AWS delivers a set of tools for data analytics, AI based predictive maintenance, and process optimization. Its cloud-based infrastructure allows manufacturers to deploy and scale AI applications seamlessly.

2.) GE Additive

General Electric (GE) incorporates AI to enhance manufacturing processes. GE Additive focus on predictive maintenance, asset performance management, and quality control, helping manufacturers reduce downtime and improve overall equipment effectiveness (OEE).

Key features

GE’s AI applications leverage data from industrial equipment and sensors to predict equipment failures, optimize maintenance schedules, and ultimately drive operational excellence in manufacturing.

3.) Google Cloud AI in Manufacturing

Google Cloud offers several AI solutions tailored for the manufacturing industry, providing tools for predictive analytics, supply chain optimization, and quality control. Leveraging Google’s manufacturing data engine solution, manufacturers can gain valuable insights into their operations.

Key features

Google Cloud AI in Manufacturing integrates with other Google Cloud services, offering a holistic approach to data analysis, enabling manufacturers to make informed decisions and drive efficiency in their production processes.

The image shows a manufacturing AI software platform from a Big Tech firm, Google cloud.
Figure 1: Google Cloud Manufacturing Data Engine platform 1

4.) IBM Watson IoT for Manufacturing

IBM Watson IoT for Manufacturing combines IoT and AI to empower manufacturers with advanced analytics and cognitive insights. The platform enables predictive maintenance, quality assurance, and supply chain optimization, fostering intelligent decision-making in the manufacturing domain.

Key features

IBM Watson IoT leverages machine learning algorithms to analyze sensor data, providing manufacturers with actionable insights to enhance product quality, reduce downtime, and optimize production workflows.

5.) Microsoft Azure AI for Manufacturing

Microsoft Azure offers a suite of AI solutions designed specifically for the manufacturing sector. The platform integrates AI, IoT, and analytics to improve production efficiency, quality control, and supply chain management for manufacturers.

Key features

Microsoft Azure AI for Manufacturing provides tools for predictive maintenance, anomaly detection, and process optimization, allowing manufacturers to transform their operations through data-driven decision-making.

6.) Oracle

Oracle’s AI solutions for manufacturing focus on enhancing operational efficiency and decision-making. The platform integrates AI capabilities into various manufacturing processes, from supply chain management to quality control, helping organizations adapt to dynamic market demands.

Key features

Oracle’s AI applications enable manufacturers to gain real-time insights, optimize inventory management, and streamline production processes, fostering agility and competitiveness in the manufacturing landscape.

The image shows the pros and cons from a user review for Oracle Manufacturing cloud, one of the big tech manufacturing AI solutions.
Figure 2: Oracle Manufacturing Cloud user review on G2 2

Pros & Cons

Pros

  • AI/ML and IoT integration: Leverages modern AI/ML and IoT efficiencies, enhancing overall functionality and value.
  • Configurability and scalability: Easy to configure, scale up, and customize according to customer preferences and requirements.

Cons:

  • Documentation Improvement: Lack of comprehensive product guides and documentation for new users, hindering quick and easy learning.
  • Performance Issues with low bandwidth: Faces performance issues when operating with limited internet bandwidth.

Manufacturing AI scale-ups

Scale-ups are manufacturing AI solutions that have surpassed the startup phase and are experiencing rapid growth and scalability. These firms have demonstrated the effectiveness of their solutions and are expanding their impact on manufacturing processes and customer satisfaction.

7.) Augury:

Augury specializes in predictive maintenance and machine health monitoring for manufacturing. Their platform integrates AI and IoT to analyze machine data, enabling manufacturers to predict equipment failures, reduce downtime, and optimize maintenance schedules.

Key features

Augury’s platform offers continuous monitoring of machine health, leveraging AI algorithms to detect anomalies and predict potential issues. The real-time insights empower manufacturers to implement proactive maintenance strategies, improving overall equipment reliability.

8.) C3 AI

C3 AI is a focused manufacturing AI software, which integrates AI, IoT, and big data analytics to drive digital transformation in manufacturing processes, enhancing operational efficiency, and facilitating data-driven decision-making.

Key features

C3 AI’s platform provides a comprehensive suite of tools for predictive analytics, process optimization, and quality control. It enables manufacturers to harness the power of AI and advanced analytics to gain insights that drive innovation and competitiveness.

9.) DataRobot

DataRobot is a automated machine learning provider, empowering organizations to build and deploy machine learning models at scale. In manufacturing, DataRobot’s AI solutions are applied to optimize processes, improve quality, and enhance decision-making.

Key features

DataRobot’s platform streamlines the machine learning model development process, making it accessible to a broader audience within manufacturing organizations. It facilitates predictive modeling, anomaly detection, and optimization, contributing to improved operational outcomes.

The image summarizes pros and cons for DataRobot
Figure 3: DataRobot user review on Trustradius 3

Pros & Cons

Pros:

  • Easy Deployment with REST API endpoints: Simplifies deployment through REST API endpoints, enhancing accessibility and integration capabilities.
  • Versatility in use cases: Well-suited for a variety of complex use cases in manufacturing and supply chain, including automated quoting, forecasting, inventory management, and machinery settings automation.

Cons:

  • Limited customization of error metrics: Users may find limitations in the customization of error metrics, potentially restricting the ability to tailor evaluations to specific needs.

10.) Rescale:

Rescale focuses on high-performance computing (HPC) solutions for manufacturing, enabling organizations to leverage the power of AI and simulation for product design, testing, and optimization. Their platform provides cloud-based HPC resources to accelerate complex simulations and analyses.

Key features

Rescale’s platform allows manufacturers to scale their computational resources dynamically, facilitating faster and more efficient simulations. This is particularly valuable for industries such as aerospace and automotive, where complex simulations are crucial for product development and innovation.

Manufacturing AI start-ups

Startups in the Manufacturing AI domain represent emerging ventures characterized by their keen focus on addressing specific challenges within the industry. Unlike industry giants, these companies are often more nimble, catering niche aspects of manufacturing processes.

11.) Cogniac Corporation

Cogniac Corporation specializes in visual-based AI solutions for manufacturing, offering computer vision applications to enhance quality control and inspection processes. The company’s platform utilizes advanced machine learning algorithms to analyze and interpret visual data, empowering manufacturers to improve product quality and reduce defects.

Key features

Cogniac’s AI platform is designed to handle complex visual inspection tasks, enabling automated identification of defects and anomalies in real-time. Its customizable and adaptive algorithms make it well-suited for a variety of manufacturing environments.

12.) Falkonry

Falkonry focuses on predictive operations and machine learning for manufacturing, providing a platform that helps organizations predict and prevent operational disruptions. The platform utilizes machine learning models to analyze time-series data, enabling manufacturers to anticipate equipment failures and optimize maintenance schedules.

Key features

Falkonry’s platform excels in predictive analytics, offering manufacturers the ability to monitor equipment health, predict failures, and proactively address maintenance needs. Its user-friendly interface empowers domain experts to build and deploy predictive models without extensive data science expertise.

13.) Fero Labs

Ferolabs specializes in AI-driven solutions for process optimization in manufacturing. The company’s platform leverages machine learning algorithms to analyze and optimize complex manufacturing processes, enhancing efficiency and reducing operational costs.

Key features

Ferolabs’ AI applications provide manufacturers with insights into process bottlenecks, inefficiencies, and opportunities for improvement. The platform facilitates data-driven decision-making, allowing organizations to streamline operations and enhance overall productivity.

Figure 4: Fero Labs Manufacturing AI tool platform 4

14.) MachineMetrics

MachineMetrics offers an industrial IoT platform with a focus on real-time data analytics for manufacturing. The platform collects and analyzes data from manufacturing equipment, providing manufacturers with insights into machine performance, production efficiency, and overall equipment effectiveness (OEE).

Key features

MachineMetrics’ platform enables manufacturers to monitor and optimize production processes in real-time. Its features include machine connectivity, performance analytics, and predictive maintenance capabilities, helping organizations maximize operational efficiency.

15.) Narrative Wave

Narrative Wave specializes in AI-driven solutions for supply chain optimization in manufacturing. The company’s platform leverages advanced analytics and machine learning to enhance demand forecasting, inventory management, and logistics planning.

Key Features

Narrative Wave’s platform helps manufacturers optimize their supply chain by providing accurate demand forecasting, reducing excess inventory, and improving overall supply chain visibility. The AI-driven insights enable organizations to make data-driven decisions for improved efficiency.

16.) Predictronics

Predictronics focuses on AI based predictive maintenance solutions for manufacturing to forecast equipment failures and optimize maintenance strategies. The company’s platform analyzes sensor data to predict potential issues, helping manufacturers reduce downtime and extend the lifespan of critical assets.

Key features

Predictronics’ predictive maintenance platform offers real-time monitoring, anomaly detection, and failure prediction, allowing manufacturers to implement proactive maintenance practices and enhance the reliability of their machinery.

17.) Sight Machine

Sight Machine specializes in manufacturing analytics, offering a platform that transforms manufacturing data into actionable insights. The company’s AI-driven analytics enable manufacturers to monitor production performance, optimize processes, and drive continuous improvement.

Key features

Sight Machine’s platform provides manufacturers with a comprehensive view of their operations, facilitating data-driven decision-making. The platform includes features for performance monitoring, quality control, and process optimization, empowering organizations to achieve operational excellence.

18.) Vanti

Vanti focuses on AI solutions for energy efficiency and sustainability in manufacturing. The company’s platform leverages machine learning to optimize energy consumption, reduce environmental impact, and enhance overall sustainability practices within manufacturing facilities.

The image is an example of Vanti's platform.
Figure 5: Vanti Manufacturing AI platform 5

Key features

Vanti’s AI applications help manufacturers achieve energy efficiency goals by analyzing data related to energy consumption, identifying opportunities for optimization, and providing actionable recommendations. The platform supports organizations in aligning with sustainability initiatives while improving operational efficiency.

What is Manufacturing AI?

Manufacturing AI, or Artificial Intelligence in Manufacturing, refers to the application of advanced technologies like machine learning, data analytics, and automation within the manufacturing sector. It involves leveraging intelligent systems to enhance production processes, improve efficiency, and make data-driven decisions.

Manufacturing AI solutions can be applied to various areas, including predictive maintenance, quality control, supply chain optimization, and process automation. By analyzing vast datasets and optimizing operations, it aims to increase productivity, reduce costs, and drive innovation, ushering in a new era of smart and adaptive manufacturing practices.

How is AI used in manufacturing industry?

The visual summarizes top technologies offered by manufacturing AI solutions

Generative AI in product design: One transformative AI technology in manufacturing is generative AI. By leveraging a generative AI software, companies can optimize components for specific criteria such as weight, strength, or cost. This innovation in product design enhances efficiency and fosters continuous improvement in manufacturing processes. Discover more on generative AI in manufacturing.
IoT for predictive maintenance: Internet of Things (IoT) devices form a critical component in manufacturing, collecting real-time data from machinery. Applied to predictive maintenance, IoT facilitates the analysis of equipment health, enabling proactive strategies to prevent breakdowns. This not only reduces downtime but also extends the operational lifespan of crucial assets. Explore more on IoT in manufacturing.
Computer vision for quality control: By employing machine learning algorithms, computer vision systems inspect products for defects in real-time, ensuring consistent and high-quality production. This application of machine vision technology significantly enhances product quality and reduces waste. Read more on computer vision applications in manufacturing.
Natural Language Processing (NLP) for data analysis: In manufacturing AI, Natural Language Processing (NLP) contributes to efficient data analysis. By understanding and interpreting textual data, NLP enhances communication and provides valuable insights for data-driven decision-making. This application aids in optimizing workflows and identifying areas for process improvement.
Predictive analytics for supply chain optimization: Predictive analytics, powered by machine learning, transforms supply chain management in manufacturing. This technology analyzes both historical data and real-time data to provide accurate demand forecasts. Manufacturers leverage this information to optimize inventory levels, minimize holding costs, and enhance overall supply chain efficiency. Find out more on manufacturing analytics.
Robotic Process Automation (RPA) for streamlining operational processes: RPA emerges as a pivotal technology in manufacturing for automating routine operational processes. RPA in manufacturing ensures redirect their focus toward more strategic initiatives, thereby increasing overall productivity and operational agility. Learn other automation tools that can replace RPA, such as intelligent automation in manufacturing.

Further reading

Explore more on AI use cases in any manufacturing process by exploring:

If you have more questions, do not hesitate to contact us:

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External sources

Access Cem's 2 decades of B2B tech experience as a tech consultant, enterprise leader, startup entrepreneur & industry analyst. Leverage insights informing top Fortune 500 every month.
Cem Dilmegani
Principal Analyst
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Hazal Şimşek
Hazal is an industry analyst in AIMultiple. She is experienced in market research, quantitative research and data analytics. She received her master’s degree in Social Sciences from the University of Carlos III of Madrid and her bachelor’s degree in International Relations from Bilkent University.

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