Manufacturing Analytics Software
Manufacturing analytics software enable companies to drill down on manufacturing data to find optimization opportunities +Show More
| Products | Position | Customer satisfaction | |||
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Tulip |
Leader
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Satisfactory
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Tulip, the leader in frontline operations, is helping companies of all sizes and across industries, including complex manufacturing, pharmaceuticals, and medical devices equip their workforce with connected apps– leading to higher quality work, improved efficiency, and end-to-end traceability across operations. A spinoff out of MIT, the company is headquartered in Somerville, MA, with offices in Germany, and Hungary. The platform’s main features are: - Intuitive drag-and-drop app editor lets you create user-friendly apps — no coding required - Boost operator productivity with human-centric apps that incorporate computer vision, connected devices, and connections to 3rd-party systems - Native edge connectivity lets you connect your machines, sensors, cameras, and smart tools to the apps you build - Gain visibility with real-time analytics and dashboards - Integrate with the systems, databases, and software you already use - Manage permissions, ensure data policy compliance, and maintain data integrity - The Tulip Library with easy to download 100+ templates and examples and configure them to your needs
Basis for EvaluationWe made these evaluations based on the following parameters; Customer satisfaction
Average rating
Market presence
Company's number of employees
300-400 employees
Company's social media followers
20k-30k followers
Total funding
$100-250m
# of funding rounds
7
Latest funding date
August 10, 2021
Last funding amount
$100-250m
Company
Type of company
private
Founding year
2014
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Augury |
Leader
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N/A
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Augury provides AI-driven insights into machines, processes, and operations so manufacturers and industry can improve business outcomes, empower their workforce, and achieve sustainable production- all at the same time. Our purpose-built AI solutions unlock overall Production Health and deliver an average of 3x-10x ROI for our customers, often in a matter of months. On average, Augury customers make their first machine improvements within thirty days of installation. Augury’s Machine Health, for both critical and supporting equipment, can predict and prevent machine failures and drive down maintenance costs by giving teams industry leading AI trained by 300M+ machine hours and backed by reliability experts. We also provide a portable diagnostic solution for route-based needs. Augury’s Process Health optimizes production lines for quality and throughput while cutting waste and energy costs by providing teams with hybrid intelligence, a combination of AI and process experts. Our end-to-end solutions help customers reduce production downtime, improve process efficiency, maximize yield, and achieve sustainability goals to realize the full potential of their production. In less than a year, DuPont achieved 7x ROI at their pilot sites. Colgate-Palmolive saved 2.8 million tubes of toothpaste by avoiding a single machine failure. ICL saved a million dollars in downtime and production loss costs at a single facility in less than 10 months. While 74% of manufacturers still fail to scale Industry 4.0 technologies, Augury customers quickly expand to multiple sites. One leading building materials manufacturer deployed Machine Health at all of its 25 facilities one year after installation at their pilot site.
Basis for EvaluationWe made these evaluations based on the following parameters; Customer satisfaction
Average rating
Market presence
Number of case studies
5-10 case studies
Company's number of employees
300-400 employees
Company's social media followers
50k-100k followers
Total funding
$250-500m
# of funding rounds
8
Latest funding date
October 26, 2021
Last funding amount
$100-250m
Company
Type of company
private
Founding year
2011
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SAS |
Leader
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N/A
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Basis for EvaluationWe made these evaluations based on the following parameters; Customer satisfactionMarket presence
Number of case studies
300-400 case studies
Company's number of employees
10k-20k employees
Company's social media followers
100k-1m followers
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Rockwell Automation |
Leader
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N/A
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Basis for EvaluationWe made these evaluations based on the following parameters; Customer satisfactionMarket presence
Number of case studies
50-100 case studies
Company's number of employees
20k-30k employees
Company's social media followers
1m-2m followers
# of funding rounds
1
Latest funding date
July 12, 2023
Company
Type of company
public
Founding year
1903
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ptc |
Leader
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N/A
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Basis for EvaluationWe made these evaluations based on the following parameters; Customer satisfactionMarket presence
Number of case studies
100-200 case studies
Company's number of employees
5k-10k employees
Company's social media followers
100k-1m followers
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Eigen |
Challenger
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N/A
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Eigen's AI-enabled vision solution helps industrial manufacturer see complex, difficult to detect issues. By providing a comprehensive and real-time view of these defects and quality issues, our customers are setting new quality benchmarks and realizing massive savings.
Basis for EvaluationWe made these evaluations based on the following parameters; Customer satisfactionMarket presence
Company's number of employees
20-30 employees
Company's social media followers
2k-3k followers
Total funding
$5-10m
# of funding rounds
8
Latest funding date
May 1, 2019
Last funding amount
$1-5m
Company
Type of company
private
Founding year
2012
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Konux |
Challenger
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N/A
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Basis for EvaluationWe made these evaluations based on the following parameters; Customer satisfactionMarket presence
Company's number of employees
100-200 employees
Company's social media followers
10k-20k followers
Total funding
$100-250m
# of funding rounds
11
Latest funding date
January 14, 2021
Last funding amount
$50-100m
Company
Type of company
private
Founding year
2014
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C Labs |
Challenger
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N/A
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Basis for EvaluationWe made these evaluations based on the following parameters; Customer satisfactionMarket presence
Company's number of employees
5-10 employees
Company's social media followers
100-200 followers
Total funding
$1-5m
# of funding rounds
1
Latest funding date
November 12, 2015
Last funding amount
$1-5m
Company
Type of company
private
Founding year
2009
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Sight Machine |
Challenger
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N/A
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Basis for EvaluationWe made these evaluations based on the following parameters; Customer satisfactionMarket presence
Number of case studies
20-30 case studies
Company's number of employees
50-100 employees
Company's social media followers
5k-10k followers
Total funding
$50-100m
# of funding rounds
6
Latest funding date
April 23, 2019
Last funding amount
$10-50m
Company
Type of company
private
Founding year
2012
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Falkonry |
Challenger
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N/A
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Basis for EvaluationWe made these evaluations based on the following parameters; Customer satisfactionMarket presence
Company's number of employees
40-50 employees
Company's social media followers
5k-10k followers
Total funding
$10-50m
# of funding rounds
3
Latest funding date
February 23, 2021
Last funding amount
$1-5m
Company
Type of company
private
Founding year
2012
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“-”: AIMultiple team has not yet verified that vendor provides the specified feature. AIMultiple team focuses on feature verification for top 10 vendors.
Sources
AIMultiple uses these data sources for ranking solutions and awarding badges in manufacturing analytics software:
Which one has collected the most reviews?
AIMultiple uses multiple datapoints in identifying market leaders:
- Product line revenue (when available)
- Number of reviews
- Number of case studies
- Number and experience of employees
- Social media presence and engagement
What are the most mature manufacturing analytics software?
Which one has the most employees?
Which manufacturing analytics companies have the most employees?
60 employees work for a typical company in this solution category which is 37 more than the number of employees for a typical company in the average solution category.
In most cases, companies need at least 10 employees to serve other businesses with a proven tech product or service. 14 companies with >10 employees are offering manufacturing analytics software. Top 3 products are developed by companies with a total of 40k employees. The largest company in this domain is Rockwell Automation with more than 20,000 employees. Rockwell Automation provides the manufacturing analytics solution: Rockwell Automation
Insights
Where are manufacturing analytics vendors' HQs located?
Trends
What is the level of interest in manufacturing analytics software?
This category was searched on average for 142 times per month on search engines in 2024. This number has decreased to 0 in 2025. If we compare with other analytics solutions, a typical solution was searched 155 times in 2024 and this decreased to 0 in 2025.
Learn more about Manufacturing Analytics Software
There are technical and organizational challenges ahead to implement successful manufacturing analytics software. First challenge comes with organizational; many production facilities have conservative mindset and have inertia to involve innovative tools for improvement through IT software systems. Second challenge is domain expertise; as all processes have unique set ups, one size fits all approach does not work. New vendors mush have a domain expertise and have a deep understanding of complicated processes of their clients. So considering the right vendor which has a domain expertise and involving right stakeholders and aligning them all for the manufacturing analytics benefits for the business is crucial.
Analytical insights that help to predict and prevent machine malfunction, machine learning algorithms analyses historical data to determine which indicators signal the malfunction so that these events can be predicted.
This requires collecting historical data from legacy machineries which is difficult for companies to do. Industrial Internet of Things (IIoT) solutions solve that challenge by combining machine to machine communications. IIoT brings industrial devises connected by communication technologies that results in the systems that can monitor, collect, exchange and deliver valuable insights.
Increase revenue;
Improving quality assurance have direct impact on the revenue streams, in addition to the quality, diminishing capacity constraints on the factory floor through data insights enable business to fulfill exceeding demand requests.
Reduce cost;
Decreasing inefficiency in every step of operations have accumulated impact on the cost reduction, potential cost benefits of manufacturing analytics software;
- Reduce maintenance costs by 40%,
- Reduce downtime by 50%
- Reduce equipment capital investment by 3-5%
- Reduce worker injuries by 10-25%, saving companies $225M collectively
- Reduce energy use by 10-20%
- Improve labor efficiency by 10-25%
Manufacturers collect everyday data from operational data, built in sensors, historian software, ERP systems and spreadsheets. However more than 90% of the collected data is thrown away.
Manufacturing analytics is about getting all the data from different variety of sources and using it for increase operational efficiencies and preventing slowdowns.
Manufacturing analytics is focused on collecting and analyzing data rather than process control, it helps to monitor operational equipment effectiveness of the facility and creates action-oriented dashboards to visualize the performance.
Primary manufacturing analytics used cases today are process optimization and predictive maintenance.
Advanced analytics detects each step of inefficiency of operations which is measured by overall equipment effectiveness (OEE). Analytics software can improve three components of OEE;
Uptime: ensuring machines are running especially in complicated systems
Throughout & Performance: Maximizing throughput by preventing slowdowns that are not visible to conventional analysis
Quality: Scrap and low quality cost the manufacturer