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Frequently Asked Questions

What makes ProcessMiner™ unique?

  1. Complete autonomous control through predictive closed-loop control.
  2. Advanced data science paired with industry expertise.
  3. Turn-key solution that is easily and quickly deployed.

How does your business model work?

During the First Application period, ProcessMiner makes the upfront investment attractive to new customers. During First Application our we typically only look to cover our costs to deliver an MVP [Minimum Viable Product] in line with the success criteria we mutually agree upon for the First Application period.

After success criteria are achieved, and the customer is ready to roll the platform into production at scale, we negotiate a familiar SaaS license model per production line. We offer discounts for achieving certain critical mass thresholds of adoption, and we ordinarily credit any money paid for the MVP towards any one-time implementation fees.

We have successfully used creative pilot models that help de-risk the up-front investment and are happy to discuss those details if we are chosen to work on your business.


What level of actual manufacturing operational experience does ProcessMiner have?

We have multiple subject matter experts on staff with practical hands-on operational and technical experience working at high volume continuous manufacturing operations, including expertise in (but not limited to):

  • Pulp & Paper
  • Packaging
  • Water Treatment
  • Automotive
  • Metallurgy
  • Food & Beverage
  • Petro-Chemical
  • Pharmaceuticals

What level of engineering expertise does ProcessMiner have?

ProcessMiner has access to an extensive group of IIoT Engineering Specialists for assistance with features, including the autonomous closed-loop features of the platform. We’ve successfully delivered closed-loop autonomous functionality [Auto-Pilot] in both the Plastics and Paper industries. We also have experts in process control.

During the “First Application” portion of the project, we closely collaborate with your process engineers – typically for a minimum of one hour each week. The iterative feedback loop between our data science, product development teams, and your process engineering members is essential as we configure the library of models on our platform for your business.

What preparation is needed to implement the ProcessMiner™ platform?

The ProcessMiner™ platform is a cloud hosted application that is interoperable with most existing technology and infrastructure already deployed at the factory. Little preparation is required. Most of the weight-lifting is done by the ProcessMiner™ team. At the initial stage, we conduct an in-depth problem discovery, run a preliminary analysis, and then deploy the real-time predictive and autonomous control.

How long does it take to deploy?

We typically have a new customer operating within four to six weeks of establishing streaming data.

How do we get started?

It’s simple! Contact a Miner today!

What is predictive analytics?

Predictive analytics uses historic data to predict process outcomes. With the advantage of advanced machine learning, these models continue to learn providing the user with accurate information that can drive better decisions.

What data is collected?

The data comprises real-time process variables (collected via sensors or IIoT devices), the control variables, product quality measurements, product failure, product grade, machine run status, and other applicable parameters.

How is data collected?

Data can be accessed from any source and in real-time or batch. We currently access data from all historians and IIoT devices operational in the factory or on the production lines.

How is data health assessed?

The data health report will identify whether the customer’s data is suitable for advanced analytics. Metrics that evaluate quantity, frequency, quality, and accuracy are used to evaluate data health and integrity. 

Please explain data privacy and data security.

At ProcessMiner, our number one goal is to be a strategic partner to our clients. We use industry-standard best practices, rigorous data security, and data privacy precautions to ensure customer data is safe and secure. We use customer data only to benefit the customer providing the data and do not share data outside of the secure platform ecosystem. We will agree to construct commercial language in any agreement that guarantees rigorous safeguards around customer data use.

Is the ProcessMiner platform considered “cutting edge” technology?

Yes. Our approach delivers simple solutions to complex problems. We work hard to make AI easy for manufacturing. Manufacturing is a complex business, and complex solutions often lead to confusion and can lead to scale problems. Our approach is to deliver the platform making it highly scalable to quickly feel the value and the impact our technology has on business operations in continuous improvement. 

How is the pilot (First Application) transition to production and implementation at scale handled?

The ProcessMiner platform is built to scale with global businesses. The transition from the first application to implementation at a global scale is handled with ProcessMiner handling first level support through transition and beyond to ensure the technology can be rapidly adopted globally.

We can achieve this in part through our cloud hosting partners AWS and MS Azure.  Service levels for support activities will be included in the commercial agreement in line with the level of support required to successfully deliver a favorable customer experience with rapid deployment at scale in mind.

How do users access the platform?

The ProcessMiner™ dashboard is accessible via a secure URL and the predictions are displayed so that the customer’s operations team can take full advantage of them.

Can the ProcessMiner Platform be customized for specific scenarios?

Yes. Our platform is highly dynamic and adaptive, and we strive to deliver solutions to complex and ever-changing environments. The interoperability of the technology we’ve developed allows you to enhance other technology investments already deployed in production lines for ease of implementation and to avoid duplicative investments.

When a variable in the process changes, will the model adapt to the change?

The ProcessMiner™ platform utilizes advanced machine learning algorithms that identifies changes in the data and adapts the proper data model for the most up-to-date predictions.

Can new variables or new technology be added to the model?


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