AI-enabled Scrap & Downtime Reduction

Predict and prevent downtime and scrap to improve your overall operational effectiveness

For organizations interested in increasing their overall operational effectiveness while simultaneously maximizing machine availability and minimizing scrap and for organizations that want to empower their workforces and actively involve personnel in reducing waste (of time and materials) throughout the production process.

Improved machine availability: prevent the occurrence and/or impact of downtimes and level out variability in machine availability
Improved product quality: predict scrap volumes take corrective actions and effectively improve the overall quality of your products

Value Proposition

AI-enabled Scrap & Downtime Reduction is a proprietary AI solution specifically designed to help predict and prevent downtimes and scrap.

1. Proof of concept package

Value analysis

A feasibility analysis is performed on real data (supplied as an Excel download) of one single pilot machine to determine whether or not the data can help predict downtime and scrap.

Implementation roadmap

If the model is sufficiently accurate at predicting downtime and scrap, the Operational Package can be implemented. If not, a root cause analysis can be performed to analyze the reason why and advise on next steps to improve the data quality, infrastructure or the AI model.

2. Operational package

Powerful real-time analysis

Ability to analyze and process a wide range of sensor data in real-time to predict downtimes and scrap in the near future.

Meaningful and actionable insights

Gain new insights into your machine data and discover how your machine behaves prior to downtime or scrap production.

Operational Dashboard

A dashboard continuously displays the probability of producing scrap or going down within X minutes, empowering operators to take preventive actions.

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  • Scrap and downtime prediction

Predicts the occurrence and the cause of scrap and any type of machine downtime in real-time based on a continuous stream of sensor data captured from various PLCs in the production line.

  • Scrap and downtime prevention

Assists machine operators in analyzing the root cause of downtime and scrap and helping them take the appropriate preventative action.

Do you have a question?

Proof-of-concept Package


Start requirements

Machine sensor data:

  • Machine sensors are logged periodically (SCADA system, data historian,…)
  • Machine sensor data is historically available (required to help train the AI model)

Downtime & scrap registration:

  • Timing of downtime and scrap are registered (manually or automatically)
  • Operators assign structured reasons to downtime and scrap occurrences

One-time extract:

  • A one-time download of the above data can be provided in Excel format

* Fixed in duration, scope and price

* Free of any licensing costs

Packaged consulting services

Limited to 15 mandays

Operational Package

On demand

Start requirements

Proof-of-concept Package

  • All start requirements of the package must be met
  • The Proof-of-concept Package should be concluded first

Presence Machine Integration Layer

  • To operationalize the solution, a machine integration layer (e.g. Kepware Server, PCo, SCADA, Data Historian) should be present

Contact our expert

Rémi Krick

Remi is a manufacturing consultant with a focus on industry 4.0. His experience helps him in guiding manufacturing companies in their digital transformation using best in class solutions and emerging technologies to digitize and optimize supply chain processes and get insights to achieve operational excellence.

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