How can coil mix-ups be reliably and automatically prevented in multi-stage production processes?

Automated coil identification is based on continuous acquisition of geometric properties such as thickness and width across multiple process stages. With ibaPDA, these measurement data are captured time-synchronously and passed to downstream analytics. ibaDatawyzer-ICC extracts characteristic features and matches them between successive process steps. This enables early detection of coil mix-ups and prevents incorrect downstream processing.

How does data-driven coil identification work without additional marking systems?

Identification is based solely on the physical properties of the material, particularly high-resolution thickness and width profiles. These are captured along the entire production process using ibaPDA and stored in a database. ibaDatawyzer-ICC calculates characteristic feature vectors that uniquely describe each coil like a digital fingerprint. This eliminates the need for any additional external marking systems.

How can coil mix-ups be detected and automatically handled in real time?

By continuously comparing current measurement data with historical coil profiles, deviations can be detected immediately. ibaDatawyzer-ICC evaluates the match between reference and actual profiles and classifies results using a traffic-light logic. In case of uncertainty or misidentification, predefined actions such as blocking or report generation are triggered automatically. This enables fast response directly within the ongoing process.

What role does high-resolution process measurement technology play in reliable coil tracking?

High spatial and temporal resolution of measurement data is essential to extract unique geometric features of each coil. With ibaPDA, process data is acquired at sufficient longitudinal resolution to ensure stable calculation of local characteristics. These form the basis for robust identification even under process variability. This ensures reliable traceability across multiple production stages.

How can coil tracking be integrated into existing production and IT systems?

Integration is achieved via an open database structure into which ibaDatawyzer-ICC writes analyzed coil features and mapping information. ibaPDA provides the raw data foundation, while analysis is automatically transformed into structured datasets. These can be used for reporting as well as MES or quality systems. This creates a seamless link between process data acquisition and IT-based production control.

Checking and Certifying Coil Tracking Automatically: Handling Flat Products in an Optimized Way With ibaDatawyzer-ICC

Flat products are manufactured in several process steps, that do not directly follow each other in chronological order. Some products (the so-called coils) have to be put into interim storage. When marking, storing or providing the coils to the next process step, errors or confusions may occur. A coil that has been mistaken for another coil runs in the next process step under a “wrong identity” and might be processed in a wrong way.

A process based on measurement data has been developed in order to detect such confusions. In course of this process, coils are clearly identified by means of their geometric properties like thickness and width – similar to the human finger print.

Coil identification

based on measurement data

Automatic online-monitoring

of the production

Easy integration

in the existing iba

A close-up view of multiple large, neatly stacked coils of metallic wire or rod.

The Technology

As a prerequisite, the geometries of the coils have to be measured at the end of the previous process and the beginning of the follow-up process with a sufficient length resolution (better than 10 cm). Using mathematic procedures, local characteristics (so-called features) are extracted from the measured geometrical data. By means of these characteristics, coil measurements that belong together can be identified rapidly and in a reliable way.

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Based on the geometric properties such as thickness and width, we can uniquely identify a coil and thus exclude confounders.

Detlef Maaß
Product Manager, iba AG

Schematic

The described procedures and the mathematical algorithms have been integrated in the ibaDatawyzer-ICC (Inline Coil tracking Certifier) product.

This product automatically analyzes the data recorded with ibaPDA and extracts the essential parameters to a database (certainty of the identity in percentage, relative information about positions like extension and shift …). Optionally, certificates can be generated.

Coils which do not match sufficiently, are displayed in colors (traffic light function – yellow). If the matching coil is found in the database (traffic light function – red), a freely configurable follow-up action can be triggered. Usually, a pdf report will be generated and sent as e-mail. Due to the open DB structure of the system, data can be integrated easily e.g. in MES systems.

Confounded coils can be detected in a timely manner. Thus, corrective actions (blockings, corrections of the markings …) can be taken. The risk of delivering the wrong coils is minimized.

Used Functions

The following functions of the iba system are used in this application.

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Frequently Asked Questions (FAQ)

How can coil mix-ups be reliably and automatically prevented in multi-stage production processes?: Automated coil identification is based on continuous acquisition of geometric properties such as thickness and width across multiple process stages. With ibaPDA, these measurement data are captured time-synchronously and passed to downstream analytics. ibaDatawyzer-ICC extracts characteristic features and matches them between successive process steps. This enables early detection of coil mix-ups and prevents incorrect downstream processing.
How does data-driven coil identification work without additional marking systems?: Identification is based solely on the physical properties of the material, particularly high-resolution thickness and width profiles. These are captured along the entire production process using ibaPDA and stored in a database. ibaDatawyzer-ICC calculates characteristic feature vectors that uniquely describe each coil like a digital fingerprint. This eliminates the need for any additional external marking systems.
How can coil mix-ups be detected and automatically handled in real time?: By continuously comparing current measurement data with historical coil profiles, deviations can be detected immediately. ibaDatawyzer-ICC evaluates the match between reference and actual profiles and classifies results using a traffic-light logic. In case of uncertainty or misidentification, predefined actions such as blocking or report generation are triggered automatically. This enables fast response directly within the ongoing process.
What role does high-resolution process measurement technology play in reliable coil tracking?: High spatial and temporal resolution of measurement data is essential to extract unique geometric features of each coil. With ibaPDA, process data is acquired at sufficient longitudinal resolution to ensure stable calculation of local characteristics. These form the basis for robust identification even under process variability. This ensures reliable traceability across multiple production stages.
How can coil tracking be integrated into existing production and IT systems?: Integration is achieved via an open database structure into which ibaDatawyzer-ICC writes analyzed coil features and mapping information. ibaPDA provides the raw data foundation, while analysis is automatically transformed into structured datasets. These can be used for reporting as well as MES or quality systems. This creates a seamless link between process data acquisition and IT-based production control.