Case study: Detecting transgressions beyond optimal operating conditions in food mills

Goals

Development of a methodology for determining the range of correct operating temperature of a device depending on the current operating point

Results

Extensive analysis of potential causes and detection of many types of anomalies

Development of a system for detection of temperatures outside the range of optimal operation with identification of potential causes (prescriptive)

Challenge

The subject of the project was 4- and 8-roll food mills. The main tasks included the development of a methodology for the dynamic determination of the optimal temperature range of the mill's rolls for given operating conditions and methods for detecting their exceedance.

Solution

Based on the historical data and expertise provided, a wide range of factors affecting production conditions and food mill behavior were analyzed. Among the main factors identified were the temperatures currently prevailing on the production floor, the current recipe of the product being ground and the mill settings made by the operator. For each of the identified factors, its effect on the change in the optimum temperature range relative to the averaged optimum range and the transit time required for the mill to stabilize under the new conditions was determined. Based on this methodology, a system was built that automatically analyzes the current temperatures and detects deviations. When an undesirable situation was detected, the system automatically analyzed potential causes based on previous analyses.

CASE: Analysis of sample requests from the system

In the course of analyzing historical data, the system detected and correctly identified the occurrence of various undesirable situations at various mills from the analyzed location.

Examples of situations detected by the system at one of the mills are highlighted below, along with the system's indication of potential factors that could be behind the occurrence of the situation as information to help the operator take appropriate action.

Benefits

Realizing the conditions and challenges set, a system was developed to automatically analyze current temperatures and detect deviations. When an undesirable situation was detected, the system automatically analyzed the potential causes based on previous analyses and enriched the notification sent to the operator with the potential causes of the notification. Other benefits of the project include:

Solution to detect temperature problems

Ability to monitor the condition of equipment in real time and know the source of the cause of the anomaly occurring

Support machine operators in responding by identifying potential causes

About company

ReliaSol is a company established in response to the growing need to increase the efficiency of machines and installations in industry.

We provide software and services that accelerate the digital transformation process. The applications we create combine real data from machines, sensors, event reports and automate drawing conclusions. The result of their work is data visualization, event prediction and monitoring of the optimal operating range of machines and entire production lines.

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Reliability Solutions Sp. z o. o.
ul. Królewska 57, 30-081 Kraków, Polska