Case Study

Sensor Maintenance Reduced by 50%

Case Study

Beet Sugar Processing Case Study

Sensor Maintenance
Sensor Maintenance

Founded in 1962, Italyʼs COPROB Group has grown from producing sugar from the beets of 30 agricultural holdings to now working with over 5,000 and processing 1.5 million tons of beets. Sugar production in Italy is highly seasonal, and COPROBʼs facility near Pontelongo, Padova only operates between August and October. With just three monthsʼ production COPROB cannot afford to make any mistakes during beet processing. Equipment at the facility therefore has to function to a very high degree of efficiency and require low maintenance.

COPROB was using an older generation of pH measurement system where the pH electrode and reference electrode were separate. This meant a significant amount of time was being spent on sensor maintenance, and while one or other of the electrodes was being cleaned or replaced, in-line pH measurement was not possible. Frustrated with the situation, COPROB looked for an alternative that would reduce maintenance, frequency of sensor replacement and ensure pH measurement reliability.

Read in the case study how for Italy's largest sugar producer, switching to robust sensors with METTLER TOLEDO's Intelligent Sensor Management (ISM®) technology has dramatically reduced pH system maintenance.
 

For a period after installation, COPROB engineers periodically compared the measurements from the METTLER TOLEDO InPro 4800i with those from a portable meter. They were always aligned, giving COPROB the confidence in the in-line system they were looking for.

Regarding time spent on pH system maintenance, due to the InPro 4800iʼs resilience and ISMʼs predictive diagnostics it has dropped by 50 %. Now, engineers have more time for ensuring COPROBʼs sugar is of the highest purity and quality.

The InPro 4800i also offers COPROB the benefits of ISM technology. These include a robust sensor-transmitter digital signal that is unaffected by the moisture in the environment; Plug and Measure for fast, error-free measurement point start up; and predictive diagnostics that keep maintenance staff aware of sensor condition at all times.