Mettler-Toledo targets efficiency with OEE reporting enhancement
Developed for the Profile, Profile Advantage and Signature Touch systems, it supports manufacturers in improving efficiency of production lines.
By streamlining collection of OEE data, it allows operatives to analyse information with reporting data from other machines on the line to reduce maintenance or changeover downtime.
Food safety standards have been updated such as the British Retail Consortium Global Standards Version 7.
Legislation including the US Food Safety Modernization Act and China’s Food Safety Law has also had an impact.
Increasing concern
Jonathan Richards, head of marketing at the firm, told FoodProductionDaily that rising production costs and growing competition has meant food and beverage manufacturers are increasingly concerned about OEE and production line efficiency.
“As such, manufacturers are increasingly looking for ways to ensure the removal of foreign body contaminants, while simultaneously optimising line efficiency,” he said.
“The OEE reporting enhancement enhances metal detector performance by providing OEE data either at the device or through various communication protocols in a company’s Management Information System.
“These features improve production efficiency and enhance metal detector performance by generating data such as alarm history, faults and warnings and changeover information.”
Information is transferred into a factory management information system through an existing RS232 or Ethernet interface, or via a Mettler-Toledo Fieldbus Interface Module (FIM), said Richards.
“By making machine integration simpler, manufacturers have complete control over the monitoring and reporting of production line data,” he added.
“This means maintenance is easier and manufacturers are able to have a more efficient production line.”
Addressing issues with technology
Mettler-Toledo developed Conditioning Monitoring software, which automatically monitors system performance, allowing operators to rectify issues before they impact production.
The company also devised a Product Clustering feature for its metal detection systems.
“This enables a range of products with varying moisture contents to be accurately inspected on a single detection frequency setting,” Richards said.
“The recent introduction of PackML version 3.0 machine language enables manufacturers to extract and analyse valuable OEE data for their metal detection systems in a standard industry language.
“Using such technology brings consistency to the production line in terms of data, thus allowing manufacturers to take the necessary steps to improve the lines overall operational performance.”
Packaging Machine Language (PackML) is the most recent version from the Organisation for Machine Automation and Control (OMAC).
The impact of OEE
Richards said the enhancement means manufacturers have a greater understanding of the impact on OEE of traditional efficiency limitations.
“For example, foods with a high moisture or salt content, such as baked goods, have proven a challenge for metal detection as they can produce an ‘active product signal’, or ‘product effect,’” he said.
“This is the signal that is generated by the product in the detector during inspection.
“This can reduce a detector’s ability to detect very small pieces of metal contaminant leading to false rejects at higher sensitivities.
“Such conditions have a greater chance of negatively impacting OEE and therefore require closer monitoring of product inspection systems.”
Richards added it has developed the PROD-X data management system that allows all data to be collated automatically and stored.
