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Industry 4.0 Figure 1: ONET’s status page where the user can get an overview about the status of all instruments added to ONET. 1/2016 eFOOD-Lab international 31 tions, measurements, etc.) as the ONET server is hosted locally by the customer itself. On the status page (see Figure 1) the user can quickly get an overview of all instruments added to ONET, making it very easy to pinpoint disturbances of specific spectrometers. The status of the instrument’s connection, last upload and download as well as the instrument’s performance and warnings are monitored at all times. Previous system test reports can easily be retrieved and the validity of the current system test is clearly visible on this page. ONET offers also the possibility to set up and adapt calibration methods centrally, thus reducing the need for local expertise and training. Calibration updates can be distributed to list of instruments or only to specific spectrometers. Furthermore, specific component configurations (e.g., bias, warning and alarm limits) for a product can be performed for each spectrometer, thus allowing for a globally harmonized network of products with local adjustments. User administration manages user permissions not only for ONET but also for the measurement software (OPUS ). Different ONET user permission tiers enable the creation of users which only have access to the products and results from specific spectrometers. Audit trails record all ONET user actions regarding products, methods and spectrometers, thus guaranteeing the transparency of products, methods and operator interactions and therefore assuring data integrity at all times. Trend charts (see Figure 2) provide a fast and easy way to monitor the performance of a product. ONET pools the data from all spectrometers on the network and stores it on a central database, thus enabling a global view of all the information collected from every spectrometer present in ONET. Comparing the NIR prediction values of several components against time can easily be accomplished. This feature enables the fast and easy location of outliers in the component curve, these anomalies could be an indication of a manufacturing problem or a bad batch of material from a vendor. The NIR prediction information can also be displayed in form of a table. ONET also removes the software complexity for the operator, since all measurement parameters and product configurations come from the ONET server according to the configurations done by the ONET administrator. The operator is presented with an extremely simple user interface, thus reducing the rate of improper use drastically. ONET was first released in 2014 and has been successfully implemented at multiple international key accounts like New Hope Liuhe Figure 2: Exemplary trend chart with two components. The component selection, Y-axis assignment and other properties can be selected from this page. A table with the same data can also be displayed.


eFOOD-Lab_International_01_2016
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