polab® AQCnet – the next generation of cement quality control

polab® AQCnet represents our take on the next generation of laboratory control software. Everything is linked, everything is supervised. Over many years AQCnet has evolved from a tool controlling laboratory automation systems into a sophisticated toolbox for plant operation using quality control data.

polab® AQCnet supervises and manages the automatic initialisation of routines and processes in the automated laboratory, serves as a data archive, and connects to systems and devices both inside and outside of the laboratory. Furthermore, AQCnet processes quality control data in raw mix calculations and returns updated set points to weight feeders and separators.

polab® AQCnet operation and administration takes place in a mobile device-optimised browser interface. It can be accessed from any PC, smartphone, or tablet with a connection to the local network, and advanced security and access routines guarantee the safety of your systems.

Communication with laboratory automation

A laboratory automation system might range from a single mill and press connected to a single analyser, to a complete quality control system for the largest plants. In these cases, polab® AQCnet controls one or more fully automatic laboratory systems such as the polab® Linea, more than two dozen sampling and dispatch stations and multiple XRF, XRD, PSD, and other devices. Connected laboratory or PGNAA analysers may be used to control our adaptive mixture control program. All data is backed up and shared with other processes in the plant, or seamlessly transferred to a separate laboratory information system.

Regardless of the level of automation, however, thyssenkrupp follows a strategy of offering a similar look and feel for all interfaces. Upgrades of all systems are possible and existing configurations transferred.

AQCnet communicates with analysers and devices of most known manufacturers. Typical installations include an XRF and XRD analyser, as well as a particle sizer. Depending on requirements, common additional analysers comprise colour measurements, moisture measurements and C/S analysers. The open interface concept can be used to connect a range of options, both laboratory-based and in the plant.

The AQCnet database is a working archive. Optionally, polab® AQCnet interfaces with customer’s LIMS and most known suppliers are supported. Data stored on an AQCnet server comprises:

Configuration data, including application websites and device management
Configuration data for sample management
Measured values of the samples
Storage of sample data for up to 15 years
Process measurement values of the control loops
Messages/alarms

When processes that use heterogeneous natural resources need a specific final composition, such as in the cement industry, blending is often required. This requires very good control of incoming and outgoing materials and is one of the key tasks of polab® laboratory automation. To achieve optimal blending, thyssenkrupp uses an adaptive mixing concept in its raw mix controller. The concept and the results go far beyond simple spreadsheet mix calculation, and the targeted composition is constantly compared relative to realised changes from changed weigh feeder settings.

First, raw material analyses are used to evaluate whether actual values have approached the target values by changing weigh feeders in the plant. If the target has not been reached, the analyses determine, together with the composition of all additives stored in the database, the level of correction necessary in the plant. This adaptive mix control approach can work on different focal points. It can be used to correct the actual analyses on the spot, or it can be set up to assure a well-homogenised silo after the raw mill. In this case, large volumes of material are corrected to achieve a targeted composition.

The adaptive mixture controller adjusts the feed quantity ratio of the initial components so that the mixture corresponds to the quality setpoint values. Using an adaptation algorithm, the controller dynamically estimates the chemical composition of the individual feed components.

Through this self-learning function the controller automatically adapts itself to the constantly changing material properties and ensures constant material quality.