Background and aims of the project

In order to save fuel costs and CO₂ emissions, coal is replaced in cement production to a large extent by RDF (residue derived fuels) made from shredded industrial and domestic waste. The composition of the alternative fuels is fluctuating strongly. Quality control of RDF usually takes place by sampling in the laboratory and is thus cannot be used for control of the process. RDF can be manually divided into different fractions such as films, hard plastics, paper. These fractions differ in burning and flying behavior and lead to changed conditions in the rotary kiln, so the composition of the RDF is crucial for a good cement quality. The aim of the project is to develop a traffic light system for RDF in cement production. The traffic light system will automatically summarise the composition and critical fuel properties by use of the prediction of a machine learning model. The traffic light shall be available to optimize the operation in the control room. To achieve the goal, samples are taken from the RDF stream and a few measurements (photography, near-infrared) will be used in machine learning models to predict the quality of the alternative fuel. The machine learning systems will include clustering as well as classification and will be trained using a database of measurements of individual RDF particles. The procedure will be investigated in operational tests in a cement plant in industrial use. The research project provides SMEs from the sectors of cement manufacturers, suppliers, RDF processing and machine learning with information required for the implementation of an automatic evaluation of RDF. Higher amount of information on the RDF can increase the process stability and therefore the product quality.

Images of the different fractions of substitute fuels: a) paper and cardboard (PC), b) textiles, c) 3D plastics, d) rubber, e) foams and f) films | © Fischer, Wirtz, Scherer 2023


The IGF project 22676 N of the research association VDZ gemeinnützige GmbH - VDZ Technology gGmbH, Toulouser Allee 71, 40476 Düsseldorf is funded by the Federal Ministry of Economics and Climate Protection via the AiF within the framework of the programme for the promotion of joint industrial research (IGF) on the basis of a resolution of the German Bundestag.

Person to contact

Do you have any questions on this subject?

Dr Kristina Fleiger

+49(0) 211 45 78 254

Other items of possible interest


Research projects

Method for rapid testing of the quality of flyable alternative fuels for use in the clinker burning process

As part of the research project, the German cement industry is to be provided with a utility model of a new type of apparatus for quasi-continuous incoming inspection of SRF deliveries. Based on a fast, technically robust and efficient characterisation of flight capability, humidity and optically detectable features of SRF, a system shall be developed, constructed and tested in practice.

Learn more


Research projects

Investigation of the robustness of AI-applications for process optimisation in cement manufacturing

AI applications or machine learning applications such as soft sensors or assistance systems for production controllers represent promising solutions for process control and optimisation. However, this requires robust AI applications that do not jeopardise the operational safety of the complex production facilities in the cement industry.

Learn more


Research projects

Increased use of alternative fuel in the main firing system of rotary cement kilns

The aim of the project was to define the sensitivities of and relationships between the various influencing factors in a form applicable to plants in general. This was achieved on the basis of plant experiences, as well as on existing and new plant measurements and CFD simulation.

Learn more

Related literature

Random forest classifier and neural network for fraction identification of refuse-derived fuel images

Fischer, J.; Wirtz, S.; Scherer, V.
Fuel, Volume 341, 1 June 2023, 127712

Find out more

Thank you for your interest in our publication: