The effect of three handheld ultrasonic devices for the pretreatment of stains on textiles was evaluated under household conditions. Twenty soiled textiles were treated and the mean increase of lightness ΔL* of the soiled textiles was used as a measure for the cleaning effect. It was shown that the combination of a pretreatment and a washing cycle at 20 °C yields a higher mean increase of lightness, ΔL* = 19.5, compared to a 40 °C washing cycle without pretreatment, ΔL* = 15.3. The effect is most pronounced for mixtures consisting of oily soils with pigments, ΔL* = 25.1. During the pretreatment, the soil was soaked in a detergent solution and the effect of soaking was measured separately.

The proper cleaning of used dishes provides an essential means to maintain a sufficient hygiene level on food contact surfaces. However, little is known on the microbiological quality of domestic dishwashers themselves, especially in relation to consumer habits. This study investigated dishwashers in German households to analyse the number and composition of microbial colonisers and their putative impact on dishwashing hygiene. Although the microbiological status of dishwashers appeared to depend on multiple factors, data suggest that a trend towards lower temperatures might effect in a decreased hygiene.

Lowering water temperatures in the cleaning step of a dishwashing program to 30°C leads to reduced energy consumption and decreased cleaning performances on persistently soiled dish- and cookware and of fatty soilings on hydrophobic surfaces. This study focusses on the question if the observed decline of the cleaning performance can be compensated for by aligning the formulation of the dishwashing detergent. A Design of experiments-method is used to quantify the effects of detergent components on the cleaning performance in mathematical models. The calculated models are used to adjust the amount of those components in a detergent formulation that increases the cleaning performance in low temperature electric household dishwashing. The modeled formulation has been verified in practical experiments.

In the past years some researches were conducted to model laundryw ashing in the automatic washing machine.T he most studies,h owever,w ere focused to some aspects of the automatic laundryw ashing (e.g.s pinning cycle)a nd not on the washing process as whole.I nt his paper am odel of aw ashing machine is presented that is based on measured data of 9different washing machines with rated capacityb etween 5kga nd 11 kg,w hich are produced by six different manufacturers.T he proposed approach is based on multiple linear regression analysis to extract the systematic,m odel independent behavior of washing machines and is used to calculate the consumption of the water,e nergya nd detergent in dependence of the rated capacity, washing temperature,d uration of the main wash,l oad size and washing performance.

The purpose of this study was to utilize NIR spectrometry to develop a novel method to detect and determine concentrations of different soils in dishwashing liquor during automatic dishwashing in real-time. If it is possible to differentiate between soils, this could be an opportunity to react specifically to them (e.g. by increasing the water temperature if fat components are not sufficiently emulsifying). The possibility of an automatic adaptation of the dishwashing process to different soils and soil levels could lead to a shorter, more environmentally friendly and cost-reducing process. In a first approach, an emulsion containing three soil types (oatmeal, egg-yolk and butterfat), water and detergent were used to develop NIR spectrometry prediction models. Transmittance spectra obtained with an Fourier transform near infrared (FT-NIR) spectrometer of testing standards of 76 automatic dishwashing cycles with seven samples per cycle were taken at various times during the main washing process for calibration (and validation) of the NIR spectrometry prediction models. The spectra were pretreated to develop NIR spectrometry prediction models for each type of soil using the partial least squares regression method with cross-validation. Overall, the coefficients of determination in cross-validation are R 2 > 0.92 for all NIR spectrometry prediction models developed. The results of the prediction models developed show that NIR spectrometry technology is a promising method to predict different levels of predefined soils in dishwashing liquor. The NIR spectrometry models were applied to an automatic dishwashing process with soiled dishes instead of emulsions containing soils to test their applicability. The resulting dishwashing process could be tracked in real-time by the dissolved soil concentrations, observed in the dishwashing liquor.