## 1 Introduction
### Applications of Split-Plot Factorials  
Split-plot factorials were first invented by [PERSON] (1984) for applications in agriculture, when he was studying the impact of different fertilizing methods on the crop yield of plots of land and smaller patches within these plots. Hence, the terms split-plot, whole plot, and sub-plot. Just a few years later, [PERSON] (1986) highlighted the usefulness and applicability of split-plot experiments essentially for almost any sector of science and technology. As previously mentioned though, the popular use of split-plots in the industry was also accompanied very often by false analysis of the data. Regardless, however, of whether the design and analysis had been performed in the correct way or not, the popularity of these factorials highlights the need for the existence of simple and explicit instruction for practitioners working with them. The classic examples of applications of split-plots usually come from the chemical, processing, and manufacturing industries. Many of these examples describe the study of the significance of factors and factor interactions affecting responses like the water resistance of wood surfaces ([PERSON] _et al._, 2007; [PERSON] _et al._, 2007), the image quality in printing processes ([PERSON] _et al._, 2007), the strength of a plastic material prepared following different recipes ([PERSON] _et al._, 2007), the corrosion resistance of steel bars subjected to different treatment conditions ([PERSON] _et al._, 2007), the strength of steel subjected to normalization treatment ([PERSON] _et al._, 2007), and the wettability of paper subjected to plasma treatment for increasing the paper's susceptibility to ink ([PERSON] _et al._, 2007). In the field of analytical chemistry, the determination of chromium VI ([PERSON] _et al._, 2007) and lead ([PERSON] _et al._, 2007) for specific analytical methods was optimized using split-plot experiments. More recently, many other scientific and technological fields have been exploring the application of split-plots. For instance, split-plots have been applied in the field of biology for investigating the in vivo effect of a drug on gene expression in different tissues ([PERSON] _et al._, 2007), in pharmaceutical science for studying the influence of polymeric composition of films and the process conditions related to their preparation on the homogeneity of drugs dispersed in the polymeric matrix ([PERSON] _et al._, 2007), in food science for studying the extraction of carotenoids from mango pulp using the bio-refinery concept ([PERSON] _et al._, 2007), and in maritime science for studying the effects of climate change on macrolalgae ([PERSON] _et al._, 2007). The diversity of the fields which can benefit from split-plot factorials becomes apparent. As mentioned earlier, factorial experiments are ideal to use as an efficient way of experimentation when there is a lack of available information and, thus, many factors which may potentially affect a response should be screened. Recycling of solar cells is a good example of a relatively recent research area with limited literature available. Factorial experiments can, therefore, play a significant role in assisting its development. More specifically, today, 4.5% of global electricity production comes from photovoltaic (PV) systems ([PERSON] _et al._, 2007). In order to stay in alignment with the International Energy Agency's \"Net Zero Emissions Scenario by 2050\", the global electricity production from PV has to reach 8300 TWh in 2030 ([PERSON] _et al._, 2007). One of the promising PV technologies due to its high energy conversion efficiency and low use of materials is the thin-film technology based on a Copper Indium Gallium diSelenide (CIGS) semiconductor ([PERSON] _et al._, 2007). Investments for the industrial production of CIGS PV have already been supported in Europe by the EU ([PERSON] _et al._, 2007).