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Photovoltaic (PV) plants typically suffer from a significant degradation in performance over time due to multiple factors. Operation and maintenance systems aim at increasing the efficiency and profitability of PV plants by analyzing the monitoring data and by applying data-driven methods for assessing the causes of such performance degradation. Two main classes of degradation exist, being it either gradual or a sudden anomaly in the PV system. This has motivated our work to develop and implement statistical methods that can reliably and accurately detect the performance issues in a cost-effective manner. In this paper, we introduce different approaches for both gradual degradation assessment and anomaly detection. Depending on the data available in the PV plant monitoring system, the appropriate method for each degradation class can be selected. The performance of the introduced methods is demonstrated on data from three different PV plants located in Slovenia and Italy monitored for several years. Our work has led us to conclude that the introduced approaches can contribute to the prompt and accurate identification of both gradual degradation and sudden anomalies in PV plants.

With the growing significance of printed sensors on the electronics market, new demands on quality and reproducibility have arisen. While most printing processes on standard substrates (e.g., Polyethylene terephthalate (PET)) are well-defined, the printing on substrates with rather porous, fibrous and rough surfaces (e.g., uncoated paper) contains new challenges. Especially in the case of inkjet-printing and other deposition techniques that require low-viscous nanoparticle inks the solvents and deposition materials might be absorbed, inhibiting the formation of homogeneous conductive layers. As part of this work, the sheet resistance of sintered inkjet-printed conductive silver (Ag-) nanoparticle cross structures on two different, commercially available, uncoated paper substrates using Van-der-Pauw's method is evaluated. The results are compared to the conductivity of well-studied, white heat stabilised and treated PET foil. While the sheet resistance on PET substrate is highly reproducible and the variations are solely process-dependent, the sheet resistance on uncoated paper depends more on the substrate properties themselves. The results indicate that the achievable conductivity as well as the reproducibility decrease with increasing substrate porosity and fibrousness.

Anomaly detection is becoming increasingly important to enhance reliability and resiliency in the Industry 4.0 framework. In this work, we investigate different methods for anomaly detection on in-production manufacturing machines taking into account their variability, both in operation and in wear conditions. We demonstrate how the nature of the available data, featuring any anomaly or not, is of importance for the algorithmic choice, discussing both statistical machine learning methods and control charts. We finally develop methods for automatic anomaly detection, which obtain a recall close to one on our data. Our developed methods are designed not to rely on a continuous recalibration and hand-tuning by the machine user, thereby allowing their deployment in an in-production environment robustly and efficiently.

An inkjet- and 3D-printed capacitive sensor system with an all-digital and flexible sensor read-out hardware is reported. It enables spectrometer devices with significantly reduced device outlines and costs. The sensor is developed as multilayer inkjet-printed electrode structure on a 3D-printed copper housing. Very high required position resolutions of r e s p o s < 50 nm and a wide measurement range of r m = 1000 μ m at an offset of d 0 = 1000 μ m in the considered spectrometers motivate this work. The read-out hardware provides high sampling rates of up to r s ≈ 10 ns and enables the generation of trigger signals, i.e., the mirror control signal, without a time lag. The read-out circuitry is designed as a carrier frequency system, which enables flexible choices of bandwidth and measurement signal frequency. It thus allows for separation in frequency from coupling parasitics, i.e., other frequencies present in the device under test, and makes the read-out quasi-noise-immune.