MEDEP: Maintenance Event Detection for Multivariate Time Series Based on the PELT Approach.

Predictive Maintenance (PdM) is one of the most important applications of advanced data science in Industry 4.0, aiming to facilitate manufacturing processes. To build PdM models, sufficient data, such as condition monitoring and maintenance data of the industrial application, are required. However, collecting maintenance data is complex and challenging as it requires human involvement and expertise. Due to time constraints, motivating workers to provide comprehensive labeled data is very challenging, and thus maintenance data are mostly incomplete or even completely missing. In addition to these aspects, a lot of condition monitoring data-sets exist, but only very few labeled small maintenance data-sets can be found. Hence, our proposed solution can provide additional labels and offer new research possibilities for these data-sets. To address this challenge, we introduce MEDEP, a novel maintenance event detection framework based on the Pruned Exact Linear Time (PELT) approach, promising a low false-positive (FP) rate and high accuracy results in general. MEDEP could help to automatically detect performed maintenance events from the deviations in the condition monitoring data. A heuristic method is proposed as an extension to the PELT approach consisting of the following two steps: (1) mean threshold for multivariate time series and (2) distribution threshold analysis based on the complexity-invariant metric. We validate and compare MEDEP on the Microsoft Azure Predictive Maintenance data-set and data from a real-world use case in the welding industry. The experimental outcomes of the proposed approach resulted in a superior performance with an FP rate of around 10% on average and high sensitivity and accuracy results.

The impact of clay-based hypoxia mimetic hydrogel on human fibroblasts of the periodontal soft tissue.

Thixotropic clays have favorable properties for tissue regeneration. Hypoxia mimetic agents showed promising results in pre-clinical models for hard and soft tissue regeneration. It is unclear if clays can be used as carrier for hypoxia mimetic agent in a periodontal regenerative setting. Here, we tested the response of human fibroblasts of the periodontal soft tissue to synthetic clay hydrogels and assessed hypoxia mimetic agent release. Cells were cultured on synthetic clay hydrogels (5.00%-0.15%). We assessed viability and differentiation capacity with resazurin-based toxicity assays, MTT staining, Live-Dead staining, and alkaline phosphatase staining. To reveal the response of fibroblasts to hypoxia mimetic agent-loaded clay hydrogels, cells were exposed to clay supplemented with dimethyloxalylglycine, deferoxamine, l-mimosine, and CoCl2. Supernatants from hypoxia mimetic agent-loaded clay hydrogels were harvested and replaced with medium at hour 1, 3, 6, 24, 48, and 72. To reveal the hypoxia mimetic capacity of supernatants, vascular endothelial growth factor production in the fibroblasts was assessed in the culture medium. Our data show that clay did not induce relevant toxic effects in the fibroblasts which remained capable to differentiate into alkaline phosphatase-positive cells at the relevant concentrations. Fibroblasts cultured on clay hydrogel loaded with dimethyloxalylglycine, deferoxamine, l-mimosine, and CoCl2 remained vital, however, no significant increase in vascular endothelial growth factor levels was found in the culture medium. Only dimethyloxalylglycine-loaded clay supernatants taken in the first hours stimulated vascular endothelial growth factor production in fibroblasts. In conclusion no pronounced toxic effects of synthetic clay were observed. Supplementation with dimethyloxalylglycine leads to hypoxia mimetic activity. This pilot study provides first insights into the impact of synthetic clay on periodontal tissue.