Publications

Showing 55 results for Author: Kris Villez

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Sep, 2026

Journal

Autonomous Layer Time Optimization in Large-format Additive Manufacturing through Machine Vision and Feedback Control

Proper thermal management in large-format additive manufacturing (LFAM) to maintain geometric control and mechanical integrity requires, in part, maintaining the substrate, or the previously deposited layer temperature, within a defined process window. Temperatures that are too low result in weak interlayer bonds; conversely, elevated temperatures cause geometric instabili…
Sep, 2026

Conference Paper

High-frequency parameter updates in digital twins: Report on a 2-week challenge test for fully autonomous adaptive operation of an effluent water recovery system.

Digital twins (DTs) that can predict the transient behaviour of a water treatment plant combined with buffer capacity, enable reductions in specific energy consumption (SEC) in response to time-of-use (TOU) electricity costs. The accuracy of a DT depends on the richness of its training data (Conejos Fuertes et al. 2020). However, process changes cannot easily be tested in…
Jul, 2026

Conference Paper

Rolling Root Mean Square Based Multimodal Anomaly Detection for Real Time Monitoring of Smart Grid

Reliable real-time monitoring is valuable for maintaining the operational integrity of modern electrical smart grids. Deployment of heterogeneous sensing technologies in substations has enabled high-resolution, multichannel waveform monitoring, but also introduces challenges for anomaly detection due to noise, baseline drift, and modality-dependent signal characteristics.…
Jun, 2026

Journal

Segmentation method comparison for residual fiber length measurement across tiled microscopy images

Fiber length distribution (FLD), in part, governs mechanical properties in discontinuous fiber composites, yet manual measurement methods limit the high-throughput characterization needed for materials design optimization. This study compares deep learning segmentation approaches for automated FLD measurement in large-field microscopy, evaluating how method choice affects…
Mar, 2026

Journal

Predicting initial trans-membrane pressure across cycles in the ultrafiltration process using random forest

With growing freshwater scarcity, direct potable reuse (DPR) systems that reclaim wastewater for drinking are becoming increasingly important for sustainable water supply. Reliable operation requires minimizing downtime in ultrafiltration (UF) units, where membrane fouling leads to elevated trans-membrane pressure (TMP). This study develops data-driven regression models ba…
Mar, 2026

Conference Paper

Data about data – when, why and how metadata can support the digital plant

A structured approach for recording data quality and contextual information about how and why a signal exists – i.e. metadata – is central to interpret and use sensor data correctly. This is becoming increasingly important with the global trend with data-driven applications such as digital twins and AI-models. But a structured metadata collection and organization of sensor…
Mar, 2026

Conference Paper

Evaluating the Hybrid Modelling Competition: A Step Towards Developing Good Modelling Practice

Hybrid modelling, a combination of mechanistic and data-driven modelling, is a promis¬ing approach to advance current mathematical models towards improved deci¬sion support tools for today's water-related challenges. Researchers have been develop¬ing guidelines or references for good modelling practices in the water field for mecha¬nistic (Rieger et al., 2012) and data-dri…
Mar, 2026

Conference Paper

Accurate and Fast Anomaly Detection in Additive Composite-Based Manufacturing using Thermal Cameras

Today, large-scale additive manufacturing with plastics and composite materials requires continuous monitoring by experienced staff to prevent, detect and correct anomalous events affecting the performance of the printed part. We address the complexity of this demanding task by designing a camera-based anomaly detection system utilizing probabilistic principal component an…
Mar, 2026

Conference Paper

Intelligent Manufacturing Support: Specialized LLMs for Composite Material Processing and Equipment Operation

Engineering educational curriculum and standards cover many material and manufacturing options. However, engineers and designers are often unfamiliar with certain composite materials or manufacturing techniques. Large language models (LLMs) could potentially bridge the gap. Their capacity to store and retrieve data from large databases provides them with a breadth of knowl…
Mar, 2026

Conference Paper

Predicting Initial Trans-Membrane Pressure for Optimized Operations in UF Unit Using Random Forest

With the growing scarcity of freshwater, innovative process design mechanisms like Ultra-filtration(UF) units are increasingly gaining attention among water treatment utilities to address the rising demand. Ensuring reliable water production necessitates efficient resource utilization, minimizing downtime in UF systems. Recent advancements in machine learning (ML) have ena…
Mar, 2026

Conference Paper

A DATA EFFICIENT SPARSE MODELING FRAMEWORK FOR POWER ESTIMATION IN WATER TREATMENT SENSING OPERATIONS

With increasing freshwater scarcity, advanced process design mechanisms such as Closed-Circuit Reverse Osmosis (CCRO) and Digital/Physical Twin systems are gaining traction in water treatment and reuse operations. While digital and physical twin models enable improved system insight and control, their development is often expensive and computationally intensive, requiring…
Mar, 2026

Conference Paper

Predicting Initial Trans-Membrane Pressure for Optimized Operations in UF Unit Using Random Forest

With the growing scarcity of freshwater, innovative process design mechanisms like Reverse Osmosis (RO) are increasingly gaining attention among water treatment utilities to address the rising demand. Ensuring reliable water production necessitates efficient resource utilization, minimizing downtime in (ultra-filtration) UF systems. Recent advancements in machine learning…

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Publications

Autonomous Layer Time Optimization in Large-format Additive Manufacturing through Machine Vision and Feedback Control

High-frequency parameter updates in digital twins: Report on a 2-week challenge test for fully autonomous adaptive operation of an effluent water recovery system.

Rolling Root Mean Square Based Multimodal Anomaly Detection for Real Time Monitoring of Smart Grid

Segmentation method comparison for residual fiber length measurement across tiled microscopy images

Predicting initial trans-membrane pressure across cycles in the ultrafiltration process using random forest

Data about data – when, why and how metadata can support the digital plant

Evaluating the Hybrid Modelling Competition: A Step Towards Developing Good Modelling Practice

Accurate and Fast Anomaly Detection in Additive Composite-Based Manufacturing using Thermal Cameras

Intelligent Manufacturing Support: Specialized LLMs for Composite Material Processing and Equipment Operation

Predicting Initial Trans-Membrane Pressure for Optimized Operations in UF Unit Using Random Forest

A DATA EFFICIENT SPARSE MODELING FRAMEWORK FOR POWER ESTIMATION IN WATER TREATMENT SENSING OPERATIONS

Predicting Initial Trans-Membrane Pressure for Optimized Operations in UF Unit Using Random Forest