activity
20232025
most citedDigital Twins of Business Processes as Enablers for IT / OT Integration

6 citations · 9 across the 5 of their papers we have counts for

collaborators

5 papers

cs.LG2025

Energy Optimized Piecewise Polynomial Approximation Utilizing Modern Machine Learning Optimizers

Hannes Waclawek, Stefan Huber

This work explores an extension of machine learning-optimized piecewise polynomial approximation by incorporating energy optimization as an additional objective. Traditional closed…

cs.LG2024

Machine Learning Optimized Orthogonal Basis Piecewise Polynomial Approximation

Hannes Waclawek, Stefan Huber

Piecewise Polynomials (PPs) are utilized in several engineering disciplines, like trajectory planning, to approximate position profiles given in the form of a set of points. While…

cs.SE2023★ 6 cited

Digital Twins of Business Processes as Enablers for IT / OT Integration

Hannes Waclawek, Georg Schäfer, Christoph Binder +2

The vision of Industry 4.0 introduces new requirements to Operational Technology (OT) systems. Solutions for these requirements already exist in the Information Technology (IT) wor…

cs.SE2023

IT/OT Integration by Design

Georg Schäfer, Hannes Waclawek, Sarah Riedmann +3

The four Industry 4.0 design principles information transparency, technical assistance, interconnection, and decentralized decisions pose challenges in integrating information tech…

cs.LG2023★ 3 cited

-continuous Spline Approximation with TensorFlow Gradient Descent Optimizers

Stefan Huber, Hannes Waclawek

In this work we present an "out-of-the-box" application of Machine Learning (ML) optimizers for an industrial optimization problem. We introduce a piecewise polynomial model (splin…