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Papers by Bernhard Oberegger

Springer eBooks, 2017

Betriebliche Informationssysteme sollen Fuhrungskrafte auf allen hierarchischen Ebenen durch ents... more Betriebliche Informationssysteme sollen Fuhrungskrafte auf allen hierarchischen Ebenen durch entscheidungsorientierte Informationen fur das strategische und operative Management unterstutzen. Wir bezeichnen betriebliche Informationssysteme als adaptive Assistenzsysteme, wenn sie den Entscheidungstragern umfassende Informationen uber bestimmte definierte Entscheidungssachverhalte liefern, indem sie an vielfaltige Entscheidungssituationen schnell anpassbar und fur komplexe Entscheidungsprobleme gut nutzbar sind.

Journal of Manufacturing Processes

International Journal of Simulation and Process Modelling, 2022

Lecture Notes in Electrical Engineering, 2020

The Electronic Components and Systems industry (ECS) is characterized by long lead times and high... more The Electronic Components and Systems industry (ECS) is characterized by long lead times and high market volatility. Besides fast technological development within this industry, cyclic market up-and downturns are influencing the semiconductor market. Therefore, adequate capacity and inventory management as well as continuous process improvements are important success factors for semiconductor companies to be competitive. In this study, the authors focus on a manufacturing excellence approach to increase front-end supply reliability and the availability of inventory within the customer order decoupling point. Here, development and manufacturing processes must be designed in a way that highest levels of product quality, flexibility, time and costs are reached. The purpose of this study is to explore the impact of return on quality in manufacturing systems. Therefore, multimethod simulation modelling including discrete-event and system dynamics simulation is applied.

International Conference on Knowledge Management and Knowledge Technologies, 2016

In the field of manufacturing systems automated data acquisition and development of technological... more In the field of manufacturing systems automated data acquisition and development of technological innovations like manufacturing execution systems (MES), Enterprise Resource Planning (ERP), Advanced Planning Systems (APS) and new trends in Big Data and Business Intelligence (BI) have given rise to new applications and methods of existing decision support technologies. Today manufacturers need an adaptive system that helps to react and adapt to the constantly changing business environment. The internal data processing system of a company can only offer minimum support because it is related to transactions. In this case, decision support systems (DSS) combine human skills with the capabilities of computers to provide efficient management of data, reporting, analytics, modeling and planning issues. DSS provide a distinction between structured, semi structured and unstructured data. In particular, a DSS reduces the quantity of data to a high quality structured amount; due to this, decisions are made to support the manufacturing process. In addition, the goal of these systems is to avoid problems within the production process even before they emerge. This paper gives an overview of the state-ofthe-art literature on DSS and describes current techniques of relevant DSS applications within manufacturing environments.

Full-waveform inversion (FWI) aims to resolve an ill-posed non-linear optimization problem in ord... more Full-waveform inversion (FWI) aims to resolve an ill-posed non-linear optimization problem in order to retrieve unknown subsurface model parameters with high resolution from seismic data. The non-linearity, in the absence of low frequencies from the recorded seismic signal, tends to increase, especially for large-velocity structures, like salt bodies and the sediments beneath them, and often prevents the inversion from obtaining an adequate model. To alleviate the ill-posedness of FWI for salt-bodies, we propose to utilize model regularization in order to promote a limited variation in the inverted model and a salt-flooding regularization from the top of the salt (without picking). On that account, we split the optimization problem into two parts: first, we minimize the data misfit and the total variation in the model, seeking to achieve an inverted model with sharp interfaces; and second, we penalize sharp velocity drops in the model by a computational flooding of the velocity field. Unlike conventional industrial salt flooding, our proposed technique requires minimal human intervention and no information whatsoever about the top of the salt. Those features are demonstrated on a dataset of the Sigsbee2A model in which the lowest available frequency is 3 Hz. We retrieve most of the salt region and also some of the fine sedimentary layering beneath the salt.

In order to remain competitive in the digital transformed economic world, the perfect match of su... more In order to remain competitive in the digital transformed economic world, the perfect match of supply and demand through supply chain and operations management is of essential importance. Flexibility, quality, costs and customer satisfaction are of major interest for companies. Programs aimed at improving these factors are often launched under the label ”Operational Excellence” (OPEX), which literally means ”excellent operational performance” [Dahm and Brückner 2014]. The pursuit of operational excellence contributes significantly to the success of companies [Issar and Navon 2016] and is intended to secure long-term survival [Dahm and Brückner 2014]. The aim of this work is to evaluate how decision support systems can help to achieve operational excellence. For this purpose, literature was analyzed to derive requirements for decision support via an OPEX framework in manufacturing systems.

IFAC-PapersOnLine, 2019

Abstract Production processes in the semiconductor industry (e.g. wafer production) are very comp... more Abstract Production processes in the semiconductor industry (e.g. wafer production) are very complex. They are characterized by a high product variety, low-volume production, high cycle time variability and diversity in lot priorities. Low prices and low profit margins lead to immense competitive pressure and semiconductor manufacturers have to bring their products to the market with short lead times according to their contractual agreements. To meet customer requirements in terms of quantity, cost and lead time, high priority lots are pushed through the factory as quickly as possible. This prioritization of certain lots affects the other lots in the line. This results in longer lead times for the non-priority lots and may require additional setup operations. We build a queueing network model to model the manufacturing system under study and develop a hybrid decomposition method to analyse it. We optimize diverse configurations of the system under different contractual agreements regarding lead times/penalty costs.

Industrie 4.0 als unternehmerische Gestaltungsaufgabe, 2016

International Journal of Simulation Modelling

The purpose of this paper is to present an applicable approach for the valuation of in-plant logi... more The purpose of this paper is to present an applicable approach for the valuation of in-plant logistics efficiency. Therefore, we developed a time-based efficiency concept that considers all relevant time losses when executing production logistics processes. The occurring delays are captured in real-time using modern auto-ID-technologies. For the valuation and improvement of in-plant logistics efficiency, we propose to use simulation modelling to investigate the cause-effect relations in the production system in advance. Thus, a discrete event simulation model has been constructed to model the workflow of a production system with discrete manufacturing processes and its in-plant logistics processes. The aim of the provided simulation study is to prove the functionality and to verify the applicability of the current approach in business practice.