Jan Reschke

Der Digitale Schatten in der Auftragsabwicklung

Kurzfassung Im Kontext Industrie 4.0 kommt der Erfassung der anfallenden Daten in der Produktion und deren Nutzung eine zentrale Bedeutung zu. Analysen betrieblicher Daten, welche auf verschiedenen Ebenen generiert werden, lassen Rückschlüsse und Erkenntnisse zur besseren Entscheidungsfindung zu. Die Basis für den Einsatz von Verfahren der Datenanalyse und -auswertung stellt ein hinreichend genaues Abbild der relevanten Daten – der Digitale Schatten – in der Auftragsabwicklung, Produktion, Entwicklung oder angrenzenden Bereichen dar. Im Rahmen des vorliegenden Beitrags wird ein Modell für den Digitalen Schatten in der Auftragsabwicklung vorgestellt, welches die Basis für die Implementierung von Methoden der Datenanalytik darstellt.

Big Data Technology for Resilient Failure Management in Production Systems

Due to a growing complexity within value chains the susceptibility to failures in production processes increases. The research project BigPro explores the applicability of Big Data to realize a pro-active failure management in production systems. The BigPro-platform complements structured production data and unstructured human data to improve failure management. In a novel approach, the aggregated data is analyzed for reoccurring patterns that indicate possible failures of the production system, known from historic failure events. These patterns are linked to failures and respective countermeasures and documented in a catalog. The project results are validated in three industrial use cases.

Cyber Physical Production Control

Currently the control of constantly increasing market dynamics and the simultaneously increasing individualization of process chains represent the central challenges for manufacturing companies. These challenges are caused by a lack of transparency in production planning, non-real-time processing of data as well as poor communication between the planning and control level. The research project ProSense addresses this problem and intends to eliminate the current problems in production by developing a high-resolution, adaptive production control based on cybernetic support systems and intelligent sensors. Through the development of a cyber-physical production control as one part of the project, which forms the basis for an innovative self-optimizing advanced planning system, ProSense provides a contribution to accomplish the goals of industry 4.0.

Big data implementation for the reaction management in manufacturing systems

Big Data is one of the most discussed trend themes worldwide in both research community and industrial practice. Thus, researchers as well as company representatives focus on the study of Big Data technologies and the potentials deriving from gaining and structuring data. In this paper, we firstly conduct a literature review. Then, we describe the approach to implement reaction management in manufacturing environment before we finally report on a research project aiming at applying Big Data technologies in producing companies. The project goal is to develop a real-time capable platform in consideration of industrial requirements. With the help of a Big Data platform, producing companies will be enabled to use several applications like e.g. monitoring, prognosis or reaction. By receiving appropriate measures defined in the platform, the ability of producing companies to detect and to react proactively to failures deriving in manufacturing will sustainably increase.

Supply Chain 4.0: Logistikdienstleister im Kontext der vierten industriellen Revolution

Der Digitalisierungsprozess in der Industrie eroffnet der Wirtschaft ein riesiges Innovationspotenzial, mit der sie ihre Wettschopfungs- und Leistungsfahigkeit deutlich verbessern kann. Im Mittelpunkt des Zukunftskonzepts Industrie 4.0 steht zurzeit die Effizient der Produktionsprozesse. Die Verfugbarkeit von Echtzeitdaten an samtlichen Schnittstellen der Supply Chain eroffnet auch Logistikdienstleistern Moglichkeiten, an aktuellen Entwicklungen zu partizipieren und ihr Leistungsportfolio optimal zu gestalten. Der FIR e. V. an der RWTH Aachen schafft mit dem Begriff „Enterprise-Integration“ einen Ordnungsrahmen fur Logistikdienstleister, der drei interdisziplinare Forschungsfelder vereint und auf eine vollstandig integrative Gestaltung komplexer Wertschopfungssysteme fokussiert, um zukunftige Herausforderungen im Kontext Industrie 4.0 zu meistern.

Discrete Event Simulation – A New Approach to Multi-level Capacitated Planning?

Discrete Event Simulation (DES) is a well-known approach to simulate production environments. However it was rarely used for operative planning processes and to our knowledge never in terms of multiple disposition levels. In this paper we develop the necessary adjustments to use DES for this purpose and show some theoretical advantages.