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Institute
- Produktionsmanagement (115) (remove)
Steigende Energiekosten sind ein zunehmendes Risiko für Unternehmen des deutschen Maschinen- und Anlagenbaus. Die Steigerung der Energieeffizienz kann somit zukünftig zu Wettbewerbsvorteilen führen. Aufgrund der Komplexität heutiger Produktionssysteme ist eine Analyse der Wechselwirkungen von Parametern der Produktionsplanung und -steuerung (PPS) auf die Energieeffizienz notwendig, um Maßnahmen zu identifizieren, die eine Steigerung der Energieeffizienz ermöglichen.
Der vorliegende Artikel stellt die Ergebnisse einer Simulationsstudie vor, in welcher der Einfluss der Losgrößenplanung auf die Energieeffizienz im Rahmen einer mehrstufigen Mehrproduktfertigung untersucht wird. Die Ergebnisse der Studie leisten einen Beitrag zum besseren Verständnis der komplexen Zusammenhänge und können als Ausgangspunkt für weitere Untersuchungen zu Wechselwirkungen von Produktionsparametern mit der Energieeffizienz dienen.
Produktionsbedarfsplanung
(2014)
Die Eigenfertigungsplanung und -steuerung erhält als Eingangsinformation das zu realisierende Eigenfertigungsprogramm aus der Produktionsbedarfsplanung. Das Ziel der Eigenfertigungsplanung und -steuerung ist die Erstellung, Umsetzung und Kontrolle eines detaillierten Ablaufplans für die Fertigung und Montage unter Berücksichtigung der tatsächlich verfügbaren Produktionsressourcen.
Zunächst werden die Kernaufgaben der Eigenfertigungsplanung und -steuerung definiert, abschließend werden die Aufgaben in Form eines Referenzprozessmodells modelliert.
Die Fremdbezugsplanung und -steuerung erhält als Eingangsinformation das zu realisierende Fremdbezugsprogramm aus der Produktionsbedarfsplanung. In diesem Fremdbezugsprogramm ist festgelegt, welche Teile, Baugruppen und Erzeugnisse in welchen Mengen und zu welchen Terminen zu beschaffen sind.
Es werden zunächst die wesentlichen Aufgaben der Fremdbezugsplanung und -steuerung definiert. Abschließend werden die Aufgaben in ihrer zeitlogischen Abfolge in Form eines Referenzprozessmodells modelliert und dabei fertigungstypspezifisch detailliert.
Today’s manufacturers are facing numerous challenges such as highly entangled and interconnected supply chains, shortening product lifecycles and growing product complexity. They thus feel the need to adjust and adapt faster on all levels of value creation. Self-optimization as a basic principle appears a promising approach to handle complexity and unforeseen disturbances within supply chains, machines and processes. Therefore it will improve the resilience and competitiveness of manufacturing companies.
This paper gives an introduction to the concept of self-optimizing production systems. After a short historical review, the different levels of value creation from supply chain design and management to manufacturing and assembly are analyzed considering their specific demands and needs for self-optimization. Examples from each of these levels are used to illustrate the concept of self-optimization as well as to outline its potential for flexibility and productivity. This paper closes with an outlook on the current scientific work and promising new fields of action.
Der Begriff „Digitaler Schatten“ steht für ein hinreichend genaues, digitales Abbild der Prozesse, Information und Daten eines Unternehmens. Dieses Abbild wird benötigt, um eine echtzeitfähige Auswertebasis aller relevanten Daten zu schaffen, um hieraus letztendlich Handlungsempfehlungen abzuleiten. Die Bildung des Digitalen Schattens ist damit ein zentrales Handlungsfeld von Industrie 4.0 und stellt die Grundlage für alle weitergehenden Aktivitäten dar.
In recent years supply chain participants are increasingly suffering the effects of disturbances in transportation supply chains. Both, dynamics in consumer demands and global supply chains lead to a growth in unplanned supply chain events. These can cause from rather manageable disturbances through to complete break-downs of transportation chains, resulting in high follow-up and penalty costs.
Consequently, concepts for an efficient supply chain disturbance management are needed, preferably with a real-time identification and reaction to disturbance events. Therefore in the following paper the research results of the German research project Smart Logistic Grids with the focus on designing an integrated model for the real-time disturbance management in transportation supply networks are presented. This includes the introduction of elaborated classification models for disturbances and action patterns as well as an associated costs and performance measurement system. Finally, a procedure model for the disturbance management is presented.
The steady increasing of supply chain complexity due to a rising global cross-linking of production and sales regions leads to an increasing sensitivity to disturbances while in the meantime the requirements of the availability, the time of delivery and the security of supplies within the supply chain increases. To meet this challenges the security of the supply chain infrastructure and the feasibility of supply chain processes need to be ensured, despite of the high specialization within the supply chain partners, the low stock and time buffers, and the information shortcoming between supply chain partners.
In this research, a System Dynamics simulation model, based on the manufacturing supply chain model of Sterman, has been developed for representing the actual complexity and dynamic in manufacturing supply chains. Therefore, the modeled manufacturing supply chain shows the processes of a four level supply chain focusing the processes and interactions of the mid-positioned two supply chain participants. The main contribution of the work described in this paper, is the description and implementation of necessary additional modules and parameters to Sterman’s basic model for the diagnosis of disturbance impacts as well as for the realization of supply chain adjustments. Finally, the model has been simulated and examined for realistic values.
Volatile electricity prices caused by an increase of renewable energy sources push producing companies towards taking in an active role in balancing the electricity grid. Possible actions at the customer side to actively adapt to volatile energy prices are called demand response actions. In production logistics such actions can be the modification of production schedules motivated by possible economic benefits. So far, the focus in scheduling problems has been the optimization in the dimensions of quality, time and costs. This paper presents the results of a simulation study on the economic benefits of demand response actions for a generic production system.