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Die Projektauswahl stellt eine Herausforderung insbesondere für mittelständische Industrieunternehmen dar. Abhängigkeiten verschiedener Alternativen und vorgegebene Investitionsbudgets führen bei Anwendung von in der Praxis standardmäßig eingesetzten Verfahren regelmäßig zu suboptimalen Projektkombinationen. In enger Abstimmung mit einem Automobilzulieferer wurde ein Ansatz zur Projektauswahl unter Berücksichtigung von Ressourcen und laufenden Projekten entwickelt sowie technisch umgesetzt. Implementierte Praxistests belegen Verbesserungen bei der Projektauswahl, aber auch bei der Budgeteinhaltung, der Fixkostenreduzierung sowie der Angebotspreisbestimmung.
Logistic activity, in particular transportation, produces green house gases (GHG). For different purposes GHG need to be allocated to objects. This paper studies how to allocate the GHG volume of a transportation process (delivery tour) to the single shipments moved by the process. First, it identifies classes of generic allocation schemes and presents 15 allocation methods. Second, since the majority of these methods has not been designed for allocating GHG, we apply and compare them in the short distance transport context within a numerical example. The aim is to study how the schemes perform according to criteria. We suggest using causality, efficiency, empty core robustness, symmetry, individual rationality, coalition stability, ease of application, and set robustness as appraisal criteria and attempt to mainstream the discussion by recommending selected allocation methods.
The assessment of greenhouse gas (GHG) emissions of supply chain activities is performed to create transparency across the supply chain and to identify emission-cutting opportunities. Literature provides several generic and case study approaches to estimate GHG emissions. But research often focuses on products. This paper sheds light on how the greenhouse performance of a fast-moving consumer goods (FMCG) distribution network depends on several (FMCG specific) variables to set up a “CO2 network footprint”. Within a quantitative computational study, the distribution network footprint of an existing FMCG manufacturer is analyzed. Three options being fundamentally able to reduce total GHG emissions are identified: number of distribution centers, performance of the engaged logistics service provider and shipment structure. First, transportation processes for the investigated FMCG manufacturer are analyzed to derive GHG emissions caused by different distribution shipments. Second, initial data are manipulated to simulate variable changes, that is, different logistics structures. Third, results are reported and analyzed to show up how different changes in logistics structures may reduce GHG, without technological propulsion or use of regenerative energy.
Distribution network design is about recommending long-term network structures in an environment where logistic variables like transportation costs or retailer order sizes dynamically change over time. The challenge for management is to recommend an optimal network configuration that will allow for longer term optimal results despite of environmental turbulences. This paper studies the robustness of cost-optimized FMCG (fast-moving consumer goods) distribution networks. It aims at observing the impact of changing variables/conditions on optimized logistic structures in terms of the optimal number and geographical locations of existing distribution centers. Five variables have been identified as relevant to the network structure. A case study approach is applied to study the robustness of an existing, typical, and optimized FMCG network. First, distribution network data of a German manufacturer of FMCG are recorded and analyzed. A quantitative model is set up to reflect the actual cost structure. Second, a cost optimal network configuration is determined as a benchmark for further analysis. Third, the variables investigated are altered to represent changes, both isolated (ceteris paribus) and in combination (scenario analysis). Each one of the variables investigated proves to be fundamentally able to suggest a change of the optimal network structure. However, the scenario analysis indicates that the expected changes will by and large compensate each other, leaving the network in near optimal condition over an extended period of time.
The recent developments in power semiconductor devices and increasing demands on reliability as well as on operation performance require innovative package technologies. Such a novel package technique based on a Planar Interconnect Technology (SiPLIT®) for power modules is introduced in this work. This package features thick Cu interconnects on a high-reliable insulating film for power semiconductor chip top contacts. Due to the conductor structure and contact technology, on-resistance and stray inductances are very low compared to state-of-the-art Al wire bonds. In addition, large area contacting improves the power cycling capability and surge current robustness significantly. These remark-able properties have been verified on several prototype modules where the manufacturing process has also been optimised in terms of cost-effectiveness, system integration and maturity for series production.
Der Gesamtenergiedurchlassgrad (g-Wert) verschiedener teiltransparenter,
gebäudeintegrierbarer Photovoltaik-Module wurde
mit und ohne Entnahme elektrischer Leistung kalorimetrisch gemessen.
Durch die Leistungsentnahme sinkt die Oberflächentemperatur
des Moduls um bis zu 4 K. Gleichzeitig reduziert sich der
g-Wert aufgrund der geringeren sekundären Wärmeabgabe. Die
Größe der Abnahme hängt von der entnommenen Leistung ab
und stimmt sehr gut mit einem einfachen, auf dem Energiesatz
basierenden Rechenmodell überein.