Adoption of logistic principles in WOODY-biomass energy clusters

Zsolt Tegla (), Istvan Hagen, Ervin Hollo and Katalin Takacs-Gyorgy
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Zsolt Tegla: Karoly Robert College, Institute of Business Sciences, Hungary
Istvan Hagen: Karoly Robert College, Institute of Business Sciences, Hungary
Ervin Hollo: KR Spektrum Ltd., Hungary
Katalin Takacs-Gyorgy: Karoly Robert College, Institute of Business Sciences, Hungary

Review of Applied Socio-Economic Research, 2012, vol. 4, issue 2, 236-246

Abstract: Applying logistics principles within production technologies is not an objective or not even a magic potion. It is a tool for getting and maintaining some competitive advantage. This is true in the case of production technology of arboreal biomass for heating purposes too. The produce is not only to compete with other arable land outputs (food or forage), but the energy gained through burning it should be competitive compared to energy coming from other sources. Our investigation dealt with questions related to the raw material provisioning of a virtual energy-cluster. We examined those elements of production technology, in which the logistics methods and the optimisation of the flow of materials showed tangible results. The competitiveness of actors in the economic sphere is significantly determined by the effectiveness of their provisioning chain. The optimal solution to these tasks is provided by that combination of apparatus wherein both the 'time factor' (JIT) and the efforts to minimise costs are realised. The provisioning chain we examined comprised of harvesting, transport and storage process elements; of these, harvesting in particular, due to its exceptionally high operating costs. We sought an answer to the question of whether it is better to transport the raw material directly to the processing plant or indirectly after temporary storage. In the case of indirect delivery, where should storage facilities be established and how many should there be, in the interests of minimising total costs? We created and utilised a simulation model to solve the task.

Keywords: logistics; energy-cluster; optimization; harvesting; simulation model (search for similar items in EconPapers)
JEL-codes: C67 Q42 Q51 (search for similar items in EconPapers)
Date: 2012
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