Analytical and economic methodology for storage of large heavyweight equipment in industrial processes
Loading...
Files
Description: Artículo principal
Identifiers
Publication date
Reading date
Collaborators
Advisors
Tutors
Editors
Journal Title
Journal ISSN
Volume Title
Publisher
Taylor & Francis
Share
Department/Institute
Keywords
Abstract
Numerous studies concerning warehouse-design methodologieshave been performed focused on the storage of products on pal-lets or of intermediate size and/or moderate weight loads. Thesestudies, however, do not provide with optimal results for indus-tries that work with equipment or objects of uncommon sizesand shapes and with large weights, which are difficult to moveand involve high costs and complex operational actions, affectingto the production processes and interfering with the logistic proc-esses or the supply-chain of a company. This study proposes ananalytical methodology using economic and technical qualitativecriteria that can be applied specifically to large and heavy equip-ment warehouses. Both quantitative aspects, such as availabilityand cost of space, and also qualitative considerations, such asflexibility requirements, impact on manufacturing process andrisks associated, are evaluated. To determine an optimum imple-mentation solution, several decision-making methods, such asElectra I & II and Analytic Hierarchy Process are employed withdue consideration of multiple criteria. The results obtained aremodulated and reinforced using a SWOT (strengths-weaknesses,opportunities- threats) and a Risk analysis to verify this singleultimate solution. The said process led to the establishment of adecision-making methodology suitable for any organization pos-sessing large-scale storage systems.
Description
Bibliographic citation
Hermoso-Orzáez, M. J., Cámara-Martínez, J., Rojas-Sola, J. I., & Gago-Calderon, A. (2019). Analytical and economic methodology for storage of large heavyweight equipment in industrial processes. Economic Research-Ekonomska Istraživanja, 33(1), 3258–3287. https://doi.org/10.1080/1331677X.2019.1696692









