000121345 001__ 121345
000121345 005__ 20241125101125.0
000121345 0247_ $$2doi$$a10.3390/machines11010066
000121345 0248_ $$2sideral$$a131736
000121345 037__ $$aART-2023-131736
000121345 041__ $$aeng
000121345 100__ $$0(orcid)0000-0002-4148-5759$$aMiqueo, Adrian$$uUniversidad de Zaragoza
000121345 245__ $$aMulti-Model In-Plant Logistics Using Milkruns for Flexible Assembly Systems under Disturbances: An Industry Study Case
000121345 260__ $$c2023
000121345 5060_ $$aAccess copy available to the general public$$fUnrestricted
000121345 5203_ $$aMass customisation demand requires increasingly flexible assembly operations. For the in-plant logistics of such systems, milkrun trains could present advantages under high variability conditions. This article uses an industrial study case from a global white-goods manufacturing company. A discrete events simulation model was developed to explore the performance of multi-model assembly lines using a set of operational and logistics Key Performance Indicators. Four simulation scenarios analyse the separate effects of an increased number of product models and three different sources of variability. The results show that milkruns can protect the assembly lines from upstream process disturbances.
000121345 536__ $$9info:eu-repo/grantAgreement/EC/H2020/814225/EU/DIGItal MANufacturing Technologies for Zero-defect Industry 4.0 Production/DIGIMAN4.0$$9This project has received funding from the European Union’s Horizon 2020 research and innovation program under grant agreement No H2020 814225-DIGIMAN4.0
000121345 540__ $$9info:eu-repo/semantics/openAccess$$aby$$uhttp://creativecommons.org/licenses/by/3.0/es/
000121345 590__ $$a2.1$$b2023
000121345 592__ $$a0.474$$b2023
000121345 591__ $$aENGINEERING, MECHANICAL$$b83 / 183 = 0.454$$c2023$$dQ2$$eT2
000121345 591__ $$aENGINEERING, ELECTRICAL & ELECTRONIC$$b193 / 353 = 0.547$$c2023$$dQ3$$eT2
000121345 593__ $$aElectrical and Electronic Engineering$$c2023$$dQ2
000121345 593__ $$aComputer Science (miscellaneous)$$c2023$$dQ2
000121345 593__ $$aMechanical Engineering$$c2023$$dQ2
000121345 593__ $$aControl and Systems Engineering$$c2023$$dQ2
000121345 593__ $$aIndustrial and Manufacturing Engineering$$c2023$$dQ2
000121345 593__ $$aControl and Optimization$$c2023$$dQ2
000121345 594__ $$a3.0$$b2023
000121345 655_4 $$ainfo:eu-repo/semantics/article$$vinfo:eu-repo/semantics/publishedVersion
000121345 700__ $$aGracia-Cadarso, Marcos
000121345 700__ $$0(orcid)0000-0002-3069-2736$$aTorralba, Marta
000121345 700__ $$0(orcid)0000-0001-8460-3076$$aGil-Vilda, Francisco
000121345 700__ $$0(orcid)0000-0001-7152-4117$$aYagüe-Fabra, José Antonio$$uUniversidad de Zaragoza
000121345 7102_ $$15002$$2515$$aUniversidad de Zaragoza$$bDpto. Ingeniería Diseño Fabri.$$cÁrea Ing. Procesos Fabricación
000121345 773__ $$g11, 1 (2023), 66 [21 pp.]$$pMachines (Basel)$$tMachines$$x2075-1702
000121345 8564_ $$s2767006$$uhttps://zaguan.unizar.es/record/121345/files/texto_completo.pdf$$yVersión publicada
000121345 8564_ $$s2649978$$uhttps://zaguan.unizar.es/record/121345/files/texto_completo.jpg?subformat=icon$$xicon$$yVersión publicada
000121345 909CO $$ooai:zaguan.unizar.es:121345$$particulos$$pdriver
000121345 951__ $$a2024-11-22-11:57:32
000121345 980__ $$aARTICLE