000099185 001__ 99185
000099185 005__ 20230323131626.0
000099185 0247_ $$2doi$$a10.3390/app10249154
000099185 0248_ $$2sideral$$a122686
000099185 037__ $$aART-2020-122686
000099185 041__ $$aeng
000099185 100__ $$0(orcid)0000-0002-2908-8697$$aMorella, P.
000099185 245__ $$aDevelopment of a new kpi for the economic quantification of six big losses and its implementation in a cyber physical system
000099185 260__ $$c2020
000099185 5060_ $$aAccess copy available to the general public$$fUnrestricted
000099185 5203_ $$aThe purpose of this work is to develop a new Key Performance Indicator (KPI) that can quantify the cost of Six Big Losses developed by Nakajima and implements it in a Cyber Physical System (CPS), achieving a real-time monitorization of the KPI. This paper follows the methodology explained below. A cost model has been used to accurately develop this indicator together with the Six Big Losses description. At the same time, the machine tool has been integrated into a CPS, enhancing the real-time data acquisition, using the Industry 4.0 technologies. Once the KPI has been defined, we have developed the software that can turn these real-time data into relevant information (using Python) through the calculation of our indicator. Finally, we have carried out a case of study showing our new KPI results and comparing them to other indicators related with the Six Big Losses but in different dimensions. As a result, our research quantifies economically the Six Big Losses, enhances the detection of the bigger ones to improve them, and enlightens the importance of paying attention to different dimensions, mainly, the productive, sustainable, and economic at the same time.
000099185 540__ $$9info:eu-repo/semantics/openAccess$$aby$$uhttp://creativecommons.org/licenses/by/3.0/es/
000099185 590__ $$a2.679$$b2020
000099185 591__ $$aPHYSICS, APPLIED$$b73 / 160 = 0.456$$c2020$$dQ2$$eT2
000099185 591__ $$aENGINEERING, MULTIDISCIPLINARY$$b38 / 91 = 0.418$$c2020$$dQ2$$eT2
000099185 591__ $$aCHEMISTRY, MULTIDISCIPLINARY$$b101 / 178 = 0.567$$c2020$$dQ3$$eT2
000099185 591__ $$aMATERIALS SCIENCE, MULTIDISCIPLINARY$$b201 / 333 = 0.604$$c2020$$dQ3$$eT2
000099185 592__ $$a0.435$$b2020
000099185 593__ $$aComputer Science Applications$$c2020$$dQ2
000099185 593__ $$aEngineering (miscellaneous)$$c2020$$dQ2
000099185 593__ $$aProcess Chemistry and Technology$$c2020$$dQ2
000099185 593__ $$aInstrumentation$$c2020$$dQ2
000099185 593__ $$aMaterials Science (miscellaneous)$$c2020$$dQ2
000099185 593__ $$aFluid Flow and Transfer Processes$$c2020$$dQ2
000099185 655_4 $$ainfo:eu-repo/semantics/article$$vinfo:eu-repo/semantics/publishedVersion
000099185 700__ $$0(orcid)0000-0003-1401-6495$$aLambán, M.P.$$uUniversidad de Zaragoza
000099185 700__ $$0(orcid)0000-0002-0692-5982$$aRoyo, J.$$uUniversidad de Zaragoza
000099185 700__ $$0(orcid)0000-0002-0321-7905$$aSánchez, J.C.
000099185 700__ $$aLatapia, J.
000099185 7102_ $$15002$$2515$$aUniversidad de Zaragoza$$bDpto. Ingeniería Diseño Fabri.$$cÁrea Ing. Procesos Fabricación
000099185 773__ $$g10, 24 (2020), 9154 [17 pp]$$pAppl. sci.$$tApplied Sciences (Switzerland)$$x2076-3417
000099185 8564_ $$s635107$$uhttps://zaguan.unizar.es/record/99185/files/texto_completo.pdf$$yVersión publicada
000099185 8564_ $$s2534772$$uhttps://zaguan.unizar.es/record/99185/files/texto_completo.jpg?subformat=icon$$xicon$$yVersión publicada
000099185 909CO $$ooai:zaguan.unizar.es:99185$$particulos$$pdriver
000099185 951__ $$a2023-03-23-12:58:37
000099185 980__ $$aARTICLE