{"id":5272,"date":"2024-10-10T10:40:18","date_gmt":"2024-10-10T08:40:18","guid":{"rendered":"https:\/\/www.mosaicfactor.com\/solution\/models-doptimitzacio\/"},"modified":"2026-03-04T12:06:18","modified_gmt":"2026-03-04T11:06:18","slug":"models-optimitzacio","status":"publish","type":"solution","link":"https:\/\/www.mosaicfactor.com\/ca\/solution\/models-optimitzacio\/","title":{"rendered":"Models d’optimitzaci\u00f3"},"content":{"rendered":"

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En un m\u00f3n on l\u2019efici\u00e8ncia i la innovaci\u00f3 s\u00f3n crucials per a l\u2019\u00e8xit, els models d\u2019optimitzaci\u00f3 d\u2019intel\u00b7lig\u00e8ncia artificial<\/em> (IA) s\u2019han convertit en eines essencials per a les empreses de diversos sectors. Aquests models ens permeten millorar processos, reduir costos i augmentar la competitivitat<\/em>.<\/p>\n

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Potenciant l\u2019efici\u00e8ncia empresarial<\/h3>\n

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Les t\u00e8cniques d\u2019optimitzaci\u00f3 no nom\u00e9s es basen en el ML, sin\u00f3 tamb\u00e9 en models ad hoc que creem: \u00e9s a dir, algorismes que creem i despr\u00e9s optimitzem.<\/p>\n

A continuaci\u00f3 es presenten alguns casos d\u2019\u00fas t\u00edpics sobre com podem ajudar les empreses de diferents sectors.<\/p>\n

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Automoci\u00f3<\/h4>\n

En el sector de l\u2019automoci\u00f3, els models d\u2019IA d\u2019optimitzaci\u00f3 s\u2019utilitzen per millorar la producci\u00f3 i la qualitat dels vehicles. Aquests models permeten optimitzar les cadenes de subministrament, reduir el temps d\u2019inactivitat de les m\u00e0quines i millorar la precisi\u00f3 en el muntatge de components. A m\u00e9s, la IA ajuda a preveure fallades en els vehicles, millorant aix\u00ed el manteniment predictiu i l\u2019experi\u00e8ncia del client.<\/p>\n

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Mobilitat<\/h4>\n

En el sector de la mobilitat, la IA d\u2019optimitzaci\u00f3 s\u2019aplica per gestionar el tr\u00e0nsit urb\u00e0, planificar rutes eficients i millorar els serveis de transport p\u00fablic. Els algorismes d\u2019optimitzaci\u00f3 permeten ajustar els temps dels sem\u00e0fors en temps real, reduir els embussos i millorar la flu\u00efdesa del tr\u00e0nsit. Tamb\u00e9 s\u2019utilitzen per desenvolupar sistemes de navegaci\u00f3 m\u00e9s eficients i serveis de mobilitat compartida.<\/p>\n

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Log\u00edstica<\/h4>\n

La log\u00edstica \u00e9s un altre sector on l\u2019optimitzaci\u00f3 mitjan\u00e7ant IA t\u00e9 un impacte significatiu. Els models d\u2019IA permeten millorar la gesti\u00f3 d\u2019inventaris, optimitzar les rutes de lliurament i preveure la demanda de productes. Amb l\u2019ajuda de la IA, les empreses poden reduir costos operatius, millorar la puntualitat en les entregues i augmentar la satisfacci\u00f3 del client. A m\u00e9s, la IA facilita l\u2019automatitzaci\u00f3 de magatzems i la coordinaci\u00f3 de flotes de vehicles.<\/p>\n

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Healthcare<\/h4>\n

En l\u2019\u00e0mbit de la salut, la IA d\u2019optimitzaci\u00f3 s\u2019utilitza per millorar la gesti\u00f3 hospital\u00e0ria, la planificaci\u00f3 de recursos i l\u2019atenci\u00f3 al pacient. Els models d\u2019optimitzaci\u00f3 permeten assignar eficientment els recursos m\u00e8dics, planificar els horaris dels professionals de la salut i reduir els temps d\u2019espera dels pacients. Tamb\u00e9 s\u2019empren en la recerca m\u00e8dica per dissenyar assaigs cl\u00ednics i optimitzar tractaments personalitzats.<\/p>\n

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Ind\u00fastria<\/h4>\n

En el sector manufacturer, els models d\u2019optimitzaci\u00f3 contribueixen a millorar la producci\u00f3, reduir el malbaratament de materials o recursos i augmentar la qualitat dels productes. Els models d\u2019IA permeten optimitzar els processos de fabricaci\u00f3, ajustar par\u00e0metres en temps real i preveure possibles fallades en les l\u00ednies de producci\u00f3. A m\u00e9s, la IA facilita la implementaci\u00f3 de la manufactura avan\u00e7ada, com la fabricaci\u00f3 additiva i la personalitzaci\u00f3 massiva.<\/p>\n

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Com ho fem?<\/h3>\n

[\/et_pb_text][et_pb_image src=”https:\/\/www.mosaicfactor.com\/wp-content\/uploads\/\/infografia-1-optimizacion-solucion-mosaicfactor-models.svg” alt=”Models d\u2019optimitzaci\u00f3 proc\u00e9s de creaci\u00f3 Mosaic Factor” title_text=”infografia-1-optimizacion-solucion-mosaicfactor-models” _builder_version=”4.27.4″ _module_preset=”default” width=”900px” global_colors_info=”{}”][\/et_pb_image][et_pb_text _builder_version=”4.27.4″ _module_preset=”default” text_font_size=”18px” text_line_height=”1.6em” custom_margin=”||||false|false” custom_padding=”||||false|false” global_colors_info=”{}”]<\/p>\n

    \n
  • Comencem definint el problema de negoci a resoldre. <\/strong>Aix\u00f2 pot incloure l\u2019optimitzaci\u00f3 de rutes de lliurament, l\u2019assignaci\u00f3 de recursos, la planificaci\u00f3 de la producci\u00f3, entre d\u2019altres. \u00c9s important tenir una comprensi\u00f3 clara dels objectius i les restriccions del problema.<\/li>\n
  • Recopilaci\u00f3 de dades:<\/strong> els models d\u2019IA d\u2019optimitzaci\u00f3 requereixen una gran quantitat de dades per funcionar correctament. Aquestes dades poden provenir de diverses fonts, com sensors, sistemes de gesti\u00f3 empresarial (ERP), bases de dades i altres sistemes d\u2019informaci\u00f3. La qualitat i la precisi\u00f3 de les dades s\u00f3n crucials per a l\u2019\u00e8xit del model. Les dades recopilades s\u2019han de netejar i transformar per eliminar errors, valors at\u00edpics i dades incompletes. El pre-processament tamb\u00e9 inclou la normalitzaci\u00f3 i l\u2019estructuraci\u00f3 de les dades en un format adequat per al model.<\/li>\n
  • Creaci\u00f3 del model:<\/strong> existeixen diferents tipus de models d\u2019optimitzaci\u00f3, com algorismes gen\u00e8tics, xarxes neuronals, programaci\u00f3 lineal i no lineal, entre d\u2019altres.\n
      \n
    • Selecci\u00f3 del model: la selecci\u00f3 del model dep\u00e8n de la naturalesa del problema i dels objectius espec\u00edfics.<\/li>\n
    • Entrenament del model: el model d\u2019IA s\u2019entrena utilitzant les dades pre-processades. Durant l\u2019entrenament, el model apr\u00e8n a identificar patrons i relacions en les dades. S\u2019utilitzen t\u00e8cniques com la validaci\u00f3 creuada i l\u2019ajust d\u2019hiperpar\u00e0metres per millorar el rendiment del model.<\/li>\n<\/ul>\n<\/li>\n
    • Integraci\u00f3 en temps real:<\/strong> un cop entrenat, el model d\u2019IA pot generar solucions \u00f2ptimes o quasi \u00f2ptimes per al problema definit. El model pot ser utilitzat en temps real per prendre decisions basades en les dades actuals. \u00c9s essencial validar i avaluar el rendiment del model per assegurar-se que compleix amb els objectius i les restriccions del problema.<\/li>\n<\/ul>\n

      [\/et_pb_text][et_pb_text _builder_version=”4.27.4″ _module_preset=”default” text_font_size=”18px” text_line_height=”1.6em” header_3_font=”|||on|||||” header_3_font_size=”28px” header_3_line_height=”1.2em” custom_margin=”||1em||false|false” custom_margin_tablet=”||0em||false|false” custom_margin_phone=”||0em||false|false” custom_margin_last_edited=”on|tablet” header_3_font_size_tablet=”28px” header_3_font_size_phone=”20px” header_3_font_size_last_edited=”on|phone” global_colors_info=”{}”]<\/p>\n

      Creaci\u00f3 de models d\u2019IA robustos i escalables<\/h3>\n

      [\/et_pb_text][et_pb_text _builder_version=”4.27.4″ _module_preset=”default” text_font_size=”18px” text_line_height=”1.6em” custom_margin=”||||false|false” custom_padding=”||||false|false” global_colors_info=”{}”]<\/p>\n

      Els models predictius no s\u00f3n est\u00e0tics, sin\u00f3 que estan en aprenentatge continu. S\u2019adapten autom\u00e0ticament a mesura que es disposa de noves dades, de manera que podem fer-los escalables.<\/p>\n

      Ens centrem en la creaci\u00f3 de models d\u2019IA optimitzats d\u2019alt rendiment<\/strong> que minimitzin l\u2019\u00fas de recursos computacionals, cosa que es tradueix en menors costos i impacte mediambiental<\/strong>.<\/p>\n

      Sempre avaluem els casos d\u2019\u00fas d\u2019IA dins del sector espec\u00edfic de l\u2019empresa per assegurar-nos que la IA predictiva permeti a les empreses prendre decisions basades en dades, optimitzar processos i mantenir-se a l\u2019avantguarda en un panorama de mercat din\u00e0mic.<\/p>\n

      [\/et_pb_text][\/et_pb_column][\/et_pb_row][\/et_pb_section]<\/p>\n","protected":false},"excerpt":{"rendered":"

      Els models d\u2019IA d\u2019optimitzaci\u00f3 permeten als nostres clients millorar processos, reduir costos i augmentar la competitivitat.<\/p>\n","protected":false},"author":2,"featured_media":5273,"parent":0,"menu_order":0,"template":"","format":"standard","meta":{"_acf_changed":false,"_et_pb_use_builder":"on","_et_pb_old_content":"","_et_gb_content_width":"","inline_featured_image":false,"footnotes":""},"industry":[],"proyecto":[227,228,229,209,230,231],"class_list":["post-5272","solution","type-solution","status-publish","format-standard","has-post-thumbnail","hentry","proyecto-bsm-tram-pkm","proyecto-corealis","proyecto-echarge-4drivers","proyecto-green-log","proyecto-myway","proyecto-pioneers"],"acf":[],"yoast_head":"\nMosaic Factor<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"\/\" \/>\n<meta property=\"og:locale\" content=\"ca_ES\" \/>\n<meta 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