{"id":9203,"date":"2026-03-18T20:05:22","date_gmt":"2026-03-18T12:05:22","guid":{"rendered":"https:\/\/bogonglaser.com\/?p=9203"},"modified":"2026-03-18T20:23:12","modified_gmt":"2026-03-18T12:23:12","slug":"laser-cutting-machines-in-modern-smart-factories","status":"publish","type":"post","link":"https:\/\/bogonglaser.com\/es\/laser-cutting-machines-in-modern-smart-factories\/","title":{"rendered":"M\u00e1quinas de corte por l\u00e1ser en las modernas f\u00e1bricas inteligentes"},"content":{"rendered":"

Primero tres palabras.<\/p>\n\n\n\n

La mayor\u00eda de los art\u00edculos sobre \u201cf\u00e1bricas inteligentes\u201d dan la impresi\u00f3n de haber sido escritos por alguien que nunca se ha encontrado junto a un estante de chapas a las 6:40 de la ma\u00f1ana, mientras un operario espera el material, la producci\u00f3n ya va con retraso y el l\u00e1ser, aunque t\u00e9cnicamente est\u00e1 disponible, en realidad no genera beneficios porque la planificaci\u00f3n previa ha sido descuidada y la clasificaci\u00f3n posterior es un caos. Eso ocurre muy a menudo. M\u00e1s de lo que la gente admite.<\/p>\n\n\n\n

Y esa es la parte que, sinceramente, creo que se pasa por alto.<\/p>\n\n\n\n

Seguimos fingiendo que la m\u00e1quina es lo importante. Pero no lo es. La m\u00e1quina es la parte visible: la parte brillante, la que aparece en los folletos, aquello a lo que el departamento de compras puede apuntar. Pero la verdadera historia es m\u00e1s fea y m\u00e1s interesante: retrasos en la carga, anidamientos defectuosos, variaciones en la calidad del gas, boquillas sucias, caos en la mezcla de piezas, archivos de anidamiento enviados con retraso y jefes que dicen querer la automatizaci\u00f3n, pero siguen dirigiendo el taller a base de llamadas telef\u00f3nicas e intuici\u00f3n. \u00bfTe suena?<\/p>\n\n\n\n

\"M\u00e1quinas
<\/figcaption><\/figure>\n\n\n\n

Ya he visto esta pel\u00edcula. Demasiadas veces.<\/p>\n\n\n\n

Una m\u00e1quina de corte por l\u00e1ser solo resulta valiosa en una f\u00e1brica inteligente cuando deja de actuar como un activo independiente y empieza a comportarse como un nodo de producci\u00f3n: uno que recibe instrucciones claras, corta con repetibilidad, proporciona datos \u00fatiles y no obliga a los humanos a supervisar cada decisi\u00f3n b\u00e1sica. Esa es la l\u00ednea divisoria. Si se cruza, la m\u00e1quina se gana su lugar. Si no se alcanza, lo \u00fanico que habr\u00e1s conseguido es una costosa fuente de optimismo.<\/p>\n\n\n\n

Por eso el\u00a0El trabajo de las Academias Nacionales en 2024 sobre la fabricaci\u00f3n inteligente<\/a>\u00a0tiene m\u00e1s importancia que la mayor\u00eda de los informes t\u00e9cnicos de los proveedores. Aborda la fabricaci\u00f3n inteligente como un problema de datos y sistemas, y no solo como un problema de maquinaria, que es precisamente c\u00f3mo deber\u00edan abordarla las plantas que se toman en serio este tema. Si los datos no pueden circular, no son fiables o no sirven para orientar la actuaci\u00f3n, la f\u00e1brica no es inteligente. Es solo una fachada. <\/p>\n\n\n\n

Por qu\u00e9 las m\u00e1quinas de corte por l\u00e1ser encajan tan bien en las f\u00e1bricas inteligentes<\/h2>\n\n\n\n

Es casi obvio.<\/p>\n\n\n\n

Una cortadora l\u00e1ser ya forma parte de un flujo de trabajo digital. Se importa el archivo CAD. Se crea el dise\u00f1o de anidamiento. Se seleccionan los par\u00e1metros. El rayo hace su trabajo. Se registra el estado. Se puede comprobar la calidad. Se puede contar la producci\u00f3n. Se pueden medir los desechos\u2026 bueno, si la direcci\u00f3n quiere realmente la cifra real de desechos y no la que resulta m\u00e1s tranquilizadora.<\/p>\n\n\n\n

Eso \u00faltimo es importante.<\/p>\n\n\n\n

Porque cuando la gente habla de \u201ccorte por l\u00e1ser en f\u00e1bricas inteligentes\u201d, lo que suele querer decir es esto: un proceso m\u00e1s f\u00e1cil de medir, m\u00e1s f\u00e1cil de automatizar, m\u00e1s f\u00e1cil de estandarizar y m\u00e1s f\u00e1cil de integrar con sistemas MES, ERP, software de anidamiento, herramientas de planificaci\u00f3n, l\u00f3gica de mantenimiento y seguimiento del rendimiento por turno. No es perfecto. Pero s\u00ed m\u00e1s limpio que muchos de los antiguos m\u00e9todos de fabricaci\u00f3n.<\/p>\n\n\n\n

Y la tendencia general en el sector industrial va precisamente en esa direcci\u00f3n. La Oficina del Censo de EE. UU. inform\u00f3 de que los trabajadores del sector manufacturero est\u00e1n m\u00e1s expuestos a las tecnolog\u00edas de automatizaci\u00f3n que el resto de la econom\u00eda, con 52% de trabajadores del sector manufacturero expuestos a estas tecnolog\u00edas frente a 28% fuera de dicho sector. Tambi\u00e9n se\u00f1al\u00f3 que la inteligencia artificial y los robots est\u00e1n especialmente vinculados a los motivos de automatizaci\u00f3n dentro del sector manufacturero. <\/p>\n\n\n\n

Eso no es una nota al margen. Es el entorno operativo.<\/p>\n\n\n\n

Fij\u00e9monos ahora en los robots. La Federaci\u00f3n Internacional de Rob\u00f3tica se\u00f1al\u00f3 que Estados Unidos alcanz\u00f3 una densidad de robots de 295 unidades por cada 10 000 empleados del sector manufacturero en 2023, mientras que China lleg\u00f3 a 470 y Corea del Sur a 1 012. No se trata de cifras meramente presuntuosas. Estas cifras revelan en qu\u00e9 tipo de ecosistema de producci\u00f3n se integran actualmente las m\u00e1quinas de corte por l\u00e1ser: uno en el que la carga automatizada, la recogida de piezas, la supervisi\u00f3n del estado, los turnos sin personal y un control m\u00e1s estricto del takt se est\u00e1n convirtiendo en algo habitual, y no en algo excepcional. <\/p>\n\n\n\n

Pues s\u00ed, un est\u00e1ndar m\u00e1quina de corte por l\u00e1ser de fibra<\/a> Sin duda, puede instalarse en una f\u00e1brica moderna. Pero, seg\u00fan mi experiencia, cuando la presi\u00f3n laboral, la estabilidad del rendimiento y la uniformidad del turno de noche se convierten en prioridades fundamentales, los compradores empiezan a considerar m\u00e1s detenidamente configuraciones como una cortadora l\u00e1ser de tubos de carga autom\u00e1tica<\/a>. Porque la cruda realidad es muy sencilla: la carga manual ha acabado con m\u00e1s casos de retorno de la inversi\u00f3n que todos los l\u00e1seres de baja potencia juntos.<\/p>\n\n\n\n

\"M\u00e1quinas
<\/figcaption><\/figure>\n\n\n\n

Lo que los compradores de f\u00e1bricas inteligentes realmente esperan de la automatizaci\u00f3n del corte por l\u00e1ser<\/h3>\n\n\n\n

Quieren cifras.<\/p>\n\n\n\n

Ni \u201cinnovaci\u00f3n\u201d. Ni \u201cexcelencia preparada para el futuro\u201d. Lo siento, pero ese tipo de lenguaje suele significar que alguien est\u00e1 intentando disimular unas operaciones deficientes. Los compradores de verdad quieren saber la producci\u00f3n por operario, la reducci\u00f3n de los desechos, la velocidad de puesta a punto, la estabilidad del tiempo de actividad, la uniformidad en los bordes y datos de alarmas que realmente puedan utilizar. Quieren que la m\u00e1quina deje de ser un misterio.<\/p>\n\n\n\n

Y quieren menos excusas.<\/p>\n\n\n\n

Si dejamos de lado el lenguaje comercial, esto es lo que las f\u00e1bricas suelen esperar de la automatizaci\u00f3n del corte por l\u00e1ser: un flujo predecible, ciclos de producci\u00f3n m\u00e1s r\u00e1pidos, un mejor aprovechamiento de las chapas, menor dependencia del operario, menos recortes, menos momentos de \u201c\u00bfpor qu\u00e9 ha pasado esto?\u201d y cierta trazabilidad cuando llega una reclamaci\u00f3n semanas m\u00e1s tarde. No quieren magia. Quieren control.<\/p>\n\n\n\n

Por eso las m\u00e1quinas de corte por l\u00e1ser siguen encajando tan bien en la l\u00f3gica de la f\u00e1brica inteligente. Se sit\u00faan justo en el punto en el que la planificaci\u00f3n digital se convierte en producci\u00f3n f\u00edsica, y si ese traspaso se gestiona bien, la m\u00e1quina pasa a formar parte de un circuito cerrado en lugar de convertirse en un simple cuello de botella.<\/p>\n\n\n\n

Demanda de f\u00e1bricas inteligentes<\/th>Lo que debe ofrecer el sistema l\u00e1ser<\/th>Lo que suele fallar<\/th><\/tr><\/thead>
Visibilidad de la producci\u00f3n en tiempo real<\/td>Estado de la m\u00e1quina, avance del corte, alarmas, datos de OEE<\/td>La m\u00e1quina funciona bien, pero los datos quedan bloqueados en el software del fabricante<\/td><\/tr>
Eficiencia laboral<\/td>Carga autom\u00e1tica, turnos sin supervisi\u00f3n, configuraci\u00f3n m\u00e1s r\u00e1pida<\/td>La carga manual borra los ajustes de ganancia<\/td><\/tr>
Consistencia en la calidad<\/td>Haz estable, control del gas, recetas de par\u00e1metros, calidad de los bordes<\/td>Los operadores siguen \u201cretocando\u201d los ajustes sin seguir ninguna disciplina<\/td><\/tr>
Producci\u00f3n flexible<\/td>Anidamiento r\u00e1pido, tiradas cortas, materiales mixtos, cambios r\u00e1pidos<\/td>El software de planificaci\u00f3n de recursos empresariales (ERP) y el de anidamiento no est\u00e1n conectados<\/td><\/tr>
Menor coste por pieza<\/td>Mejor aprovechamiento de las chapas, menos reelaboraciones y menos tiempos de inactividad<\/td>Las tasas de desechos y recortes no se registran con transparencia<\/td><\/tr>
Seguridad y cumplimiento normativo<\/td>Recintos, enclavamientos, formaci\u00f3n, barreras fotoel\u00e9ctricas<\/td>La seguridad se incorpor\u00f3 posteriormente, no se tuvo en cuenta en la fase de dise\u00f1o<\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n

Y ah\u00ed lo tienes.<\/p>\n\n\n\n

La m\u00e1quina no lo es todo en la compra. Lo importante es el sistema. Los compradores que no lo tienen claro acaban ech\u00e1ndole la culpa a la cortadora de los problemas causados por la planificaci\u00f3n, la carga, los h\u00e1bitos de los operarios o una mala disciplina en los procesos \u2014lo que algunos trabajadores de planta llamar\u00edan sin rodeos \u201cdesperdicio de la direcci\u00f3n\u201d\u2014.\u201d<\/p>\n\n\n\n

La cruda realidad del corte por l\u00e1ser en la Industria 4.0<\/h2>\n\n\n\n

Most factories aren\u2019t there.<\/p>\n\n\n\n

They\u2019re halfway there. Maybe.<\/p>\n\n\n\n

A few dashboards. A few machine screens. Some digital drawings. A software subscription nobody fully uses. And then everybody acts shocked when the so-called Industry 4.0 line still depends on one veteran operator who remembers which settings actually work on 5 mm stainless when the humidity gets weird.<\/p>\n\n\n\n

Here\u2019s the ugly truth: digitized is not the same as smart. Connected is not the same as controlled. And monitored is not the same as managed.<\/p>\n\n\n\n

A real Industry 4.0 laser cutting setup does something much harder than \u201chaving software.\u201d It links planning, execution, reporting, and reaction speed. Job comes in. Material is ready. Nest is right. Parameter library is locked down. Cut runs. Alarm data flows. Someone can actually see deviation fast enough to do something useful. That\u2019s a loop. Most factories still have fragments.<\/p>\n\n\n\n

Want proof that systems beat slogans? Look at the World Economic Forum\u2019s 2024 Lighthouse examples. Foxconn\u2019s B\u1eafc Giang site used 40+ Fourth Industrial Revolution use cases and lifted labor productivity by 190%, hit 99.5% on-time delivery, and cut manufacturing costs by 45%. Siemens\u2019 Erlangen electronics factory used more than 100 AI algorithms plus digital twins and improved labor productivity by 69%, cut time to market by 40%, and reduced energy use by 42%. GE HealthCare\u2019s Beijing site used 45 digital solutions across 26 lines and cut cycle times and scrap by 66% while reducing customer complaints by 73%. That\u2019s not showroom language. That\u2019s operating leverage.<\/p>\n\n\n\n

Now, no, those aren\u2019t \u201claser-only\u201d case studies. Exactly. That\u2019s the lesson.<\/p>\n\n\n\n

Laser cutting machines get stronger inside smart factories because they\u2019re relatively easy to standardize, relatively easy to instrument, and relatively easy to connect to the rest of the production stack. But if the stack itself is weak\u2014bad scheduling, poor material staging, fuzzy ownership, no one watching scrap honestly\u2014the machine won\u2019t save you. It\u2019ll just reveal you.<\/p>\n\n\n\n

A bit painful. But useful.<\/p>\n\n\n\n

\"M\u00e1quinas
<\/figcaption><\/figure>\n\n\n\n

So when someone asks me for the best laser cutting machines for smart factories, I don\u2019t start with wattage. I start with part flow, SKU churn, material mix, shift pattern, handling pain, nesting discipline, and whether the customer wants real data or presentation data. Those are two very different appetites.<\/p>\n\n\n\n

Where fiber laser cutting in manufacturing earns its keep<\/h3>\n\n\n\n

On the hard jobs.<\/p>\n\n\n\n

Not the easy demo cuts. Not the cherry-picked samples sales teams love. I mean real factory work: enclosures, cabinets, brackets, server chassis, tube components, panel parts, weld-prep pieces, mixed batch sizes, ugly scheduling windows, and customers who suddenly want the same part in three revisions and five materials by next Thursday.<\/p>\n\n\n\n

That\u2019s where fiber laser cutting in manufacturing makes sense.<\/p>\n\n\n\n

It\u2019s especially strong when you need speed plus repeatability plus digital control. Sheet metal shops know this. Electrical cabinet producers know this. Chassis fabricators know this. Anyone doing medium- to high-mix fabrication knows it too, even if they complain about consumables, assist gas, pierce settings, and all the other practical details outsiders rarely understand.<\/p>\n\n\n\n

And yes, application fit matters more than brochure specs.<\/p>\n\n\n\n

If bevel prep is eating time downstream, then a m\u00e1quina de corte l\u00e1ser de fibra en bisel para el corte y biselado de ranuras<\/a> may solve a welding problem before the first tack. If the plant is juggling both sheet and tube with constant scheduling friction, an all-in-one metal sheet and tube laser cutting machine<\/a> might make more operational sense than splitting work across scattered assets. And if the buyer is still trying to map actual use cases, the aplicaciones de la m\u00e1quina de corte por l\u00e1ser<\/a> page is a better starting point than obsessing over maximum power.<\/p>\n\n\n\n

Because\u2014this is important\u2014more kW doesn\u2019t automatically mean more money.<\/p>\n\n\n\n

I\u2019ve watched factories chase 12 kW, 20 kW, even bigger names, while the real limiter was unload time, poor nesting, or the fact that the parts came off the table faster than the shop could sort them. That\u2019s not a laser problem. That\u2019s cell design. Or, if we\u2019re being blunt, a planning problem dressed up as an equipment problem.<\/p>\n\n\n\n

Smart factory laser cutting is also a safety and management problem<\/h2>\n\n\n\n

Nobody loves this topic.<\/p>\n\n\n\n

But they should.<\/p>\n\n\n\n

As soon as you move toward automated loading, remote status checks, unattended shifts, and more aggressive output targets, safety stops being a compliance checkbox and becomes part of production architecture. That means guarding, interlocks, authorization levels, extraction, gas handling, maintenance discipline, and access logic all have to be treated like production variables\u2014not legal afterthoughts.<\/p>\n\n\n\n

I know that sounds dry. It isn\u2019t. It gets real very fast.<\/p>\n\n\n\n

A valla protectora l\u00e1ser<\/a> isn\u2019t decorative. It\u2019s part of how a serious factory manages risk when a cutting cell is expected to run hard and run consistently. Same goes for enclosure design, lockout behavior, maintenance access, and whether operators are quietly bypassing procedures because the process was set up in a way that makes the \u201csafe\u201d path slow and annoying. That happens too.<\/p>\n\n\n\n

And then there\u2019s software.<\/p>\n\n\n\n

Everyone wants AI in manufacturing right now. Of course they do. But Reuters reported in July 2024 that manufacturers were rolling out planned generative AI projects more slowly than expected because of accuracy worries; 58% of manufacturing leaders planned to increase AI spending in 2024, but only 20% of planned AI projects had actually been implemented in the prior year. Forty-four percent of manufacturing respondents cited response accuracy concerns. Honestly, that caution sounds healthy to me. A plant can survive bland software. It can\u2019t afford confident nonsense near live equipment.<\/p>\n\n\n\n

So yes, smart factory laser cutting needs software. But not theater software. Not dashboard wallpaper. It needs systems that are accurate, auditable, floor-aware, and boring in the best possible way.<\/p>\n\n\n\n

Reliable beats flashy.<\/p>\n\n\n\n

Siempre.<\/p>\n\n\n\n

What a serious buyer should measure before signing<\/h3>\n\n\n\n

Start here.<\/p>\n\n\n\n

Part mix. Material range. Sheet thickness. Tube share. Assist gas cost. Nozzle consumption. Setup time. Handling time. Unload flow. Scrap visibility. Re-cut rate. Operator skill spread. Software compatibility. Maintenance response. Safety design. That\u2019s the shopping list.<\/p>\n\n\n\n

And I\u2019d add one more thing most buyers ignore: decision lag.<\/p>\n\n\n\n

How long does it take your plant to notice that the laser cell is drifting, backing up, throwing rejects, or sitting idle because the next nest wasn\u2019t released properly? Ten minutes? Two hours? Monday morning? That answer tells you more about your smart-factory maturity than any sales presentation ever will.<\/p>\n\n\n\n

From my experience, the best laser cutting machines for smart factories are not the ones with the prettiest spec sheet. They\u2019re the ones that fit the factory\u2019s actual production metabolism\u2014the pace, the handoffs, the part family, the staffing reality, the ERP mess, the maintenance culture, all of it. If the machine fits the work, it wins. If the machine outruns the system, the system punishes it.<\/p>\n\n\n\n

Why laser cutting machines will stay central to modern factories<\/h2>\n\n\n\n

Because they keep scaling.<\/p>\n\n\n\n

Not effortlessly. Not cheaply. And not without headaches. But they scale better than a lot of competing fabrication methods when the plant needs precision, throughput, recipe control, flexible routing, and a straight path into automation.<\/p>\n\n\n\n

That\u2019s why they aren\u2019t going anywhere.<\/p>\n\n\n\n

Global automation density keeps climbing, leading plants keep proving that tightly integrated digital production can deliver hard gains, and laser cutting remains one of the cleanest bridges between digital instruction and physical output. That bridge matters. Especially now. Especially when customers want faster turns, more revisions, and cleaner quality records without paying for chaos. <\/p>\n\n\n\n

And there\u2019s the simplest truth of all: in a modern factory, ambiguity is expensive. Laser cutting machines reduce ambiguity. They cut what the file says, if the file is right, the setup is right, and the system around them isn\u2019t broken. That\u2019s exactly why smart factories keep pulling them closer to the center.<\/p>\n\n\n\n

Preguntas frecuentes<\/h2>\n\n\n\n

\u00bfC\u00f3mo contribuyen las m\u00e1quinas de corte por l\u00e1ser a mejorar las f\u00e1bricas inteligentes?<\/h3>\n\n\n\n

Laser cutting machines improve smart factories by converting digital production instructions into repeatable, traceable parts while feeding operating data\u2014such as machine status, cut progress, alarm history, and throughput\u2014into connected software systems that support scheduling, maintenance, quality tracking, and production visibility across the factory. That\u2019s the clean answer.<\/p>\n\n\n\n

The longer answer is more practical. They help plants cut down setup drag, standardize quality, support short runs, and expose waste that older processes often hide. If connected properly, they don\u2019t just make parts\u2014they make problems visible sooner.<\/p>\n\n\n\n

\u00bfCu\u00e1l es la diferencia entre una cortadora l\u00e1ser CNC est\u00e1ndar y un sistema de corte por l\u00e1ser para f\u00e1bricas inteligentes?<\/h3>\n\n\n\n

A standard CNC laser cutter is a programmable cutting machine, while a smart factory laser cutting system is a connected production unit that exchanges useful data with planning, quality, maintenance, and material-handling systems to improve output consistency, traceability, and reaction speed across the broader manufacturing process. That\u2019s the distinction.<\/p>\n\n\n\n

In plain language, one machine cuts. The other participates. A smart-factory system can support recipe locking, automated loading, job prioritization, status alerts, traceability, and tighter links to bending, welding, or packing. Same beam, very different operating logic.<\/p>\n\n\n\n

\u00bfSon las m\u00e1quinas de corte por l\u00e1ser de fibra la mejor opci\u00f3n para las f\u00e1bricas inteligentes modernas?<\/h3>\n\n\n\n

Fiber laser cutting machines are often the best option for modern smart factories when the core work involves metal fabrication, high throughput, variable batch sizes, tight tolerances, and a need for stable integration with automation and digital production systems across sheet or tube processing workflows. That\u2019s usually the answer.<\/p>\n\n\n\n

But not always. If your factory still struggles with loading, scheduling, or material staging, the machine won\u2019t fix that by itself. Fiber is powerful\u2014but it works best when the rest of the cell isn\u2019t chaotic.<\/p>\n\n\n\n

\u00bfQu\u00e9 deben tener en cuenta los compradores antes de elegir las mejores m\u00e1quinas de corte por l\u00e1ser para f\u00e1bricas inteligentes?<\/h3>\n\n\n\n

Buyers should check part families, material types, sheet and tube volumes, automation goals, software compatibility, gas and energy costs, safety requirements, service support, and actual handling bottlenecks before choosing the best laser cutting machines for smart factories, because machine value depends heavily on production flow and system discipline. That\u2019s the shortlist.<\/p>\n\n\n\n

I\u2019d also push buyers to verify real integration capability. Not just installation. Ask whether the vendor can support alarm reporting, recipe control, MES links, unattended-shift safeguards, and usable production data. If they can\u2019t, the machine may still cut well\u2014but it won\u2019t truly behave like part of a smart factory.<\/p>\n\n\n\n

Your next step<\/h2>\n\n\n\n

If you\u2019re evaluating laser cutting machines for a modern smart factory, don\u2019t begin with \u201cHow much power do we need?\u201d Start with a harsher question: where does the factory lose control today? Material release? Loading? Scrap visibility? Re-cut rates? Scheduling lag? Operator variance? That\u2019s where the buying logic should begin.<\/p>\n\n\n\n

Then narrow the machine around the reality.<\/p>\n\n\n\n

If you want practical options to compare, review Bogong Laser\u2019s m\u00e1quinas de corte por l\u00e1ser de fibra<\/a>, look at its automatic loading tube cutting systems<\/a>, and factor in soluciones de vallado de protecci\u00f3n l\u00e1ser<\/a> before you treat the cell like a finished answer. It isn\u2019t. A smart factory is built through disciplined choices\u2014one linked decision at a time.<\/p>","protected":false},"excerpt":{"rendered":"

La charla sobre f\u00e1bricas inteligentes se vuelve esponjosa r\u00e1pidamente. Quiero volver a la realidad. Las m\u00e1quinas de corte por l\u00e1ser son importantes en las f\u00e1bricas inteligentes modernas no porque parezcan avanzadas, sino porque convierten instrucciones digitales en piezas repetibles y trazables a velocidad industrial. La cruda realidad: la m\u00e1quina por s\u00ed sola nunca es la mejora. La mejora es el sistema que la rodea.<\/p>","protected":false},"author":1,"featured_media":9204,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_gspb_post_css":"","footnotes":""},"categories":[156],"tags":[278,279,276,280,274,275,277],"class_list":["post-9203","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-laser-cutting-machine-for-application-blog","tag-cnc-laser-cutting-machines","tag-fiber-laser-cutting-in-manufacturing","tag-industrial-laser-cutting-systems","tag-industry-4-0-laser-cutting","tag-laser-cutting-automation","tag-laser-cutting-machines","tag-smart-factory-laser-cutting"],"blocksy_meta":{"styles_descriptor":{"styles":{"desktop":"","tablet":"","mobile":""},"google_fonts":[],"version":7}},"_links":{"self":[{"href":"https:\/\/bogonglaser.com\/es\/wp-json\/wp\/v2\/posts\/9203","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/bogonglaser.com\/es\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/bogonglaser.com\/es\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/bogonglaser.com\/es\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/bogonglaser.com\/es\/wp-json\/wp\/v2\/comments?post=9203"}],"version-history":[{"count":1,"href":"https:\/\/bogonglaser.com\/es\/wp-json\/wp\/v2\/posts\/9203\/revisions"}],"predecessor-version":[{"id":9207,"href":"https:\/\/bogonglaser.com\/es\/wp-json\/wp\/v2\/posts\/9203\/revisions\/9207"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/bogonglaser.com\/es\/wp-json\/wp\/v2\/media\/9204"}],"wp:attachment":[{"href":"https:\/\/bogonglaser.com\/es\/wp-json\/wp\/v2\/media?parent=9203"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/bogonglaser.com\/es\/wp-json\/wp\/v2\/categories?post=9203"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/bogonglaser.com\/es\/wp-json\/wp\/v2\/tags?post=9203"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}