{"id":10944,"date":"2026-05-15T09:55:04","date_gmt":"2026-05-15T09:55:04","guid":{"rendered":"https:\/\/www.kinghamtech.com\/why-suspension-oem-projects-fail-after-sop-emerging-markets\/"},"modified":"2026-05-15T10:00:51","modified_gmt":"2026-05-15T10:00:51","slug":"why-suspension-oem-projects-fail-after-sop-emerging-markets","status":"publish","type":"post","link":"https:\/\/www.kinghamtech.com\/es\/why-suspension-oem-projects-fail-after-sop-emerging-markets\/","title":{"rendered":"Why Motorcycle Suspension OEM Projects Fail in Emerging Markets: Supply Chain Reality vs Production Stability"},"content":{"rendered":"<figure class=\"wp-block-image aligncenter size-large\"><img fetchpriority=\"high\" decoding=\"async\" width=\"1536\" height=\"1024\" src=\"https:\/\/www.kinghamtech.com\/wp-content\/uploads\/2026\/05\/image_1778837327-6ptdz44n.jpeg\" alt=\"Motorcycle suspension OEM program failure after SOP: prototype bench vs production stability\" class=\"wp-image-10943\" title=\"\" srcset=\"https:\/\/www.kinghamtech.com\/wp-content\/uploads\/2026\/05\/image_1778837327-6ptdz44n.jpeg 1536w, https:\/\/www.kinghamtech.com\/wp-content\/uploads\/2026\/05\/image_1778837327-6ptdz44n-300x200.jpeg 300w, https:\/\/www.kinghamtech.com\/wp-content\/uploads\/2026\/05\/image_1778837327-6ptdz44n-1024x683.jpeg 1024w, https:\/\/www.kinghamtech.com\/wp-content\/uploads\/2026\/05\/image_1778837327-6ptdz44n-768x512.jpeg 768w, https:\/\/www.kinghamtech.com\/wp-content\/uploads\/2026\/05\/image_1778837327-6ptdz44n-18x12.jpeg 18w\" sizes=\"(max-width: 1536px) 100vw, 1536px\" \/><\/figure>\n\n\n\n<p>OEM suspension programs often look rock-solid during development: the prototype lands on the target damping curve, the dyno plot is clean, and early ride reports feel reassuring.<\/p>\n\n\n\n<p>Then SOP happens\u2014the moment the line has to repeat that result at volume\u2014and the same program can start bleeding time and credibility: inconsistent damping feel from batch to batch, early leakage complaints, uneven warranty signals across regions, and constant sorting at the receiving dock.<\/p>\n\n\n\n<p>It\u2019s not hard to build a great prototype. It\u2019s hard to keep production centered and stable week after week.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\">Why OEM suspension programs look successful in development but fail after SOP<\/h2>\n\n\n\n<p>This is the core pattern behind motorcycle suspension OEM program failure after SOP: the design may be validated, but the manufacturing system isn\u2019t proven to hold CTQs batch after batch.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\">Prototype success is not production readiness<\/h3>\n\n\n\n<p>Hand-built samples are usually built by your best people under your best conditions.<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li><p>Parts are often hand-selected.<\/p><\/li><li><p>Processes are slower and more controllable.<\/p><\/li><li><p>Engineering attention is continuous.<\/p><\/li><li><p>Tooling is new, and fixtures are not worn.<\/p><\/li>\n<\/ul>\n\n\n\n<p>That\u2019s why prototype units can be excellent while the production system is still immature.<\/p>\n\n\n\n<p>Prototype \u2260 scalable system.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\">SOP introduces real-world variation that prototypes never test<\/h3>\n\n\n\n<p>Once the line runs for volume, you expose variables that were muted or absent during development:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li><p>operator-to-operator differences across shifts<\/p><\/li><li><p>material lot variation as procurement expands<\/p><\/li><li><p>fixture wear and tooling drift over time<\/p><\/li><li><p>line-speed pressure that changes how assemblies are executed<\/p><\/li>\n<\/ul>\n\n\n\n<p>A good reference point is how manufacturing teams distinguish validation stages: early validation proves the design intent; production validation proves the system can repeat output at scale (see Formlabs\u2019 overview of <a target=\"_blank\" rel=\"nofollow noopener\" class=\"link\" href=\"https:\/\/formlabs.com\/uk\/blog\/validation-testing-product-development-poc-evt-dvt-pvt-mp\/\">EVT\/DVT\/PVT and mass production validation<\/a>). In other words: prototype vs production validation suspension logic is about proving the system, not the hero sample.<\/p>\n\n\n\n<p>Production environment changes everything.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\">The real failure point is consistency, not performance<\/h3>\n\n\n\n<p>A single dyno curve can be \u201cright\u201d while the batch is unstable.<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li><p>One unit can be tuned to perfection.<\/p><\/li><li><p>A batch tells you whether the process is centered and controlled.<\/p><\/li><li><p>Field quality is the result of distribution, not the best sample.<\/p><\/li>\n<\/ul>\n\n\n\n<p>Stability &gt; peak performance.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\">The core issue is system variability, not suspension design<\/h2>\n\n\n\n<h3 class=\"wp-block-heading\">Supply chain fragmentation creates hidden inconsistency<\/h3>\n\n\n\n<p>In emerging markets, \u201cthe supply chain\u201d often isn\u2019t one chain. It\u2019s a multi-tier network with uneven standards.<\/p>\n\n\n\n<p>Common instability drivers include:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li><p>multi-tier outsourcing (Tier 2 and Tier 3 changes you can\u2019t see)<\/p><\/li><li><p>non-uniform sourcing for the same part number<\/p><\/li><li><p>inconsistent upstream process controls and acceptance logic<\/p><\/li>\n<\/ul>\n\n\n\n<p>Even when drawings don\u2019t change, lot-to-lot variation is a real, standard source of variation in production systems. Accendo Reliability explicitly lists <a target=\"_blank\" rel=\"nofollow noopener\" class=\"link\" href=\"https:\/\/accendoreliability.com\/sources-of-variation\/\">lot-to-lot variation<\/a> as a distinct category because inputs are not identical across batches.<\/p>\n\n\n\n<p>Variation starts before assembly.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\">Cost pressure reduces process discipline<\/h3>\n\n\n\n<p>Emerging-market programs typically have aggressive cost targets and frequent price-down cycles. When cost becomes the dominant KPI, process discipline degrades in predictable ways:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li><p>inspection shortcuts under pricing pressure<\/p><\/li><li><p>reduced process control to increase output<\/p><\/li><li><p>efficiency prioritized over stability<\/p><\/li>\n<\/ul>\n\n\n\n<p>Cost optimization often creates quality instability.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\">Production knowledge is not aligned with engineering intent<\/h3>\n\n\n\n<p>Engineering capability concentrates in the prototype phase.<\/p>\n\n\n\n<p>In production, the work shifts to a different reality:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li><p>the assembly sequence is optimized for throughput<\/p><\/li><li><p>controls are simplified to keep the line moving<\/p><\/li><li><p>decisions are made under schedule pressure<\/p><\/li>\n<\/ul>\n\n\n\n<p>Design intent \u2260 manufacturing execution.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\">Why suspension problems amplify during scaling<\/h2>\n\n\n\n<h3 class=\"wp-block-heading\">Small process deviations become large field issues<\/h3>\n\n\n\n<p>Suspension is sensitivity-driven. Small process shifts can create big differences in feel and durability.<\/p>\n\n\n\n<p>Examples:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li><p>minor changes in damping force at key velocities can show up as instability or harshness<\/p><\/li><li><p>small sealing variation can become leakage, then oil loss, then damping fade<\/p><\/li>\n<\/ul>\n\n\n\n<p>This is the same basic mechanism that makes suspension tunable in the first place: hydraulic damping depends on flow restrictions and valve behavior (UTI\u2019s overview of <a target=\"_blank\" rel=\"nofollow noopener\" class=\"link\" href=\"https:\/\/www.uti.edu\/blog\/motorcycle\/motorcycle-suspension-systems\">motorcycle suspension systems<\/a> explains the hydraulic damping principle and shim-based cartridges at a high level).<\/p>\n\n\n\n<p>Suspension is highly sensitivity-driven.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\">Batch-to-batch variation drives most real failures<\/h3>\n\n\n\n<p>A typical failure arc in OEM programs:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li><p>first batch acceptable<\/p><\/li><li><p>later batches drift as tooling wears, suppliers change, and throughput increases<\/p><\/li><li><p>field complaints arrive after scaling<\/p><\/li>\n<\/ul>\n\n\n\n<p>That\u2019s why batch-to-batch variation shock absorber behavior is the signal to watch. It tells you whether your approved sample represents a controlled distribution or a one-off win.<\/p>\n\n\n\n<p>SOP reveals hidden variability.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\">Scale exposes weak process control<\/h3>\n\n\n\n<p>If your output depends on who built the unit, you don\u2019t have a process\u2014you have a dependency.<\/p>\n\n\n\n<p>Scaling requires controls that survive shift changes, tool wear, and line-speed pressure.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\">Why \u201cgood samples\u201d do not guarantee OEM success<\/h2>\n\n\n\n<h3 class=\"wp-block-heading\">Suppliers optimize for sample approval, not production stability<\/h3>\n\n\n\n<p>Prototype builds often receive extra attention:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li><p>tighter informal inspection<\/p><\/li><li><p>slower, careful assembly<\/p><\/li><li><p>engineering \u201ctouches\u201d that don\u2019t exist at line speed<\/p><\/li>\n<\/ul>\n\n\n\n<p>Samples are optimized artifacts, not system proof.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\">Sample approval hides real manufacturing risk<\/h3>\n\n\n\n<p>The same drawing can be executed in different ways.<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li><p>different fixture strategy<\/p><\/li><li><p>different torque discipline<\/p><\/li><li><p>different fill\/bleed execution<\/p><\/li><li><p>different measurement rigor<\/p><\/li>\n<\/ul>\n\n\n\n<p>Approval \u2260 capability.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\">Dyno results do not reflect production variation<\/h3>\n\n\n\n<p>Dyno testing is valuable, but it\u2019s usually run under controlled conditions.<\/p>\n\n\n\n<p>A dyno curve from one or two samples is not evidence of batch stability. The evidence you need is distribution: what does the curve look like across a lot, after changeovers, and after the line has been running for weeks.<\/p>\n\n\n\n<p>Test results \u2260 production stability.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\">What actually defines a reliable suspension supplier<\/h2>\n\n\n\n<h3 class=\"wp-block-heading\">Consistency across batches is the real KPI<\/h3>\n\n\n\n<p>A mature supplier is defined by repeatability.<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li><p>stable output across batches<\/p><\/li><li><p>stable mean and spread after changeovers<\/p><\/li><li><p>predictable performance in the field<\/p><\/li>\n<\/ul>\n\n\n\n<p>Consistency is the core manufacturing value.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\">Controlled manufacturing behavior matters more than tuning ability<\/h3>\n\n\n\n<p>Tuning skill can make one unit great.<\/p>\n\n\n\n<p>Production readiness depends on whether the supplier can:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li><p>reduce operator dependency<\/p><\/li><li><p>define CTQs (Critical-to-Quality characteristics) that link engineering intent to shop-floor control<\/p><\/li><li><p>run a control plan that keeps those CTQs stable<\/p><\/li>\n<\/ul>\n\n\n\n<p>Process control &gt; tuning skill.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\">Ability to explain variation is a maturity signal<\/h3>\n\n\n\n<p>When drift happens, mature suppliers can explain it.<\/p>\n\n\n\n<p>They can trace variation to:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li><p>lot change<\/p><\/li><li><p>tooling or fixture wear<\/p><\/li><li><p>shift differences<\/p><\/li><li><p>measurement system issues<\/p><\/li>\n<\/ul>\n\n\n\n<p>This is where MSA (Measurement System Analysis) matters. If you can\u2019t trust the measurement, you can\u2019t trust the conclusion. ASQ defines <a target=\"_blank\" rel=\"nofollow noopener\" class=\"link\" href=\"https:\/\/asq.org\/quality-resources\/gage-repeatability\">gage repeatability and reproducibility (GR&amp;R)<\/a> as the process used to evaluate a gauging instrument\u2019s accuracy by ensuring measurements are repeatable and reproducible.<\/p>\n\n\n\n<p>Transparency indicates system maturity.<\/p>\n\n\n\n<p>If you need the language buyers and suppliers can align on, APQP (Advanced Product Quality Planning) and PPAP (Production Part Approval Process) are designed to turn \u201cwe can build it\u201d into documented evidence.<\/p>\n\n\n\n<p>A practical APQP\/PPAP-style supplier review boils down to four evidence blocks:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li><p><strong>CTQs<\/strong> tied directly to performance and durability<\/p><\/li><li><p>a <strong>control plan<\/strong> that keeps those CTQs stable at line speed<\/p><\/li><li><p><strong>MSA (including GR&amp;R)<\/strong> for the measurements you\u2019ll use to accept\/reject parts<\/p><\/li><li><p><strong>traceability<\/strong> that can connect field complaints back to lot\/shift\/process parameters<\/p><\/li>\n<\/ul>\n\n\n\n<p>This isn\u2019t paperwork. It\u2019s how you catch drift before it becomes a warranty event.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\">Why emerging markets increase OEM suspension risk<\/h2>\n\n\n\n<h3 class=\"wp-block-heading\">Scaling speed exceeds process maturity<\/h3>\n\n\n\n<p>Demand can scale faster than the factory system matures.<\/p>\n\n\n\n<p>Volume exposes problems that were irrelevant at low build rates: drift across shifts, tool wear effects, fixture degradation, and parameter stability.<\/p>\n\n\n\n<p>A useful way to frame this is validation maintenance: MedTech Intelligence notes that scale-up often increases variability (tool wear, thermal drift, fixture degradation) and that SPC should be tied to validation maintenance, with signals like <a target=\"_blank\" rel=\"nofollow noopener\" class=\"link\" href=\"https:\/\/medtechintelligence.com\/feature_article\/from-prototype-to-production-building-a-validation-strategy-that-scales-with-manufacturing-volume\/\">parameter drift across shifts and lot-to-lot material response<\/a>.<\/p>\n\n\n\n<p>Growth outpaces control systems.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\">Mixed supply ecosystems increase variability<\/h3>\n\n\n\n<p>Emerging-market ecosystems often mix imported and local components.<\/p>\n\n\n\n<p>That can mean:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li><p>different supplier standards coexisting<\/p><\/li><li><p>uneven documentation quality<\/p><\/li><li><p>inconsistent traceability depth<\/p><\/li>\n<\/ul>\n\n\n\n<p>Ecosystem complexity increases instability.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\">Weak feedback loops between field and factory<\/h3>\n\n\n\n<p>If field failures are not systematically analyzed, the factory keeps repeating them.<\/p>\n\n\n\n<p>Multi-tier networks make this worse. Visibility problems and mismatched management systems are common obstacles in multi-tier supply chains; QIMAone summarizes several <a target=\"_blank\" rel=\"nofollow noopener\" class=\"link\" href=\"https:\/\/www.qimaone.com\/resource-hub\/sc-visibility-series-multi\">multi-tier supply chain visibility challenges<\/a> that reduce the ability to detect upstream issues early.<\/p>\n\n\n\n<p>No feedback = repeated failure.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\">How OEMs can reduce failure risk before scaling<\/h2>\n\n\n\n<p>If you want a suspension OEM supplier evaluation checklist that engineering, SQE, and procurement can actually use, start by separating \u201csample proof\u201d from \u201cprocess proof,\u201d then demand repeatability evidence.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\">Separate prototype validation from production validation<\/h3>\n\n\n\n<p>Treat samples as design proof, not production proof.<\/p>\n\n\n\n<p>A practical gating approach:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li><p>prototype validation: performance targets and functional durability<\/p><\/li><li><p>production validation: CTQs, measurement capability, process capability, and reaction plans<\/p><\/li>\n<\/ul>\n\n\n\n<p>Two-stage thinking is required.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\">Evaluate suppliers based on repeatability, not samples<\/h3>\n\n\n\n<p>If you want to avoid \u201cgood samples, bad SOP,\u201d ask for evidence that the supplier can repeat outcomes:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li><p>batch-to-batch dyno sampling rules and acceptance windows<\/p><\/li><li><p>a traceability model (batch, shift, key process parameters) that matches your warranty risk<\/p><\/li>\n<\/ul>\n\n\n\n<p>Evidence &gt; demonstration.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\">Build escalation and correction logic early<\/h3>\n\n\n\n<p>A stable program assumes drift will happen at some point. The question is whether the control system catches it early.<\/p>\n\n\n\n<p>Define upfront:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li><p>what triggers containment (stop-ship conditions)<\/p><\/li><li><p>who owns corrective action<\/p><\/li><li><p>response-time expectations<\/p><\/li><li><p>what evidence is required to release production again<\/p><\/li>\n<\/ul>\n\n\n\n<p>Control system &gt; inspection system.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\">Decision framework: when motorcycle suspension OEM program failure after SOP risk is low enough to scale<\/h2>\n\n\n\n<h3 class=\"wp-block-heading\">Green zone (low risk)<\/h3>\n\n\n\n<ul class=\"wp-block-list\">\n<li><p>stable batch output<\/p><\/li><li><p>repeatable dyno results across defined sampling rules<\/p><\/li><li><p>predictable field behavior<\/p><\/li><li><p>supplier can explain and control variation<\/p><\/li>\n<\/ul>\n\n\n\n<h3 class=\"wp-block-heading\">Yellow zone (controlled risk)<\/h3>\n\n\n\n<ul class=\"wp-block-list\">\n<li><p>sample success but limited batch evidence<\/p><\/li><li><p>partial visibility into CTQs and control plan<\/p><\/li><li><p>early signs of variation (shift-to-shift drift, lot sensitivity)<\/p><\/li>\n<\/ul>\n\n\n\n<h3 class=\"wp-block-heading\">Red zone (high risk)<\/h3>\n\n\n\n<ul class=\"wp-block-list\">\n<li><p>prototype-only validation<\/p><\/li><li><p>no batch stability proof<\/p><\/li><li><p>no clear explanation of process controls or drift mechanism<\/p><\/li>\n<\/ul>\n\n\n\n<hr class=\"wp-block-separator\" \/>\n\n\n\n<h2 class=\"wp-block-heading\">Where Kingham Tech fits in this evaluation<\/h2>\n\n\n\n<p>If your core risk is SOP instability, you\u2019re not just selecting a shock absorber\u2014you\u2019re selecting a manufacturing system.<\/p>\n\n\n\n<p>If you\u2019re an OEM buyer, SQE, or distributor building a program in an emerging-market supply ecosystem, the fastest way to reduce post-SOP surprises is to qualify the supplier\u2019s <em>system<\/em> before you qualify the product. In practice, that means three checks: CTQs tied to ride feel and durability, proven measurement capability, and traceability that\u2019s strong enough to contain issues fast.<\/p>\n\n\n\n<p>Kingham Tech works with partners who take that stability-first approach, with an OEM\/ODM workflow designed to repeat results at scale.<\/p>\n\n\n\n<p>If you want a quick sanity check, share your current supplier\u2019s evidence pack (control plan summary, MSA\/GR&amp;R, dyno sampling rules, and traceability approach). We\u2019ll highlight common gaps that cause drift after SOP and suggest what to tighten before you scale.<\/p>\n\n\n\n<p>Learn more about our OEM\/ODM workflow: <a target=\"_self\" rel=\"follow\" class=\"link\" href=\"https:\/\/www.kinghamtech.com\/es\/oem-odm-partner\/\">Kingham Tech OEM\/ODM partner<\/a><\/p>","protected":false},"excerpt":{"rendered":"<p>Why good suspension samples fail after SOP: supply chain variation, process drift, and what evidence proves batch stability.<\/p>","protected":false},"author":2,"featured_media":10943,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"site-sidebar-layout":"default","site-content-layout":"","ast-site-content-layout":"default","site-content-style":"default","site-sidebar-style":"default","ast-global-header-display":"","ast-banner-title-visibility":"","ast-main-header-display":"","ast-hfb-above-header-display":"","ast-hfb-below-header-display":"","ast-hfb-mobile-header-display":"","site-post-title":"","ast-breadcrumbs-content":"","ast-featured-img":"","footer-sml-layout":"","ast-disable-related-posts":"","theme-transparent-header-meta":"","adv-header-id-meta":"","stick-header-meta":"","header-above-stick-meta":"","header-main-stick-meta":"","header-below-stick-meta":"","astra-migrate-meta-layouts":"default","ast-page-background-enabled":"default","ast-page-background-meta":{"desktop":{"background-color":"var(--ast-global-color-5)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"tablet":{"background-color":"","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"mobile":{"background-color":"","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""}},"ast-content-background-meta":{"desktop":{"background-color":"var(--ast-global-color-4)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"tablet":{"background-color":"var(--ast-global-color-4)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"mobile":{"background-color":"var(--ast-global-color-4)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""}},"footnotes":""},"categories":[103,104],"tags":[],"class_list":["post-10944","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-rear-shock","category-front-shock"],"acf":[],"_links":{"self":[{"href":"https:\/\/www.kinghamtech.com\/es\/wp-json\/wp\/v2\/posts\/10944","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.kinghamtech.com\/es\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.kinghamtech.com\/es\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.kinghamtech.com\/es\/wp-json\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/www.kinghamtech.com\/es\/wp-json\/wp\/v2\/comments?post=10944"}],"version-history":[{"count":1,"href":"https:\/\/www.kinghamtech.com\/es\/wp-json\/wp\/v2\/posts\/10944\/revisions"}],"predecessor-version":[{"id":10945,"href":"https:\/\/www.kinghamtech.com\/es\/wp-json\/wp\/v2\/posts\/10944\/revisions\/10945"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.kinghamtech.com\/es\/wp-json\/wp\/v2\/media\/10943"}],"wp:attachment":[{"href":"https:\/\/www.kinghamtech.com\/es\/wp-json\/wp\/v2\/media?parent=10944"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.kinghamtech.com\/es\/wp-json\/wp\/v2\/categories?post=10944"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.kinghamtech.com\/es\/wp-json\/wp\/v2\/tags?post=10944"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}