T/XZBX 0192-2026 Active Group standards

T/XZBX 0192-2026 Guidelines for debugging, optimizing, and validating the process parameters of painting robots

Publish Date: 2026-03-16 Implement Date: 2026-04-01 For services related to genuine standard inquiry, procurement, translation, and other related services in China, please Contact Us

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Basic Information

Standard Code: T/XZBX 0192-2026

Standard Type: Group standards

Standard Status: Active

is_force_gb: no

CCS Name: Orthopaedic surgery, orthopaedic instruments

ICS Name: Industrial robots and manipulators

Publish Date: 2026-03-16

Implement Date: 2026-04-01

Scope

As a key process in surface engineering of the manufacturing industry, painting directly affects the appearance quality, corrosion resistance, assembly adaptability, and lifecycle maintenance costs of products. In industries such as automobiles and auto parts, construction machinery, rail transit, home appliances and 3C products, steel structure anti-corrosion, and aerospace, the spraying objects are complex in shape, with high batch production speed and diverse coating systems, which place higher demands on coating thickness uniformity, appearance defect control, material utilization rate, volatile organic compound emissions, and stability and consistency. Painting robots have become important equipment in modern painting production lines due to their high trajectory repeat accuracy, stable operating pace, and ability to operate continuously in enclosed spray booths while reducing personnel exposure risks. However, just because a robot can spray doesn't mean it can do it well. Factors such as process parameter setting, path and posture planning, spray window control, airflow organization in the spray booth, and curing conditions all contribute to the final coating effect. Common problems in engineering sites include film thickness fluctuations, drip marks, orange peel, dry spraying, pinholes, shrinkage holes, exposed substrates, thin coating at edges and corners, insufficient coverage in shaded areas, color and gloss instability, and increased material loss due to overspray and rebound. If parameter adjustment lacks a systematic method, it often results in a "experience-driven, repeated trial spraying, difficult to reproduce, and hard to transfer" situation, which not only affects the production cycle but also increases quality risks and comprehensive costs. Painting robot process parameters exhibit multi-variable, strong coupling, and significant sensitivity to operating conditions. Typical influencing factors include but are not limited to: spray cup or spray gu