应急管理部新规为1800万名特种作业人员减负增效

Core Viewpoint - The Ministry of Emergency Management has revised the "Regulations on Safety Technical Training and Assessment Management for Special Operations Personnel," which will take effect on June 1, 2024, introducing several measures to facilitate convenience for businesses and workers [1][2]. Group 1: Key Changes in Regulations - The renewal requirement for special operation certificates has been optimized, changing from a three-year review to a six-year renewal, with no review required for certificates expiring after June 1, 2026 [1]. - The regulations eliminate the requirement for retraining for those who have completed training but failed the exam, allowing unlimited attempts for theoretical exams and increasing practical exam attempts from one to five [1][2]. - The regulations promote "cross-province handling," allowing applicants to apply for exams at any authorized assessment agency nationwide, removing the requirement for local residency [1]. Group 2: Educational and Certification Adjustments - The educational requirements for special operations personnel have been adjusted, no longer requiring a minimum of junior high school education for roles such as electrical work and welding [2]. - The regulations state that individuals holding valid vocational skill certificates can directly take the special operation certificate exam without undergoing safety technical training [2]. Group 3: Safety and Compliance Measures - In 2024, the Ministry of Emergency Management will collaborate with other governmental bodies to conduct special governance in the special operations sector, addressing issues such as the use of fake certificates, with 19,000 fake certificates identified and criminally prosecuted [2]. - In 2025, efforts will be made to consolidate governance results, with nearly 6,000 cases of unlicensed or fake certificate operations being investigated, aiming to curb the prevalence of such issues [2]. - Future plans include stricter assessment and training management, implementation of AI evaluation systems for practical exams, development of big data analysis models for exam anomalies, and enhanced supervision to address serious issues in training and examination processes [2].