引入工艺优化智能体 碳化转化率提升0.5% 作为传统化工企业，山东海化的数智化转型之路难题和压力不小，但"零手动"项目写下的"效率账 本"上，实实在在的数字见证着转型的足迹和成效。 打造设备预测性维护智能体 故障识别准确率超95% 1月22日，山东海化氯碱公司调度室的大屏上，一条"氯气压缩机振动异常"的红色预警弹出，让调度员 立马警觉起来。此时系统已自动"凝时回溯"异常阶段全量数据，并通过交互分析，同步推送故障原因与 检修方案。 "过去我们一直困在'过度维护'和'非计划停机'的两难里。"闫国辉算了笔账，单条氯碱产线非计划停机1 小时，直接损失超3万元，而每次停机至少8个小时才能恢复生产，若引发氯气泄漏，安全风险更是不堪 设想。 2025年2月，山东海化联合浪潮数字企业共同打造设备预测性维护智能体。据浪潮数字企业平台产品事 业部副总经理吴铭福介绍，该智能体首次部署时，准确率只有60%~70%。为此，工程师们一遍遍对接 老师傅，把经验转化为技术参数，搭建AI预测模型与专家系统，实现氯气压缩机故障毫秒预警、智能 诊断与自动派单，故障识别准确率超95%。该智能体的应用，也让氯气压缩机非计划停机次数由2024年 的4次 ...

Core Viewpoint - The article highlights the advancements in intelligent manufacturing at Shandong Haihua Group, showcasing the implementation of AI-driven predictive maintenance and process optimization, which significantly enhance operational efficiency and reduce costs [2][5][6]. Group 1: Intelligent Manufacturing and Efficiency - Shandong Haihua has developed a "zero manual" intelligent factory, which is expected to generate over 23 million yuan in benefits this year [2][5]. - The company has successfully reduced unplanned downtime of chlorine compressors from four times last year to zero, and maintenance costs have decreased from 800,000 yuan to 200,000 yuan annually [5][6]. - The implementation of AI has led to a 55% improvement in process stability and a 61% increase in key indicator automation rates, while manual operation frequency has decreased by 68% [5][6]. Group 2: Digital Transformation and Strategic Goals - The company aims to leverage AI to optimize three key areas: predictive maintenance, process optimization, and intelligent inspection, addressing core challenges in chemical production [5][6]. - Shandong Haihua has streamlined 1,803 business processes down to 400, achieving a 77.8% reduction, and has improved approval efficiency by 99.8% [6]. - The company plans to expand the application of mature technologies to other equipment and explore new areas such as intelligent management of salt wells, contributing to the broader digital transformation in the chemical industry [7].

Core Viewpoint - Shandong Haohua Group and Inspur Digital Enterprise Technology have signed a partnership to build an "industrial big data + industry big model" intelligent decision-making hub, enhancing AI-driven smart transformation in the chemical industry [1] Group 1: Production Efficiency - The collaboration has led to the development of an intelligent model that optimizes production processes, resulting in an annual increase of 8,760 tons of soda ash and over 10 million yuan in efficiency gains [1] - The operational frequency in the calcium chloride plant has decreased from 3,300 times daily to 83 times, a reduction of 97.5% [1] - The bromine plant has reduced its workforce from 172 to 58, saving over 20 million yuan in labor costs [1][2] Group 2: Equipment Maintenance - An AI-driven predictive maintenance system has been established, transitioning from passive repairs to proactive alerts, significantly reducing maintenance costs and unplanned downtimes [3] - The platform integrates equipment fault mechanisms with multi-source operational data, enabling real-time assessment and early risk identification of critical equipment [3] - The AI predictive model has achieved over 95% accuracy in fault identification for chlorine compressors [3] Group 3: Safety Management - The intelligent inspection system has upgraded safety inspections from human-dependent to AI-led processes, enhancing operational efficiency [4] - Continuous data collection and reinforcement learning have improved the model's ability to autonomously assess hazard levels and generate standardized work orders [4] - The introduction of a "robot + digital human" dual inspection model has increased inspection efficiency by 50% and improved risk analysis and hazard identification completion rates by 20% [4]