Key elements of the pilot project of the Ministry of Industry and Information Technology: Five modes of intelligent manufacturing
In order to implement the overall deployment of "Made in China 2025" and in accordance with the requirements of the "Development Plan for Intelligent Manufacturing (2016-2020)" and "Implementation Guidelines for Intelligent Manufacturing Engineering (2016-2020)", the Ministry of Industry and Information Technology is now carrying out the recommendation of pilot demonstration projects for intelligent manufacturing in 2018. The elements and conditions of the 2018 intelligent manufacturing pilot demonstration project have been clearly defined, and the following are for reference.
Elements and conditions of intelligent manufacturing mode
（1） Discrete intelligent manufacturing
1. The overall design, process flow, and layout of the workshop/factory have been digitized and simulated to achieve digital management of the entire planning, production, and operation process.
2. Apply digital 3D design and process technology for product and process design and simulation, and verify and optimize through physical testing and experimentation.
Establish a Product Data Management System (PDM) to achieve integrated management of product design and process data.
3. The CNC rate of manufacturing equipment exceeds 70%, and information interconnection and integration between high-end CNC machine tools and key technical equipment such as industrial robots, intelligent sensing and control equipment, intelligent detection and assembly equipment, intelligent logistics and warehousing equipment are achieved.
4. Establish a production process data collection and analysis system to automatically upload production site data such as production progress, on-site operations, quality inspection, equipment status, and material transfer, and achieve visual management.
5. Establish a workshop manufacturing execution system (MES) to achieve management functions such as planning, scheduling, quality, equipment, production, and energy efficiency.
Establish an Enterprise Resource Planning (ERP) system to achieve business management functions such as supply chain, logistics, and cost management.
6. Establish an internal communication network architecture for the factory to achieve information interconnection between various stages of the manufacturing process, including design, process, manufacturing, inspection, logistics, as well as between the manufacturing process and the Manufacturing Execution System (MES) and Enterprise Resource Planning System (ERP).
7. We have established an industrial information security management system and technical protection system, with the ability to ensure information security such as network protection and emergency response. Establish a functional safety protection system and adopt a full lifecycle approach to effectively prevent system failure.
Through continuous improvement, we aim to achieve dynamic optimization of the entire product lifecycle in enterprise design, process, manufacturing, management, logistics, and other aspects. We will promote rapid improvements in digital design, equipment intelligence upgrading, process optimization, lean production, visual management, quality control and traceability, intelligent logistics, and other aspects of the enterprise.
（2） Process oriented intelligent manufacturing
1. The overall design, process flow, and layout of the factory have been digitized and simulated to achieve visualization of production process data and optimization of production processes.
2. Realize full process monitoring of logistics, energy flow, physical properties, and assets, establish data collection and monitoring systems, and achieve an automatic data collection rate of over 90% for production process data.
Realize the collection and integrated utilization of raw material, key process, and finished product testing data, and establish real-time quality warning.
3. By adopting advanced control systems, the factory's self-control utilization rate has reached over 90%, and key production processes have achieved model-based advanced control and online optimization.
4. Establish a Production Execution System (MES), with models for production planning and scheduling, to achieve model-based analysis and decision-making, process quantification management, dynamic tracking of costs and quality, and integrated collaborative optimization from raw materials to finished products.
建立企业资源计划系统（ERP），实现企业经营、管理和决策的智能优化。
5、对于存在较高安全与环境风险的项目，实现有毒有害物质排放和危险源的自动检测与监控、安全生产的全方位监控，建立在线应急指挥联动系统。
6、建立工厂通信网络架构，实现工艺、生产、检验、物流等制造过程各环节之间，以及制造过程与数据采集和监控系统、生产执行系统（MES）、企业资源计划系统（ERP）之间的信息互联互通。
7. We have established an industrial information security management system and technical protection system, with the ability to ensure information security such as network protection and emergency response. Establish a functional safety protection system and adopt a full lifecycle approach to effectively prevent system failure.
通过持续改进，实现生产过程动态优化，制造和管理信息的全程可视化，企业在资源配置、工艺优化、过程控制、产业链管理、节能减排及安全生产等方面的智能化水平显著提升。
（三）网络协同制造
1、建有网络化制造资源协同云平台，具有完善的体系架构和相应的运行规则。
2、通过协同云平台，展示社会／企业／部门制造资源，实现制造资源和需求的有效对接。
3、通过协同云平台，实现面向需求的企业间／部门间创新资源、设计能力的共享、互补和对接。
4、通过协同云平台，实现面向订单的企业间／部门间生产资源合理调配，以及制造过程各环节和供应链的并行组织生产。
5、建有围绕全生产链协同共享的产品溯源体系，实现企业间涵盖产品生产制造与运维服务等环节的信息溯源服务。
6、建有工业信息安全管理制度和技术防护体系，具备网络防护、应急响应等信息安全保障能力。
通过持续改进，网络化制造资源协同云平台不断优化，企业间、部门间创新资源、生产能力和服务能力高度集成，生产制造与服务运维信息高度共享，资源和服务的动态分析与柔性配置水平显著增强。
（四）大规模个性化定制
1、产品采用模块化设计，通过差异化的定制参数，组合形成个性化产品。
2、建有基于互联网的个性化定制服务平台，通过定制参数选择、三维数字建模、虚拟现实或增强现实等方式，实现与用户深度交互，快速生成产品定制方案。
3、建有个性化产品数据库，应用大数据技术对用户的个性化需求特征进行挖掘和分析。
4、个性化定制平台与企业研发设计、计划排产、柔性制造、营销管理、供应链管理、物流配送和售后服务等数字化制造系统实现协同与集成。
通过持续改进，实现模块化设计方法、个性化定制平台、个性化产品数据库的不断优化，形成完善的基于数据驱动的企业研发、设计、生产、营销、供应链管理和服务体系，快速、低成本满足用户个性化需求的能力显著提升。
（五）远程运维服务
1、采用远程运维服务模式的智能装备／产品应配置开放的数据接口，具备数据采集、通信和远程控制等功能。
利用支持IPv4、IPv6等技术的工业互联网，采集并上传设备状态、作业操作、环境情况等数据，并根据远程指令灵活调整设备运行参数。
2、建立智能装备／产品远程运维服务平台，能够对装备／产品上传数据进行有效筛选、梳理、存储与管理。
并通过数据挖掘、分析，向用户提供日常运行维护、在线检测、预测性维护、故障预警、诊断与修复、运行优化、远程升级等服务。
3、智能装备／产品远程运维服务平台应与设备制造商的产品全生命周期管理系统（PLM）、客户关系管理系统（CRM）、产品研发管理系统实现信息共享。
4、智能装备／产品远程运维服务平台应建立相应的专家库和专家咨询系统，能够为智能装备／产品的远程诊断提供智能决策支持，并向用户提出运行维护解决方案。
5、建立信息安全管理制度，具备信息安全防护能力。
通过持续改进，建立高效、安全的智能服务系统，提供的服务能够与产品形成实时、有效互动，大幅度提升嵌入式系统、移动互联网、大数据分析、智能决策支持系统的集成应用水平。
二、新技术创新应用要素条件
（一）工业互联网
1、建立工业互联网工厂内网，采用工业以太网、工业PON、工业无线、IPv6等技术，实现生产装备、传感器、控制系统与管理系统等的互联。
实现数据的采集、流转和处理；利用IPv6、工业物联网等技术，实现与工厂内、外网的互联互通，支持内、外网业务协同。
2、采用各类标识技术自动识别零部件、在制品、工序、产品等对象，在仓储、生产过程中实现自动信息采集与处理，通过与国家工业互联网标识解析系统对接，实现对产品全生命周期管理。
3、实现工厂管理软件之间的横向互联，实现数据流动、转换和互认。
4、在工厂内部建设工业互联网平台，或利用公众网络上的工业互联网平台，实现数据的集成、分析和挖掘，支撑智能化生产、个性化定制、网络化协同、服务化延伸等应用。
5、通过部署和应用工业防火墙、安全监测审计、入侵检测等安全技术措施，实现对工业互联网安全风险的防范、监测和响应，保障工业系统的安全运行。
(II)Artificial Intelligence
1、关键制造装备采用人工智能技术，通过嵌入计算机视听觉、生物特征识别、复杂环境识别、智能语音处理、自然语言理解、智能决策控制以及新型人机交互等技术，实现制造装备的自感知、自学习、自适应、自控制。
2、结合行业特点，基于大数据分析技术，应用机器学习、知识发现与知识工程以及跨媒体智能等方法，在产品质量改进与缺陷检测、生产工艺过程优化、设备健康管理、故障预测与诊断等关键环节具备人工智能特征。
3、目标产品采用智能感知、模式识别、智能语义理解、智能分析决策等核心技术，实现复杂环境感知、智能人机交互、灵活精准控制、群体实时协同等方面性能和智能化水平的显著提高。
4、人工智能技术已在产品开发、制造过程等产品全生命周期过程中实际运用，实现对制造过程优化，技术方案和应用模式等具有可复制性、可推广性。
Article source:e-works数字化企业网
He Yang/Organizing and recommending
