智能制造系统转型方案

1、智能制造系统转型方案技术创新，变革未来Agenda智能制造的目标智能制造的参考产业智能制造的场景案例 智能制造的开始3智能制造的目标 : 利用终端的需求来驱动产品的制造市场和产品定位需求和客户制造管理配送和物流运营和风险智 能 產 品智 能 營 運智 能 工 厂认知制造Digital Reinvention 数位重塑New Way: Innovation Garage 創新工厂、Agile at Scale 规模化敏捷Cognitive Demand and Sales 认知型需求与销售Smart Customer EngagementSmart Customer Service 智能化客服

2、智能化客户管理Cognitive Procurement 认知型採购AI as Service 人工智能即服务平台Cognitive Supply Chain 认知供应链J 2Cognitive ERP 认知营运核心平台CSmart Factory Platform 智能工厂平台云 端Smart Health Safety Environment (HSE) 智能环安迁Cognitive Asset Management 认知资产管理Cognitive Equipment Advisor 认知设备预警移AI Inspector 智能视觉检测Smart Yield Management 智能良率

3、管理Smart MES Platform 智能工厂执行核心系统IoT 串流分析平台IT智能运 营、IT执 行 自动 化C P A认 知 流 程 自 动 化T&T认 知 人 力 资 源 转 型 S Fi S S C智 能共 享 服 务 作 业 中 心智能工廠平台是智能制造的基礎建設使用者行动装置系统操作介面智能质量分析(SPC/FDC)智能中央监控 (CFM)设备参数管控 (RMS)智能快捷派工 (XMS)ERPPLMWMSAMHSSCM邮件/简讯Web网页自动警报系统 (AMS)行动化立即叫修(Mobile)生产追踪与管控 (SFC)设备预防保养 (PMS)情境模拟最佳化(Optimizer)

4、产能计划调整 (APS)数据串联分析 (APC) 分析工艺效率 (YMS) 缺陷分析追踪 (EDA) 设备自动化 (Auto)智能视觉检测缺陷自动类型识别模型参数评定定制化类神经模型影像前处理强化缺陷特徵缺陷影像自动扩增模型成效通知智能环安环安管理平台智能环安管理决策中心智能安全、环境监控敏捷生产计划排程流程/资源限制调配智能工厂执行核心系统 (MES)智能资产效能管理认知资产管理智能资产预测智能资产监控资产管理平台AI as ServiceAIBig DataRPARobotEquipmentPLC/SCADA智能制造是本次价值链改革的核心，要成功实现数字化重塑，就必须从根本上重新思考企业的

5、运营模 式以及企业与生态环境的互动方式。数字化重塑旅程七大要素 组织人才数据 技术架构 工作流程安全 企业文化 商业模式利用智能工厂平台重新思考企业的核心价值挑战因为设备的故障保养、或是换线生产，前置准备等因素，而无法及时掌握未来的产能，供货商交期, 透过电话确认交期，造成无法及时回复客户的订单。因为少量多样的短交期生产模式，无法及时的根据产线上的状况备料，造成原物料 和零组件的库存不足或太多，增加生产成本。因为没有足够的数据支撑和系统化的智能分析，造成良率到达一个瓶颈之后，无法再向上提升。品管流程过去最大的痛点在于，会受检验机的能力和设计有诸多限制，导致需要耗 费大量的复检人力，对于时程管理

6、及营运效益都会有一定的负担。主要设备的控制参数或工艺参数没有在系统上有效的管理，並随时追踪稽核各种参 数的任何改变，造成良率或质量不稳定。少数老师傅雍有工艺参数和流程的机密资讯和经验，造成竞争者只需要透过购买相同设备和挖角，便可以生产相同的产品，造成市场价格崩落。无法性统性的有效管理和监控操作员的操作流程，造成质量的不稳定或设备的故障 率增加，增加产品的成本无法确认并追踪设备或管线厂商或工程师的保养流程是否确实，因而造成良率下降，甚至工安和环保问题。生产资料手写纪录，下班时再将纸本的资料输入到系统，造成生产数据不及时。现有的系统只是报工，没有生产前检核，包括首件检查、物料检核、模具检核、SOP

7、检核、生产参数检核等，容易造成人为的疏失。没有端到端的总负责人，出问题时才提出问题分析，已有实时的数据，但没有实时分析的能力。Agenda智能制造的目标智能制造的参考产业智能制造的场景案例 智能制造的开始智能制造带给产业的革命性的创新和快速的进步手机产业99了解每个产业智能制造的成熟度，透过產、官、學、研和公協會的协同合作，分阶段实施典型客户挑战自行开发IT设备仪器不连通数据分散大量使用Excel烟囱系统建立了企业应用程序，但缺乏集成缺乏数字化缺乏数据治理和分析安全性不足流程断开缺乏流程自动化没有数据湖有限的外部协作需要市场和客户洞察生产创新供应链透明度不足基于最终用户端的价值链整合面向材料工

8、程价值链面向工艺技术价值链跑-Run走-Walk冲刺-Sprint爬-Crawl手工制程智能制造能力和成熟度低高生产流程价值低高生态智能化大量的组织处于这个位置Level 1: 孤岛型组织Level 2:车间层面已连接Level 3:制造企业单元之间互联Level 4:企业价值链互联半自动化制程全面自动化制程柔性自动化制程芯片制造产业案例分享(芯片制造) : 高价值的产业规模、複杂的生产流程和分工，利用 智能制造协助产业水平分工的价值极大化，改变产业的价值链关係11案例分享(芯片制造) : 智能制造之旅利用单一MES平台 跨厂协同运作， 超越竞争者，转化成利润，建立起极高的产业进入门槛一条芯片

9、生产线根据产品的技术节点，涉 及2000-5000道工序如果每道工序的良率为 99.9%，一条2000 道工序的生产线良率为 13.5%Agenda智能制造的目标智能制造的场景案例 智能制造的开始智能制造的参考产业1313运营成本全球供应链整合以订单为单位0库存为目标实时质量与成本追溯管理标准数据标准体系质量管理标准标准作业流程技能培训认证体系生产周期快速生产(在规定时间内多生产)：多厂协同减少浪费(时间和物料损耗)：最佳OEE从订单到交付订单自动化面向制造的设计DFMA现场供应链可视化产品质量数字化生产过程：数字化装备数字化配方数字产品智能实时质检实时生产良率分析与决策系统 数字化工艺开发与

10、推荐系统智能制造的三大切入点制造协同统一工厂协同制造设备效率精益生产良率管理黄金配方数字工艺整合运营产销平衡全球整合快速反应管理数据 标准组织技术人才咨询与规划Use case 1 Enterprise MES + Centralized CockpitProblem StatementUse Case ScopeBenefitCant dynamically share the capacity of equipment or line in time base on real-time information of WIP and Capacity through visualized f

11、actories.Cant share the capital investment of critical/most expensive equipment in different factories to maximize the capacityNo efficient/precise algorithm of planning to support real-time dynamic productionBuild up a integrated MES-Platform to visualize process detail of factory toward factory-le

12、vel Digital TwinAggregate individual factorys data through theintegration of Enterprise MES.Monitor/Manage the production in every factoryof enterprise or supplier.Case A (Semiconductor): Capital Saving : 6% Throughput Increasing : 10% Tool Utilization Improved : 6%Tool Maintenance Cost Saving : 12%

13、Use case 2 Smart MES + Planning/SchedulingProblem StatementUse Case ScopeBenefitCant real-time track exact status and information of WIP, detail process, materials, stocks, tools, product errors and trigger alarm or warning in time.Cant assess the cost of changing line/product to response available

14、capacity or promise order in time.Cant reduce cycle time to improve the throughput and optimize the production and cost for specific products.15Build up MES-Platform to visualize, control and manage process detail of factory including making more informed decisions about production, improving produc

15、t quality, getting rid of just-in-case inventory, etc.Optimize Production Planning and SchedulingAbility to visualize and understand availability of input materialsAbility to schedule against tool availability .Case A (Shoes Maker) :Direct-Labor HC reduction : 8%In-direct-Labor HC reduction : 2% Inv

16、entory Cost Saving : 16% Cycle Time Improved : 6%Use case 3 Recipe Management System (RMS)+ SPC + Out of Control Action Plan (OCAP) + Advance Process Control (APC)Problem StatementUse Case ScopeBenefitAny unauthorized changing of process recipe may cause big yield loss after processing production lo

17、tsManual paper-based recipe (or device history records) management has caused higher production errors and lower process efficiencyProcess know-how cannot be improved or inherited, and IP cannot be protected.How to combined with Equipment Auto + Process Auto for Full-Auto16Extract real-time recipe (

18、or device history records) of equipment to integration with RMS for tracing/auditing every parameters.Setup/manage golden recipe in RMS to improve yield in production, and avoid unauthorized change from equipment applications or others.Record every related change in the history to collaborate with a

19、ny production issue for yield improvement.Case A (Semiconductor):Yield Improvement : 8%0% Mis-operation rate of recipe errors of to cause product recallsRe-work Rate Reduction : 12%Problem StatementUse Case ScopeBenefitPeriodical preventative maintenance cause lower output and cant be flexible for H

20、igh-Complexity- Low-Volume manufacturing.Critical tool PM cant be executed with qualityprocedure to cause low yield rate or accident.No systematically developing failure pattern for prediction and analysis to cause higher production errors.17Build up MES-Platform to visualize, control and manage pro

21、cess detail of factory including making more informed decisions about production, improving product quality, getting rid of just-in-case inventory, etc.Single platform of Asset Management solution for both factory and enterprise to optimize the stock of raw materials, components, and key parts.Case

22、A: (Semiconductor) Tool Utilization Improved6% Tool Utilization Improved through predictive maintenance with quality procedure and execution.Stock Cost Saving20% Stock Cost Saving through single platform to centralize the ID of parts, component and raw materials, and balance inventory level cross 25

23、 factoriesUse case 4 Smart MES + Asset Management + Health， Safety，Environment (HSE) ManagementProblem StatementUse Case ScopeBenefitProduct 1 7 before PM, metrology data of 1-7 is in the warning specificationAfter PM, Metrology data of product is out of warning specification but over the specificat

24、ion of 2-sigmaBut, product 8-9 is still in the product specification.Then, tools heater works normally18How SPC Work:SPC system trigger automatically to inhibit tool + recipe after SPC check of product 9Root Case & Action Request:机台保养后，讯号线接触异常，造成加温速 度控制异常，但是不会影响温度，故产品依然在 规格内，预先告警没有产品损失。更换加温零件，追踪厂商的质

25、量，避免再发生。Labor Cost reduction : 9000 14000 hours reduction of labor efforts in false call management per yearRe-work Rate Reduction : 13% re-work rate reduction equivalent to annual 4000 units no need to re-workUnscheduled Downtime Reduction : 123 Hrs unscheduled downtime reduction per year in mounti

26、ng equivalent 2% Tool utilization improvementUse case 5 - Statistic Process Control (SPC) - 西电规则Problem StatementUse Case ScopeBenefit缺陷判定维度众多，难以建构一般模型解决 问题不易发现并分类，有些缺陷太小，不易发现， 且缺陷类别多，易混淆人力成本高，因分类不易，所以需投入大量人力时间，检测品质也不一致Extract real time data from AOI machinesDevelop the deep learning model to analyz

27、e parts,components, and products and identify defects by matching patternsProvide inspectors with information to increase efficiency and supervisors with quality inspection metricsCase A (Flat Panel Display):节省数个站点人力: 50%每个站点缩短检测lead time: 90%改善总体製程 cycle time: 7%Case B (Printed Circuit Board):节省数个站

28、点人力: 70%减少漏检率/误判率: 300 ppm节省每年每厂检测支出: RMB 14MUse case 6 Visual Inspection (VI)Problem StatementUse Case ScopeBenefit各种数据散落各地的系统，或是部分没 系统，质量分析方法各自想办法数据来源多元，非结构资料渐渐增多数据的前后因子之间的关係越来越複杂， 难以综合性考虑后，建构一致性可追踪 的指标缺乏统计分析经验, 分析手法不易传承20Extract real time data from SPI / AOI / Mounting / ICT machinesDeploy the IOT gateway solution to convert the