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生产的下一步:使用 AI 获得更好的结果.pdf

上传人: c** 编号:465080 2025-01-12 26页 2.22MB

1、The Next Step in Production:Using AIto Achieve Better ResultsRalph J.Woerheide-Metromation Inc.Coatings Trends&Technology Summit,Lombard 9/6/2024IntroductionSales and Business DevelopmentModular FactoryWhat is Modular Factory(MoFa)?Traditional ManufacturingModular ManufacturingRaw MaterialsPROCESSPr

2、oductRaw MaterialsDispersingGrindingMixingMasterSlurriesBinderCocktailPPPPPPPMoFa as a basis for production data Recipe Modularization Compact Setup Dispersion and Mixing PLC Controlled Sensors and interfaces AI Enabled Benefits in productionefficiency,stability andsustainabilityWhere are we and whe

3、re do we want to goto?Instable processes complex formulationsRaw material variation final productDifficult prediction of product qualityMoFaAI?Where are we and where do we want to goto?Case Study at a Paint FactoryProblem to solve:Heterogeneous recipe structures adapted to the customer Low productio

4、n frequencies Difficult continuous data collection Raw material and recipe information is not sufficient as a basis for a qualityprediction Is an AI implementation possible at all?Phase 1:Status AnalysisInternal Analysis:Screening Data Get to know the data Data collection Data Bundling Creation of a

5、 database structure Based on this,further analysis AI-based data analysis on a defined product group Evaluation of correlations and patterns from the database Mathematical modelling to validate solutions for O.K.and not O.K.productsInternal Analysis:AUC EvaluationIdeal classifier100%TPR and 0%FPRPre

6、diction is consistent with the observedresultsClear distinction between TN and TPRandom Classifier50%TPR and 50%FPRIt is not possible to distinguish between TNand TPPredictive model is inappropriateInsufficient data basis=+=+Area under Curve(AUC)Internal Analysis:Check Models=+=+Area under Curve(AUC

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本文介绍了Metromation Inc.公司如何利用人工智能(AI)提高生产效率和产品质量。文章首先提出了一个问题:在生产过程中,如何通过AI实现更好的结果。接着,文章介绍了模块化工厂(MoFa)的概念,并指出通过模块化生产可以提高生产效率、稳定性和可持续性。然后,文章以一个涂料厂为例,介绍了一个案例研究,通过分析数据和建立数学模型,成功地预测了产品质量。在第二阶段,文章讨论了如何通过整合传感器技术、建立中央数据库和优化AI算法来实现更精确的质量预测。最终,文章指出,通过AI质量预测和决策支持系统,可以成功地预测产品的质量,其中预测OK和不合格产品的准确性达到了89%。
"AI在生产中的下一步是什么?" "如何通过模块化工厂提高生产效率?" "模块化工厂如何帮助预测产品质量?"
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