Due to the rising usage of sensors and networked equipment in manufacturing, artificial intelligence solutions help extract significant value from extensive data infrastructure. These methods may aid manufacturing sustainability and decision-making. Failure to check tool condition causes a lot of scrap in machining. This work develops an intelligent (IoT) tool condition monitoring system to detect sustainability-related production tradeoffs and optimum machining settings by monitoring machine tool status. A Pareto optimum front visualizes the ideal operating conditions found via evolutionary artificial intelligent (AI) algorithm-based multi-objective optimization.


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    Tool condition monitoring by quality during the micro milling process by using IoT and AI


    Beteiligte:
    Kumar, V. naveen (Autor:in) / Singh, Gurpreet (Autor:in) / Rudresha, S. (Autor:in) / Sampath Kumar, S (Autor:in)


    Erscheinungsdatum :

    2022-12-01


    Format / Umfang :

    718843 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



    Tool Condition Monitoring in Face Milling Process Using Decision Tree and Statistical Features of Vibration Signal

    Vaithiyanathan, Muralidharan / Durairaj, Pradeep Kumar | SAE Technical Papers | 2019


    Micro to macro. Wear debris analysis as a condition monitoring tool

    Chapman, R.W. / Hodges, D.J. / Nowell, T.J. | Tema Archiv | 2002


    IN-PROCESS TOOL CONDITION MONITORING USING ACOUSTIC EMISSION SENSOR IN MICROENDMILLING

    Prakash, M. / Kanthababu, M. | British Library Online Contents | 2013


    Machining Characteristics of Micro-Flow Channels in Micro-Milling Process

    Koo, Joon-Young / Kim, Jeong-Suk / Kim, Pyeong-Ho | British Library Online Contents | 2014


    Machining Characteristics of Micro-Flow Channels in Micro-Milling Process

    Koo, J.-Y. / Kim, J.-S. / Kim, P.-H. | British Library Online Contents | 2014