Kanban system based on manufacturing equipment operation monitoring

6th ModTech International Conference - Modern Technologies in Industrial Engineering

Belu, N.^1 ; Ionescu, L.M.^2 ; Mazre, A.-G.^2 ; Rachieru, N.^1

University of Pitesti, Faculty of Mechanics and Technology, Department of Manufacturing and Industrial Management, Targu din Vale Street, no.1, Pitesti Arges

110040, Romania^1

Faculty of Electronics, Computers and Electrical Engineering, University of Pitesti, Targu din Vale, no.1, Pitesti, Romania^2

关键词: Ad hoc radio networks;    Complex event processing;    Degree of scalability;    Experimental modeling;    Interdisciplinary research;    Manufacturing equipment;    Non-invasive monitoring;    Operation monitoring;   

Others  :  https://iopscience.iop.org/article/10.1088/1757-899X/400/6/062005/pdf
DOI  :  10.1088/1757-899X/400/6/062005

来源: IOP

【 摘 要 】

This work paper presents a single-channel Kanban solution where ticketing from downstream operator to the upstream operator in production flow is automatically performed when the completion of operations is identified. Thus, a more efficient transmission and placement mechanism for the tickets is provided for real-time operation of the machines, compared with others Kanban solutions. Our proposed solution contains elements of modern interdisciplinary research: industrial process improvement solutions using one Just in Time methodology: Kanban system, self - harvesting sensors, non-invasive monitoring solutions, multiple-source acquisition software, complex event processing and real-time parallel processing, use of Machine Learning analysis techniques (Deep Learning networks) to identify equipment operating regimes, use of ad hoc radio networks for data communication. The system was developed at an experimental model level. The article presents, with results, a case study in which we have two operators in a production stream. As will be shown, the system has a high degree of scalability, so it can easily be extended to any number of operators in the production stream.