Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/64835
Title: Data acquisition from machines with legacy system
Authors: Surendrakumar Madasamy Poosapandian
Keywords: DRNTU::Engineering::Computer science and engineering::Data
Issue Date: 2014
Abstract: Contention for leading the market in terms of productivity and quality drives the manufacturing companies to renew itself with new technologies frequently. With the advancement in automation, computer programming and networking, equipping legacy systems with data acquisition and monitoring applications have been made possible. Collecting data from machines and using it to monitor machine's states have the advantage of detecting events happened in shop floor without the need for manual intervention as data collected manually may contain delayed and inaccurate information. This machine monitoring system is accomplished by acquiring data from different machines in shop floor using a network for local communication. In this project, ServBox, which provides a method for collecting data from many CNC machines, is used as a local server. The acquired data is pre-processed to suit the needs of processing at later stages and relationship between various parameters is analysed so as to formulate a data model for extracting information from the collected data. This project also discusses about using the extracted information for developing different monitoring applications. One application is to develop a system that automatically calculates machine's production efficiency through Overall Equipment Effectiveness (OEE) technique and monitor the reason behind idle state of the machines and using the same to identify non-productive activities (wastes) for the implementation of lean manufacturing. The other application is to develop a strategy for monitoring tool wear using information obtained from acquired data. User interface is designed and created to enable operator to view or update the machine statuses when needed.
URI: http://hdl.handle.net/10356/64835
Fulltext Permission: restricted
Fulltext Availability: With Fulltext
Appears in Collections:EEE Theses

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