Prethodno priopćenje

https://doi.org/10.17559/TV-20220702054333

Development of the Adaptive System for Tool Management

Jenn-Yih Chen ; Department of Mechanical and Computer-Aided Engineering, National Formosa University, Yunlin 632, Taiwan
Yi-Ling Lin ; Department of Power Mechanical Engineering, National Formosa University, Yunlin 632, Taiwan
Bean-Yin Lee ; Department of Mechanical and Computer-Aided Engineering, Smart Machinery and Intelligent Manufacturing Research Ceneter, National Formosa University, Yunlin 632, Taiwan

Sažetak

Technological developments in the manufacturing industry have accelerated recently. Although many traditional manufacturing factories had adopted automated production, owing to the inability to control the status of individual tools, it is challenging for manufacturers to accurately track the real time status of production line tools. To bring smart production into existence, a robust database system needs to be ensured. New models of computer numerical control machines are equipped with a built-in tool management system (TMS), but most versions of this system are only able to set a machining time limit or a total number of workpieces limit for each tool to determine tool replacement intervals. Such system could likely cause early tool replacement, resulting in waste and increased tool costs. In order to implement green manufacturing, the prediction of tool wear is essential to reduce wastage of materials. In this study, we developed a TMS that is based on a not only SQL (NoSQL) database, which not only stores several different types of data, but also can store prediction models to make it suitable for the demands of varying enterprise scales. It will be more helpful to ensure processing safety and effectively reduce manufacturing costs.

Ključne riječi

group method of data handling; NoSQL database; polynomial network; tool management system

Hrčak ID:

294408

URI

https://hrcak.srce.hr/294408

Datum izdavanja:

26.2.2023.

Posjeta: 398 *