| Title |
Development of a solution for monitoring and recording the state of a sewing machine |
| Translation of Title |
Siuvimo mašinos būsenos stebėjimo ir surinkimo sprendimo kūrimas. |
| Authors |
Stražinskas, Paulius |
| Full Text |
|
| Pages |
56 |
| Keywords [eng] |
sewing machine ; process automation ; data collection ; data monitoring ; sensors comparison |
| Abstract [eng] |
During this work an in depth analysis of existing data collection and recording solutions have been made. The analysis includes methods used in the manufacturing industry to collect information, and how they can be implemented in the sewing industry. The structure of a PFAFF 951 lockstitch sewing machine has been analysed to better understand the working principles of the sewing machine and existing solutions of sewing machine state monitoring have been reviewed. The acquired knowledge of the structure of a lockstitch sewing machine and possible monitoring solutions applied in the industry have been combined in effort to create a simple, yet versatile monitoring and recording system for sewing station data collection. In effort to select the most compatible sensors that would provide the monitoring and recording system with the most representative data, a sensor analysis and comparison has been done. The found sensors have been integrated into a monitoring system and verified by a higher or equal accuracy class instrument to prove their accuracy and reliability of the retrieved data. To integrate recording capabilities into the created monitoring system a Raspberry Pi 3B+ micro-computer has been implemented as the main data collection server. The collection of different sensor data retrieved from the Raspberry Pi 3B+ has been analysed and compared on the same real-time axis. The comparison consists of different action recognition from the retrieved data. It has been found that the most appropriate sensors to depict sewing machine state are current sensors. The possibility of integrating a non-complex data collection system into an existing sewing machine, could allow smaller scale manufacturers to implement big business methods such as LEAN and 6σ to increase efficiency of their production process. |
| Dissertation Institution |
Kauno technologijos universitetas. |
| Type |
Master thesis |
| Language |
English |
| Publication date |
2025 |
