Evaluation Improvement of Production Productivity Performance using Statistical Process Control, Overall Equipment Efficiency, and Autonomous Maintenance
Manufacturing firms are more focusing on improving the production performance in term of productivity output in order to survive in the competitive market, because a high productivity performance has a direct relationship with the equipment efficiency and process control. Absence of the proper produ...
| Main Author: | |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Elsevier Ltd
2015
|
| Subjects: | |
| Online Access: | http://umpir.ump.edu.my/id/eprint/11114/ http://umpir.ump.edu.my/id/eprint/11114/ http://umpir.ump.edu.my/id/eprint/11114/ http://umpir.ump.edu.my/id/eprint/11114/1/Evaluation%20Improvement%20of%20Production%20Productivity.pdf |
| Summary: | Manufacturing firms are more focusing on improving the production performance in term of productivity output in order to survive in the competitive market, because a high productivity performance has a direct relationship with the equipment efficiency and process control. Absence of the proper productivity measurement indicators locates manufacturing firm at an unknown production line performance. Unstable and uncontrollable process causes producing nonconforming product, which affect the overall production performance. The integration between the Statistical Process Control (SPC), Overall Equipment Efficiency (OEE), and Autonomous Maintenance (AM) is proposed to achieve continuous improvement in the production capability. This integration can enhance the productivity performance of manufacturing firms. The purpose of this study is to evaluate production productivity by continuously improve the equipment efficiency and process control in tiles manufacturing industry. For this purpose, OEE is proposed as the indicator to measure the equipment efficiency. Analysis and efficiency improvement are carried out using Define, Measure, Analyze, Improve and Control (DMAIC). SPC is suggested as monitor function for evaluating the process quality performance and the seven basic tools are used to tackle the manufacturing process variations. AM is applied in the glazing line to improve the machine efficiency by giving more responsibility and authority to the operators to do more improvement and preventative actions to their own machines. This study shows that loss mechanism of the equipment is unknown to the company's employees even though the condition of low production performance has been observed. Result of the study presents that the implementation of AM has successfully reduced 8.49% of the defect rates of glazing line from 14.61% to 6.12%. Machine breakdown time has been decreased from 2502 minutes to 1161 minutes whereas the OEE has been improved 6.49% from 22.12% to 28.61%. |
|---|