| Title |
Intelligent VSM Model: a way to adopt Industry 4.0 technologies in manufacturing industry |
| ID_Doc |
68531 |
| Authors |
Mariappan, RCS; Veerabathiran, A; Paranitharan, KP; Vimal, KEK |
| Title |
Intelligent VSM Model: a way to adopt Industry 4.0 technologies in manufacturing industry |
| Year |
2023 |
| Published |
International Journal Of Advanced Manufacturing Technology, 129, 5-6 |
| DOI |
10.1007/s00170-023-12406-w |
| Abstract |
In the present scenario, the industry and manufacturers find hardship in running the business profitably by enhancing the production and efficiency of the system, Multiple factors influence the industry to meet the customer's requirements and to sustain itself in this competitive environment. The purpose of this research is to develop an Intelligent VSM (IVSM) Model which integrates with Industry 4.0 and lean tools to monitor the real-time manufacturing setup with recent trends in information technology. Our research is focused on developing an IVSM system enabled by IoT for the industry which caters for the need to enhance the performance of any manufacturing setup. A study has been conducted in an electronics component industry through the current state IVSM, and the IVSM Model for the future state was designed and implemented. The IoT-enabled future state Intelligent VSM system facilitates the need of today's dynamic manufacturing environment scenario, which continuously monitors through an integrated efficiency monitoring system (IEMS). The improved performance of the system is visualized in the dashboard at the specified regular intervals. A major highlight of this study is reduction in the lead time from 35.5 to 24 days, a reduction in the time required to verify the results of PDCA using IVSM from 30 to 1 h, and a 0.9% improvement in overall process cycle efficiency. Further to improve the effectiveness of the Intelligent VSM system, Kaizen activities have been implemented to eliminate the shortfalls and increase the efficiency in the future DVSM system. The proposed system integrates all the processes in the industry to predict the uncertainty. This research work can further extend to all other manufacturing and service support systems to integrate SMART sustainable systems and to predict critical conditions in advance. |
| Author Keywords |
Intelligent value stream mapping; Industry 4.0; Internet of things (IoT); Kaizen |
| Index Keywords |
Index Keywords |
| Document Type |
Other |
| Open Access |
Open Access |
| Source |
Science Citation Index Expanded (SCI-EXPANDED) |
| EID |
WOS:001087781000003 |
| WoS Category |
Automation & Control Systems; Engineering, Manufacturing |
| Research Area |
Automation & Control Systems; Engineering |
| PDF |
https://www.researchsquare.com/article/rs-2702005/latest.pdf
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