CHAPTER 4: SOLUTION TO IMPROVE HEADCOUNT STANDARD MODEL FOR
4.3. Expected result after improvement
The future CAP is forecasted after proposed solution. This may be used as a standard because of improvement as author mentioned above.
Table 4.8. Concept of area profile for MTs after improvement Operation name
8 Reject units take loss
9 Lot
move out Pull Lot to Mark 10 WIP, and put reject units in reject cart
(Source: Author research)
Category
EXT INT INT INT EXT EXT INT EXT EXT EXT EXT INT
STHI
According to the current state, MT takes around 52,1 minutes to complete 1 lot. With the new solution, the amount of time drop to 44,7 minutes. This means that saving at least 7 minutes per lot. This is meaningful for MT to perform their task better and meet the capacity effectively.
80
CSM vs FSM Value Analysis
Minutes
60,00 50,00 40,00 30,00 20,00 10,00
0,00
CSM FSM
VA NVA-R NVA
Figure 4.16. The future statistics about performance (Source: Author research)
Forecast MMR data analysis after improvement:
The data will be calculated by SQL pathfinder by entering the new data in the CAP table. SQL pathfinder will run automatically and export a new model for user to carry out a design of experiment (DOE). The expected result will normalize the speed of lot processing, independent of lot size.
The motivation behind MMR: It help anticipate total units out per period time. Move the product faster and make the result be predictable and repeatable. Optimize the speed of each lot through an operation. Divide the factory and the product in discrete groups.
Optimize the result at the discrete level. Optimize the speed of each lot through an operation.
Table 4.9. MMR for each product of STHI module after improvement
Operation Product
Name family
KB01
HL01
STHI QC03
ST02 BT02
(Source: Author research)
Table 4.10. MMR standard for STHI module after improvement
Operation Name
STHI
(Source: Author research)
With the proposed improvement, STHI module will step by step reduce the idle tool time, especially idle no support tool as MT spend almost their time to implement the NVA- R/NVA tasks. Hopefully, the new solution can cut down the percentage of idle tool time to nearly the standard of machine actual utilization defined by Engineering department.
82
Table 4.11. Semi-E10 future data analysis for STHI module
DATA ANALYSIS EE
NST TolUn
SDT Idle USDT TOTAL (Source: Author research)
FCM DATA ANALYSIS
100%
90%
80%
70%
60%
50%
40%
30%
20%
10%
0%
Figure 4.17. The future statistics about idle tool time in the period shown (Source: Author research)
Moreover, because the improvement impact all the activities that the MTs carry out, and lessen the impact of idle time to the processing time. Therefore not only produce more product, but can enhance the Run rate goal for future plan.
Kunits
Figure 4.18. STHI monthly output report (Source: Author research)
Last but not least, increase the current MMR 1:8 up to 1:9, this means module Headcount can cut down 3 MTs per shift and total 12 MTs for 4 shifts for STHI module.
According to the return on investment (ROI) report, saving 42.000 USD for ATM in 2020.
After the proposed solution for the STHI module, author also see a few opportunities to continue to apply this method for some Test modules with the same function like STHI module for the rest of 2020. Below is the POR table for the upcoming plan:
Table 4.12. Headcount plan of record (POR)
Site
VNAT VNAT VNAT Total (Source: Author research)
CONCLUSION
This thesis not only stresses the important of Headcount standard model in accordance with MMR at STHI module, but also be a reliable resource for further research on control and improvement of manufacturing aspects. During 6-month internship at Intel Products Vietnam Co., Ltd, author has leant a lot about the production process of the company, including STHI module. Through embarking in doing research as well as completing the graduate thesis, author explained the challenges that STHI module faced in order to balance and optimize the resources. First, author pointed out the misalignment between standard and current state of module. Second, author applied knowledge of Lean, MMR theory to bring out a solution in order to address the current situation.
The solution author proposed to improve Headcount standard model for STHI module somehow reaped good results. The proposed solution step by step lessen the gap and be a reference for any further investigation and inspection. However, because author’s knowledge is limited, especially in terms of technical skills as well as other related module processes, author just mentioned the gap of some technical tasks and did not drill down on them. Besides, there are some problems that still be in research and author has not found the solutions yet. If author is assigned to any module improvement projects with the help of stakeholders, author will thoroughly equip extensive knowledge and skills to enhance all the aspects of module and process.
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