Production System Performance Improvement by Assembly Line-seru Conversion

Author(s):  
Luming Shao ◽  
Zhe Zhang ◽  
Yong Yin
2020 ◽  
Vol 6 (1) ◽  
Author(s):  
Lance Clarence ◽  
Wan Muhammad Noor Sarbani Mat Daud

In the competition among organization on the global market, no organization will tolerate losses. Overall Equipment Effectiveness (OEE) overall is a new process in which the efficiency of a system is calculated and complicated manufacturing issues are truly simplified to simple and intuitive knowledge delivery. It thinks about the exceptionally important measures of productivity. An endeavour has been done to measure and analyse existing Overall Equipment Effectiveness (OEE) at company Kirino in hope to reduce unplanned downtime losses on equipment failure and tooling damage to maximize the productivity. The methods used to analyse these various causes were analysis tools and Intelligence Systems. After knowing the causes of various activities that leads to high rates of defects, then recommendations for improvements that could be used by company Kirino were ready to be made using intelligent system as a medium of solution


2021 ◽  
Vol 13 (15) ◽  
pp. 8502
Author(s):  
Polinpapilinho F. Katina ◽  
James C. Pyne ◽  
Charles B. Keating ◽  
Dragan Komljenovic

Complex system governance (CSG) is an emerging field encompassing a framework for system performance improvement through the purposeful design, execution, and evolution of essential metasystem functions. The goal of this study was to understand how the domain of asset management (AsM) can leverage the capabilities of CSG. AsM emerged from engineering as a structured approach to organizing complex organizations to realize the value of assets while balancing performance, risks, costs, and other opportunities. However, there remains a scarcity of literature discussing the potential relationship between AsM and CSG. To initiate the closure of this gap, this research reviews the basics of AsM and the methods associated with realizing the value of assets. Then, the basics of CSG are provided along with how CSG might be leveraged to support AsM. We conclude the research with the implications for AsM and suggested future research.


2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Rajat Kumar Giri

Abstract In this paper, a hybrid-subcarrier-intensity-modulation (hybrid-SIM) technique for the performance improvement of free-space-optical (FSO) communication system has been proposed. Subsequently, for further error performance improvement, avalanche photodiode (APD) based receiver is used in the proposed system. The system performance is analyzed at various atmospheric turbulence levels over weak and strong turbulence channels. The bit error rate (BER) is theoretically derived using Gauss–Hermite approximation and Meijer-G function and it is simulated in the MATLAB environment. The simulation result shows that the BER performance of hybrid-SIM is better than BPSK-SIM technique irrespective of the channel types and also the significant BER performance improvement is observed by APD receiver.


2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Jinqing Hao ◽  
Bingchen Han

Abstract In the discretely amplified transmission systems with erbium-doped fiber amplifiers, the system performance of nonlinearity-compensated optical transmission based on pre-dispersed spectral inversion (PSI) is investigated numerically. We find that PSI offers more significant performance improvement in dispersion-managed (DM) links than that in non-dispersion-managed (noDM) links. On the other hand, the DM link is more sensitive to the span offset from the center of the transmission link than noDM link. The performance difference between DM and noDM links is 1 dB if the span offset equals four spans in 20 × 90 km nonlinear transmission. Furthermore, we show that for the dispersion-managed transmission, in order to obtain the best system performance, the amount of pre-dispersion of the PSI, should be optimized over different dispersion maps.


2016 ◽  
Vol 14 (5) ◽  
pp. 050608-50611
Author(s):  
Jie Su Jie Su ◽  
Xinying Li Xinying Li ◽  
and Jianjun Yu and Jianjun Yu

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