Chia-Nan Wang

Evaluating the manufacturing capability of a lithographic area by using a novel vague GERT

This study proposes a novel vague graphical evaluation and review technique (GERT) for evaluating wafer manufacturing yield and finishing time in lithographic area. Wafer manufacturing reparability in lithographic area often requires reentry operations. Besides, many manufacturing steps, variable products, and flows can cause many difficulties and uncertainties. Hence, lithographic area is always the bottleneck in wafer fab manufacturing procedures. The main purpose of this study is to resolve the reentry problem in wafer manufacturing by GERT, and to solve the uncertainty problem by using vague set. Based on the manufacturing procedure of lithographic area in the 300mm wafer fab, the algorithm steps for vague GERT are proposed, and a simple decision support system is developed to process the complex calculation procedure for providing more information to managers. We also hope to enhance the capability of lithographic area in order to improve overall system performance.

The heuristic preemptive dispatching method for convey-based automated material handling system of 450mm wafer fabrication

The 450mm wafer fabrication is the current trend of semiconductor industry.Conveyor-based automated material handling system (AMHS) has been suggested.A heuristic preemptive dispatching method is proposed for a convey-based AMHS.The AMHS is restructured based on activated roller belt (ARB).Experimental results show the proposed preemptive dispatching method is effective. The 450mm transition of wafer fabrication is the current trend of semiconductor industry. However, the increased size and weight of wafers pose challenges on wafer handling and transportation. To address this issue, conveyor-based automated material handling system (AMHS) has been suggested as a solution due to its advantages. However, the lack of an effective and efficient dispatching method will make a convey-based AMHS to remain suffer traffic-jams problem and short the capability to handle hot lots to meet customer needs. In this study, a heuristic preemptive dispatching method (HPDB) is proposed for controlling the movements of wafer lots in a convey-based AMHS that is restructured based on activated roller belt (ARB) and to be used for 450mm wafer fabrication. To investigate the effectiveness of the HPDB, simulation experiments have been conducted and the results obtained from HPDB has been compared to that obtained from HPD. The experimental results show that HPDB outperforms HPD in terms of average delivery time, with the advantages of 55.11% for hot lots and 55.76% for normal lots. This indicates that HPDB can better solve the traffic-jam problem and reduce transportation time.

Three-step approach for wafer sawing lane inspection

Wafer sawing performance must be closely monitored to ensure a satisfactory integrated circuits manufacturing yield. The inspection must allow the GO/NG decision to be fast and reliable, while also assuring that the training of the inspector is simple and not time consuming. The traditional neural-network approach to inspect images, while simple to implement, presents some disadvantages, including training efficiency and model effectiveness. Based on contour detection of the sawing lane, this work proposes a novel method combined with cross-center localization of sawing lanes, detection of sawing track, and four signatures to detect the abnormality of sawing effectively and timely. Our method does not need pretraining but runs faster and provides a better method with more effectiveness, higher flexibility, and immediate feedback to the sawing operation. An experiment using real data collected from an international semiconductor package factory is conducted to validate the performance of the proposed framework. The accurate acceptance rate and the accurate rejection rate are both 100%, while the false acceptance rate and false rejection rate are both zero as well. The results demonstrate that the proposed method is sound and useful for sawing inspection in industries.

Analyzing PSU’s Performance: A Case from Ministry of Petroleum and Natural Gas of India

The high economic growth in the past few years and increasing industrialization coupled with a burgeoning population have created a lot of concern for India’s energy scenario. India’s crude oil production has not shown significant growth in the last 10 or more years whereas its refining capacity has grown by more than 20% over the last 5 years. Oil consumption is growing at approximately 4.1% per year and natural gas consumption is growing at 68% per year. Therefore, evaluation performances and pushing energy companies to improve become important issues. The purpose of this research is of evaluation the performance of Indian energy industry under multiple different inputs and outputs criteria. The data envelopment analysis (DEA) and grey theory are used to conduct this study. There are total 14 public sector undertakings (PSUs) under this industry and no any private company. However, only 10 of them are mature enough to be published in India stock markets. Therefore, the realistic data of all 10 companies are used for this evaluation. The results demonstrate that Gas Authority of India Limited (GAIL), Chennai Petroleum Corporation Limited (CPCL), and Oil India Limited (OIL) are the top 3 of ranking influences. This integrated numerical study gives a better “past-present-future” insights into evaluation performance in India energy industry.

Estimation of the Market Size of Medical Tourism Industry Using Grey Models -- Case Study in South Korea

South Korea (Korea) is a highlight of medical tourism in Asia in the recent years. It has become an attractive destination with the large number of foreign patients around the world. Although, the businesses of medical tourism in this country are quickly expanding, its market size is still unclear due to the shortage of statistical number. Therefore, this study aims to employ forecast tool to estimate the number of foreign patients in Korea in the future. To conduct, the grey forecast has been utilized to construct several forecast models based on the data of foreign patients in Korea from 2009 to 2014. Empirical results indicated that, the GM(1,1) model was presented best forecasted performance with high precision (from 92.1% to 96.7%), compared with the Verhulst model (from 45.5% to 81.3%) and the DGM(2,1) model (from 71.3% to 94.9%). According to the forecasted results of GM(1,1) model, the foreign medical tourists visit to Korea will increase significantly year-on-year. Koreas medical tourism market will attract to 1,378,954 foreign patients in 2020, up to approximately four times from 352,976 in 2015. Among that, to 2020, the number of medical tourists in department of cosmetic and plastic surgeries will achieve 483,615 patients. In addition, for the origin of medical tourist, the number of Chinese and American medical tourist will be estimated to reach 1,163,965 and 82,227 patients respectively in 2020.

Modelling of a PMSG Wind Turbine with Autonomous Control

The aim of this research is to model an autonomous control wind turbine driven permanent magnetic synchronous generator (PMSG) which feeds alternating current (AC) power to the utility grid. Furthermore, this research also demonstrates the effects and the efficiency of PMSG wind turbine which is integrated by autonomous controllers. In order for well autonomous control, two voltage source inverters are used to control wind turbine connecting with the grid. The generator-side inverter is used to adjust the synchronous generator as well as separating the generator from the grid when necessary. The grid-side inverter controls the power flow between the direct current (DC) bus and the AC side. Both of them are oriented control by space vector pulse width modulation (PWM) with back-to-back frequency inverter. Moreover, the proportional-integral (PI) controller is enhanced to control both of the inverters and the pitch angle of the wind turbine. Maximum power point tracking (MPPT) is integrated in generator-side inverter to track the maximum power, when wind speed changes. The simulation results in Matlab Simulink 2012b showing the model have good dynamic and static performance. The maximum power can be tracked and the generator wind turbine can be operated with high efficiency.

A Model for Candidate Selection of Strategic Alliances: Case on Industry of Department Store

In a globally competitive environment, how corporations use strategic alliances to gain a competitive advantage has become an important topic. Based on data envelopment analysis (DEA) and the heuristic technique, this study proposes a model which is termed the candidate selection of strategic alliance (CSSA). The objective is to find the most proper partner for strategic alliance. Realistic data for the industry of department store are collected from Taiwan published stock market. The results are sound by review of many industrial managers and indicate that CSSA can effectively provide recommendations for enterprises to find the proper candidates of alliance.

Partner Selection in Supply Chain of Vietnam’s Textile and Apparel Industry: The Application of a Hybrid DEA and GM (1,1) Approach

Vietnam is currently among the top-five textile and apparel exporters, and the industry is considered quite attractive to foreign investors. Nevertheless, the global textile and garment industry is experiencing important changes. The three main producing regions in the world are China, Southwest Asia (India, Pakistan, Bangladesh, and Turkey), and ASEAN. In order to maintain its positioning and to establish stable and sustainable Vietnam textile and apparel development, there must be radical changes. Due to this necessity, the authors conducted this study by using grey forecasting to predict and reflect the condition of businesses in the period of 2017–2020, together with combining a DEA model to help businesses select the most appropriate strategic partner in the supply chain in order to achieve economic goals and promote the strength of the businesses partaking in the association. Besides, this helps businesses exploit market opportunities and take advantage of the capabilities of the textile and apparel industry.

The Selection of Strategic Alliance Partner in Vietnam Garment Industry Using Grey Theory and DEA

This study applies an assessment model to measure the efficiency of companies in Vietnam garment industry based on Grey theory (GM (1, 1)) and data envelopment analysis model. The objective of this research is to provide an effective method to find the right strategic partners. Total 11 companies of garment industry are chosen with realistic data collected from financial statements of Vietnam published stock market during period 2007 to 2010. Firstly, the GM (1, 1) is employed to predict the inputs and outputs factor. Secondly, Slack based measure of supper efficiency (Super-SBM) model is applied to help the target company to find the right partners. The empirical results show that companies who have better efficiencies do not guarantee them to get the good performance after alliances, companies with low-mid efficiencies may have the chance to put in efforts for alliances because they may get some benefits for both candidate and target companies. This study could give companies some recommendations about how to improve productivity as well.

Performance assessment for electronic manufacturing service providers using two-stage super-efficiency SBM model

ABSTRACT Manufacturing Service providers (EMSs) offer services to Original Equipment Manufacturers (OEMs). However, increasing challenges require an EMS to be more capable, adaptable and responsive. For survival, an EMS manager has to understand its relative efficiency in the industry. In addition, an investor also requires such information for investments. In this research, we propose a novel approach, which combines GM(1,1) with a two-stage super-efficiency slacks-based measure (SBM) model, to forecast and assess the efficiencies of 18 EMSs. The GM(1,1) was first used to forecast future data of EMSs, and then the two-stage super-efficiency SBM model was used to measure the marketability and profitability efficiencies for an EMU in two stages. The results build a ‘past-current-future’ view on the two efficiencies for each EMS. In addition, the profitability efficiency can help justify the reasonability of marketability efficiency. Our results showed that Hon Hai tops the rankings in both profitability and marketability efficiencies. These results also provided information about relative efficiencies of these EMSs, which helps EMS managers and investors to make better decisions.