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3rd International Conference on Smart Manufacturing, Industrial and Logistics engineering, SMILE 2023 and the 7th Asian Conference of management Science and Applications, ACMSA 2023

作者： Sakurai, Wataru Nakade, Koichi Nagoya Institute of Technology Systems Management and Engineering Program Gokiso-cho Showa-ku Nagoya-shi Aichi466-8555 Japan

ISBN: (纸本)9789819701933

In recent years, the development of a green supply chain model that takes sustainability into consideration has become an urgent issue in corporate management and policy operation. For example, in the fashion industry, the proper circulation of not only used items purchased by consumers, but also unsold items generated in retail stores is one of the most important issues. In this study, we examine a supply chain model for the appropriate circulation of unsold new products from retail outlets. Specifically, we considered a supply chain model in which a retailer’s inventory is divided into two states under stochastic demand fluctuations: new and old items, and the unsold old items are collected and reproduced by a manufacturer. By formulating this model as a Markov decision process, the optimal decisions regarding the retailer’s ordering policy and the retail price and the manufacturer’s wholesale price are obtained. Optimal investment and appropriate institutional design to reduce CO2 emissions generated in a supply chain are also considered. Specifically, we examine the decision of green investment in manufacturing technology to reduce CO2 emissions when a manufacturer produce items. And we examine the design of a carbon tax system to control CO2 emissions. Sensitivity analysis on the carbon tax system shows that raising the carbon tax rate increases the optimal retail price, the optimal wholesale price, and the optimal green investment. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Investments

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Machine-learning-based sampling inspection under OQC capacity for real-time quality monitoring in the TFT-LCD industry

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International Journal of Production Research 2025年第6期63卷 2090-2113页

作者： Shih, Ming-Sung Chen, James C. Chen, Tzu-Li Chiang, Chih-Hsiung Hsu, Ching-Lan International Intercollegiate Ph.D. Program National Tsing Hua University Hsinchu Taiwan Department of Industrial Engineering and Engineering Management National Tsing Hua University Hsinchu Taiwan Graduate Institute of Intelligent Manufacturing Technology National Taiwan University of Science and Technology Taipei Taiwan Division of Quality Control AUO Corporation Taichung Taiwan

In the thin film transistor-liquid crystal display (TFT-LCD) industry, the competition is fierce, and the external failure cost is high. To improve the quality of released products, sampling inspection under outgoing quality control (OQC) is conducted before products are released. Owing to the variety and complexity of inspection items, the task must be carried out manually while realising automation is difficult. Traditional random sampling inspection is limited by sampling quantity, manpower, and material resources. To effectively improve acceptable quality levels, this paper proposes a quality predictive monitoring framework tailored to the production and inspection characteristics of the TFT-LCD industry. This framework includes real-time automatic quality monitoring based on an optimal machine learning prediction model with two-phase feature creation, and it also addresses OQC inspection capacity constraints. Experimental results show the prediction performance based on proposed model is better than the traditional random sampling process. In practice, superior average outgoing quality improves by more than 70% at the same sampling level. In addition, the features of the process can be further controlled and managed based on the prediction model to monitor the key parameters in real time and respond to abnormalities quickly, thereby further improving the quality of released products. © 2024 Informa UK Limited, trading as Taylor & Francis Group.

关键词： Liquid crystal displays

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Application of Process Failure Modes and Effect Analysis for Acceptance Quality Limit in Lot Sentencing 24

Application of Process Failure Modes and Effect Analysis for...

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2024 7th International Conference on Computers in management and Business, ICCMB 2024

作者： Reihana, Nafadza Salsabila Nurprihatin, Filscha Islam, Sri Susilawati Redi, Anak Agung Ngurah Perwira Young, Michael Nayat Prasetyo, Yogi Tri Department of Industrial Engineering Faculty of Engineering and Technology Sampoerna University 12780 Indonesia School of Industrial Engineering and Engineering Management Mapua University Manila Philippines International Bachelor Program in Engineering Yuan Ze University Chung Li Taiwan

ISBN: (纸本)9798400716652

The quality control process performs an acceptance sampling plan to determine if a batch of products meets quality specifications. Acceptance Quality Limit (AQL) defines the acceptable level of defects, but determining the appropriate AQL rate is challenging due to manufacturing process variations. This study utilized Process Failure Mode and Effect Analysis (PFMEA) to determine the AQL for acceptance sampling plans and evaluate its performance against the current method using Operating Characteristic Curve. The study identified eighteen failure modes from PFMEA, with severity level 7, occurrence level 3, and detection level 3. The results demonstrated that PFMEA can serve as a valuable reference for modeling acceptance sampling plans. Acceptance sampling with AQL effectively assesses defective batches compared to the current method. Incorporating PFMEA in acceptance sampling plans enables companies to enhance their understanding of process performance and potential risks, empowering them to make informed decisions and improve product quality. © 2024 ACM.

关键词： Failure modes

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A Social Analysis of Thailand's 2023 Election Through Twitter Feeds 15

A Social Analysis of Thailand's 2023 Election Through Twitte...

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15th International Conference on Information technology and Electrical engineering, ICITEE 2023

作者： Sarapugdi, Wanaporn Namkhun, Songphon Rajabhat Mahasarakham University Program in Management of Digital Innovation Faculty of Information Technology Maha Sarakham Thailand Rajabhat Mahasarakham University Program in Computer Engineering Faculty of Engineering Maha Sarakham Thailand

ISBN: (纸本)9798350304466

Nowadays, it cannot be denied that social media has been in many parts of people's lives, especially in entertainment, business and education. Public figures including politicians frequently use social platforms to connect with their audience, for example Facebook, Instagram, Tiktok and etc. One of the most commonly used is a platform called Twitter or also known as X. It is a platform that people can share their opinions in short messages. Since there is an alphabet limitation, people can deliver and receive message rapidly. It is a perfect platform that we could use to update the real-time situations for example election, emergency alert, natural disasters and etc. According to its characteristic, it can be used as a data source for social media analytics, which involves collecting and analyzing data to perform business decisions. The social media analytics has become commonplace because the number of people using social media tends to increase every second. Specifically, Twitter sentiment analysis offers a quick and inexpensive tool for monitoring and predictions. In this work, Twitter is used as a data source to monitor and predict Thailand Election in 2023 because this election highly attracts attention from Thais and international. Moreover, Twitter is a significant platform that is used to debate about political events in Thailand. The result of this election potentially indicates Thailand's future, including economics, public health, environment, international relations and etc. Our work performs sentiment analysis to categorize the data and mainly focuses on extracting sentiment from text without considering semantic word relations and co-occurrences because it is appropriate and functional for Thai sentence analysis. Based on the result, it can be seen that Twitter plays a significant role in politics, with politicians wielding considerable influence over public perception. Comparing of the actual election result and the predicted result, this analysis dem

关键词： Sentiment analysis

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Optimizing Value Proposition and Customer Engagement in Mobile Applications: Using UML with Process Chain Analysis Enhancing Start-Up Coffee Chain Mobile Apps with UML and PCN Analysis 24

Optimizing Value Proposition and Customer Engagement in Mobi...

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2024 7th International Conference on Computers in management and Business, ICCMB 2024

作者： Sinawang, Beatrice Hillary Redi, Anak Agung Ngurah Perwira Young, Michael Nayat Prasetyo, Yogi Tri Department of Industrial Engineering Faculty of Engineering and Technology Sampoerna University Jakarta12780 Indonesia School of Industrial Engineering and Engineering Management Mapua University Manila Philippines International Bachelor Program in Engineering Yuan Ze University Chung Li Taiwan

ISBN: (纸本)9798400716652

This study examines value proposition enhancement and customer engagement techniques in the context of the integration of mobile applications in small scale start up coffee chains. Startups do not have the same resources and infrastructure for extensive technological integration, like well-established chains, thus operating in unique segment of the industry. The study investigates the transformative influence of mobile applications ordering platforms on customer interactions, and operational efficiency. Specifically, the value proposition, as most mobile applications offer similar promises all centered around convenience, encapsulated in the phrase "Use the App, Skip the Queue". Process Chain Analysis identified the difference of direct interaction for offline orders and the surrogate interactions of application orders, is the root of operational issues, causing frustration in the ordering process. This finding acts as the foundation for the multi-criteria decision tree to assist in selecting the appropriate solution, through calculated weighted score. The solutions selected through this method were kitchen display system, and QR tracking system both scoring 4.64 and 4.84 respectively. UML diagrams were used to provide visual representation for the concepts, to aid in comprehension of how the concept should be implemented and used in the store. The outcomes highlight how the solutions improve operational efficiency and customer satisfaction through transparency. The study is simply a concept, which has not been tested and all conclusions have been based on heuristic from previous implementation of similar solutions in restaurants and other food and beverage chains. © 2024 ACM.

关键词： Mobile applications

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Enhancing logistics performance measurement: an effectiveness-based hierarchical data envelopment analysis approach

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INFOR 2024年第3期62卷 449-479页

作者： See, Kok Fong Guo, Yongli Yu, Ming-Miin Economics Program School of Distance Education Universiti Sains Malaysia Malaysia Technology Management Economics and Policy Program Seoul National University Korea Republic of Fudan Development Institute Fudan University China School of Engineering Shandong Xiandai University China Department of Transportation Science National Taiwan Ocean University Taiwan

The logistics performance index (LPI) is a comprehensive and comparable composite index developed by the World Bank to assess a country’s logistics and trade facilitation environment. However, the existing LPI relies on externally assigned weights. To enhance LPI scores, this study adopts an effectiveness-based hierarchical data envelopment analysis method that internally allocates objective weights based on the dataset. Such endogenous weight information can provide additional valuable insights for countries to prioritize and strategize efforts to enhance their performance in the future. The results of this study indicate that focusing on improving the policy category yields greater benefits than improving the service category in terms of ranking national logistics performance. Furthermore, this study finds that logistics performance is influenced by income levels and geographical area. Income levels impact the regulatory and trade facilitation environment, with varying income levels leading to different priority policy areas. Geographical location also plays a crucial role in regional economic integration and trade facilitation. A favorable geographical location reduces costs and time while enhancing supply chain predictability and reliability. It is hoped that this study serves as a valuable resource for countries in identifying optimization strategies to improve their logistics performance. © 2024 Canadian Operational Research Society (CORS).

关键词： Data envelopment analysis

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Understanding AI Application Dynamics in Oil and Gas Supply Chain management and Development: A Location Perspective

HighTech and Innovation Journal

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HighTech and Innovation Journal 2022年第SPECIAL ISSUE期3卷 1-14页

作者： Deif, Ahmed Vivek, Thejas Industrial Technology and Packaging Dept California Polytechnic State University United States Industrial Engineering Management Program Qatar University Doha Qatar

The purpose of this paper is to gain a better understanding of Artificial Intelligence (AI) application dynamics in the oil and gas supply chain. A location perspective is used to explore the opportunities and challenges of specific AI technologies from upstream to downstream of the oil and gas supply chain. A literature review approach is adopted to capture representative research along these locations. This was followed by descriptive and comparative analysis for the reviewed literature. Results from the conducted analysis revealed important insights about AI implementation dynamics in the oil and gas industry. Furthermore, various recommendations for technology managers, policymakers, practitioners, and industry leaders in the oil and gas industry to ensure successful AI implementation were outlined. © Authors retain all copyrights.

关键词： Gases

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Diversity-Optimized Group Extraction in Social Networks

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IEEE Transactions on Computational Social Systems 2024年第1期11卷 756-769页

作者： Hsu, Bay-Yuan Chen, Yi-Ling Ho, Ya-Chi Chang, Po-Yuan Chang, Chih-Chieh Shia, Ben-Chang Shen, Chih-Ya National Tsing Hua University Department of Industrial Engineering and Engineering Management Hsinchu30013 Taiwan National Taiwan University of Science and Technology Department of Computer Science and Information Engineering Taipei10607 Taiwan Hsinchu31040 Taiwan Fu Jen Catholic University Department of Business Administration New Taipei City24205 Taiwan National Taiwan University of Science and Technology Management Undergraduate Program Taipei10607 Taiwan National Tsing Hua University Department of Computer Science Hsinchu30013 Taiwan

In this article, we propose to study a novel research problem to boost group performance, that is, social-aware diversity-optimized group extraction (SDGE), which takes into consideration the two important factors: 1) group diversity and 2) social tightness. We prove the NP-hardness of SDGE and propose an effective algorithm, named group shrinking for diversity maximization (GSDM) with a performance guarantee, that is, GSDM is a three-approximation algorithm to the SDGE problem studied in this article. We further propose three effective pruning strategies that are able to boost the efficiency of GSDM but do not deteriorate its performance. We conduct extensive experiments on multiple large-scale real datasets to evaluate the performance of GSDM. The experimental results show that our proposed GSDM outperforms the other baseline approaches significantly, in terms of solution quality and efficiency. Moreover, the experimental results also confirm that our proposed pruning strategies indeed boost the efficiency of the algorithm. © 2014 IEEE.

关键词： Costs

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Identification of Extreme Precipitation Changes Due to Climate Change in Indonesia 3rd

Identification of Extreme Precipitation Changes Due to Clima...

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3rd International Conference on Radioscience, Equatorial Atmospheric Science and Environment, INCREASE 2023

作者： Aminah, Siti Riawan, Edi Syahputra, Muhammad Ridho Kuntoro, Arno Adi Master Program in Water Resource Management Faculty of Civil and Environmental Engineering Bandung Institute of Technology Bandung Indonesia Atmospheric Sciences Research Group Faculty of Earth Science and Technology Bandung Institute of Technology Bandung Indonesia Water Resources Engineering Research Group Faculty of Civil and Environmental Engineering Bandung Institute of Technology Bandung Indonesia

ISBN: (纸本)9789819707393

This study uses Global Precipitation Measurement (GPM) and Coupled Model Intercomparison Project Phase 6 (CMIP6) precipitation data to identify extreme precipitation intensity and frequency changes in Indonesia. Extreme precipitation calculations were performed using the Gumbel distribution and return period fitted to annual maxima data. Extreme precipitation and frequency of extreme events were compared between the historical period and the near-future period (2026–2055) and the far-future period (2070–2099) to identify changes. The results showed that there were changes in extreme precipitation in Indonesia both in intensity and frequency of occurrence. Extreme precipitation with a 5-year return period in Indonesia generally has a change value in the range of − 5 to + 25% with most areas likely to increase. The increased value reaches + 20% in the near-future period and + 40% in the far-future period. For the frequency of extreme precipitation above the 5-year return period in Indonesia, the change value is generally in the range of − 40 to + 120% with most areas likely to increase. The increased value reaches + 160% in the near-future period and + 200% in the far-future period. In the higher emission scenario (SSP5-8.5), the areas with higher values of increase will expand both in the change in intensity and frequency of occurrence. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Climate change

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The Water-Energy Nexus of Urban Services in a Tourism City: The Case of Pattaya City

The Water-Energy Nexus of Urban Services in a Tourism City: ...

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2022 International Conference and Utility Exhibition on Energy, Environment and Climate Change, ICUE 2022

作者： Janchai, Surasak Phdungsilp, Aumnad Vorarat, Suparatchai Graduate Program in Engineering Management College of Innovative Technology and Engineering Dhurakij Pundit University Bangkok Thailand

ISBN: (纸本)9798350333268

Urban services, such as water and energy resources, are usually consumed more in a tourism city, than in other city types. The water-energy nexus also contributes to the CO2 emissions from urban areas. The purpose of this research is to investigate the link between water distribution systems, electricity consumption, and energy-related CO2 emissions from water networks in Pattaya city, Thailand. These networks operate under the Provincial Waterworks Authority (PWA). The water distribution system was modeled in EPANET software, to simulate and examine the water supply capacity in the service pipes, to ensure that it meets the requirement set by PWA. Data were collected from PWA, in terms of the pressure and flow rate of the water supply and the amount of electricity consumption. The current water distribution system consists of 18 junctions, a with flow rate of 1,000 m3/hour and pressure at 45 m. The electricity consumption is 720 kWh/day and energy-related CO2 emissions are 419.11 kgCO2eq/day. The water distribution system was modeled and analyzed to find the optimum flow rate and pressure for the least electricity consumption. The results show that the optimum solution is the flow rate of 1,500 m3/hour and a pressure at 50 m. Consequently, the electricity consumption is 300 kWh/day, while CO2 emissions are reduced to 174.63 kgCO2eq/day. The findings from this study would benefit the PWA by reducing the electricity consumption and CO2 emissions equivalent to 109 MWh/year and 63.73 tCO2eq, respectively. © 2022 IEEE.

关键词： Energy conservation

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