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An improved skip-lot sampling scheme with resampling mechanism using an advanced capability index

International Journal of Production Research 2025年第1期63卷 104-118页

作者： Wang, Zih-Huei Wu, Chien-Wei Li, Pei-Yi Department of Industrial Engineering and Systems Management Feng Chia University Taichung Taiwan Department of Industrial Engineering and Engineering Management National Tsing Hua University Hsinchu Taiwan

In today’s competitive market, product quality holds significant importance for consumers, motivating companies to prioritise high-quality product development and enhance their competitiveness. Acceptance sampling plans have proven to be indispensable tools in quality control practices, enabling producers and consumers to protect their interests by establishing evaluation rules for product batches. As defective rates decrease in modern manufacturing, skip-lot sampling plans (SkSP) have emerged as a suitable way for lots exhibiting stable and excellent product quality. Additionally, repetitive group sampling plan (RGSP) offers a cost-effective way to maintain desired protection for both parties, especially in costly or destructive inspection scenarios. Therefore, this study integrates the benefits of process capability indices, SkSP, and RGSP to develop a new variables SkSP with RGSP as its reference plan based on an advanced capability index Cpmk (called Cpmk-based SkSP-RGSP). The proposed plan achieves comparable discriminatory power to traditional sampling plans while significantly reducing the required sample size. Detailed tables of plan parameters are given to facilitate effective implementation for practitioners. © 2024 Informa UK Limited, trading as Taylor & Francis Group.

关键词： Quality assurance

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Developing variables two-plan sampling scheme with consideration of process loss for lot sentencing

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Quality engineering 2025年第2期37卷 273-291页

作者： Darmawan, Armin Wu, Chien-Wei Wang, Zih-Huei Chiang, Ping-Jung Department of Industrial Engineering and Engineering Management National Tsing Hua University Hsinchu Taiwan Department of Industrial Engineering Hasanuddin University Makassar Indonesia Department of Industrial Engineering and Systems Management Feng Chia University Taichung Taiwan

This paper considers a well-known two-plan sampling system, Tightened-Normal-Tightened (TNT) sampling scheme, which includes two single sampling plans (SSPs) with regulations for transitioning between tightened and normal inspections. Tightened inspection is conducted when there is a noticeable decline in quality, and normal inspection is employed when the quality is satisfactory. Most acceptance sampling plans evaluate product quality in terms of process yield, which does not differentiate between products that fall within specification limits. To address this issue, a new performance measure called the process loss index Le was developed, which accounts for the quality loss function. This index is determined by dividing the "expected quadratic loss" by the "square of half the specification width." Using this index, two primary types of variables TNT sampling scheme were constructed and evaluated in this study. Their efficacy and features were investigated, discussed, and compared. The findings reveal that the TNT sampling strategy delivers the required quality assurance with a reduced sample size compared to the conventional SSP. © 2024 Taylor & Francis Group, LLC.

关键词： Inspection

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Browsing History Data Analysis Based on a Modified Latent LSTM Allocation Model Considering Browsing Time and its Application to a Fresh Flower EC Site

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Journal of Japan Industrial management Association 2024年第3期75卷 89-101页

作者： Zhang, Zhiying Yang, Tianxiang Goto, Masayuki Department of Industrial and Management Systems Engineering School of Creative Science and Engineering Waseda University Japan Department of Industrial and Systems Engineering Faculty of Science and Technology Keio University Japan

In recent years, it has become possible to accumulate a large amount of browsing history data from users on websites and it is desirable to make use of such data for marketing purposes. In particular, customer browsing history collected on EC sites is an important resource for analyzing purchasing behavior because it shows the differences in user preferences and their motivations behind purchasing products. In a previous study, the Latent LSTM Allocation model was proposed for grouping customers’ browsing history data. This is a model that combines the Long Short-Term Memory and the Latent Dirichlet Allocation models, but it does not consider the relationship between browsing behavior and purchase made. In addition, a customer’s browsing time on each page is not taken into consideration, and a page is treated the same regardless of whether a user has spent a long time carefully browsing it, or if they have quickly moved on to the next page. In this study, a new analysis model is proposed that can analyze a user’s willingness to purchase each product based on their relationship between their user’s browsing behavior data including their browsing time and the purchasing behavior, based on the understanding that their browsing time for each page is also an important factor in the customer’s browsing behavior. Specifically, the present paper proposes a new modified Latent LSTM Allocation model that is able to consider not only the information related to a user’s browsing and purchasing behaviors but also the time intervals for their browsing behaviors on individual pages on the target EC site. The proposed model enables to the extraction of groups based on purchasing tendencies considering users’ browsing times for each page. Finally, the proposed model is applied to a case study for an EC site that handles fresh flower products. The obtained findings are then analyzed by applying the proposed model to actual usage history data on the flesh flower EC site. © 2024 Japan

关键词： Sales

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The Interplay of Incentives, Electricity Price, and Demand on Transport Decarbonization: The Case of Electric Vehicles in the U.S.

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IEEE engineering management Review 2024年第2期52卷 38-54页

作者： Wang, Tianye Deason, Jonathan Shittu, Ekundayo The George Washington University Department of Engineering Management and Systems Engineering WashingtonDC20052 United States

While extant research explores the impact of electric vehicle (EV) incentives on EV market shares, less is known about how such policies and other socioeconomic factors interact that ultimately affect the goal of transportation emission reductions. The study summarized herein employed a sample of 510 state-year CO_2 emissions datasets in the transportation sector spanning a decade (2010-2019) in a multiple linear regression model. Going beyond earlier studies, we find that, while a higher number of EV incentives would significantly contribute to transportation emission reductions, this effect could be dampened by population growth. In addition, we find that, while higher electricity prices may weaken the effectiveness of EV incentives, a high count of EV incentives is more effective in reducing CO_2 emissions than a low count of EV incentives when the electricity price is low. This finding implies that having multiple EV incentives can be effective in reducing transportation carbon emissions even in the face of rising prices of electricity. The study also examines the effectiveness of promoting the density of charging stations and alternative fuel incentives in advancing carbon emission reductions. © 1973-2011 IEEE.

关键词： Climate change

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Assessing high-quality process performance using the quality-yield index: An innovative methodology

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Quality and Reliability engineering International 2024年第6期40卷 3407-3421页

作者： Wu, Chien-Wei Darmawan, Armin Wang, Zih-Huei Lin, Meng-Tzu Department of Industrial Engineering and Engineering Management National Tsing Hua University Hsinchu Taiwan Department of Industrial Engineering Hasanuddin University Makassar Indonesia Department of Industrial Engineering and Systems Management Feng Chia University Taichung Taiwan

Manufacturers must meet high-quality standards and exceed customer expectations to stay competitive due to significant technological advancements in recent decades. While implementing the yield measure is useful for achieving process performance by focusing on products that fall within specified limits, it does not accommodate specific customer requirements, particularly when a product's quality characteristic deviates from target value. To address this need, the quality-yield index (Q-yield) has been proposed, which combines the process-yield index and loss-based capability index, providing a more advanced performance measure. However, the Q-yield index's confidence interval is challenging to derive due to the complicated sampling distribution involved. Several existing methods have attempted to construct an approximate confidence interval but none have performed well. Therefore, this article proposes an innovative approach, called the generalized confidence intervals (GCIs), that utilizes the idea of generalized pivotal quantities to establish the confidence interval for the Q-yield index. The proposed approach is evaluated through simulations and compared to existing methods. The results reveal that the proposed approach provides the most accurate results for constructing the lower confidence bound of the Q-yield index. This approach is recommended to evaluate process performance using the Q-yield index for high-quality customer requirements. © 2024 John Wiley & Sons Ltd.

关键词： Sales

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A Survey on Recent Advances and Challenges in Reinforcement Learning Methods for Task-oriented Dialogue Policy Learning

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Machine Intelligence Research 2023年第3期20卷 318-334页

作者： Wai-Chung Kwan Hong-Ru Wang Hui-Min Wang Kam-Fai Wong The Systems Engineering and Engineering Management Department The Chinese University of Hong KongHong Kong 999077China

Dialogue policy learning(DPL)is a key component in a task-oriented dialogue(TOD)*** goal is to decide the next action of the dialogue system,given the dialogue state at each turn based on a learned dialogue *** learning(RL)is widely used to optimize this dialogue *** the learning process,the user is regarded as the environment and the system as the *** this paper,we present an overview of the recent advances and challenges in dialogue policy from the perspective of *** specifically,we identify the problems and summarize corresponding solutions for RL-based dialogue policy *** addition,we provide a comprehensive survey of applying RL to DPL by categorizing recent methods into five basic elements in *** believe this survey can shed light on future research in DPL.

关键词： Dialogue policy learning(DPL) task-oriented dialogue system(TOD) reinforcement learning(RL) dialogue system Markov decision process

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Supply Chain Optimization Considering Fluctuations in Price Sensitive Demand

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Journal of Japan Industrial management Association 2023年第4 E期73卷 251-259页

作者： Dei, Masato Sato, Tetsuya Shiina, Takayuki Department of Industrial and Management Systems Engineering Waseda University Japan

In modern global supply chain system strategies, the importance of risk management to prevent disruption thereto is increasing. One efficient approach for overcoming this problem is a collaboration between manufacturers and retailers. This study extends a deterministic supply chain model based on the joint economic lot-sizing problem (JELP) to a stochastic programming model, which considers the uncertainty of price sensitive demand. A comparison of the results from numerical experiments based on individual and cooperative models suggests that a manufacturer-retailer collaboration could be beneficial in increasing the overall profit of the entire supply chain system. For instance, total profits were increased by 0.11-12.92% under joint optimization in the range of parameters used in this paper and the growth ratio was considerably higher for the cases in which the demand was more price sensitive. However, the above collaboration can decrease the retailer’s profits. For this reason, this study proposes and formulates a collaborative model by adding profit constraints to the above model. As a result, the diminution of the retailer’s profits is decreased to 0.0020-0.0164%, that is, the proposed model is able to maximize the total profit by minimizing the reduction of the profits for both the manufacturer and the retailer as much as possible. © 2023 Japan Industrial management Association. All rights reserved.

关键词： Supply chain management

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A quantitative assessment of policy-driven impacts on circular economy of electric vehicle batteries in the United States

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Environment systems and Decisions 2025年第1期45卷 1-21页

作者： Ren, Guannan Eveleigh, Timothy Department of Engineering Management and Systems Engineering The George Washington University Washington DC United States

Electric vehicle battery recycling has emerged as a critical process in transitioning to sustainable transportation. As the demand for electric vehicles continues to rise, so does the need to address the end-of-life management of their batteries. Current battery recycling rates need to be increased to meet the growing demands for raw materials. This work incorporates system dynamics to model crucial factors, such as regulatory frameworks, economic incentives, and technological processes that influence the cost-effectiveness and efficiency of battery recycling systems. A composite model that integrates stock-and-flow structures with delays to capture the interconnectedness of variables such as battery production rates, demand and price fluctuations, recycling infrastructure capacity, and the effectiveness of recycling processes is developed to study the overall supply chain efficiency. By simulating scenarios like stricter regulations on battery disposal, incentives for recycling, or investments in research and development for battery designs and advanced recycling technologies, the aggregate model offers policymakers, industry stakeholders, and researchers insights into the effects of policies or process updates on electric vehicle battery recycling rates. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024.

关键词： Circular economy Closed-loop supply chain Electric vehicle Policy Recycling Sustainability

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Very Short-Term Probabilistic Prediction Method for Wind Speed Based on ALASSO-Nonlinear Quantile Regression and Integrated Criterion

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CSEE Journal of Power and Energy systems 2023年第6期9卷 2121-2129页

作者： Yan Zhou Yonghui Sun Sen Wang Linquan Bai Dongchen Hou Rabea Jamil Mahfoud Peng Wang the College of Energy and Electrical Engineering Hohai UniversityNanjing 210098China Department of Systems Engineering and Engineering Management the University of North CarolinaCharlotte NC 28223USA

To enhance the performance of the prediction intervals (PIs), a novel very short-term probabilistic prediction method for wind speed via nonlinear quantile regression (NQR) based on adaptive least absolute shrinkage and selection operator (ALASSO) and integrated criterion (IC) is proposed. The ALASSO method is studied for shrinkage of output weights and selection of variables. Furthermore, for the better performance of PIs, composite weighted linear programming (CWLP) is proposed to modify the conventional linear programming cost function of quantile regression (QR), by combining it with Bayesian information criterion (BIC) as an IC to optimize the coefficients of PIs. Then, the multiple fold cross model (MFCM) is utilized to improve the PIs performance. Multistep probabilistic prediction of 15-minute wind speed is performed based on the real wind farm data from the northeast of China. The effectiveness of the proposed approach is validated through the performances' comparisons with conventional methods.

关键词： Composite weighted linear programming least absolute shrinkage and selection operator integrated criterion wind speed

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Design and construction of a quick-switching sampling system with a third-generation capability index

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Communications in Statistics - Theory and Methods 2023年第11期52卷 3633-3651页

作者： Wang, Zih-Huei Wu, Chien-Wei Jhu, Jhen-Jia Department of Industrial Engineering and Systems Management Feng Chia University Taichung Taiwan Department of Industrial Engineering and Engineering Management National Tsing Hua University Hsinchu Taiwan

Acceptance sampling, the most widely used technique in practice, provides rules for making decisions on product acceptance with specified quality standards. A quick-switching sampling (QSS) system, which involves a Normal sampling plan and a Tightened sampling plan with switching rules between them, has recently been discussed. This paper proposes a variables QSS system with parameters (Formula presented.) based on a third-generation capability index, which takes process yield and quality loss into consideration. A nonlinear optimization model is formulated to determine the designed plan parameters by minimizing average sample number and subject to the quality and risk levels specified by both the producer and the consumer. The comparison study between the designed sampling system and conventional sampling plan is also conducted in terms of common metrics including operating characteristic curve, average sample number, and average run length. Finally, a practical example is presented along with a step-by-step description of the procedure. © 2021 Taylor & Francis Group, LLC.

关键词： Nonlinear programming

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