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  • 1
    Online Resource
    Online Resource
    Simulating a Semiconductor Packaging Facility: Sustainable Strategies and Short-time Evidences
    Elsevier BV ; 2017
    In:  Procedia Manufacturing Vol. 11 ( 2017), p. 787-795
    Details
    In: Procedia Manufacturing, Elsevier BV, Vol. 11 ( 2017), p. 787-795
    Type of Medium: Online Resource
    ISSN: 2351-9789
    URL: Article
    DOI: 10.1016/j.promfg.2017.07.180
    Language: English
    Publisher: Elsevier BV
    Publication Date: 2017
    detail.hit.zdb_id: 2840662-X
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  • 2
    Online Resource
    Online Resource
    Fuzzy approach for production planning by using a three-dimensional printing-based ubiquitous manufacturing system
    Cambridge University Press (CUP) ; 2019
    In:  Artificial Intelligence for Engineering Design, Analysis and Manufacturing Vol. 33, No. 4 ( 2019-11), p. 458-468
    Details
    In: Artificial Intelligence for Engineering Design, Analysis and Manufacturing, Cambridge University Press (CUP), Vol. 33, No. 4 ( 2019-11), p. 458-468
    Abstract: A ubiquitous manufacturing (UM) system is used in manufacturing for obtaining the Internet of things solutions and provides location-based manufacturing services. Human-induced uncertainty and early termination are two complications that hamper the effectiveness of an UM system based on three-dimensional (3D) printing. To resolve these complications, several solutions were considered in this study. First, fuzzy-valued parameters were defined to determine uncertainty. Subsequently, slack was derived to determine whether to restart an early terminated 3D printing process in the same 3D printing facility. Consequently, two optimization models – a fuzzy mixed-integer linear programming model and a fuzzy mixed-integer quadratic programming model – were developed in this study. Based on the two optimization models, a fuzzy 3D printing-based UM system that considers uncertainty and early termination was developed. The effectiveness of the proposed methodology was tested by conducting a regional experiment. The experimental results revealed that the proposed methodology could shorten the average cycle time by 9% and could enable 3D printing facilities to make real-time, online reprinting decisions.
    Type of Medium: Online Resource
    ISSN: 0890-0604 , 1469-1760
    URL: Article
    DOI: 10.1017/S0890060419000222
    Language: English
    Publisher: Cambridge University Press (CUP)
    Publication Date: 2019
    detail.hit.zdb_id: 2025375-8
    SSG: 9,11
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    Online Resource
  • 3
    Online Resource
    Online Resource
    A systematic approach to enhance the explainability of artificial intelligence in healthcare with application to diagnosis of diabetes
    Elsevier BV ; 2023
    In:  Healthcare Analytics Vol. 3 ( 2023-11), p. 100183-
    Details
    In: Healthcare Analytics, Elsevier BV, Vol. 3 ( 2023-11), p. 100183-
    Type of Medium: Online Resource
    ISSN: 2772-4425
    URL: Article
    DOI: 10.1016/j.health.2023.100183
    Language: English
    Publisher: Elsevier BV
    Publication Date: 2023
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  • 4
    Online Resource
    Online Resource
    A FAHP-FTOPSIS approach for bioprinter selection
    Springer Science and Business Media LLC ; 2020
    In:  Health and Technology Vol. 10, No. 6 ( 2020-11), p. 1455-1467
    Details
    In: Health and Technology, Springer Science and Business Media LLC, Vol. 10, No. 6 ( 2020-11), p. 1455-1467
    Type of Medium: Online Resource
    ISSN: 2190-7188 , 2190-7196
    URL: Article
    DOI: 10.1007/s12553-020-00469-8
    Language: English
    Publisher: Springer Science and Business Media LLC
    Publication Date: 2020
    detail.hit.zdb_id: 2581463-1
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  • 5
    Online Resource
    Online Resource
    Forecasting the unit cost of a DRAM product using a layered partial-consensus fuzzy collaborative forecasting approach
    Springer Science and Business Media LLC ; 2020
    In:  Complex & Intelligent Systems Vol. 6, No. 3 ( 2020-10), p. 479-492
    Details
    In: Complex & Intelligent Systems, Springer Science and Business Media LLC, Vol. 6, No. 3 ( 2020-10), p. 479-492
    Abstract: A layered partial-consensus fuzzy collaborative forecasting approach is proposed in this study to forecast the unit cost of a dynamic random access memory (DRAM) product. In the layered partial-consensus fuzzy collaborative forecasting approach, the partial-consensus fuzzy intersection (PCFI) operator is applied instead of the prevalent fuzzy intersection (FI) operator to aggregate the fuzzy forecasts by experts. In this way, some meaningful information, such as the suitable number of experts, can be obtained through observing changes in the PCFI result when the number of experts varies. After applying the layered partial-consensus fuzzy collaborative forecasting approach to a real case, the experimental results revealed that the layered partial-consensus fuzzy collaborative forecasting approach outperformed three existing methods. The most significant advantage was up to 13%.
    Type of Medium: Online Resource
    ISSN: 2199-4536 , 2198-6053
    URL: Article
    DOI: 10.1007/s40747-020-00146-3
    Language: English
    Publisher: Springer Science and Business Media LLC
    Publication Date: 2020
    detail.hit.zdb_id: 2834740-7
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  • 6
    Online Resource
    Online Resource
    Assessing cloud manufacturing applications using an optimally rectified FAHP approach
    Springer Science and Business Media LLC ; 2022
    In:  Complex & Intelligent Systems Vol. 8, No. 6 ( 2022-12), p. 5087-5099
    Details
    In: Complex & Intelligent Systems, Springer Science and Business Media LLC, Vol. 8, No. 6 ( 2022-12), p. 5087-5099
    Abstract: Cloud Manufacturing (CMfg) is a new manufacturing paradigm that promises to reduce costs, improve data analysis, increase efficiency and flexibility, and provide manufacturers with closer partnerships. However, most past CMfg research has focused on either the information technology infrastructure or the planning and scheduling of a hypothetical CMfg system. In addition, the cost effectiveness of a CMfg application has rarely been assessed. As a result, a manufacturer is not sure whether to adopt a CMfg application or not. To address this issue, an optimally rectified fuzzy analytical hierarchy process (OR-FAHP) approach is proposed in this study to assess a CMfg application. The OR-FAHP approach solves the inconsistency problem of the conventional FAHP method, a well-known technology assessment technique, to make the analysis results more trustable. The OR-FAHP approach has been applied to assess and compare 10 CMfg applications.
    Type of Medium: Online Resource
    ISSN: 2199-4536 , 2198-6053
    URL: Article
    DOI: 10.1007/s40747-022-00737-2
    Language: English
    Publisher: Springer Science and Business Media LLC
    Publication Date: 2022
    detail.hit.zdb_id: 2834740-7
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  • 7
    Online Resource
    Online Resource
    Constructing a Precise Fuzzy Feedforward Neural Network Using an Independent Fuzzification Approach
    MDPI AG ; 2021
    In:  Axioms Vol. 10, No. 4 ( 2021-10-28), p. 282-
    Details
    In: Axioms, MDPI AG, Vol. 10, No. 4 ( 2021-10-28), p. 282-
    Abstract: This study discusses how to fuzzify a feedforward neural network (FNN) to generate a fuzzy forecast that contains the actual value, while minimizing the average range of fuzzy forecasts. This topic has rarely been investigated in past studies, but is an essential step to constructing a precise fuzzy FNN (FFNN). Existing methods fuzzify all parameters at the same time, which re-sults in a nonlinear programming (NLP) problem that is not easy to solve. In contrast, in this study, the parameters of a FNN are fuzzified independently. In this way, the optimal values of fuzzy parameters can be derived theoretically. An illustrative example is used to illustrate the ap-plicability of the proposed methodology. According to the experimental results, fuzzifying the thresholds on hidden-layer nodes or the connection weights between input and hidden layers may not guarantee that all fuzzy forecasts contain the corresponding actual values. In contrast, fuzzi-fying the threshold on the output node and the connection weights between the hidden and out-put layers is more likely to achieve a 100% hit rate. The results lay a foundation for establishing a precise deep FFNN in the future.
    Type of Medium: Online Resource
    ISSN: 2075-1680
    URL: Article
    DOI: 10.3390/axioms10040282
    Language: English
    Publisher: MDPI AG
    Publication Date: 2021
    detail.hit.zdb_id: 2661511-3
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  • 8
    Online Resource
    Online Resource
    A Fuzzy Collaborative Approach for Evaluating the Suitability of a Smart Health Practice
    MDPI AG ; 2019
    In:  Mathematics Vol. 7, No. 12 ( 2019-12-03), p. 1180-
    Details
    In: Mathematics, MDPI AG, Vol. 7, No. 12 ( 2019-12-03), p. 1180-
    Abstract: A fuzzy collaborative approach is proposed in this study to assess the suitability of a smart health practice, which is a challenging task, as the participating decision makers may not reach a consensus. In the fuzzy collaborative approach, each decision maker first applies the alpha-cut operations method to derive the fuzzy weights of the criteria. Then, fuzzy intersection is applied to aggregate the fuzzy weights derived by all decision makers to measure the prior consensus among them. The fuzzy intersection results are then presented to the decision makers so that they can subjectively modify the pairwise comparison results to bring them closer to the fuzzy intersection results. Thereafter, the consensus among decision makers is again measured. The collaboration process will stop when no more modifications are made by any decision maker. Finally, the fuzzy weighted mean-centroid defuzzification method is applied to assess the suitability of a smart health practice. The fuzzy collaborative approach and some existing methods have been applied to assess the suitabilities of eleven smart health practices for a comparison. Among the compared practices, only the fuzzy collaborative approach could guarantee the existence of a full consensus among decision makers after the collaboration process, i.e., that the assessment results were acceptable to all decision makers.
    Type of Medium: Online Resource
    ISSN: 2227-7390
    URL: Article
    DOI: 10.3390/math7121180
    Language: English
    Publisher: MDPI AG
    Publication Date: 2019
    detail.hit.zdb_id: 2704244-3
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  • 9
    Online Resource
    Online Resource
    An Evolving Partial Consensus Fuzzy Collaborative Forecasting Approach
    MDPI AG ; 2020
    In:  Mathematics Vol. 8, No. 4 ( 2020-04-10), p. 554-
    Details
    In: Mathematics, MDPI AG, Vol. 8, No. 4 ( 2020-04-10), p. 554-
    Abstract: Current fuzzy collaborative forecasting methods have rarely considered how to determine the appropriate number of experts to optimize forecasting performance. Therefore, this study proposes an evolving partial-consensus fuzzy collaborative forecasting approach to address this issue. In the proposed approach, experts apply various fuzzy forecasting methods to forecast the same target, and the partial consensus fuzzy intersection operator, rather than the prevalent fuzzy intersection operator, is applied to aggregate the fuzzy forecasts by experts. Meaningful information can be determined by observing partial consensus fuzzy intersection changes as the number of experts varies, including the appropriate number of experts. We applied the evolving partial-consensus fuzzy collaborative forecasting approach to forecasting dynamic random access memory product yield with real data. The proposed approach forecasting performance surpassed current fuzzy collaborative forecasting that considered overall consensus, and it increased forecasting accuracy 13% in terms of mean absolute percentage error.
    Type of Medium: Online Resource
    ISSN: 2227-7390
    URL: Article
    DOI: 10.3390/math8040554
    Language: English
    Publisher: MDPI AG
    Publication Date: 2020
    detail.hit.zdb_id: 2704244-3
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  • 10
    Online Resource
    Online Resource
    Energy-Efficient Production Planning Using a Two-Stage Fuzzy Approach
    MDPI AG ; 2021
    In:  Mathematics Vol. 9, No. 10 ( 2021-05-13), p. 1101-
    Details
    In: Mathematics, MDPI AG, Vol. 9, No. 10 ( 2021-05-13), p. 1101-
    Abstract: Analyzing energy consumption is an important task for a factory. In order to accomplish this task, most studies fit the relationship between energy consumption and product design features, process characteristics, or equipment types. However, the energy-saving effects of product yield learning are rarely considered. To bridge this gap, this study proposes a two-stage fuzzy approach to estimate the energy savings brought about by yield improvement. In the two-stage fuzzy approach, a fuzzy polynomial programming approach is first utilized to fit the yield-learning process of a product. Then, the relationship between monthly electricity consumption and increase in yield was fit to estimate the energy savings brought about by the improvement in yield. The actual case of a dynamic random-access memory factory was used to illustrate the applicability of the two-stage fuzzy approach. According to the experiment results, product yield learning can greatly reduce electricity consumption.
    Type of Medium: Online Resource
    ISSN: 2227-7390
    URL: Article
    DOI: 10.3390/math9101101
    Language: English
    Publisher: MDPI AG
    Publication Date: 2021
    detail.hit.zdb_id: 2704244-3
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