Usage of the Analytic Hierarchy Process for Production Optimization

Дубровін, В. І.; Mironova, N. A.

doi:10.1109/tcset.2006.4404638

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) Making Services Tangible and Visible Via Visualizations1

Overview and Model1

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“…The AHP enables groups of people to interact and focus on a certain problem, modify their judgments and, as a result, combine group judgments in accordance with the main criteria [23]. Applying the AHP to weight CRs in a QFD matrix provides a rational framework for structuring a decision problem.…”

Section: ) Making Services Tangible and Visible Via Visualizationsmentioning

confidence: 99%

Service Design for Developing Multimodal Human-Computer Interaction for Smart Tvs

Wang¹,

Huang²

2015

ijacsa

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Section: ) Making Services Tangible and Visible Via Visualizationsmentioning

confidence: 99%

Service Design for Developing Multimodal Human-Computer Interaction for Smart Tvs

Wang¹,

Huang²

2015

ijacsa

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“…While the method of contrast assignment will make it clear for customers to tell the difference, however, the absolute satisfaction level is not obtained. Consequently, we make a compromise between the two methods, that is, to obtain a comparative accurate result [8] shown as Eq. 3, in which we could make use of the difference from pairwise comparison to revise the absolute satisfaction.…”

Section: Overview and Modelmentioning

confidence: 99%

A Quantization Method for Customers' Fuzzy Demand in BOM Product Matching

Sun

Chen

et al. 2013

AMR

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In BOM product matching, there will be several product solutions based on the matching mechanism owing to the fuzziness and diversity of the customers needs. To select the optimal BOM through the matching process, a quantization method, which evaluates the product solutions according to customers intuitive estimate, is proposed. Customers needs are consisted by many parameters, and each parameter has several values. First, initialize the satisfaction level of every parameter value in the requirements through customers intuitive assessment. Second, as to a parameter, get the difference of satisfaction level of each parameter value by pairwise comparison. Third, revise the satisfaction level by the difference got by the second step. Other parameters are processed by the same method. Then, the satisfaction level of product BOM is calculated by the weighted average of the satisfaction levels of its constituent parameters. In this way, the BOM that best meets the customers requirements can be found out. The feasibility of the method is finally verified through an empirical study. This method can also be used in some other situations that contain fuzzy concept quantization.

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Usage of the Analytic Hierarchy Process for Production Optimization

Cited by 2 publications

References 0 publications

Service Design for Developing Multimodal Human-Computer Interaction for Smart Tvs

Service Design for Developing Multimodal Human-Computer Interaction for Smart Tvs

A Quantization Method for Customers' Fuzzy Demand in BOM Product Matching

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