The Experts below are selected from a list of 15354 Experts worldwide ranked by ideXlab platform
Zheng Xiao - One of the best experts on this subject based on the ideXlab platform.
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Customer Requirement information mapping method for product module configuration
2016 IEEE Advanced Information Management Communicates Electronic and Automation Control Conference (IMCEC), 2016Co-Authors: Zheng Xiao, Xinggang Wang, Buyun Sheng, Miao Zhimin, Shu YaoAbstract:Always, Customer Requirement information is foundation for product configuration in an enterprise, which is also the ultimate goal of mass customization. A research on Customer Requirement information mapping method for product module configuration possesses theoretical and practical significance. In this article, mathematical models of both Customer Requirement information and product family module are constructed. Based on this, a mapping method from Customer Requirement information to product family module is introduced. The method can quantitatively match Customer Requirement information with product family module, which will simplify mapping processes and avoid mapping error.
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A New Classification Analysis of Customer Requirement Information Based on Quantitative Standardization for Product Configuration
Mathematical Problems in Engineering, 2016Co-Authors: Zheng Xiao, Zude Zhou, Buyun ShengAbstract:Traditional methods used for the classification of Customer Requirement information are typically based on specific indicators, hierarchical structures, and data formats and involve a qualitative analysis in terms of stationary patterns. Because these methods neither consider the scalability of classification results nor do they regard subsequent application to product configuration, their classification becomes an isolated operation. However, the transformation of Customer Requirement information into quantifiable values would lead to a dynamic classification according to specific conditions and would enable an association with product configuration in an enterprise. This paper introduces a classification analysis based on quantitative standardization, which focuses on (i) expressing Customer Requirement information mathematically and (ii) classifying Customer Requirement information for product configuration purposes. Our classification analysis treated Customer Requirement information as follows: first, it was transformed into standardized values using mathematics, subsequent to which it was classified through calculating the dissimilarity with general Customer Requirement information related to the product family. Finally, a case study was used to demonstrate and validate the feasibility and effectiveness of the classification analysis.
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an analytical approach to Customer Requirement information processing
Enterprise Information Systems, 2013Co-Authors: Zude Zhou, Zheng Xiao, Quan LiuAbstract:‘Customer Requirements’ CRs management is a key component of Customer relationship management CRM. By processing Customer-focused information, CRs management plays an important role in enterprise systems ESs. Although two main CRs analysis methods, quality function deployment QFD and Kano model, have been applied to many fields by many enterprises in the past several decades, the limitations such as complex processes and operations make them unsuitable for online businesses among small-and medium-sized enterprises SMEs. Currently, most SMEs do not have the resources to implement QFD or Kano model. In this article, we propose a method named Customer Requirement information CRI, which provides a simpler and easier way for SMEs to run CRs analysis. The proposed method analyses CRs from the perspective of information and applies mathematical methods to the analysis process. A detailed description of CRI's acquisition, classification and processing is provided.
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a method for determining Customer Requirement weights based on tfmf and tlr
Enterprise Information Systems, 2013Co-Authors: Ting Shu, Quan Liu, Zude Zhou, Zheng XiaoAbstract:‘Customer Requirements’ CRs management plays an important role in enterprise systems ESs by processing Customer-focused information. Quality function deployment QFD is one of the main CRs analysis methods. Because CR weights are crucial for the input of QFD, we developed a method for determining CR weights based on trapezoidal fuzzy membership function TFMF and 2-tuple linguistic representation TLR. To improve the accuracy of CR weights, we propose to apply TFMF to describe CR weights so that they can be appropriately represented. Because the fuzzy logic is not capable of aggregating information without loss, TLR model is adopted as well. We first describe the basic concepts of TFMF and TLR and then introduce an approach to compute CR weights. Finally, an example is provided to explain and verify the proposed method.
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acquisition and analysis for Customer Requirement information
Advanced Materials Research, 2010Co-Authors: Zheng Xiao, Quan LiuAbstract:This paper summarized the popular methods for acquiring Customer Requirement (CR) information, where the internet-based method is especially efficient when an enterprise's web possesses the function of real-time communication, guiding investigation and online experience. However, current classification and analysis of CR mainly depends on a subjective judgment, awareness and assessment of the enterprise's staff, which exists with human errors. From the point of view of CR information, the authors classified it into certain information and uncertain information; there are two types of uncertain information----the random and the fuzzy. Based on this classification, CR information can be analyzed by means of probability theory and fuzzy logic. Therefore, the enterprise will acquire CR information more effectively and analyze it more accurately.
Quan Liu - One of the best experts on this subject based on the ideXlab platform.
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a method for determining Customer Requirement weights based on tfmf and tlr
Enterprise Information Systems, 2013Co-Authors: Ting Shu, Quan Liu, Zude Zhou, Zheng XiaoAbstract:‘Customer Requirements’ CRs management plays an important role in enterprise systems ESs by processing Customer-focused information. Quality function deployment QFD is one of the main CRs analysis methods. Because CR weights are crucial for the input of QFD, we developed a method for determining CR weights based on trapezoidal fuzzy membership function TFMF and 2-tuple linguistic representation TLR. To improve the accuracy of CR weights, we propose to apply TFMF to describe CR weights so that they can be appropriately represented. Because the fuzzy logic is not capable of aggregating information without loss, TLR model is adopted as well. We first describe the basic concepts of TFMF and TLR and then introduce an approach to compute CR weights. Finally, an example is provided to explain and verify the proposed method.
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an analytical approach to Customer Requirement information processing
Enterprise Information Systems, 2013Co-Authors: Zude Zhou, Zheng Xiao, Quan LiuAbstract:‘Customer Requirements’ CRs management is a key component of Customer relationship management CRM. By processing Customer-focused information, CRs management plays an important role in enterprise systems ESs. Although two main CRs analysis methods, quality function deployment QFD and Kano model, have been applied to many fields by many enterprises in the past several decades, the limitations such as complex processes and operations make them unsuitable for online businesses among small-and medium-sized enterprises SMEs. Currently, most SMEs do not have the resources to implement QFD or Kano model. In this article, we propose a method named Customer Requirement information CRI, which provides a simpler and easier way for SMEs to run CRs analysis. The proposed method analyses CRs from the perspective of information and applies mathematical methods to the analysis process. A detailed description of CRI's acquisition, classification and processing is provided.
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acquisition and analysis for Customer Requirement information
Advanced Materials Research, 2010Co-Authors: Zheng Xiao, Quan LiuAbstract:This paper summarized the popular methods for acquiring Customer Requirement (CR) information, where the internet-based method is especially efficient when an enterprise's web possesses the function of real-time communication, guiding investigation and online experience. However, current classification and analysis of CR mainly depends on a subjective judgment, awareness and assessment of the enterprise's staff, which exists with human errors. From the point of view of CR information, the authors classified it into certain information and uncertain information; there are two types of uncertain information----the random and the fuzzy. Based on this classification, CR information can be analyzed by means of probability theory and fuzzy logic. Therefore, the enterprise will acquire CR information more effectively and analyze it more accurately.
Zude Zhou - One of the best experts on this subject based on the ideXlab platform.
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A New Classification Analysis of Customer Requirement Information Based on Quantitative Standardization for Product Configuration
Mathematical Problems in Engineering, 2016Co-Authors: Zheng Xiao, Zude Zhou, Buyun ShengAbstract:Traditional methods used for the classification of Customer Requirement information are typically based on specific indicators, hierarchical structures, and data formats and involve a qualitative analysis in terms of stationary patterns. Because these methods neither consider the scalability of classification results nor do they regard subsequent application to product configuration, their classification becomes an isolated operation. However, the transformation of Customer Requirement information into quantifiable values would lead to a dynamic classification according to specific conditions and would enable an association with product configuration in an enterprise. This paper introduces a classification analysis based on quantitative standardization, which focuses on (i) expressing Customer Requirement information mathematically and (ii) classifying Customer Requirement information for product configuration purposes. Our classification analysis treated Customer Requirement information as follows: first, it was transformed into standardized values using mathematics, subsequent to which it was classified through calculating the dissimilarity with general Customer Requirement information related to the product family. Finally, a case study was used to demonstrate and validate the feasibility and effectiveness of the classification analysis.
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an analytical approach to Customer Requirement information processing
Enterprise Information Systems, 2013Co-Authors: Zude Zhou, Zheng Xiao, Quan LiuAbstract:‘Customer Requirements’ CRs management is a key component of Customer relationship management CRM. By processing Customer-focused information, CRs management plays an important role in enterprise systems ESs. Although two main CRs analysis methods, quality function deployment QFD and Kano model, have been applied to many fields by many enterprises in the past several decades, the limitations such as complex processes and operations make them unsuitable for online businesses among small-and medium-sized enterprises SMEs. Currently, most SMEs do not have the resources to implement QFD or Kano model. In this article, we propose a method named Customer Requirement information CRI, which provides a simpler and easier way for SMEs to run CRs analysis. The proposed method analyses CRs from the perspective of information and applies mathematical methods to the analysis process. A detailed description of CRI's acquisition, classification and processing is provided.
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a method for determining Customer Requirement weights based on tfmf and tlr
Enterprise Information Systems, 2013Co-Authors: Ting Shu, Quan Liu, Zude Zhou, Zheng XiaoAbstract:‘Customer Requirements’ CRs management plays an important role in enterprise systems ESs by processing Customer-focused information. Quality function deployment QFD is one of the main CRs analysis methods. Because CR weights are crucial for the input of QFD, we developed a method for determining CR weights based on trapezoidal fuzzy membership function TFMF and 2-tuple linguistic representation TLR. To improve the accuracy of CR weights, we propose to apply TFMF to describe CR weights so that they can be appropriately represented. Because the fuzzy logic is not capable of aggregating information without loss, TLR model is adopted as well. We first describe the basic concepts of TFMF and TLR and then introduce an approach to compute CR weights. Finally, an example is provided to explain and verify the proposed method.
Richard Y K Fung - One of the best experts on this subject based on the ideXlab platform.
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an intelligent hybrid system for Customer Requirements analysis and product attribute targets determination
International Journal of Production Research, 1998Co-Authors: Richard Y K Fung, Keith PopplewellAbstract:Aligning its quality initiatives in synchronization with the Customer's perception of values is one of the key management strategies for improving the competitive edge of an organization. Therefore, it will be a distinct advantage if one can succeed in effectively capturing the genuine and major Customer attributes (Requirements), systematically analysing and duly transforming them into the appropriate product attributes (features). This paper puts forward a novel approach for analysing Customer attributes and projecting them into the relevant design, engineering and product attributes in order to facilitate decision-making and to guide downstream manufacturing planning and control activities. The proposed hybrid system incorporates the principles of quality function deployment, analytic hierarchy process and fuzzy set theory to tackle the complex and often imprecise problem domain encountered in Customer Requirement management. It offers an analytical and intelligent tool for decoding, prioritizing and i...
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the prioritisation of attributes in Customer Requirement management
Systems Man and Cybernetics, 1996Co-Authors: Richard Y K Fung, Shouju Ren, Jinxing XieAbstract:This paper expounds on a hybrid approach for capturing the Customer Requirements, translating them into design and product features, and finally prioritising them through quantitative analyses. The Customer's voice is often ambiguous and nontechnical. Many enterprises have attempted to convert Requirements into product specifications by the technique of quality function deployment (QFD) which could be described graphically using a house of quality (HoQ). With this approach, Customer Requirements are transformed into product attributes, and subsequently into engineering characteristics for appropriate actions. Hence, the resulting product would be more readily accepted by Customers as they could see how the product features are related to their needs. Although the conventional HoQ could map the Customers' wants and needs against the relevant product attributes, the relationships among the various entries are normally represented qualitatively. The modified approach described in this paper employed the principles of analytic hierarchy process (AHP) which could help transform the relationships into quantitative terms as well as identify the priority of each attribute to facilitate decision-making in resource allocation. A case study on a Hi-Fi equipment series is given.
M Mahdavi - One of the best experts on this subject based on the ideXlab platform.
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a sustainable reverse supply chain for Customer Requirement fulfillment
Uncertain Supply Chain Management, 2013Co-Authors: R Khoshnoodi, Hamed Fazlollahtabar, M MahdaviAbstract:In this paper, we study a reverse supply chain consists of three layers of the supply chain including suppliers, producers and Customers by considering Customers’ Requirements. In the Customer layer, we analyze the Customer’s data to identify and fulfill their needs by collecting a list of Customers’ views into consideration. In this case, the proposed model analyzes the Customers view in the three areas of transport, production and quality and it uses the coding system for getting Customers’ opinions. Then, by using the K-means algorithm, which is one of the data analyzing algorithms, the proposed model clusters the data so that similar data enter to the same cluster. The mathematical model is developed for each of the categories and Lingo software package is employed to solve the resulted problem in each category.
