Key indexes choosing approach of complex equipment’s development cost based on grey incidence cluster model

Abstract

Purpose – The purpose of this paper is to establish a combined model for selecting key indexes of complex equipment, and then improve the cost forecasting precision of the model. The problem how to choose the key elements of complex products has always been concerned on many fields, such as cost assessment, investment decision making, etc. Design/methodology/approach – Using Grey System Theory to establish a cost estimation model of complicated equipment is more reasonable under the few data and poor information. Therefore, this paper constructs cost index’s system of complex equipment, and then quantitative and qualitative analysis methods are utilized to calculate the grey entropy between the characteristic parameter and the behavior parameters. Further, establish the grey relational clustering matrix of the behavior sequences by using the grey relative incidence analysis. Finally, the authors select key indicators according to the grey degree. Findings – The experiment demonstrates that the cost key parameters of complex equipment can be successfully screened out by the proposed approach, and the cost estimation accuracy of complicated products is improved. Practical implications – The method proposed in this paper could be utilized to solve some practical problems, particularly the selection of cost critical parameters for complex products with few samples and poor information. Taking the cost key indexes of civil aircraft as an example, the results verified the validity of the GICM model. Originality/value – In this paper, the authors develop the method of GICM model. Taking the data of civil aircraft as an example, the authors screen the key indicators of complex products successfully, and improve the prediction accuracy of the GM (1, N) model by using the selected parameters, which provides a reference for some firms.

Application of grey clusters in the development of a Synthetic Model of the goals of Polish family enterprises' successors

“…Nowadays, grey theory has been widely used to solve many practical problems of science, technology, economy and social interactions (education, health care) (Liu et al, 2011(Liu et al, , 2013(Liu et al, , 2016bYang et al, 2019). Grey correlation analysis is an important part of the grey system and constitutes the basis for grey modelling (Xie et al, 2016). However, the publications on grey system theory application to solving problems of family enterprises are still limited (Mierzwiak and Więcek-Janka, 2015;Więcek-Janka et al, 2016a, b, 2019.…”

“…Thus, the complex system of successors' goals, referred to as the Synthetic Model of successors' goals, was simplified and proposed herein. The task to filter representative factors from the factors clustered is realized based on computation, referring for example to factors in relation to the selected system characteristics (Xie et al, 2016) or based on the analysis of literature (Więcek-Janka et al, 2016a). In this paper, it is first proposed to refer to the review of literature, which facilitates the reference of the studied system to the higher supersystem and its properties, and then apply the computations based on the data related to the analysed example.…”

Prediction of Vegetable Supply in Henan Province Based on PSO-GM (1, N) Model

“…For expression (13), the method determined in 2.3.2 is used for processing, and the results are shown in Table 3. Because ε 4 (4.93%) is the minimum value of ε i (i � 2, 3, .…”

Identifying key industry factors of remanufacturing industry using grey incidence analysis

“…Compared with other systems analysis methods like regression analysis, variance analysis and principal component analysis, the major advantages of this method are as follow: it can generate satisfactory results using a relatively small amount of data or with great variability in indices, which make it best suited for small samples and uncertain systems (Rajesh and Ravi, 2015; Liu et al , 2012), and it does not require a large amount of statistical data as well as all certain probability distribution in the data. So this method has been successfully applied to areas of industry, agriculture, economics, computer, social affairs and architecture (Xie et al , 2016; Wang et al , 2016; Goyal and Grover, 2012; Tan, 2014; Cui et al , 2009; Guo and Zhang, 2015; Zhu et al , 2016; Karimi and Forrest, 2014).…”