Research on the Quality Competence in Manufacturing Industry

Abstract In this article, we established the evaluation index system of manufacturing quality competence, implemented the comprehensive evaluation of quality competence by AHP (Analytic Hierarchy Process), empirically studied the evaluation objects including more than one thousand manufacturing enterprises, and validated the rationality of the evaluation index system and the evaluation method.


Introduction of the problem
The so-called quality competence is the ability that the organization acquires sustainable competitive predominance and realizes sustainable development in virtue of excellent quality, and it can be measured by the quality competence index.In this article, we established the evaluation index system of manufacturing quality competence, and evaluated and analyzed the quality competence of the evaluation objects including more than one thousand manufacturing enterprises.

Index system of quality competence
The index system of manufacturing quality competence can be divided into four layers including object layer, criterion layer, judgment layer and index layer.The object layer is the first class index, i.e. "the manufacturing quality competence index", the criterion layer is the second class index which includes two indexes such as "explicit competence" and "potential competence", and the judgment layer is the third class index which includes "practicality quality", "performance", "technical innovation", "human resource" and "quality management ability", and the index layer includes 11 indexes, and the concrete structure is seen in Table 1.

Evaluation analysis method of quality competence
The evaluation of quality competence belongs to the problem of multiple index comprehensive evaluation.The multiple index comprehensive evaluation methods usually include subjective weight average method, AHP, main components analysis method and factor analysis method.The evaluation of quality competence can be evaluated by above methods, and in this article, we adopt AHP to analyze and evaluate the quality competence.
(1) Establishing judgment matrix Judgment matrix is the core of AHP, and it is acquired by the comparison between two factors, and its factor ij a can be confirmed by Table 2.
The judgment matrix obtained by this way is A =  (2) Confirmation of weight There are many single ranking methods to confirm the weight W from the judgment matrix A, but the eigenvector method put forward by T. L. Saaty is the optimal method.The method first solves the character equation AW= max W, where, max is the maximum latent root of matrix A, W is the character vector corresponding to max .We can obtain the weight by the normalization to W. All works can be implemented by Matlab.
(3) Consistent test The consistent test is implemented through the computation of consistent index and test coefficients.

CI CR RI
Where, RI is the average consistent index which can be checked through Table 3.Generally, when CR<0.1, we can think the judgment matrix possesses satisfactory consistence, or else, we need readjust the judgment matrix.

Comprehensively evaluating the quality competence by AHP
According to AHP, we first establish judgment matrixes of various layers (Table 4-Table 11).To avoid the limitations such as individual ability level, we can use many methods which utilize collective wisdom such as experts grading method and Delphi method to compare and judge.To various indexes evaluating quality competence, we can compose the expert group including some experts in the domain of quality management, persons who engage relative works of quality management in enterprises, competitors in same industry and consumers to evaluate.
Next, compute the weights of various indexes in the index layer to the object layer by the weight coefficients obtained by the above method, and then rank the object layer.
Cumulate and multiply the weight coefficients of various layers, we can obtain the weights (seen in Table 12) of various indexes corresponding to the object layer.
So, we can get the score Z of the total object through the weight coefficients of above various indexes.x Where, x i is the actual observation value of corresponding i'th index in various samples, and to eliminate the influence induced by the differences among various quality index dimensions, we can first implement normalization processing to the sample observation data, and here, we think x i is normalized.
Finally, we translate Z i into percent, and so we can obtain the micro-quality competence index QI A1 , and rank original data by the size of QI A1 , which can be realized in the software of SPSS.

Conclusion
In this article, we established the index system of manufacturing quality competence, utilized AHP and factor analysis method to comprehensively evaluate the quality competences of more than one thousands manufacturing enterprises, and ranked these enterprises according to various layers and various classes based on the results of evaluation.Because of too much data, we didn't list the ranking result in the article.

Table 1 .
Index system of manufacturing quality competence

Table 2 .
Confirmation of various factors in judgment matrix

Table 12 .
Weighted coefficients of various indexes