| In recent years,China's contribution to the overall growth of the world economy is obvious to all.E-commerce is one of the main boosters,and its rapid development can bring more opportunities and changes to offline and online related industries.After the development of the first two decades of the 20 th century,the offline logistics industry has long become an indispensable part of the social economy,and the well-connected logistics network can deliver all kinds of goods to thousands of households.The more and more logistics companies have also led to increasing competition pressure in the logistics market,and companies must gain more market share by improving service or product quality.As a necessary transportation tool for any logistics enterprise,the logistics trolley is related to the efficiency of logistics operations to a certain extent.The design of logistics trolleys on the market is mostly controlled by the subjective feelings of designers.The similarities and differences in product upgrades make it difficult for customers to achieve their satisfaction.Nowadays,various online trading platforms have increased the volume of online transactions year by year,which has also led to the explosive growth of online reviews.With the improvement of text mining technology,more and more researchers have begun to explore its hidden value.Among them,the use of data to drive product quality optimization is the research direction of many works,but it is difficult to find research on the method of logistics trolley quality optimization.Therefore,the application of online reviews is not only of theoretical significance for the study of quality optimization methods of logistics trolleys,but also of practical significance in the face of today's developed logistics network system in my country.Based on this background and significance,this research uses online reviews mining,QFD,LDA and other theories and methods to study the quality optimization methods of logistics trolleys based on the related research results of the predecessors.Based on obtaining and preprocessing online reviews,build a house of quality that transforms customer needs and engineering characteristics,and ultimately provide references for designers to optimize the quality of logistics trolleys.The main research contents of this thesis are as follows:(1)Analyze and filter out useful online reviews.Based on obtaining online comments,the characteristics of useful online comments and the filtering method of useless online comments are analyzed.Only in this way can we provide data support for subsequent chapters and draw correct conclusions.(2)Use TF-IDF algorithm,k-means algorithm and statistical methods to determine customer needs and their weights.Use the TF-IDF algorithm to quantitatively analyze the online reviews after preprocessing,use the k-means algorithm to cluster online reviews of different expressions,and re-coordinate the TF-IDF algorithm to obtain specific customer needs,and finally obtain the weights corresponding to the customer needs.(3)Use the LDA model to determine the correlation between engineering characteristics and topics.On the basis of obtaining the engineering characteristics of the product,the preprocessed online comments are used to train the LDA model,and the distribution generated by the model is used to analyze the correlation between the engineering characteristics and the topic.(4)Use the LDA model to determine the incidence matrix of the house of quality.The results of the clustering algorithm will be combined with the trained LDA model,through the correlation between the engineering characteristics and the theme,to finally determine the relationship between customer needs and engineering characteristics,which is the association matrix of the House of Quality.(5)The quality optimization design of the logistics trolley.For the new product quality optimization method of this research,a new design idea for a certain brand of logistics trolley is proposed. |
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