| Ever since the Lean Production came up, it has gradually formed a comparatively perfect theory and technology system, and in many foreign companies especially in Toyota, Lean Production has produced many good results. Even though China had introduced Lean Production decades ago, the results are barely satisfactory. One of the most important reasons is that there is no complete evaluation system to guide the companies while they are introducing Lean Production.This thesis puts forward the activity coefficient system for Lean Production on the basis of previous studies. The higher the activity of a system, the easier to evolve and develop for the system.After reading many related literatures and discussing with experts on Lean Production, this thesis selects 5 factors as the key indicators of the Lean Production activity coefficient system, which includes staff activity, Enterprise Culture activity, logistics activity, production technology activity and environmental adaptability activity. Then we select 26 second class indicators to correspond with the 5 key indicators. This thesis firstly weighs the 26 second class indicators with Analytic Network Process, and in order to show the system in a more intuitive way, this thesis builds the Lean Production sand pile model for it. When it comes to the evaluation for the enterprise Lean Production activity, this thesis chooses three layer BP neural network model as the evaluation model. Firstly we train and examine the BP neural network with the survey data from enterprises, then we take Enterprise C as an example, evaluate the Lean Production activity of it with the well-trained BP neural network, and give some advices for the future Kaizen emphasizes of Enterprise C on the basis of the evaluation result. The last part of the thesis is a summary of the achievements and shortages of the research, and puts forward some points need to be paid more attention to in the future research. |
PDF Full Text Request