| dc.description.abstract | The global market structure has been dominated by consumers. Therefore, the manufacturing industry is currently facing the shortened product life cycle and the decline in profits. In order to enhance competitiveness, it is necessary to continue to improve operations. In order to gain more market share, this brand owner believes that as long as the delivery cycle is shortened, it should have the opportunity to win more customers in some markets. The factory′s mission is to do its best.
The brand customer voice is the most important part of each electronic factorty. However, due to the large number of departments within the company, they often cannot quickly integrate opinions and unify the direction. Therefore, after considering many documents, it is likely that multi criteria decision making may be a direction that can be considered. The decision making model that has been developed since the 1980s has been proven to be quite practical. The analytic hierarchy analysis process is relatively easy to understand, and there are already a large number of examples, and the Lean Six Standard Deviation is the same familiar strategy for the manufacturing industry, because the lean production and the six standard deviations have been implemented in the manufacturing industry for a long time, most of which Problems can be solved as a result. This study will explore how to use the lean six sigma and theory of constraints to design an improvement plan and use the criteria decision to choose so as to avoid too many opinions within the company affecting the decision.
In this study, we first set up the improvement goals of the delivery cycle according to the requirements of our customers, and use the DMAIC approach to design a variety of solutions. Then we use the analytic hierarchy process. Quality, cost, delivery these three elements are inputted into the first level, then departmental experts brainstormed several elements which are are inputted into the the second layer. The related personnel make questionnaires and use matrix analysis to make decisions. Finally, the effectiveness of the actual import is reviewed, and related data and problems are sorted out, finally, we have summary. | en_US |