Fractal thought-based learning curve product unit cost evaluation method

Abstract

The invention relates to a fractal thought-based learning curve product unit cost evaluation method. The method comprises the following steps that: a product structure isdivided into a plurality of levels from bottom to top, wherein the bottommost level comprises parts for forming an assembly component in the previous level, and the middle level comprises parts and assembly components for formingan assembly component in the previous level, the topmost layer is a product; learning curve models of all parts are established; a learning curve model of the assembly component of the middle layer ofthe product structure is constructed from the bottommost layer in a bottom-up iterative mode according to the learning curve models of the parts, and the learning curve model of the product is obtained; and the unit cost of the product is obtained according to the learning curve model of the product. Compared with the prior art, the method is constructed in a bottom-up iteration mode, overcomes the defects of difficult historical data collection and a statistical mode of the historical data, supports analysis of top-down learning behaviors and learning effects of the learning behaviors and effectively evaluates and analyses the unit cost of the product.

Description

technical field [0001] The invention relates to a product cost evaluation method, in particular to a learning curve product unit cost evaluation method based on fractal thinking. Background technique [0002] The learning curve, also known as the experience curve, originated from the monitoring and analysis results of the production data of the aircraft industry during the "World War II" period. It shows that products in many industries have a certain learning effect in their life cycle, that is, through the use of products, valuable experience can be accumulated continuously, and then the efficiency of product use can be improved. Its quantitative characteristics are reflected in that as the cumulative output of products increases, the cost per unit of product will decrease in a certain proportion. Learning curve theory has become an important tool for business managers to carry out forecasting and decision-making activities, and is widely used in the production field. ...

AI Technical Summary

Problems solved by technology

[0005] (1) Difficulty obtaining historical data

Historical data is usually collected step by step from bottom-up, involving many factors and spanning a wide range of time and space, which increases the depth and breadth of historical data collection, resulting in uneven data quality

Judging from the analysis of existing literature, the incompleteness of historical monitoring data and large data errors lead to obvious deviations in the analysis results

[0006] (2) The statistical method of historical data is too rough

However, the processing of existing historical data is to count the data under the same measurement scale, which conceals the differences of different components for learning.

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