Bottleneck device forecasting method for re-entrant manufacturing system

Abstract

The invention discloses an adaptive neural fuzzy inference system (ANFIS)-based bottleneck device forecasting method for a re-entrant manufacturing system. The method comprises the following steps of: determining parameters for influencing a bottleneck device of the system, and the input and output of an adaptive neural fuzzy inference system (ANFIS); acquiring prototype system data by using a method for fixing the space of shift quantity of workpieces and preprocessing data by using a data comparison method to obtain an input / output data set of the ANFIS; and determining parameters of the ANFIS by using training data, forecasting by using test data to obtain the numerical number of a bottleneck device at the next moment, device utilization rate and queue length, analyzing forecasting results to obtain forecasting accuracy, and regulating parameters of an ANFIS model on line by using a pattern matching method before bottleneck forecasting each time. By the method, a bottleneck device forecasting scheme for the re-entrant manufacturing system can be constructed, the bottleneck device of the system at the next moment and related parameters are accurately forecast, and the method has instructive significance for a subsequent scheduling method based on the bottleneck device.

Description

technical field [0001] The invention belongs to the field of advanced manufacturing. It specifically relates to a method for bottleneck equipment prediction in large-scale reentrant manufacturing systems. technical background [0002] The reentrant manufacturing system is proposed based on the typical background of the semiconductor manufacturing system. Semiconductor manufacturing, as its key basic industry, has become a current hot industry. How to adopt a control strategy with excellent performance to improve the overall efficiency and performance of the semiconductor manufacturing system has become the focus of attention of the semiconductor manufacturing industry. In a semiconductor manufacturing system, bottleneck equipment is a key factor that restricts system output, production cycle, and WIP level. Therefore, how to quickly and effectively identify bottleneck equipment in the production line, and focus on key bottleneck equipment control in the production line to ...

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Problems solved by technology

There are mainly the following problems in the bottleneck research: (1) There are many parameters affecting the bottleneck equipment, which parameters are selected as the calculation bottleneck and the key factors affecting the bottleneck will directly affect the accuracy of the identification of the bottleneck equipment; (2) No matter what A bottleneck calculation method, the determination of the bottleneck is based on the selected results after sorting the calculated values ​​of the bottleneck, but various uncertain events in the production process may cause changes in the calculated values ​​and sorting, resulting in bottleneck drift, many scheduling methods based on bottlenecks do not Consider this more complicated situation; (3) The bottleneck-based scheduling method adopts a reasonable scheduling method when the bottleneck is known, but this scheduling method has a certain lag, and the production line may have accumulated , leading to a decline in performance, so the above-mentioned bottleneck-based method is difficult to effectively control the bottleneck equipment load and maintain a reasonable operation of the production line

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