The purpose of this paper is to propose an automatic pattern matching template generating method for the automatic optical inspection system in TFT LCD assembly and…
The purpose of this paper is to propose an automatic pattern matching template generating method for the automatic optical inspection system in TFT LCD assembly and positioning process, to improve the conventional image technology. Besides, focusing on integrating the image system with the existing control system, the double aligner mark searching time is decreased to reduce the working time of the integrated system.
The improved pattern matching method of genetic algorithm was adopted, including setting for template image selecting, encoding, calculating fitness function, pattern matching, template generating and genetic algorithm steps. The predetermined pixels were selected from the target template based on the minimum difference to the block image to be tested by utilizing the genetic algorithm, and the other pixels which have not been selected were neglected.
The selected pixels were encoded for recording by sequence mode, and then the target template and the image to be tested were compared based on the calculated fitness function. This method has the advantages of using the fitness function to reduce the searching time, with the help of genetic algorithm to find the optimal target template, and saving memory space by recording target template based on the sequence mode.
The genetic algorithm used in this study is a kind of optimal tool free from gradient data. As long as the fitness function and after continuous iteration are determined, the optimal solution can be found out, and then the optimal target template can be generated.
This system uses fitness function to reduce the pattern matching time. Plural pixels are preset inside the target template, and its fitness function value is calculated. When the target template is compared with the image to be tested, only the fitness function value (also the difference of the plural pixels) is calculated and compared.
The remaining pixels are neglected, so that the searching time can be reduced greatly. The sequence mode is used to save the required memory space for recording target template. Since sequence mode is adopted to record the information of selected pixels, lots of required memory space for recording target template information will be saved.
This paper develops a smart system based on the concept of Industry 4.0 to prevent customer dissatisfaction. The value of this prevention system is that it enables…
This paper develops a smart system based on the concept of Industry 4.0 to prevent customer dissatisfaction. The value of this prevention system is that it enables hoteliers to interact with customers by understanding what they like/dislike from their behaviors via data analysis. Therefore, this system helps hoteliers to enhance service quality by predicting service issues.
The system, named the dissatisfaction identification system (DIS), is developed. A total of 127 service items were examined by a hotel manager who preset the threshold values for the measurement of service quality. A big data set for the questionnaire survey is statistically generated by a pseudorandom number generator and 10,000 mock data sets are taken as input for comparison.
The results indicated that 36 out of 127 service items are identified as service issues for the participating hotel. Examples include customer code number 01d, “Space of parking lot is adequate” in the safety management category, and number 05a, “A hotel's service time meets my needs” in the front office service category. The items identified require improvement action plans for preventing customer dissatisfaction.
This paper offers a new perspective paper emphasizing customer dissatisfaction using a big data-driven technology system. The DIS, prevention system, is developed to aid hotels by enhancing their relationships with customers using a data-driven approach.