Monitoring and controlling of EMS-SCADA via SMS gateway

Anugraha, Rino Andias; Mulyana, Tatang

doi:10.1109/icoict.2015.7231496

Cited by 4 publications

(3 citation statements)

References 2 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Development of the SCADA application leverages the Wonderware Information Server with Active Factory and Generic Data Grid in order to obtain reporting system a system that can be accessed online. The researcher has been presented these SCADA such as [2][3][4][5]. The modelization for the control system is made using Simulink graphical model.…”

Section: Introductionmentioning

confidence: 99%

Optimizing Woven Fabric Defect Detection using Image Processing and Fuzzy Logic Method at PT. Buana Intan Gemilang

Safitri¹,

Mulyana²

2019

Proceedings of the 2018 International Conference on Industrial Enterprise and System Engineering (IcoIESE 2018)

Self Cite

View full text Add to dashboard Cite

The development of textile industry which 3rd position in the largest export values in Indonesia prove that the quality of textile must be one of factors that should be considered for all of textile companies. Buana Intan Gemilang is one of the companies that produce woven fabric. This company s produce curtain woven fabric. Quality is the most important factor to reach high level customer satisfaction. To get the best quality of product needs to consider their quality control. According to inspection process in Buana Intan Gemilang, manual inspection for woven fabric defect detection need 19.87 second for average inspection time. Therefore, unbalance of production volume with inspection process cause the bottle neck in inspection process. In this research, proposed designing automated fabric inspection using image processing and Fuzzy Logic Model. This processed uses GLCM as feature extraction with three parameters are cluster shade, cluster prominence, and number of object. The proposed fabric inspection using Fuzzy Logic implemented with MATLAB provides better result in identifying fabric defect and optimizing process time. This research using 120 training data, 80 offline test data, and 80 real time test data. Identification automation defect of woven fabric test data can produce accuracy 97, 5% and averaging process time 1.15 second. This result is better than manually inspection process that took 19.87 second for scanning defect of woven fabric.

show abstract

Section: Introductionmentioning

confidence: 99%

Optimizing Woven Fabric Defect Detection using Image Processing and Fuzzy Logic Method at PT. Buana Intan Gemilang

Safitri¹,

Mulyana²

2019

Proceedings of the 2018 International Conference on Industrial Enterprise and System Engineering (IcoIESE 2018)

Self Cite

View full text Add to dashboard Cite

show abstract

“…Conversely fuzzy logic is a logic that has a value of fuzziness between right and wrong. In fuzzy logic theory, a value can be true or false at the same time but how much truth and error a value depends on the weight of its membership [9][10][11][12].…”

Section: Introductionmentioning

confidence: 99%

“…The membership value or membership degree or membership function is the main characteristic of reasoning with the fuzzy logic [9][10][11][12].…”

Section: Introductionmentioning

confidence: 99%

Design of Automation System for Ceramic Surface Quality Control Using Fuzzy Logic Method at Balai Besar Keramik (BBK)

2017

View full text Add to dashboard Cite

Abstract. Indonesia is the world's top 10 ceramic users. Currently, the process of ceramic quality inspection in Indonesia, particularly in Balai Besar Keramik (BBK) is still done manually by human vision. Therefore, it is necessary to design a visual inspection system for digital image processing of ceramic automation using a Fuzzy Logic method. Fuzzy model is one method that can be used to determine ceramic surface quality control. This study aims to apply the fuzzy model in the design of automation system for ceramic surface quality control and describes its accuracy rate and automatic database. To perform feature extraction using GLCM extraction method to obtain autocorrelation, the sum of square (variance), and a number of the object. The information is used as input for data processing using the fuzzy model in the identification of quality of ceramic surface defect. In this research used Fuzzy model with GLCM extraction feature and process by using MATLAB software. This research used 32 training data can produce the accuracy of 96.87% and based on the real time system of 92.31% used 13 real time test data.

show abstract

Optimizing Woven Curtain Fabric Defect Classification using Image Processing with Artificial Neural Network Method at PT Buana Intan Gemilang

Shadika¹,

Mulyana²,

Rendra³

2017

MATEC Web Conf.

Self Cite

View full text Add to dashboard Cite

Abstract. The textile industry is one of the industries that provide high export value by occupying the third position in Indonesia. The process of inspection on traditional textile enterprises by relying on human vision that takes an average scanning time of 19.87 seconds. Each roll of cloth should be inspected twice to avoid missed defects. This inspection process causes the buildup at the inspection station. This study proposes the automation of inspection systems using the Artificial Neural Network (ANN). The input for ANN comes from GLCM extraction. The automation system on the defect inspection resulted in a detection time of 0.56 seconds. The degree of accuracy gained in classifying the three types of defects is 88.7%. Implementing an automated inspection system results in faster processing time.

show abstract

Monitoring and controlling of EMS-SCADA via SMS gateway

Cited by 4 publications

References 2 publications

Optimizing Woven Fabric Defect Detection using Image Processing and Fuzzy Logic Method at PT. Buana Intan Gemilang

Optimizing Woven Fabric Defect Detection using Image Processing and Fuzzy Logic Method at PT. Buana Intan Gemilang

Design of Automation System for Ceramic Surface Quality Control Using Fuzzy Logic Method at Balai Besar Keramik (BBK)

Optimizing Woven Curtain Fabric Defect Classification using Image Processing with Artificial Neural Network Method at PT Buana Intan Gemilang

Contact Info

Product

Resources

About