A lot of sensor and control signals is generated by an industrial controller and related internet-of-things in discrete manufacturing system. The acquired signals are such records indicating whether several process operations have been correctly conducted or not in the system, therefore they are usually composed of binary numbers. For example, once a certain sensor turns on, the corresponding value is changed from 0 to 1, and it means the process is finished the previous operation and ready to conduct next operation. If an actuator starts to move, the corresponding value is changed from 0 to 1 and it indicates the corresponding operation is been conducting. Because traditional fault detection approaches are generally conducted with analog sensor signals and the signals show stationary during normal operation states, it is not simple to identify whether the manufacturing process works properly via conventional fault detection methods. However, digital control signals collected from a programmable logic controller continuously vary during normal process operation in order to show inherent sequence information which indicates the conducting operation tasks. Therefore, in this research, it is proposed to a recurrent neural network-based fault detection approach for considering sequential patterns in normal states of the manufacturing process. Using the constructed long short-term memory based fault detection, it is possible to predict the next control signals and detect faulty states by compared the predicted and real control signals in real-time. We validated and verified the proposed fault detection methods using digital control signals which are collected from a laser marking process, and the method provide good detection performance only using binary values.

As the development environment is changing with the development of information communication technology, the systems that were used by each service became used with integration. In the process of integrating from existing legacy systems to new system, it should be smoothly integrated or shared, however, it cannot help holding existing technology or component due to significant cost burden for conversion. In this paper, it was not only classified by types with analyzing the various elements that make up legacy system but an approach and monitoring system were developed to each type. After System application results, data's information generated in each process is provided to other system in real time, so that it has not only secured the work efficiency and reliability but also it is made possible by integrating data in various formats for efficient data management, rapid search and tracking to history. With real-time monitoring system developed in this study, It can be very useful in a variety of industries which require real-time monitoring of distributed legacy system data.

In an environment where manufacturing conditions such as product lines keep changing, manufacturing control systems need to be continually maintained and upgraded according to the change. This requires an effective system implementation methodology. In th

In the recent years, the companies have manually recorded a production status in a work diary or have mainly used a bar code in order to collect each process's progress status, production performance and quality information in the production and logistics process in real time. But, it requires an additional work because the worker's record must be daily checked or the worker must read it with the bar code scanner. At this time, data's accuracy is decreased owing to the worker's intention or mistake, and it causes the problem of the system's reliability. Accordingly, in order to solve such problem, the companies have introduced RFID which comes into the spotlight in the latest automatic identification field. In order to introduce the RFID technology, the process flow must be analyzed, but the ASME sign used by most manufacturing companies has the difficult problem when the aggregation event occurs. Hence, in this study, the RFID logistic flow analysis Modeling Notation was proposed as the signature which can analyze the manufacturing logistic flow amicably, and the manufacturing logistic flow by industry type was analyzed by using the proposed RFID logistic flow analysis signature. Also, to monitor real-time information through EPCglobal network, EPCISEvent template by industry was proposed, and it was utilized as the benchmarking case of companies for RFID introduction. This study suggested to ensure the decision-making on real-time information through EPCglobal network. This study is intended to suggest the Modeling Notation suitable for RFID characteristics, and the study is intended to establish the business step and to present the vocabulary.

Reliability evaluation considering the qualitative factors is major criterion for customer's satisfaction with the products. Especially, the normalized model is very efficient method for the systematic evaluation of hazardable possibility. Therefore this paper presents reliability evaluation model through the normalized model by the quantitative and the function, information control, flexibility, and maintenance factors in the flexible manufacturing systems under uncertainty. Finally, this paper can be simply used in the more efficient decision making in flexible manufacturing systems under uncertainty.

최근 들어 제조가 발생되는 모든 분야에서 정보의 의미론적 전달방법 및 체계를 정형화하는 작업이 표준화와 더불어 활발히 진행되고 있다. 제조시스템에서 문제가 발생하였을 때 간결하고 정확한 문제 진단에 대한 정보전달은 비용의 절감은 물론 생산성 향상을 위해서도 필수적인 요소이다. 본 연구에서는 제조시스템에서 최적화된 정보전달을 위한 상황이론적 방법론을 제시한다. 본 연구에서 제시하는 방법론의 궁극적인 목적은 실제 제조공정이나 현장에서 발생되는 복잡한 정보의 흐름, 표현, 관리를 효율적으로 할 수 있고 작업자, 관리자, 경영자 모두가 공통적으로 활용할 수 있는 정형화된 틀을 만드는데 있다. 본 연구에서 제시하는 방법론은 제조 현장에서 공정상의 문제점을 분석하고 검사할 수 있는 도구로 활용될 수 있을 것이다.

Manufacturing firms have adapted seriously the Design for Manufacture and Assembly (DFMA) techniques which consider concurrently all factors related to the product development by using effective communications and sharing of information on product development processes. This study performed modelling and characterizing the data related to product manufacturing information for Design for Manufacture(DFM) evaluation and analysis. It adapted component-based development method for communicating and managing manufacturing information among distributed manufacturing organizations. Introducing component-based development offers safety and speed to network based system. This development using Unified Modelling Language(UML) provides efficient way for reconstruction and distribution of applications. Also, the integration of database and component into the internet environment enables to communicate and manage effectively manufacturing information for DFM evaluation and analysis at any place in the world. Therefore this system can make it more reasonable that evaluating, analyzing, and effective decision making of product design using DFM technique.