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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.

This study aims to validate the cost of building the infrastructure to commercialize online electric vehicles. For that purpose, we probe the cost to construct the necessary infrastructure for online electric vehicles regarding Seoul area public bus transit. OLEV and PEV are considered as alternative electric vehicle schemes, and each of them has their own cons and pros in terms of rechargeable battery cost and charger cost. An optimization model which minimizes the cost to install online electric bus feeding devices is proposed in order to compare the total costs of the two alternative schemes. We developed a Mixed Integer Programming model to locate the feeding devices of several different lengths at each bus stops. Furthermore, we implemented a computer simulator to obtain the parameters which will be used in the MIP model and a Web-based system which determines the optimal location of infrastructure for the whole city area from a result of the MIP model. The cost comparison result shows that the total cost of OLEV is cheaper than that of PEV considering the real data of Seoul area public transit, and, as a result, confirms the feasibility of the commercialization of OLEV.

As companies introduced ERP (Enterprise Resource Planning) systems since the middle of 1990s, the databases of the companies has become centralized and gigantic. The companies are now developing data-mining based applications on those centralized and gigantic databases for knowledge management. Almost of them are using /C++, a embedded SQL programming language, and it`s because the /C++ is independent of platforms and also fast. However, they suffer from difficulties in development and maintenance due to the characteristics of corporate databases which have intrinsically large number of tables and fields. The purpose of this research is to design and implement a methodology which makes it easier to develop and maintain embedded SQL applications based on relational databases. Firstly, this article analyzes the syntax of /C++ and addresses the concept of repetition and duplication which causes the difficulties in development and maintenance of corporate information systems. Then, this article suggests a management architecture of source codes and databases in which a preprocessor generates /C++ source codes by referring a DB table specification, which would solve the problem of repetition and duplication. Moreover, this article also suggests another architecture of DB administration in which the preprocessor generates DB administration commands by referring the same table specification, which would solve the problem of repetition and duplication again. The preprocessor, named , has been developed under the UNIX command-line prompt environment to preprocess /C++ source codes and SQL administration commands, and is under update to be used in another DB interface environment like ODBC and JDBC, too.

This article identifies factors affecting successful ERP systems by focusing on the stages after stabilizing ERP systems and overcoming temporary performance dip by introduction of ERP systems, and suggests change management tactics to control those identified factors. We can not expect that every users are familiar with the usage of an ERP system even after they are informed about the expected advantage of the newly implemented ERP system and trained intensively for changed business process and system usage while implementing a new ERP system. Moreover, even after more than six months usage of the system, the users may still have some trouble due to the reason why they have insufficient information about the expected advantage of the system (recognition gap) and insufficient knowledge about the changed usage of the system (knowledge gap). Hence, this article diagnoses by conducting a case study that those recognition and knowledge gap would have a severe bad influence upon the users` trust and satisfaction on ERP systems. This article suggests an appropriate change management tactics to overcome those recognition and knowledge gap by considering the relationship with the efforts for change management before, during, and after the introduction of ERP systems and performing an in-depth analysis on the users` dissatisfaction and request for update during the stages after the stabilization of the ERP systems. This article also shows a corroborative evidence that these efforts of change management consequently contributes to the solution of users` distrust and dissatisfaction. In sum, this article identifies the factors influencing badly on the magnitude and seriousness of knowledge and recognition gap, and suggests a conceptual research model which says that the satisfaction of ERP users could be uplifted by the solution of their knowledge and recognition gap if we keep making efforts on appropriate change management considering those identified factors during the stages after the stabilization of an ERP system.

As more and more consumer-to-consumer e-marketplaces have been introduced with rapidly increasing transaction volumes, consumers now hope that computer technology will support their transaction processes in these electronic markets. To satisfy their expectations, many researchers have delved into developing intelligent agent systems to support customer-to-customer electronic commerce more efficiently. However, many of these researchers have focused only upon supporting simple negotiation for the price of undifferentiated goods. To expand the object of negotiation to differentiated goods, customers should be allowed to negotiate over multiple attributes of the product besides the price, including attributes which are related to the transaction activity itself, such as delivery time and payment method. To satisfy this requirement, we propose an agent marketplace for differentiated goods where the agent of a customer can negotiate not only for the price but also various attributes of a product and transaction in order to provide a better utility level for both buyer and seller. To achieve these goals, we have developed a formal protocol and system architecture to support the proposed e-marketplace and individual agents, and a prototype system is developed to validate our approach and show that negotiation resulting from our scheme is Pareto optimal.

With the proliferation of the WWW, providing more intelligent Websites has become a major concern in the e-business industry. Recently, this trend has been even more accelerated by the success of Customer Relationship Management (CRM) in terms of product recommendation, and self after service, etc. As a result, many e-companies are eager to embed Web-enabled, rule-based systems, i.e. that is, expert systems, into their Websites, and several well-known commercial tools to facilitate this are already available in the market. So far, most of those tools are based on CGI, but CGI-based systems inherently suffer from problems related to overburdening, when there are too many service demands at the same time. To overcome the limitations of the existing CGI-based expert systems, we propose a new form of Web-enabled expert system that uses a hyperlink-based inference mechanism. In terms of burden to the Web server, our approach has proven to outperform the CGI-based approach theoretically as well as empirically. For practical purposes, our approach is implemented in a software system, WeBIS, and uses a graphic rule editing methodology, Expert’s Diagram, that is incorporated into the system to facilitate rule generation and maintenance. WeBIS is now successfully operating for financial consultation on the Website of a leading financial consulting company in Korea. q 2004 Published by Elsevier Ltd.

Post-Model Analysis (PMA) is a framework that unifies an optimization model with a rule-based system and enables the multi-objective decision modeling that considers both numeric and symbolic objectives and decision variables. In this research, we have developed a system UNIK-PMA that implements the PMA procedure on the knowledge-assisted optimization modeler UNIK-OPT and a backward chaining rule-based system UNIK-BWD. This paper particularly elaborates the process of generating constraints of the linear programming model from the rule-based goals, which is a crucial step of PMA. UNIK-PMA is illustrated with an example of aggregate production planning.

We attempt to unify a linear programming model with a rule-based system via overlapped decision variables. Since a rule base can be regarded as an acyclic AND/OR digraph, the unified model is virtually a multiobjective decision making problem that considers both numeric and symbolic objectives and decision variables. To solve this problem, the Post-model Analysis approach is adopted. An essential feature of the Post-model Analysis is that it supports nondominated tradeoffs among the numeric and symbolic objectives. So, this paper proposes a set of methods for computing the nondominated solutions. A prototype, UNIK-PMA that realizes the idea is developed as a subsystem of the UNIK (UNIfied Knowledge) system.