Namkyu Park

An XML-based process definition language for integrated process management

Business processes are increasingly recognized as important corporate assets that need to be managed throughout their lifecycle. Specially, interests in supply chain management and virtual enterprises require a new paradigm that provides lifecycle support for business processes. Integrated Process Management (IPM) has been proposed as a business process management paradigm that aims at integrating processes using eXtensible Markup Language (XML) and supporting design, analysis, automation, and management of business process knowledge. This paper introduces IPM-PDL, an XML-based process definition language for IPM. Process definitions and related data are integrated using XML which will be translated to a colored Petri Net. Various analysis and simulation can be performed to check the validity of a new process and estimate its performance. The paper also introduces ProcessWare, a prototype system for IPM-process definition language (PDL), along with an extended example which will demonstrate how IPM can effectively manage business processes throughout their lifecycle ranging from process modeling to process knowledge management.

Applying genetic algorithm to a new location and routing model of hazardous materials

Nowadays – particularly in systems dealing with hazardous materials (HAZMAT) – in addition to minimising the cost of operations in facility location and routing problems, the risk of these operations is considered an important objective. In this paper, a new mathematical model for the location and routing in facilities and disposal sites is proposed. Also, the risk and cost of transporting goods from facilities to customers is considered. The model minimises weighted sum of the cost and risk by answering these questions: (1) where to open the facilities which produce HAZMAT; (2) where to open disposal sites; (3) to which facilities every customer should be assigned; (4) to which disposal site each facility should be assigned; (5) which route a facility should choose to serve the customers; and (6) which route a facility should choose to reach a disposal site. A novel GA is applied to solve the mathematical model. The results show the robustness of GA in terms of finding high-quality non-dominated solutions and running time.

Online discovery of Heart Rate Variability patterns in mobile healthcare services

Recent years, advances in day-to-day wearable sensors have led to the development of low powered physiological sensor platforms, which can be integrated in body area networks, a new enabling technology for real-time health monitoring. The bottleneck in health state awareness is the algorithm that has to interpret the sensor data. Nowadays Coronary Heart Disease (CHD) is still the leading cause of death. Many classification techniques such as decision tree and neural networks proposed for an early detection of individual at risk for CHD are not able to continuously detect heart state based on sensor data stream. In this study, we propose an online three-layer neural network to recognize Heart Rate Variability (HRV) patterns related to CHD risk in consideration of daily activities. ECG sensor data is preprocessed using Poincare plot encoding. Incremental learning is utilized to train the network with new data without forgetting the previously learned patterns. The algorithm is named Poincare-based HRV patterns discovering Incremental Artificial neural Network (PHIAN). When a sample is presented, the nodes in the hidden layer of PHIAN compete for determining the node with the highest similarity to the input. Error variables associated with the neuron units are used as criteria for new node insertion in hopes of allowing the network to learn new patterns and reducing classification error. However, the node insertion has to be stopped in the overlapping decision areas. We suppose that the overlaps between classes have lower probability than the centric part of the classes. Therefore, after a period of learning we remove the nodes with no neighbor. Plus, the error probability density is taken into account instead of input probability density. Finally, the predictive capability of PHIAN is compared with three previous classification models, namely Self-Organizing Map (SOM), Growing Neural Gas (GNG), and Multilayer Perceptron (MLP) in terms of classification error and network structure. The results show that PHIAN outperforms the existing techniques. Our proposed model can be efficiently applied to early detection of abnormal conditions and prevent the abnormal becoming serious.

An integrated decision support system for FMS production planning and scheduling problems

This paper discusses planning and scheduling problems for efficient use of an FMS and presents an integrated decision support system for dealing with these problems.The decision support system, FMSDS (Flexible Manufacturing Systems Decision Support System), includes several modules: data handling module, part selection module, loading module, load adjusting module, scheduling module and simulation module.This paper suggests the solution methodology of each subproblem. Also, an integrated interface scheme between the subproblems is presented. The interface scheme considers the relationships between the subproblems and generates solutions using hierarchical and looping approaches.FMSDS is made up of six alternative models considering three loading objectives and two production order processing strategies. Performance comparison among the six alternatives is shown using the non-terminating simulation techniques.

A shared process model for independent and synchronized e-business transactions

Two of the most essential values we can expect from the application of information technology to daily business practices are speed and credibility. When it comes to business-to-business (B2B) interactions, these virtues play a role of primary driving forces on the ongoing and ever-increasing innovation in manufacturing operation and business transactions. All too often the achievement of the virtues requires reconciliation of two seemingly conflicting objectives, independence and synchronization. The industry as a whole seems to be seeking a breakthrough to this issue in a bunch of de facto standards. In this paper, we analyze the rationale laid behind the current standards based on the review of B2B principles and propose how to articulate the standards with existing IT infrastructures.

Enterprise Viability Model: Extending Enterprise Architecture Frameworks for Modeling and Analyzing Viability under Turbulence

The business environment has become increasingly turbulent, making it difficult for many companies to maintain their viability. Despite the increasing prevalence of turbulence and the challenges it poses, managers have few tools to conceptualize, analyze, and develop strategies to address the problem. The authors developed the enterprise viability model as a modeling and analysis framework for evaluating the robustness of the management control system (MCS) of enterprises. The authors present the rationale for integrating axiomatic design and the viable system model into the enterprise viability model and illustrate the use of the enterprise viability model in business process analysis.

A high performance finite capacitated MRP process using a computational grid

A material requirement planning (MRP) process generates a production plan which guarantees an exact quantity of the right materials available at the needed time. Providing an executable production plan at high speed has remained a goal for MRP since the process was first developed in the 1970s. However, due to the time consuming characteristic of the process with its intensive database interaction, real time processing remained unattainable. Moreover, this performance issue became worse, as the utilisation of production resources on the shop floor are expected to be maximised by the process due to a dynamic market environment. This paper presents a recent work by the authors on the concept of using a computational grid to achieve a breakthrough in its performance under conditions of finite capacity. The proposed system resolves capacity constraints by applying a simple heuristic called longest tail first rule, which is proved to minimise the total lead time, to each distributed cluster obviating the need for any rescheduling procedures. Implementation of this concept in a distributed database environment and its performance analysis are described. The experimental results suggest that the proposed finite capacitated MRP process has desirable characteristics in terms of processing time with a deep bill of material as in current supply chain practice.

A Look-Ahead Routing Procedure for Machine Selection in a Highly Informative Manufacturing System

Many dispatching rules have been developed for the on-line control of product flow in a job shop. The introduction of a highly informative manufacturing system (HIMS) has added a new requirement to a classical job-shop control problem: the selection of machines by parts of different types. An HIMS can keep a great deal of information on the status of the system, such as information on what is scheduled in the near future with great accuracy, which can be used for shop floor control. For example, the knowledge of the time when the next parts arrive at the machines can be used for better routing. This article tests the effect of the use of this knowledge for part routing on the parts flow time and tardiness under a look-ahead routing procedure (LARP). LARP assigns a new part to a machine so that the assignment minimizes the flow time or tardiness of the current part and the next N parts arriving after the current part. A test shows that the reduction of part flow time is up to 11% and the reduction of tardiness is up to 21% for the cases with this procedure.

The discrete Unconscious search and its application to uncapacitated facility location problem

In this paper a discrete variant of Unconscious search (US) for solving uncapacitated facility location problem (UFLP) is proposed. Unconscious search mimics the process of psychoanalytic psychotherapy in which the psychoanalyst tries to access the unconscious of a mental patient to find the root cause his/her problem, which is encapsulated in unconsciousness. Unconscious search is a multi-start metaheuristic which has three main stages, namely construction, construction review and local search. In construction phase a new solution is generated. In construction review the generated solution in construction phase is used to produce more starting points for using in the local search phase. The results of applying US to UFLP shows that this metaheuristic can determine high quality solutions in short processing time comparing to other heuristics.

A study on e-Transformation effectiveness analysis with cases in manufacturing and retail industries

This research suggests a framework for e-Transformation effectiveness analysis to explain the industrial e-Work transformation phenomenon. The framework consists of three-tier indices, which are general indices, effectiveness indices and measurement indices. In the effort to specialize the framework in industry-specific processes, the core business processes are extracted from both manufacturing and retail industries respectively. To prove the practical value of the suggested framework, it is applied to 20 representative companies of Korean manufacturing and retail industries.