The business process of global third party logistics company is defined as a network of logistics activities which involves the products that are manufactured in the developing countries, such as Vietnam, China and so on, and delivered to North or South American countries via intermediate stopover sites. The third party logistics company usually uses proprietary logistics information system to support the related logistics activities. However, each consignor sometimes may require different business process based on the customer type or characteristics of their products. Therefore, the third party logistics company need to modify their business process to reflect customer’s requirements, resulting in the modification of logistic information systems and additional costs. Therefore, a flexible mechanism is required to efficiently support the various types of requirements by the owners of the products. In this paper, first, we figured out various business rules related to third party global logistics activities. Second, we grouped the identified business rules into business processes, objects, relations, dependency, policy, representations, execution, and resources and further into precondition, postcondition, and invariant based on checking point in time. Furthermore, the categorized rules are classified into inter-activity and intra-activity rules based on the execution range. Third, we proposed a rule syntax to describe the defined rules into scripts which are understood by user and information system together. When each activity is executed, the rule manager checks whether there are rules related with the activity execution. Finally, we developed a prototype rule management system to show the feasibility of our proposed methodology and to validate it with an example.

The market size of plant projects in overseas is so large that domestic EPC project contractors are actively seeking the overseas projects and then trying to meet completion plans since successful fulfillment of these projects can provide great opportunities for them to expand into new foreign markets. International EPC projects involve all of the uncertainties common to domestic projects as well as uncertainties specific to foreign projects including marine transportation, customs, regulations, nationality, culture and so on. When overseas project gets off-schedule, the resulting uncertainty may trigger unexpected exceptions and then critical effects to the project performance. It usually require much more time and costs to encounter these exceptions in foreign sites compared to domestic project sites. Therefore, an exception handling approach is required to manage exceptions effectively for successful project progress in foreign project sites.In this research, we proposed a methodology for prediction and evaluation of exceptions caused by risks in international EPC projects based on sensitivity analysis and Bayesian Networks. First, we identified project schedule risks and related exceptions, which may meet during the fulfillment of foreign EPC projects that is performed in a sequence of engineering, procurement, preparatory manufacture, foreign shipping, construction, inspection and modification activities, and affect project performance, using literature review and expert interviews. The impact of exceptions to the schedule delay were also identified. Second, we proposed a methodology to predict the occurrence of exceptions caused by project risks and evaluate them. Using sensitivity analysis, we can identify activities that critically affect schedule delay and need to focus by priority. Then, we use Bayesian Networks to predict and evaluate exceptions. Third, we applied the proposed methodology to an international EPC project example to validate the proposed approach. Finally, we concluded the research with the further research topics. We expect that the proposed approach can be extended to apply in exception management in project management.

The project schedule risk in the engineering and facility construction industry is increasingly considered as important management factor because the risks in terms of schedule or deadline may significantly affect the project cost. Especially, the project-based operating companies attempt to find the best estimate of the project completion time for use at their proposals, and therefore, usually have much interest in accurate estimation of the duration of the projects. In general, the management of projects schedule risk is achieved by modeling project schedule with PERT/CPM techniques, and then performing risk assessment with simulation such as Monte-Carlo simulation method. However, since these approaches require the accumulated executional data, which are not usually available in project-based operating company, and, further, they cannot reflect various schedule constraints, which usually are met during the project execution, the project managers have difficulty in preparing for the project risks in advance of their occurrence in the project execution. As these constraints may affect time and cost which role as the crucial evaluation factors to the quality of the project result, they must be identified and described in advance of their occurrence in the project management. This paper proposes a Bayesian Net based methodology for estimating project schedule risk by identifying and enforcing the project risks and its response plan which may occur in storage tank engineering and construction project environment. First, we translated the schedule network with the project risks and its response plan into Bayesian Net. Second, we analyzed the integrated Bayesian Net and suggested an estimate of project schedule risk with simulation approach. Finally, we applied our approach to a storage tank construction project to validate its feasibility.

Recently as the manufacturers want competitiveness in dynamically changing environment, they are trying a lot of efforts to be efficient with their production systems, which may be achieved by diminishing unplanned operation stops. The operation stops and maintenance cost are known to be significantly decreased by adopting proper maintenance strategy. Therefore, the manufacturers were more getting interested in scheduling of exact maintenance scheduling to keep smooth operation and prevent unexpected stops. In this paper, we proposedan integrated maintenance approach in injection molding manufacturing line. It consists of predictive and preventive maintenance approach. The predictive maintenance uses the statistical process control technique with the real-time data and the preventive maintenance is based on the checking period of machine components or equipment. For the predictive maintenance approach, firstly, we identified components or equipment that are required maintenance, and then machine parameters that are related with the identified components or equipment. Second, we performed regression analysis to select the machine parameters that affect the quality of the manufactured products and are significant to the quality of the products. By this analysis, we can exclude the insignificant parameters from monitoring parameters and focus on the significant parameters. Third, we developed the statistical prediction models for the selected machine parameters. Current models include regression, exponential smoothing and so on. We used these models to decide abnormal patternand to schedule maintenance. Finally, for other components or equipment which is not covered by predictive approach, we adoptedpreventive maintenance approach. To show feasibility we developed an integrated maintenance support system in LabView Watchdog Agent and SQL Server environment and validated our proposed methodology with experimental data.

The project-based business companies usually have much interest in predicting the expected finish date and related probability of project completion to refer at their proposals for projects. In general, the management of projects schedule risk is achieved by modeling project schedule with PERT/CPM techniques, then performing risk assessment with Monte-Carlo simulation method. However, since these approaches cannot reflect various schedule constraints, the project managers cannot prepare for the project risks in advance of their. This paper proposed a methodology for predicting project schedule risk by identifying and enforcing the constraints which may occur in a storage tank engineering and construction project environment. We applied our approach to a storage tank construction project to validate its feasibility. By using the methodology proposed in this paper, the project schedule risk can be evaluated and predicted more accurately and practically than the PERT/CPM or Monte-Carlo simulation approach.

In the project management context, the impotance of risk management is increasing because the risks in terms of time and cost may significantly affect the result of the project. In general, the management of projects schedule risk is achieved by modeling project schedule with PERT/CPM techniques, then performing risk assesment with monte-carlo simulation method. However, these approach can not reflect constraints, which may be occurred during the project execution, and cope with uncertainty in the future. As these constraints may affect time and cost which are the crucial evaluation factor to the project, they must be identified and evaluated to manage the future project risk before the project is started. This paper proposes a methodology for project schedule risk management by identifying and enforcing the constraints which may be occurred in complex and uncertain project environment. First, project risk constraints are identified and categorized into time, dependancy, and branching. Then, project schedule model with constraints is converted to CPN(Colored Petri Net) which can represent all the identified constraints to assess and predict schedule risk. Finally, the expected risk of the project (in terms of time and cost) is assessed and predicted by performing Petri Net simulation. By using the methodology proposed in this paper, the risk in terms of time and cost in project schedule model can be assessed and predicted more accurately and practically than the PERT/CPM and/or Monte-carlo simulation method. Furthermore, the constraints, which may occur unexpectedly after the project launch, can be evaluated to determine the schedule risk. The expected risk can be used to decide whether risk mitigation or project termination process undertake.

W3C에서 XML 표준을 발표한 이후 XML을 지원하는 관련 기술들이 지속적으로 개발되고 있으며 데이터의 중립성을 응용하는 것을 주제로 하는 연구가 활발하게 진행되고 있으며 응용범위가 확대되고 있다. 이들 연구는 Business 현장에서 발생하는 데이터의 통합 및 재활용을 과제로, XML Schema간의 통합, 데이터의 저장 및 생성을 위한 DB 스키마와 XML 스키마 통합, 대용량 XML 데이터 관리를 위한 DB 저장 및 검색 등의 분야에서 큰 성과를 거두고 있다. 최근 활발하게 진행되고 있는 기업간 전자상거래(B2B) 에서는 일반 디지털 파일 또는 전자거래에 사용되는 전자문서 등 다양한 형식의 데이터들이 존재한다. 이러한 자료들을 이용하여 거래 당사자간에는 주문신청부터 송금 및 수금 확인까지 B2B 거래 프로세스에 관련된 다양한 데이터 들이 교환된다. 기업간 교환되는 데이터에는 일정한 규칙이 존재하며 이들을 확인하는 것은 중요하다고 볼 수 있다. 즉, 관련 자료의 통합시 고려되어야 하는 제약조건의 관리에 대한 연구가 필요하다고 볼 수 있다. 본 연구에서는 기업간 전자상거래 환경에서 데이터 교환의 표준으로 자리잡고 있는 XML 데이터를 중심으로 데이터 통합시 고려되어야 할 제약조건들을 정리하고 이를 해결하는 방안을 제시하고자 한다. 먼저 스키마 충돌에 따른 제약조건과 자료 자체의 무결성 및 업무규칙 제약조건을 정리하여 분류하였으며, 이들 제약조건을 표현하여 관리할 수 있는 메커니즘을 제안하였다. 즉, XML의 특징을 활용하여 분산 이기종 데이터 간의 통합 및 제약조건을 해결하는 방안을 제시하였다. 본 연구의 결과는 B2B 전자거래에서 교환되는 문서의 생성, 검색, 저장 및 재활용 과정에서 필요한 데이터의 검증에 기여할 것으로 기대된다.