In the case of nuclear projects, when developing a new reactor type, it is necessary to confirm the reactor type, secure the safety, and especially obtain the construction permit approval of the licensing authority for construction. Schedule management is necessary to carry out nuclear projects, and progress rate management of project progress management is largely composed of three elements: scope management, cost management, and resource management. However, in the case of the small modular reactor (SMR) project currently being carried out, it is difficult to calculate the progress rate including budget and resources due to the nature of the project. Therefore, in the SMR project, it took two years from the beginning to prepare the integrated project master schedule (IPMS) to prepare the draft, and then two revisions were made over a year and a half. In this SMR project, we will consider the entire construction period such as design, purchase and production, construction, commissioning, and operation in terms of scope management. The entire document list was created using the document review and approval sheet created at the beginning of the design. In the PMIS (Project Management Information System), the number of approved documents was calculated by comparing the list of engineering documents. In the purchase production part, the main core equipment such as the primary system nuclear steam supply system (NSSS), the secondary system turbine and condenser, and the man machine interface system (MMIS) are managed. Purchasing and manufacturing management shall be managed so that major equipment can be delivered in a timely manner in accordance with the schedule for delivery of equipment in the IPMS. In order to prevent delays in the start of production, it is necessary to minimize the waiting time for work through advance management tasks such as insurance of drawing, stocking of materials, availability of production facilities, etc. In this way, we decided to carry out the schedule management for the design, purchase and manufacturing part in the SMR project first, and the installation, construction and commissioning part will be prepared for the future schedule management.

This study focuses on a job-shop scheduling problem with the objective of minimizing total tardiness for the job orders that have different due dates and different process flows. We suggest the dispatching rule based scheduling algorithm to generate fast and efficient schedule. First, we show the delay schedule can be optimal for total tardiness measure in some cases. Based on this observation, we expand search space for selecting the job operation to explore the delay schedules. That means, not only all job operations waiting for process but also job operations not arrived at the machine yet are considered to be scheduled when a machine is available and it is need decision for the next operation to be processed. Assuming each job operation is assigned to the available machine, the expected total tardiness is estimated, and the job operation with the minimum expected total tardiness is selected to be processed in the machine. If this job is being processed in the other machine, then machine should wait until the job arrives at the machine. Simulation experiments are carried out to test the suggested algorithm and compare with the results of other well-known dispatching rules such as EDD, ATC and COVERT, etc. Results show that the proposed algorithm, MET, works better in terms of total tardiness of orders than existing rules without increasing the number of tardy jobs.

As a system complexity increases and technology innovation progresses rapidly, leasing the equipment is considered as an important issue in many engineering areas. In practice, many engineering fields lease the equipment because it is an economical way to lease the equipment rather than to own the equipment. In addition, as the maintenance actions for the equipment are costly and need a specialist, the lessor is responsible for the maintenance actions in most leased contract. Hence, the lessor should establish the optimal maintenance strategy to minimize the maintenance cost. This paper proposes two periodic preventive maintenance policies for the leased equipment. The preventive maintenance action of policy 1 is performed with a periodic interval, in which their intervals are the same until the end of lease period. The other policy is to determine the periodic preventive maintenance interval minimizing total maintenance cost during the lease period. In addition, this paper presents two decision-making models to determine the preventive maintenance strategy for leased equipment based on the lessor’s preference between the maintenance cost and the reliability at the end of lease period. The structural properties of the proposed decision-making model are investigated and algorithms to search the optimal maintenance policy that are satisfied by the lessor are provided. A numerical example is provided to illustrate the proposed model. The results show that a maintenance policy minimizing the maintenance cost is selected as a reasonable decision as the lease term becomes shorter. Moreover, the frequent preventive maintenance actions are performed when the minimal repair cost is higher than the preventive maintenance cost, resulting in higher maintenance cost.

An aircraft engine is supposed to be used for a specified lifespan, and it is reused through the depot maintenance for a major overhaul when its cumulative service life reaches the lifespan. However, the depot maintenance takes a long time due to the complexity of its process, and thus to continuously operate aircraft, spare engines are required to substitute engines under renovation. Considering the limited capacity of the depot, the uniformity of the quantity and cycle of engines entering the depot maintenance provides an opportunity to the decrease of the spare engines and the improvement of aircraft availability. It is the purpose of engine life management. Furthermore, in establishing flight plans, the time for essential maintenance activities, such as pre/post-flight inspection, servicing, the preparation for next flight, has to guarantee. Especially, fighters additionally require much time for installing weapons for their mission. That is, the rearming procedure can be left out if the adjoining missions are identical. Otherwise, the rearming time is varyingly spent depending on the types of adjacent duties. Therefore, this study proposes the mathematical model for an aircraft-mission assignment considering engine life management and maintenance schedule, and it is formulated based on the time-space network. Moreover, to verify and validate the model, an example was developed by applying realistic aircraft operating environment and simulation to perform air operations for several days was fulfilled. The experimental results presented flight plans corresponding to the purpose of this study, such as engine life management and the assurance of maintenance time.

As a system complexity increases and technology innovation progresses rapidly, it tends to lease a system rather than own one. This paper deals with a decision-making model to determine the preventive maintenance strategy for leased equipment. Various maintenance options are presented and formulated via the non-homogeneous Poisson process. During the lease period, the preventive maintenance strategy that minimizes the total cost among the presented maintenance options is selected. A numerical example is provided to illustrate the proposed model.

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.

Logistics project scheduling problem in indeterminate environment is gaining more and more attention in recent years. One effective way to cope with indeterminacy is to develop robust baseline schedule. There exist many related researches on building robust schedule in stochastic environment, where historical data is sufficient to learn probability distributions. However, when historical data is not enough, precise estimation on variables may be impossible. This kind of indeterminate environment can be described by uncertainty according to uncertainty theory. Related researches in uncertain environment are sparse. In this paper, our aim is to solve robust project scheduling in uncertain environment. The specific problem is to develop robust schedule with uncertain activity durations for logistics project. To solve the problem, an uncertain model is built and an intelligent algorithm based on simulated annealing is designed. Moreover, we consider a logistics project as a numerical example and illustrate the effectiveness of the proposed model and algorithm.

다양한 전자제품의 조작법을 빠르고 정확하게 학습하는 것은 일상적이고 중요한 과제가 되었다. 특히 소프트 웨어는 여러 제품들의 통제 및 조작에서 핵심적인 지위를 차지하고 있다. 본 연구는 기존 학습연구에서 중요한 변인으로 연구되어온 학습방법, 학습계획, 과제난이도가 소프트웨어 학습에 미치는 영향을 검증하였다. 실험1에 서는 2 (학습방법: 경험적 vs. 언어적) x 2 (학습계획: 간격 vs. 덩이진) x 2 (난이도: 쉬움 vs. 어려운)의 피험자간 요인설계를 사용하여 각 조건에서 참가자들이 윈도우 무비메이커를 사용하여 파일을 조작하는 방법을 학습하는 실험을 실시하였다. 그 결과 학습계획에 따른 수행의 차이는 발견할 수 없었으나, 언어적 학습보다 경험적 학습 에서 참가자들은 더 빠르게 평가과제를 완료하였다. 특히 과제난이도가 높아질 경우 참가들은 언어적 조건에서 경험적 조건보다 두드러진 수행저하를 보였는데, 이는 과제가 어려워질수록 경험적 학습이 효과적인 학습방법이라는 것을 시사한다. 즉 소프트웨어 학습에서 간단한 조작의 경우에는 매뉴얼 혹은 지시문의 형태로 구성된 언 어적 학습으로 충분하지만 어려운 과제의 경우에는 체험 프로그램이나 투토리얼 모드를 통해 학습하는 것이 효 과적일 것이다. 추가실험에서 난이도 증가에 따른 언어적 학습의 선형적 이득을 확인하기 위해 난이도를 3단계 로 세분화하여 검증하였으며 (실험 2) 학습계획의 효과를 확인하기 위해 학습시행간 간격을 증가시켰으나 (실험 3) 유의미한 결과를 발견하지는 못했다.

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.