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- 저자 : Solomon Sackey (검색결과 6 건)
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Solomon Sackey,김병수 대한토목학회 2018 KSCE JOURNAL OF CIVIL ENGINEERING Vol.22 No.11
The human knowledge of a specific domain is dissipated either in books and journals or exists in the minds of few human experts. Expert system technology, which is of late becoming an important tool, uses the power of the human brain to store knowledge electronically so that information regarding decision-making can easily be accessed at anywhere and at any time. More often than not most decisions in the industry are based on just subjective decisions. But since each project is different from the other, there is the need to integrate heuristic approach in other to arrive at better decisions. Therefore the system, ESCONPROCS (Expert system for construction procurement selection) which is an expert system tool was developed based on extensive literature review of the available procurement systems as well as clients’ priorities and other external factors that influence the selection of an appropriate procurement system. An expert survey was conducted and their responses were used to provide a recommendation for the rules. The system, ESCONPROCS is developed to assist decision-maker (client) reaches a more informed decision on procurement system selection and contracting.
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Solomon Sackey,김병수 대한토목학회 2019 KSCE JOURNAL OF CIVIL ENGINEERING Vol.23 No.4
The Program Evaluation and Review Technique (PERT) model uses parameters such as the specified project completion time, mean, and variance to estimate the probability of project completion time. However, this model uses a weighted average and unweighted value in the variance, which is based on six sigma of the mean. Despite many proposed modifications to improve the traditional PERT model, the hidden error in the calculation of the variance and mean of the PERT approach has not been adequately addressed. This error leads to underestimation of the schedule risk. Considering the impact of variance and mean on the probability of project completion times, this study contributes to the improvement of the accuracy of schedule risk estimation by proposing a modified variance and mean of the original PERT model. The original PERT model was first used to estimate the project completion time. However, using the proposed modified model to estimate the completion time, a 95% confidence interval assumption and the corresponding distribution within ±2 standard deviation of the mean and standard or Z values were employed to model the new mean and variance equations. To prove the validity of the proposed modified variance and mean assumptions, we performed a schedule risk analysis through simulation using Oracle Crystal Ball for comparison. The results showed that the proposed PERT model had a better mean error rate of 2.46% as compared to 3.31% of the original PERT model.
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Duration Estimate at Completion: Improving Earned Value Management Forecasting Accuracy
Solomon Sackey,이동은,김병수 대한토목학회 2020 KSCE JOURNAL OF CIVIL ENGINEERING Vol.24 No.3
Earned Value Management (EVM) has been established as a project management technique for project monitoring and control. The traditional EVM performs well in forecasting Cost Performance index and other cost metrics. However, in terms of schedule performance, the accuracy of the forecasted schedule metrics through the traditional EVM approach are always questionable. The schedule performance is not measured in time unit but rather in monetary units or uses cost information, which may cause misleading in the interpretation of the EVM schedule metrics. The schedule performance is not accurately forecasted, resulting in underestimating the estimate at completion (t). Even the renowned Earned Schedule also uses cost as a proxy to determine the earned schedule. This paper presents a new EVM tool, Duration estimate at completion (DEAC-model) developed to accurately forecast the time estimate at completion. DEAC-model uses the actual time spent on each activity, either in progress or upon completion, where the Performance is measured in time units. The benefits of DEAC-model to project management team and researchers are that it can be used: 1) to forecast schedule metrics accurately so that resources can be effectively allocated to complete the remaining activities, 2) as a gauge to assess if the project can be completed within the plan schedule, and 3) to apply time series and simple linear regression model concepts using excel worksheet syntax to forecast duration estimate at completion that is easily applicable.
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Solomon Sackey,김병수(Amugae Kim) 한국구매조달학회 2017 한국구매조달학회지 Vol.16 No.1
대규모 건설프로젝트는 방대한 양의 재정적 투자, 긴 프로젝트 기간, 많은 프로젝트 참여자, 넓은 건설규모, 고도로 복잡한 기술 등 다양한 미래를 가진 복잡한 방식 및 절차에 의해 적용된다. 건설업계의 성과에 대한 주요 개선영역 중 하나는 적절한 조달방법을 사용하는 것이다. 조달시스템 선택은 불확실성과 애매모호함으로 인해 어려움을 겪는다. 특정 프로젝트에 대한 조달방식은 선택하려는 대부분의 고객의 결정은 대개 개이적인 직감과 과거경험을 기반으로 한다. 그러나 이러한 접근방식은 각 프로젝트마다 고유한 특성이 있다는 점에서 성공적이지는 못하다. 본 연구에서 제시하는 건설조달방법 선정모형은 실존적 지식으로 인해 조달시스템 선별프로세스의 요구사항을 충족시키는 대표적인 기술이라 할 수 있다. 이 모형은 의사결정자가 조달시스템 선택 및 계약에 대한 정보에 입각한 결정에 도달 할 수 있도록 돕기 위한 것이다. Large-scale construction projects are applied by complex methods and procedures with various futures, including vast amounts of financial investment, long project duration, large project participants, large building scale, and highly sophisticated technologies. One of the major areas of improvement in the performance of the construction industry is the use of appropriate procurement methods. Procurement system seletion suffers from uncertainty and ambiguity. Most customer decisions to choose a procurement method for a particular project are usually based on personal intuition and past experience. However, this approach is not successful because it has unique chracteristics for each project. The construction procurement method selection model proposed in this study is a reperesentative technology that meets the requirements of procurement system seletion process due to existential knowledge. This model is to help decision makers reach decision-making based on information on procurement system selection and contracting.
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