Project Completion Time Research Articles

Analisis Anggaran Biaya dan Waktu Optimal dengan Metode Least Cost Sheduling

Cost Scheduling aims to shorten project completion time and look for optimal project schedules using direct, indirect and minimal total costs. This research was conducted on the rehabilitation project of the Lawe alas sub-district office in the Southeast Aceh sub-district. Least. This research was conducted to determine the suitability of physical work in the field with the planning schedule, to find out the optimum amount of time in the project and to know the comparison between the normal costs and costs after the project has accelerated. The calculation results show the normal project implementation time is 182 days with a normal charge of Rp. 160.151.592,33 by adding 1 hour additional working hours hence can speed up time as much as 12 days with additional cost equal to Rp. 2,564,736.09. By adding 2 hours additional hours working hours can accelerate as much as 23 days with an additional cost of Rp. 33.460.241,48. By adding 3 hours additional hours working hours can accelerate as much as 33 days with an additional charge of Rp. 64.355.746,88. By adding 4 hours additional hours working hours can accelerate as much as 42 days with an additional charge of Rp. 95.251.252,27..

OPTIMALISASI WAKTU DAN BIAYA PROYEK DENGAN METODE CPM DAN PERT DI PROYEK ABC CONDOTEL

Abstract Planning until controlling process during construction work are important activity of a project. Success or failing of the project caused by not maximal planning and insufficiently effective controlling, so that the project activity is inefficient. As the consequences of these impacts suffered project delay, decreasing of quality, and increasing performing cost. Project management working time drew the line by given schedule, so the manager of project shall get to anticipate condition changing. CPM and PERT methods can be used to manage the time of project completion more efficiently and effectively. To be able to reduce the impact of delays and swelling of project costs, a crashing process can be proposed with additional working hours. Duration acceleration is carried out on the work that is on the critical path because the work on the critical path does not have a delay time. With the addition of working hours besides being able to shorten the completion time, it also results in additional operational costs. Keywords : Project management, CPM and PERT method.

Application of Optimization to Select Contractors to Develop Strategies and Policies for the Development of Transport Infrastructure

Many factors influence the efficiency and quality of transport works. In particular, consultants and construction contractors of these works play important roles, and critical factors directly affect the quality of traffic works. If the quality of consultancy and construction is good, the project will reduce the total investment; if the contractor is good, the completion time of the new project is guaranteed, thus reducing construction costs. The longer the construction time is, the higher the cost of the project. In this study, the authors used optimal algorithms to evaluate past, present, and future contractors’ technical, technological, and performance effectiveness. Research results show that bidders are divided into three groups: highly effective bidders, stable contractors, and inefficient groups. Research results for this subject will help the government, regulatory agencies, and investors select good contractors as the basis for developing strategies and policies for the development of transport infrastructure.

Schedule Risk Analysis using a Proposed Modified Variance and Mean of the Original Program Evaluation and Review Technique Model

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.

Evaluation of mean and variance approximations in three point estimation of task completion times using the beta and the Kumaraswamy distribution

Estimation of task and project completion times within IT projects remains one of the most error-prone, but also most critical duties of an IT project manager. Various three-point methods of PERT have been evaluated by assuming that the true distribution is a beta-distribution. We evaluate PERT methods by comparing additionally with the Kumaraswamy distribution, which has an equal claim to be the true a-priori distribution for project completion times. We use skew and kurtosis in order to define test sets instead of simply choosing a range of shape parameters. We validate various approximations proposed in the literature and show that valid approximations are possible.

Evaluation of mean and variance approximations in three point estimation of task completion times using the beta and the Kumaraswamy distribution

Estimation of task and project completion times within IT projects remains one of the most error-prone, but also most critical duties of an IT project manager. Various three-point methods of PERT have been evaluated by assuming that the true distribution is a beta-distribution. We evaluate PERT methods by comparing additionally with the Kumaraswamy distribution, which has an equal claim to be the true a-priori distribution for project completion times. We use skew and kurtosis in order to define test sets instead of simply choosing a range of shape parameters. We validate various approximations proposed in the literature and show that valid approximations are possible.

Multi-skill project scheduling problem under time-of-use electricity tariffs and shift differential payments

In real-world environments, project activities may be performed using multi-skill resources. When both manpower and equipment are needed to perform project activities, wage and energy costs may form the main components of total project cost. Most energy-consuming activities do not need to be performed at specific times, and regarding time-of-use electricity tariffs may be performed during off-peak hours to reduce both energy cost and power peak demand. Performing such activities in off-peak hours obliges employers to pay shift differentials which increases the wage cost. Since energy and wage costs move in opposite directions, a model that optimally schedules activities, such that the total cost (sum of energy and wage costs) is minimized is of particular importance from the demand side viewpoint. The present paper presents a bi-objective optimization model for the multi-skill project scheduling problem considering shift differential payments and time-of-use electricity tariffs, aiming to minimize project total cost and completion time. The proposed model is solved using multi-objective decision making techniques. Results show that taking into account both time-of-use electricity tariffs and regular/overtime payments not only reduces energy cost and total project cost, but also reduces the power peak demand, thereby benefiting power distribution networks as well.

Computing project makespan distributions: Markovian PERT networks revisited

This paper analyses the project completion time distribution in a Markovian PERT network. Several techniques to obtain exact or numerical expressions for the project completion time distribution are evaluated, with the underlying assumption that the activity durations are exponentially distributed random variables. We show that some of the methods advocated in the project scheduling literature are unable to solve standard datasets from the literature. We propose a framework to analyse the applicability, accuracy and sensitivity of different methods to compute project makespan distributions. An alternative data generation process is proposed to benchmark the different methods and the influence of project dataset parameters on the obtained results is extensively assessed.

Personal Extreme Programming with MoSCoW Prioritization for Developing Library Information System

Software development projects require experience and knowledge of the developer or clients related to the system which will be developed. Unclear clients' needs potentially emerge many changes of needs during the process of development which can not be resolved by using conventional software development methodology. The implementation on the less significant requirements either from the clients or the system cause the development of the project took a long time. In this paper, we combine personal extreme programming (PXP) methodology with Moscow technique to overcome those problems. PXP is suitable to use in small to medium-sized projects if the clients do not know in detail about the needs in the development of application, application needed in relatively quick time, and the development phase is adjusted to use by a single programmer. Moscow technique was used for prioritizing requirements elicited in PXP methodology. Moscow is a method to determine priority needs based on cost, risk, and business value. This technique was applied during the planning phase of PXP to develop library application, thereby it reduced the time of project completion. The result was a library application suited the needs of clients to support business processes at Batu State Attorney's library.

Multiple Modular Building Construction Project Scheduling Using Genetic Algorithms

Modular construction offers several advantages, such as safe working conditions, fast construction, and high-quality end products. The project scheduling of modular construction should consider the time involved in the factory production, transportation, and erection processes of the units given limited resources (e.g., the number of modular units, available transportation, and workers) and project restrictions (e.g., the sequences of manufacturing production and on-site installation). However, current modular construction project scheduling techniques and previous academic approaches cannot deal with the overall project processes and production/on-site installation sequences simultaneously. This is one reason few mass-production multiple projects exist in the manufacturing industry. Moreover, it can lead to inappropriate project management guidelines and fail to minimize the overall project duration. This paper suggests a model for modular construction projects scheduling using a genetic algorithm. The results show that implementing both overall project processes and project requirements is an efficient way to develop a modular construction project schedule. The proposed optimization tool will help project managers allocate resources efficiently and reduce the completion time of multiple projects.

Modification of the PERT method for project time evaluation taking into account unexpected delays

The PERT-based method for estimation of project implementation time, which uses Rayleigh distribution instead of β-distribution, was proposed. The modification of the PERT, which made it possible to involve the quality of an expert into the assessment and to simplify the examination procedure was proposed. We offered a new method for project evaluation, based on the properties of Rayleigh distribution and taking into consideration the peculiarities of plotting a network diagram in IT- projects with a high degree of work detailing in the face of the existing possibilities of extending the time of particular tasks. Three different methods project time evaluation, based on two different statistics and two different methods for calculation of project time, were compared. Comparison was performed with the view to search for the simplest method in terms of information acquisition and suitable for algorithmic implementation. It was shown that the estimation result is more consistent with specificity of complex IT-projects and makes it possible to reduce the number of iterations within project implementation time, as well as to use an objective assessment of the main sources of errors in determining time, giving evaluation with the probability that was assigned beforehand. It was shown that the estimate of the most probable and minimum time of project completion during the calculation by the new method is consistent with the results of the calculations using the PERT method, while the evaluation of maximum time differs strongly, as the new method is more pessimistic in this sense, and it matches better the characteristics of complex IT-projects that have a high probability of unexpected delays during implementation. We draw conclusions on the possible application of results in creation of a project time evaluation system based on the methods of artificial intelligence, and determined parameters for setting such a system.

Examining critical and near-critical paths: an Excel-based classroom exercise

The author’s goals in this exercise were to use an Excel project to teach students about the effects of changing states of nature on critical path emergence as well as compare the impact of the PERT beta and triangular distributions on project completion times. Previous research into the PERT (program evaluation and review technique) beta distribution indicated a tendency for this distribution to overstate the impact of the dominant critical path on project completion times. The author used a Monte Carlo simulation and a new Excel function to explore the effects of random variation on critical path emergence. He used both the triangular distribution and the PERT beta distribution to calculate project completion times. The author found that three of the possible five paths became critical in both the PERT beta and triangular distributions. However, the triangular distribution moderated the PERT beta distribution’s tendency toward the dominate critical path.

PENERAPAN NETWORK PLANNING PADA PROYEK PEMBANGUNAN PERUMAHAN MUTIARA RESIDENCE DI DESA PENGAMBENGAN KABUPATEN JEMBRANA

ABSTRACT
 The increasing number of construction companies in Indonesia poses a challenge for companies to improve the effectiveness and efficiency of resource management in order to excel among competitors. The purpose of this study is to determine whether the implementation of Network Planning can improve efficiency and effectiveness in the allocation of time and cost on the construction project. The research method is a case study to address the problem at Putra Dewata PT Karya Tama concerning network planning of Mutiara Residence Housing project. Data analysis technique used is Critical Path Method. The results show that the project completion time is 142.5 days, 14.5 days faster than the calculation result by the company with Gantt Chart method. This will provide benefits in terms of cost of completion of the project, where cost efficiencies that can be gained is Rp. 20,807,500.
 
 Keywords: network planning, critical path method, critical path.

New Approach to the Distribution of Project Completion Time in PERT Networks

AbstractNormal distribution has been commonly accepted as the probability function for whole project duration estimation. Nevertheless, this assumption does not hold in complex projects with many a...

Stochastic Multi-variate Performance Trade-off Method for Technical Tender Evaluation

This paper presents a computational method called Stochastic Multi-variate Performance Trade-off (SMPT), which identifies optimal sets of construction methods for activities, hence appropriately trading-off the project completion time, cost, environmental impact, and quality. SMPT computes exact solution(s), near-optimal solution(s), and stochastic optimal solution(s) using an enumerative analysis, genetic algorithm, and simulation, respectively. This study is of value to project planners because SMPT identifies the sets of construction methods that satisfy user-defined constraints relative to specific performance indicators. SMPT is also of relevance to researchers because it facilitates experiments using different performance indicators, either jointly or independently. Three test cases verify the validity of the computational methods.

A Project Management Model for Investigation of a Construction Project

Various projects are realized by private sector and public institutions in recent days. Machine, material, manpower, time and money are the main resources required for these projects. Since, each one is a cost item, these sources should be used effectively in order to provide competitive advantage in the project planning process. In this context, an efficient project management system provides effective usage of resources, good working environment and timely completion of projects. Critical Path Method (CPM) and Program Evaluation and Review Technique (PERT) are utilized as project planning methods in order to determine the completion time of projects. On the other hand, it can be possible to complete a project earlier using additional sources with project crashing approach. In this study, initially activities and durations for a construction project realized in Kocaeli have been determined. Afterwards, expected completion time, critical activities and critical path have been determined for this project. In the second phase, project crashing cost for critical activities has been calculated through a mathematical model. Thus, the applicability of the project management model has been revealed.

ОСНОВНЫЕ ТЕНДЕНЦИИ ИСПОЛЬЗОВАНИЯ ИНСТРУМЕНТОВ ПРОЕКТНОГО МЕНЕДЖМЕНТА В МИРОВОМ ГОСТИНИЧНОМ БИЗНЕСЕ


 
 
 In this article practical aspects of using project management in popular restaurants of different countries are considered. Within the framework of this study, the experience of using the Hard Rock Cafe project management tools is highlighted. It is noted that the management of the project in Hard Rock Cafe includes three phases: planning, setting goals, defining the project and organizing the team; drawing up of a calendar schedule of works; control. Considered the project of opening a new restaurant from Pizza Duono (Italy). It stands out that in this restaurant project managers are in sight, they are responsible for: all necessary activities have been completed in the right sequence and on time; the project did not go beyond the budget; the project would meet the quality standards, etc. The study also examined an example of project caching to change the project completion time from the restaurant Pizza Duono (Italy, Rome). According to the methodology of this restaurant, on each of the critical paths the restaurant must identify one type of activity that can be subjected to crashing.
 
 

A quantitative risk assessment methodology for construction project

It is observed that most of the infrastructure projects fail to meet their cost and time constraints, which will lead to a low return on investment. The paper highlights that the present risk management tools and techniques do not provide an adequate basis for response selection in managing critical risks specific to infrastructure projects. This paper proposes a risk quantification methodology and demonstrates its application for an industrial construction project. A case study is used to present an application of the proposed risk management methodology to help organisations efficiently choose risk response strategy and allocate limited resources. The research adopts an integrated approach to prioritize risks using Group Technique for Order Preference by Similarity to Ideal Solution (GTOPSIS) and to quantify risks in terms of overall project delays using Judgemental Risk Analysis Process (JRAP), and Monte Carlo Simulation (MCS). A comparison between the results of qualitative risk analysis using GTOPSIS and quantitative risk analysis i.e., JRAP and MCS is presented. It is found that JRAP along with MCS could provide some powerful results which could help the management control project risks. The crux of this paper is that the risks are highly dependent on project schedule and the proposed methodology could give a better risk priority list because it considers slackness associated with the project activities. The analysis can help improve the understanding of implications of specific risk factors on project completion time and cost, while it attempts to quantify risks. In turn, this enables the project manager to devise a suitable strategy for risk response and mitigation.

Automation of feature engineering for IoT analytics

This paper presents an approach for automation of interpretable feature selection for Internet Of Things Analytics (IoTA) using machine learning (ML) techniques. Authors have conducted a survey over different people involved in different IoTA based application development tasks. The survey reveals that feature selection is the most time consuming and niche skill demanding part of the entire workflow. This paper shows how feature selection is successfully automated without sacrificing the decision making accuracy and thereby reducing the project completion time and cost of hiring expensive resources. Several pattern recognition principles and state of art (SoA) ML techniques are followed to design the overall approach for the proposed automation. Three data sets are considered to establish the proof-of-concept. Experimental results show that the proposed automation is able to reduce the time for feature selection to 2 days instead of 4 -- 6 months which would have been required in absence of the automation. This reduction in time is achieved without any sacrifice in the accuracy of the decision making process. Proposed method is also compared against Multi Layer Perceptron (MLP) model as most of the state of the art works on IoTA uses MLP based Deep Learning. Moreover the feature selection method is compared against SoA feature reduction technique namely Principal Component Analysis (PCA) and its variants. The results obtained show that the proposed method is effective.

Project Scheduling with Simultaneous Optimization, Time, Net Present Value, and Project Flexibility for Multimode Activities with Constrained Renewable Resources

Project success is assessed based on various criteria, every one of which enjoys a different level of importance for the beneficiaries and decision makers. Time and cost are the most important objectives and criteria for the project success. On the other hand, reducing the risk of finishing activities until the predetermined deadlines should be taken into account. Having formulated the problem as a multi-objective planning problem, the present study aims at minimizing the project completion time as well as maximizing the net present value and project flexibility by taking into account the resource constraints and precedence relations. Here the flexibility of project is calculated by considering a free float for each activity and maximizing the sum of these flotation times. Although most of the researches considered the resources as non-renewable resources, here the resources are considered as renewable ones. Moreover, performing each activity may be possible in various states of using resources (mode) which can change the project completion time and cost. Owing to the complexity of the problem, the Multi Objective Simulated Annealing Meta-heuristic Algorithm is used to solve the proposed model. In doing so, first a feasible answers is proposed and then, using the aforementioned algorithm, it was attempted to find Pareto answers. For accrediting the algorithm, four benchmark problems have been considered. Since the algorithm performed well in finding the optimal answers to the benchmark problems, it was used to find the optimal answer of large scale problems.