Internet-Based Distance Learning

This case teaches project management concepts (traditionally called PERT / CPM) using the more accurate and modern approach via simulation. The case asks students to construct the network precedence diagram to help a fictitious school design an MBA over the Internet program. Using a spreadsheet model and simulation ad-in program (such as @RISK or Insight), the simulation tells management what the critical activities are and whether or not the project can be completed by a certain date. Probabilistic calculations can be made from the simulation. Finally, the case shows how the simulation gives superior results compared to the traditional approaches of PERT / CPM

Planning and scheduling software programs with PERT

The use of the Program Evaluation and Review Technique (PERT) in planning and scheduling software programs was discussed in this thesis. A real world program, referred to as the Wrap-Around Simulation or WAS Project, was selected to illustrate that complex efforts in the software domain can respond favorably to modern planning and scheduling techniques The WAS Project included the provision of a digital simulation of the shipboard environment in which a Digital Fire Control Computer (DFCC) would operate as part of a Digital Fire Control System. The digital simulation afforded a well controlled and conclusive checkout of the operational program contained in the DFCC and as such precluded the necessity of installing the DFCC aboard ship to evaluate its performance. Basic PERT theory was presented and the mechanics of network generation were developed. The WAS Project was Planned and scheduled in detailed step-by-step fashion as dictated by the philosophy and techniques discussed The analysis indicated that PERT can be an effective if not necessary tool for the manager of software as well as hardware projects. It was recommended that the greatest emphasis be placed on the activity time estimate. The accuracy of the entire PERT approach is completely dependent on the validity of the time estimates. If time and funding permit, an analysis of variance of activity durations was strongly recommended to determine the feasibility of possible alternate plans

Pert using Fuzzy variables and probability distribution function randomly selected

Program Evaluation and Review Technique (PERT) is widely used for project management in real world applications. The aim of this paper is to simulate and analyze a PERT network under conditions of uncertainty though a hybrid model. The basic assumption is that a project under extreme conditions of uncertainty can be satisfactorily modelled by using simple fuzzy linguistic variables to estimate activities durations, and a probability distribution function randomly selected in order to measure the activity times. Fuzzy linguistic expressions are used to estimate the activity time. Activity parameters are calculated by using basic operations between triangular fuzzy numbers and centroid method with classical Beta PERT definition. For each activity time a probability distribution function is randomly selected from a set of four possible distributions commonly cited in the literature. Hypothetical projects with 4, 40, 400 and 4000 activities using the proposed model are analyzed; the project duration is estimated through Monte Carlo Simulation. Finally, results are analyzed and compared with classical Beta PERT technique

Probabilistic Scheduling Based On Hybrid Bayesian Network–Program Evaluation Review Technique,

Project scheduling based on probabilistic methods commonly uses the Program Evaluation Review Technique (PERT). However, practitioners do not widely utilize PERT-based scheduling due to the difficulty in obtaining historical data for similar projects. PERT has several drawbacks, such as the inability to update activity dura- tions in real time. In reality, changes in project conditions related to resources have a highly dynamic nature. The availability of materials, fluctuating labor productiv- ity, and equipment significantly determine the project completion time. This research aims to propose a probabilistic scheduling model based on the Hybrid Bayesian Network-PERT. This model combines PERT with Bayesian Network (BN). BN is used to accommodate real-time changes in resource conditions. The modeling of BN diagrams and variables is obtained through an in-depth literature review, direct field observations, and distributing questionnaires to experts in project scheduling. The model is validated by applying the proposed model to a 60 m concrete bridge construction project in Indonesia. The simulation results of the proposed model are then compared with the case study project to assess the model’s accuracy. The result of the study shows that the proposed hybrid Bayesian-PERT model is accurate and can eliminate the weaknesses of the PERT method. Besides being able to provide an accurate prediction of project completion time (93.4%), this model can also be updated in real-time according to the actual condition of the projec

APPLYING PERT AND CRITICAL PATH METHOD IN HUMAN RESOURCE TRAINING

The subject of the article is referring to the modelling and simulating of the formation of human resources by applying the PERT/CPM (Program Evaluation and Review Technique/Critical Path Method) and the taking into consideration of some risks associated to this activity. The aim of the article is to offer practical support to the management of organizations in order to make a formation program of human resources, which implies activities of precedence and interrelated, critical paths, the distribution of time resources and necessary costs for the fulfilment of the organizational objectives.PERT chart, critical path, risk, human resources, modelling, simulation.

Closed-loop well construction optimization (CLWCO) using stochastic approach under time uncertainty

There is a digital step change taking place in well construction today. More and better data will become available for a vast number of analyses. The well construction process is complicated and includes several hundred parameters. There are many inhouse drilling analytics tools used by service and consulting companies. The objective of this paper is to aim at a complete time optimization and to improve health, safety and the environment (HSE) in a time-effective way. In this paper we establish and apply a full approach methodology for closed Loop well construction optimization (CLWCO) under time uncertainty. CLWCO involves six major steps: data gathering,a work-breakdown structure (WBS) in drilling scenarios, time estimation (budget time &technical time),time simulation (MCS&PERT), scenario analysis & optimization and finally updating time model. CLWCO involves three major concepts: optimizing the time plan based on current time knowledge, drilling new wells and collecting time data, finally updating multiple time models based on all of the available data. In the CLWCO step, work breakdown structure (W.B.S), time and controls for new wells are optimized by Monte-Carlo Simulation and program evaluation review technique (PERT). This paper goals are to identify and in best case quantify “the value of Monte Carlo simulation and Program Evaluation Review Technique (PERT) in batch & conventional time drilling optimization” in offshore wells for clients or operating company. Batch drilling does not combine professionally with modern techniques yet.we fill this gap by using modern techniques to optimize and enhance drilling work. We evaluate and analysis above-mentioned approach for batch drilling which has become increasingly prevalent in the petroleum industry as large and small investors alike seek to increase their profit margin. The insight of many of these oil and gas companies was to drill and complete wells using new techniques with the desire of considerable reduction in drilling time and cost for the field. when similar hole sections such as 32″,24″,16″,12 ¼″ and 8 ½″ of different wells were drilled one after the other efficiency and profits would be greatly increased. According to obtained results in closed loop well construction optimization (CLWCO), these methods are successful as it needs less time and cost to drill a lot of wells using the same platform. we simulated a drilling program for the case study of SP field by Monte-Carlo Simulation and program evaluation review technique (PERT),at the end we propose the optimum probable time to do future drilling program in SP field. The time versus depth graph of drilling project show that the improved drilling efficiency for drilling project designed as 11 wells would reduce the total drilling time around 15% in compare of previous drilling projects in phase SP6,SP7 and SP8,totally average drilling time have been improved between 2.5 and 8 days in MCS and PERT simulation technique for each well by using CLWCO.We presented the optimal plan coupling with batch drilling could be implemented in the future phases of SP field, which has resulted in decreasing drilling time to 30 days by using casing-drilling and liner-drilling technology.acceptedVersio

The Use of Refined Descriptive Sampling and Applications in Parallel Monte Carlo Simulation

Refined descriptive sampling is designed to improve upon the descriptive sampling method for experimentation in simulation. The former reduces significantly the risk of sampling bias generated by descriptive sampling and eliminates its problem related to the sample size. In this paper, we propose an optimal parallel Monte Carlo simulation algorithm using refined descriptive sampling and evaluate in parallel architecture, performance measures of a stable M/M/1 queueing system, a Pert network and the Newsboy problem

Varying the Explanatory Span: Scientific Explanation for Computer Simulations

This article aims to develop a new account of scientific explanation for computer simulations. To this end, two questions are answered: what is the explanatory relation for computer simulations? And what kind of epistemic gain should be expected? For several reasons tailored to the benefits and needs of computer simulations, these questions are better answered within the unificationist model of scientific explanation. Unlike previous efforts in the literature, I submit that the explanatory relation is between the simulation model and the results of the simulation. I also argue that our epistemic gain goes beyond the unificationist account, encompassing a practical dimension as well