Repetitive Projects Research Articles

Construction flow index: a metric of production flow quality in construction

A new, process-oriented approach is needed in construction management. Lean construction emphasizes the concept of flow as a way to understand production in construction, yet there is still no accepted metric for measurement of flow quality. This has hampered research and practice. The proposed construction flow index (CFI) is a composite measure that reflects the quality of production flow in repetitive construction projects. It incorporates measures of work continuity for crews, processing continuity for locations, production rate variation, amounts of work in progress, interference and operation sequence logic. Expert knowledge was acquired to establish weights for the CFI parameters, and its use was tested in evaluating the planned and actual production flows for a number of projects. Project managers can use the CFI to evaluate the quality of their construction plans and to measure and communicate production flow quality status to trade crews, enabling management and improvement of production flow. The CFI is also a valuable tool for construction research. The CFI challenges traditional construction management by measuring flow, where standard practice only measures transformation (earned value). It challenges lean construction practice using the Last Planner System, suggesting that the percent plan complete measure of plan reliability is insufficient.

Resource Leveling Based on Backward Controlling Activity in Line of Balance

The line of balance method that provides continuous and uninterrupted use of resources is one of the best methods for repetitive project resource management. This paper develops a resource leveling algorithm based on the backward controlling activity in line of balance. The backward controlling activity is a kind of special activity, and if its duration is prolonged the project duration could be reduced. It brings two advantages to the resource leveling: both the resource allocated on the backward activity and the project duration are reduced. A resource leveling algorithm is presented which permits the number of crews of the backward controlling activity to be reduced until the terminal situation is reached, where the backward controlling activity does not exist or the number of crews cannot be reduced. That adjustment enables the productivity of all activities to be consistent. An illustrative pipeline project demonstrates the improvement in resource leveling. And this study designed a MATLAB program to execute the design algorithm. The proposed model could help practitioners to achieve the goals of both resource leveling and project duration reduction without increasing any resource.

Optimized scheduling and buffering of repetitive construction projects under uncertainty

Purpose Construction projects are complex projects taking place in dynamic environments, which necessitates accounting for different uncertainties during the planning stage. There is a significant lack of management tools for repetitive projects accounting for uncertainties in the construction environment. The purpose of this paper is to present an algorithm for the optimized scheduling of repetitive construction projects under uncertainty. Design/methodology/approach Fuzzy set theory is utilized to model uncertainties associated with various input parameters. The developed algorithm has two main components: optimization component and buffering component. The optimization component presents a dynamic programming approach that processes fuzzy numbers. The buffering component converts the optimized fuzzy schedule into a deterministic schedule and inserts time buffers to protect the schedule against anticipated delays. Agreement Index (AI) is used to capture the user’s desired level of confidence in the produced schedule while sizing buffers. The algorithm is capable of optimizing for cost or time objectives. An example project drawn from literature is analysed to demonstrate the capabilities of the developed algorithm and to allow comparison of results to those previously generated. Findings Testing the algorithm revealed several findings. Fuzzy numbers can be utilized to capture uncertainty in various inputs without the need for historical data. The modified algorithm is capable of optimizing schedules, for different objectives, under uncertainty. Finally AI can be used to capture users’ desired confidence in the final schedule. Originality/value Project planners can utilize this algorithm to optimize repetitive projects schedules, while modelling uncertainty in different input parameters, without the need for relevant historical data.

Mixed-Integer Linear Programming Approach for Scheduling Repetitive Projects with Time-Cost Trade-Off Consideration

AbstractThis paper studies a repetitive project scheduling problem considering multiple crews and fixed logic with the objective to minimize the total cost without exceeding a given deadline. Multi...

Accelerating repetitive construction projects: with uncertainty and contractors’ judgment

Project acceleration is a common yet complicated task performed by contractors in construction projects. In repetitive projects, contractors often face having to accelerate their projects using too...

TASK-TECHNOLOGY FIT IN THE ADOPTION OF LINEAR SCHEDULING METHOD

Although the general consensus is that linear scheduling methods (LSMs) are quite powerful, their use in construction has been very limited. The linkage between the characteristics of scheduling methods and the requirements of the tasks performed by schedulers has been an on-going concern in the construction industry. This study proposes a “task-technology fit” model to understand why LSMs are not being used as extensively as expected. The model aims to determine whether the characteristics of LSM (technology) satisfy the duties and obligations of construction schedulers (tasks). By scrutinizing the task-technology fit in LSM applications, deficiencies can be detected which hinder the wider use of these methods in the industry. A questionnaire survey was administered to measure task-technology fit in LSM applications. The target population included schedulers, project managers, construction managers, and other professionals listed in the directory of the Construction Management Association of America (CMAA). The findings indicate that LSM is effective in repetitive projects and is able to provide a smooth and efficient flow of resources by adjusting activities’ rate of production. In addition, research findings point out that LSM effectively shows activity sequences as well as progress. However, the findings also reveal that LSM is not applicable when reliable resource data are not available. It should also be noted that very few software packages that perform LSM scheduling are commercially available on the market.

Developing a Process Model for Optimizing Linear Process Plans Based on Three Types of Buffers and Brute-Force Algorithm

The network and the bar chart scheduling method have been widely used so far without distinguishing non-repetitive and repetitive construction projects. However, these scheduling methods have limitations when it comes to establishing effective process plans for construction projects in which construction crews with different levels of productivity carry out repetitive activities by shifting their locations in serial order. Thus, in construction projects with many repetitive processes, the linear scheduling method (LSM) would be more appropriate for establishing effective process plans because it visually expresses the crew productivity for each activity in a unit space. In the case of LSM, however, since the relationship between activities is not clear and its establishment also has limitations, the optimization on LSM in terms of the construction cost or time is a very limited and subjective matter, even for scheduling experts. Therefore, the objective of this research is to develop a process model based on Brute-Force Algorithm for optimizing linear process plans, in consideration of the correlation between the construction cost and time, by utilizing the three types of buffers. These buffers are developed to establish the relations between activities both quantitatively and logically by considering the characteristics of LSM.

Genetic Algorithm–Based Method for the Deadline Problem in Repetitive Construction Projects Considering Soft Logic

AbstractThe discrete time-cost trade-off problem (DTCTP) is a multiobjective problem usually encountered in practical projects. Current optimization methods for this problem in repetitive construction projects often assume that there is only one work sequence between units. In practice, however, the work sequence is not necessarily unchangeable. Scheduling with variable work sequences is known as the soft logic method. This study develops a mathematical model considering soft logic to address the DTCTP in repetitive construction projects. The objective is to select a set of activity modes, start times, and work sequences between units such that the total cost is minimized while meeting a given deadline. A targeted genetic algorithm is also presented, in which only the activity modes and work sequences between units are encoded, and suitable start times of all subactivities are then determined using a linear programming approach. Two example projects are analyzed, and their computation results support that...

Repetitive Scheduling Method: Requirements, Modeling, and Implementation

AbstractProjects with repeating activities, such as multistory buildings and highways, present unique scheduling challenges. This paper presents the necessary requirements that scheduling systems should address to meet the needs and complexities of repetitive projects in practice. The repetitive scheduling method (RSM) provides a unified scheduling framework that applies to all types of repetitive projects. In RSM, projects are classified as discrete (vertical) or continuous (horizontal or linear) and then as uniform and nonuniform, depending on whether progress is measured using a counting scale or a dominant-attribute scale. RSM modeling elements include three types of activities (line, block, and bar) and 10 types of relationships (links) between activities. RP2, a computer program developed by the authors to validate the proposed scheduling approach, is used to develop the production diagrams and tabular reports of the target schedule for a complex of four-story apartment buildings for a low-income ho...

Multi Objective Optimization for Scheduling Repetitive Projects Using GA

Projects that contain several identical or similar units are usually referred to as repetitive projects. Repetitive projects may be due to the uniform repetition of a set of activities throughout the project, or due to the physical layout of the project. Activities that repeat from one project unit to other project unit create a very important need for a project schedule that ensures the uninterrupted flow of crew from one unit to the next. This study will help to develop a method for scheduling repetitive projects with objectives of minimizing project duration, project cost and both of them with constraints of precedence relationships between activities, constraints of precedence relationships between units and constraints of the due date in which work should be complete.

Development for Sustainable Construction System Glass Fiber Reinforced Gypsum (GFRG) in Egypt Using Nanotechnology

One of the mile stones for the success of construction projects is the project management triangle (time, cost and quality). During the past decade, a lot of construction systems have been developed to this triangle. GFRG system was one of these systems (for example that was established in Australia), it fulfilled LEED certificate for construction materials. When it is compared with traditional systems in Egypt, Glass Fiber Reinforced Gypsum (GFRG) system superior to traditional systems in time, cost in case of repetitive projects and quality. The world awareness for sustainability have increased lately in different aspects, thermal comfort is one of the main sustainable aspects that influence users. This paper aims to study thermal comfort for GFRG system in Egypt and comparing with traditional systems, it also aims to study the nanotechnology to develop this construction material in order to increase thermal comfort performance.

A Study on Assessment of Non-conformances Using Multiple Domain Matrix: A Case Study from Metro Projects

Non-Conformance is defined as deviation in terms of quality during the construction execution. Whenever there is a deviation in quality, a non-conformance report (NCR) is issued. This non-conformance leads to rectification, repair or rework of an activity that ultimately result in time and/or cost overrun. Also, deviation in quality can have a direct or indirect impact on the successor activities and subsequently on the project performance. Every NCR has its origin with an activity and there exist dependencies among the activities and NCRs. The objective of the present study is to capture the dependencies among activities and NCRs using a structured approach that can be utilized to estimate the total project duration, which is inclusive of the delays due to nonconformances. To achieve this objective, a case study-based MDM (Multiple Domain Matrix) solution methodology has been proposed and the same has been demonstrated with the case study of a metro project. This NCR-activity mapping using MDM is effective in planning repetitive projects.

Incorporating Multiskilling and Learning in the Optimization of Crew Composition

AbstractThe presence of multiskilled workers in a crew can increase the crew’s productivity through reducing inefficiencies and supervision requirements, while also providing on-the-job learning opportunities for single-skilled workers. The effect of the presence of multiskilled workers on the learning rate of workers, which is also a function of skill level and experience, and thus on the crew’s productivity, is especially significant in repetitive construction projects. This paper presents a mathematical model for identifying the optimal combination of single-skilled and multiskilled workers with different levels of experience in the crew to minimize the duration of construction projects by accounting for the overlapping effects of multiskilling, skill level, and learning on the crew’s productivity. The model is applied to an illustrative case project to demonstrate the practicality of the model. The optimum crew compositions for different activities involved in the case project are identified using a s...

Application of Weibull Analysis to Evaluate and Forecast Schedule Performance in Repetitive Projects

AbstractConstruction managers regularly monitor projects to ensure that the project performance is under control. The earned value method (EVM) is a widely used tool to forecast project cost and time at completion. However, the effectiveness of the EVM in forecasting schedule performance has been questioned particularly because of its inability to address the associated uncertainties and poor performance in predicting project duration. The objective of this study is to present an activity-based model to conduct a probabilistic assessment and estimation of schedule performance in repetitive construction projects. This model, called the Weibull evaluation and forecasting model (WEFM), emphasizes the recurring nature of major activities in repetitive projects to evaluate and forecast schedule performance. WEFM estimates activity completion time and its upper and lower bounds of possibility and presents these estimates in the form of prediction graphs. Moreover, it provides reliability graphs that demonstrate...

Learning curve modelling of gas pipeline construction in Egypt

It is commonly accepted that production rates for repetitive tasks will improve with acquired experience and learning. Several mathematical models, or learning curves, have been proposed to investigate improvement in productivity as a function of the number of units produced. Deciding the best-fit learning curve model for construction activities is a managerial challenge. In this paper, the best-fit learning curve model for describing past performance of gas pipeline construction in Egypt is investigated. Data were collected from eight real-life projects, which are constructed in different types of land, under various weather conditions with different sizes, lengths, and pipe diameters. Only labour-intensive activities are considered in the present work. Cumulative average data is used to represent collected data in order to ensure curve smoothness as well as to avoid scattered data. The commercial Statistical Package for Social Science (SPSS) is used to determine Pearson's coefficient of correlation. The cubic model is found to be the best fitting curve to describe welding activities in gas pipeline construction activities in Egypt. This work helps both academics and practitioners in deciding the best-fit learning curve model(s) for gas pipeline construction. This will aid in making realistic estimates of the time and cost of repetitive projects.

Managing repetitive construction in a dynamically changing project environment: Conceptualizing the system–model–simulator nexus

Abstract This paper presents a methodology for modeling repetitive construction projects by introducing a modeling procedure based on the system–model–simulator nexus, with the aim of developing an intelligent tool to facilitate decision-making in the construction implementation phase. The study offers a conceptualization of the construction processes designed for the monolithic construction computer-aided system (MoCCAS) that enables a flexible approach to managing repetitive projects within a dynamically changing construction environment. The discussion deals with the art of modeling the construction process and introduces a repetitive construction process formulated as (1) a dynamic construction process model in a temporal perspective (DCPM-TP), which is a construction process representation in a three coordinate system; and (2) a managing assumed goals (mag_811) module, designed to simulate process behavior and to create execution strategies. Both models are capable of handling variability during the construction process execution and address the complexity of the relations among the production system components, including resource mutual constraints. A case study is discussed which involves the execution of construction processes by means of a slip formwork system, which exhibits a large degree of repetition and, therefore, is a particularly useful example for illustrating the effectiveness of the modeling approach proposed. The original contribution of this research lies in (i) representing construction process by acknowledging the specificity deriving from the nature of repetitive projects and technological regime; (ii) developing flexible structures (DCPM-TP and mag_811) that enable the construction process complexity to be addressed; (iii) designing a representation of the construction process within the system–model–simulator nexus developed for MoCCAS. A significant outcome of the overall study is the development of a system capable of harnessing the cyclic nature of the repetitive processes and converting the repetitiveness into a vital asset in the construction management.

A trade-off between time and cost in scheduling repetitive construction projects

The discrete time/cost trade-off problem (DTCTP) is commonly encountered in repetitive project scheduling. The current models for this problem assume that logical sequences of activities cannot be changed in different units. However, logical sequences are often changed to shorten the project time and minimize project total cost in many practical situations. This characteristic of repetitive activities is referred to as the soft logic. This paper presents a mixed integer nonlinear programming model that combines the general DTCTP and the concept of soft logic. The execution modes of an activity in different units are also considered. The DTCTP is known to be strongly NP-hard, and the introduction of soft logic makes it even more complex. A genetic algorithm (GA) is proposed to resolve the problem. The effectiveness of the proposed GA is verified using the example of a bridge construction project presented in the previous literature. The model proposed in this paper provides more flexibility to reduce the total cost and time of a repetitive project for the planners.

Application of Relationship Diagramming Method (RDM) for Resource-constrained Scheduling of Linear Construction Projects

The traditional techniques for project scheduling such as Arrow Diagramming Method (ADM) and Precedence Diagramming Method (PDM) are continuously undergoing improvisation in order to replicate real-time construction scenario. Quite often, these methods are criticized for their limited information capturing ability. Relationship Diagramming Method (RDM) proposed by Plotnick in the recent past, is an improved variant of PDM, which can store additional information on relationships that would improve the scheduling process. In addition to basic data on the activities, additional information can be represented through five codes in RDM. Sequencing of activities in a construction project is primarily driven by the construction logic and/or the availability of resources. There is scope for arriving at alternate sequences with varying availability of resources to achieve the objectives of project scheduling as long as the construction logic is preserved. In order to achieve such a resource-constrained project scheduling, additional information on the restraints of the activities are necessary, which can be modelled using RDM through one of the five codes of RDM. The objective of this paper is to explore and exploit the Reason/Why code of RDM. The Reason and Why codes are associated with a restraint and for recording the description respectively. An activity's dependence on a resource has been captured using Reason/Why code in this study. It has been attempted to understand the impact of varying resource availability using an empirical equation on sequencing such resource dependent activities and its effect on critical path. The proposed concept is tested with data from a repetitive high rise construction project. The preliminary results have been well received.

반복공구 작업조 동기화 시스템 개발

Repetitive project planning and scheduling method requires complementing the disadvantages of the critical path method (CPM) and the line of balance (LOB) method, which are confined in time-driven and graphical analysis, respectively. CPM is lack of capability to handle repetitive projects. LOB is also lack of analytical qualities of schedule information due to its' dependency on graphical technique. Existing studies attempt to combine CPM and LOB techniques in a system. However, they are mostly graphical methods. A new method integrating CPM and LOB techniques is presented so as to schedule repetitive projects using formula computing schedule information of each and every units of a project schedule. The proposed method perform basic LOB calculations to ensure resource employment continuity. Each and every activity durations at all units, floats and project completion time are computed using CPM method. Test cases are conducted to verify the potential of the proposed method.

A fast affine-invariant features for image stitching under large viewpoint changes

Image alignment and stitching is a popular application on many smart phones, but it is time consuming and creates a critical bottle neck in the course of implementation. In this paper, a fast and high-quality image stitching method is proposed. First, a series of simulated images is obtained by simulating the latitude and longitude angles of a raw image; second, FAST detector is used to detect the features of all the simulated images and described by Fast Retina Key-point (FREAK) before all the feature information is projected to the raw image; third, Hamming distance is used as a feature similarity metric and all the features are matched directly instead of using the repetitive projection in Affine-SIFT (ASIFT). RANSAC is then used to achieve the optimal affine-transformations, and lastly, a weighted average bending algorithm is used to smooth the intensities of the overlapping regions. The experimental results demonstrate that the proposed image stitching method greatly increases the speed of the image alignment process and produces a satisfactory result.