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The purpose of this paper is to present a new method for project tracking and control of integrated offsite and onsite activities in modular construction considering practical characteristics associated with this type of construction.

The design embraces building information modelling and integrates last planner system (LPS), linear scheduling method (LSM) and critical chain project management (CCPM) to develop tracking and control procedures for modular construction projects. The developed method accounts for constraints of resources continuity and uncertainties associated with activity duration. Features of proposed method are illustrated in a case example for tracking and control of modular projects.

Comparison between developed schedule and Monte Carlo simulation showed that baseline duration generated from simulation exceeds that produced by developed method by 12% and 10% for schedules with 50% and 90% confidence level, respectively. These percentages decrease based on interventions of members of project team in the LPS sessions. The case example results indicate that project is delayed 5% and experienced cost overrun of 2.5%.

Developed method integrated LPS, LSM and CCPM while using metrics for reliability assessment of linear schedules, namely, critical percent plan complete (PPC_cr) and buffer index (BI). PPC_cr and BI measure percentage of plan completion for critical activities and buffer consumption, respectively. The developed method provides a systematic procedure for forecasting look-ahead schedules using forecasting correction factor Δ_t and a newly developed tracking and control procedure that uses PPC_cr and BI. Quantitative cost analysis is also provided to forecast and monitor project costs to prove the robustness of proposed framework.

The purpose of this paper is cost optimization of project schedules under constrained resources and alternative production processes (APPs).

The model contains a cost objective function, generalized precedence relationship constraints, activity duration and start time constraints, lag/lead time constraints, execution mode (EM) constraints, project duration constraints, working time unit assignment constraints and resource constraints. The mixed-integer nonlinear programming (MINLP) superstructure of discrete solutions covers time–cost–resource options related to various EMs for project activities as well as variants for production process implementation.

The proposed model provides the exact optimal output data for project management, such as network diagrams, Gantt charts, histograms and S-curves. In contrast to classic scheduling approaches, here the optimal project structure is obtained as a model-endogenous decision. The project planner is thus enabled to achieve optimization of the production process simultaneously with resource-constrained scheduling of activities in discrete time units and at a minimum total cost.

A set of application examples are addressed on an actual construction project to display the advantages of proposed model.

The unique value this paper contributes to the body of knowledge reflects through the proposed MINLP model, which is capable of performing the exact cost optimization of production process (where presence and number of activities including their mutual relations are dealt as feasible alternatives, meaning not as fixed parameters) simultaneously with the associated resource-constrained project scheduling, whereby that is achieved within a uniform procedure.

The purpose of this paper is to suggest the application of the line‐of‐balance (LoB) scheduling technique in combination with a 4D CAD workspace model as a method to improve the management of the flow of resources through locations in construction projects, defined as work flow. Current scheduling methods fail to consistently manage work flow, which can disrupt the construction process, leading to waste such as conflicts in time and space by construction crews.

LoB and 4D CAD are applied to a case study of multi‐story timber housing project involving the construction of 95 apartments in five six‐storey buildings. Based on the case study results, the benefits and limitations of the combined use of both methods are discussed.

The majority of the problems experienced during the actual construction process quickly become evident from an analysis of a relatively simple LoB diagram. Furthermore, the 4D CAD workspace model provides additional insights in the scheduling of construction activities, such as workspace availability, the spatial context of workspaces and partial overlap of workspaces.

Virtual design and construction methods based on principles from lean construction can contribute significantly to the value of the product and the elimination of waste in any construction project.

The paper refers to the guiding principles from lean construction in relation to virtual design and construction methods, such as simulations with 4D CAD. Additional research and studies of practical applications are suggested to facilitate the combination of principles from lean construction with virtual design and construction methods.

The overall contribution of this work is to provide a usable maturity model for collaborative scheduling (CS) that extends the literature, identifies inconsistencies in schedule development, and improves collaboration in the construction industry.

Via subject matter expert elicitation and focus groups, the maturity model establishes five pillars of collaboration—scheduling significance, planners and schedulers, scheduling representation, goal alignment with owner, and communication. The maturity model is then validated through iterative feedback and chi-squared statistical analysis of data obtained from a survey. The five pillars are tied to the literature and previous work in CS.

The analysis shows that current industry projects are not consistent in collaboration practice implementation, and the maturity model identifies areas for collaboration improvement. The study's contributions to the body of knowledge are (1) developing a maturity model-based approach to define and measure the current level of collaboration and (2) discovering the level of consistency in scheduling collaboration practice implementation.

The findings provide a benchmark for self-evaluation and peer-to-peer comparison for project managers. The model is also useful for project managers to develop effective strategies for improvement on targeted dimensions and metrics.

The construction engineering and management (CEM) literature does not contain targeted models for scheduling collaboration in the context of maturity and, broadly speaking, neither does the literature at large. The literature also lacks actionable items as presented for the maturity model for collaborative scheduling (MMCS).

Nowadays, building information modeling (BIM) represents an evolution in the architecture, engineering and construction (AEC) industries with its various applications. BIM is capable to store huge amounts of information related to buildings which can be leveraged in several areas such as quantity takeoff, scheduling, sustainability and facility management. The main objective of this research is to establish a model for automated schedule generation using BIM and to solve the time–cost trade-off problem (TCTP) resulting from the various scenarios offered to the user.

A model is developed to use the quantities exported from a BIM platform, then generate construction activities, calculate the duration of each activity and finally the logic/sequence is applied in order to link the activities together. Then, multiobjective optimization is performed using nondominated sorting genetic algorithm (NSGA-II) in order to provide the most feasible solutions considering project duration and cost. The researchers opted NSGA-II because it is one of the well-known and credible algorithms that have been used in many applications, and its performances were tested in several comparative studies.

The proposed model is capable to select the near-optimum scenario for the project and export it to Primavera software. A case study is worked to demonstrate the use of the proposed model and illustrate its main features.

The proposed model can provide a simple and user-friendly model for automated schedule generation of construction projects. In addition, opportunities related to the interface between an automated schedule generation model and Primavera software are enabled as Primavera is one of the most popular and common schedule software solutions in the construction industry. Furthermore, it allows importing data from MS Excel, which is used to store activities data in the different scenarios. In addition, there are numerous solutions, each one corresponds to a certain duration and cost according to the performance factor which often reflects the number of crews assigned to the activity and/or construction method.

Project schedules have a vital role in the effective management of time, cost, scope and resources in construction projects, and creating schedules requires schedulers with construction knowledge and experience. The increase in the complexity of building projects and the emergence of building information modeling (BIM) in the architecture, engineering and construction industry have encouraged researchers to explore BIM capabilities for automated schedule generation. The scope and capabilities of the developed systems, however, are limited and the link between design and scheduling is still underdeveloped. This paper aims to investigate methods to develop a BIM-based framework to automatically generate schedules for concrete-framed buildings.

This system first extracts the required data from the building information model, including elements’ dimensions, quantities, spatial information, materials and other related attributes. It then applies construction rules, prior knowledge and production rate data to create project work-packages, calculate their durations and determine their relationships. Finally, it organizes these results into a schedule using project management software.

This system provides an automated and easy-to-use approach to generate schedules for concrete-framed buildings that are modeled in a BIM platform. It provides two schedules for each project, both a sequential and an overlapped solution, which the schedulers can modify into a practical schedule based on conditions and available resources.

This research project presents an innovative approach to use BIM-based attributes of structural elements to develop list of work-packages and estimate their durations, and then it uses a combination of rule-based and case-based reasoning to generate the schedules.

This paper is based on research addressing quality of construction schedules. The paper aims to structure a Schedule Health Assessment method and present it as a means to carry out the evaluation of construction schedules.

The development of the Schedule Health assessment method can be characterised as constructive research. The structuring of the method is based on analysis of factors forming the overall quality of construction schedules. The method has been tested in a proof of concept study. This comprised a case study in which four master schedules developed by junior production managers were evaluated using the Schedule Health assessment method.

It is possible to construct a method for the quality evaluation of construction schedules.

The completed testing is still rather limited since it is based merely on experiences of junior production managers with a single case.

The Schedule Health assessment method can in a useful manner make the quality evaluation of construction schedules easy to approach and effective process.

This research has produced a novel method for the quality evaluation of construction schedules.

This paper presents the development of a novel model for optimizing the scheduling of crew deployments in repetitive construction projects while considering uncertainty in crew production rates.

The model computations are performed in two modules: (1) simulation module that integrates Monte Carlo simulation and a resource-driven scheduling technique to calculate the earliest crew deployment dates for all activities that fully comply with crew work continuity while considering uncertainty; and (2) optimization module that utilizes genetic algorithms to search for and identify optimal crew deployment plans that provide optimal trade-offs between project duration and crew deployment plan cost.

A real-life example of street renovation is analyzed to illustrate the use of the model and demonstrate its capabilities in optimizing the stochastic scheduling of crew deployments in repetitive construction projects.

The original contribution of this research is creating a novel multiobjective stochastic scheduling optimization model for both serial and nonserial repetitive construction projects that is capable of identifying an optimal crew deployment plan that simultaneously minimizes project duration and crew deployment cost.

Safety planning in construction project management is separated from other planning functions, such as scheduling. This separation creates difficulties for safety engineers to analyse what, when, why and where safety measures are needed for preventing accidents. Another problem occurs due to the conventional practice of representing project designs using two‐dimensional (2D) drawings. In this practice, an engineer has to convert the 2D drawings into three‐dimensional (3D) mental pictures which is a tedious task. Since this conversion is already difficult, combining these 2D drawings with safety plans increases the difficulty. In order to address the problems, 4DCAD‐Safety is proposed. This paper discusses the design and development of 4DCAD‐Safety application and testing its usefulness in terms of assisting users in analysing what, when, where and why safety measures are needed.

The purpose of this paper is to address the problem of scheduling under uncertainty in construction projects. The existing methods for determining a project schedule are based on assumption of complete knowledge of project parameters; but in reality there is uncertainty in construction projects, deriving from a multitude of context‐dependent sources and often provided as outcome of a risk analysis process. Thus, classical deterministic analysis might provide a schedule which is not sufficiently protected against possible disruptions.

A quantitative methodology is developed for planning construction projects under uncertainty aimed at determining a reliable resource feasible project schedule by taking into account the available probabilistic information to produce solutions that are less sensitive to perturbations that occur on line. The methodology relies on a computer‐supported system that allows to identify, analyze and quantify the schedule reliability and the impact of possible disruptions on the duration of the project.

It is found that the proposed methodology can exploit more information about the uncertain parameters than the commonly‐used deterministic method, and it provides an improved understanding of the schedule reliability in presence of uncertainty. The schedule generated with a classical deterministic method sets a completely unrealistic planned project delivery date of about 1,250 days, with a probability around 50 per cent to be exceeded. This behavior can be very unsatisfactory for construction projects for which high penalties are usually associated to heavy due date violations.

This paper presents an approach for robust scheduling of construction project problem under uncertainty. We provide a tool able to support managers in developing a workable and realistic project schedule to be used as a guideline for project control and monitoring.