Systematic Evaluation of Construction Equipment Alternatives: Case Study

Selecting the right equipment for the project is inherently a multifaceted cost and benefit evaluation process that is further compounded by the complexity of today’s building projects and the lack of systematic tools for the consideration of soft factors. This paper presents a detailed application example of a model based on an analytical hierarchy process (AHP) approach. This model was developed to address the difficulties experienced during the multifaceted process. The example illustrates how an AHP-based model helps address the multitude of qualitative, intangible factors, both among the factors themselves and then vis-à-vis costs, by means of a systematic and traceable process. The method enables project managers and their equipment selection teams to exercise their knowledge, intuition, and professional judgment, and at the same time to address the context and specifics of the particular projects under examination. The example should be helpful for construction practitioners dealing with similar equipment selection issues. Researchers may find interest in the implementation of a multiattribute-decision-making method for a typical construction management problem.     

“Soft” Considerations in Equipment Selection for Building Construction Projects

This paper raises the issue of “soft” considerations in the selection of equipment for building construction projects. The paper aims at increasing the awareness: (1) to the nature, variety, and richness of soft factors; (2) to their significant role and potential impact on the outcome of decision making; and (3) to the inherent difficulty of evaluating them and integrating them within a comprehensive selection process. Existing state-of-the-art equipment selection models were analyzed and found to be inadequate in terms of both considering soft factors and providing mechanisms for their systematic evaluation. Six cases of large-size, complex construction projects were investigated to obtain an extensive list of typical soft factors. This investigation revealed that the consideration of soft factors in current practices is essentially unstructured and is not integrated within the selection process in a systematic manner. A desirable selection process is outlined that generally responds to the needs identified in the study. The proposition of a specific method for the quantitative treatment of soft factors and their tradeoff with cost factors is the subject of another paper.     

Formulating Procurement Selection Criteria through Case-Based Reasoning Approach

An appropriate procurement system is a catalyst to the success of a construction project. In practice, the solutions and outcomes of previous procurement selection decisions could be extremely useful in supporting decision making. As a technique that captures and reuses experiential knowledge, case-based reasoning (CBR) has a high potential for modeling the procurement selection decision within a complex dynamic environment. This paper examines the suitability of CBR approaches for procurement selection. The process involved in procurement selection is examined first. A conceptual framework for case-based procurement selection is proposed. The structure of a prototype model on procurement selection criteria (PSC) formulation is presented in this paper. The model applies the CBR approach to procurement criteria selection irrespective of the variability in the characteristics of the client, project, and external environment.     

Project Delivery System Selection under Uncertainty: Multicriteria Multilevel Decision Aid Model

Selecting an optimal project delivery system is a critical task that owners should do to ensure project success. This selection is a complex decision-making process. The complexity arises from the uncertain or not well-defined parameters and/or the multiple criteria structure of such decisions. In this study, a decision aid model using the analytical hierarchy process (AHP) coupled with rough approximation concepts is developed to assist the owners. The selection criteria are determined by studying a number of benchmarks. The model ranks the alternative delivery systems by considering both benchmark results and owner’s opinion. In interval AHP, an optimization procedure is performed via obtaining the upper and the lower linear programming models to determine the interval priorities for alternative project delivery systems. In cases having incomparable alternatives, which is the most likely case in uncertain decision making, the model uses rough set-based measures to reduce the number of decision criteria to a subset, which is able to fully rank the alternatives. To illustrate the applicability and usefulness of this methodology, a real world case study will be demonstrated.     

Optimal Construction Site Layout Considering Safety and Environmental Aspects

A good site layout is vital to ensure the safety of the working environment and effective and efficient operations. Site layout planning has significant impacts on productivity, costs, and duration of construction. Construction site layout planning involves identifying, sizing, and positioning temporary and permanent facilities within the boundary of the construction site. Site layout planning can be viewed as a complex optimization problem. Although construction site layout planning is a critical process, systematical analysis of this problem is always difficult because of the existence of a vast number of trades and interrelated planning constraints. The problem has been solved using two distinct approaches: Optimization techniques and heuristics methods. Mathematical optimization procedures have been developed to produce optimal solutions, but they are only applicable for small-size problems. Artificial intelligent techniques have been used practically to handle real-life problems. On the other hand, heuristic methods have been used to produce good but not optimal solutions for large problems. In this paper, an optimization model has been developed for solving the site layout planning problem considering safety and environmental issues and actual distance between facilities. Genetic algorithms are used as an optimization bed for the developed model. In order to validate the performance of the developed model, a real-life construction project was tested. The obtained results proved that satisfactory solutions were obtained.     

Quantitative Methods for Design-Build Team Selection

The use of design/build (DB) contracting by transportation agencies has been steadily increasing as a project delivery system for large complex highway projects. However, moving to DB from traditional design-bid-build procurement can be a challenge. One significant barrier is gaining acceptance of a best-value selection process in which technical aspects of a proposal are considered separately and then combined with price to determine the winning proposal. These technical aspects mostly consist of qualitative criteria, thus making room for human errors or biases. Any perceived presence of bias or influence in the selection process can lead to public mistrust and protests by bidders. It is important that a rigorous quantitative mathematical analysis of the evaluation process be conducted to determine whether bias exists and to eliminate it. The paper discusses two potential sources of bias—evaluators and weighting model—in the DB selection process and presents mathematical models to detect and remove biases should they exist. A score normalization model deals with biases from the evaluators; then a graphical weight-space volume model and a Monte Carlo statistical sampling model are developed to remove biases from the weighting model. The models are then tested and demonstrated using results from the DB bridge replacement project for the collapsed Mississippi River bridge of Interstate 35W in Minneapolis.     

Developing Construction Professionals of the 21st Century: Renewed Vision for Leadership

The construction industry faces several technical, social, financial, political, and cultural challenges. Developments such as the growing volume of activity, increasing number of active stakeholders, advancement in technology, more intense global competition, and demand for fast-track completion, have created many distinct challenges for construction professionals. Consequently, there is a need to equip the professionals with hard (technical) as well as soft (management and leadership) skills. Construction professionals invariably work in teams and often assume leadership roles as the design manager, construction manager, procurement manager, contracts manager, or project manager. They deal with various project stakeholders and often get involved in sensitive decision making and dispute resolution processes. There is a broad sentiment in the industry that today’s new graduates are not adequately trained to deal with the soft issues on complex construction projects. In particular, academic programs do not prepare professionals with an appropriate blend of hard and soft skills. In this paper, it is argued that in order to develop competent professionals who have strong leadership skills, the universities, the construction industry, professional organizations, and the government need to form a broad collaboration. A conceptual model of this potential collaborative relationship is presented, and specific roles for the universities, the industry, professional bodies, and government in the lifelong professional development of the industry’s human resources are discussed.     

Determination of Most Economical Scrapers Fleet

Scrapers are valuable construction equipment for large earthmoving operations. Their production rates vary widely as they depend on the equipment performance, operation’s travel time, and haul-road conditions. Determining the most economical selection of the size, model, and number of scrapers is a rather tedious process that involves repetitive calculations. A spreadsheet application was created in order to facilitate such calculations and select the most economical scraper from the list of available equipment for the job under consideration. The application is made of seven spreadsheets containing a scrapers’ database, performance charts, soil properties, and other supporting worksheets. The application provides a user interface to solicit all data entries specific to a project. Once the user enters the required data the system compares the production rate, time required for the job, determines the estimated unit cost for each scraper in the database, and recommends the most economical selection.     

Multiperspective Approach to Exploring Comprehensive Cause Factors for Interface Issues

The severity of interface issues and the necessity of interface management (IM) have not received adequate recognition from both industry and academia. The understanding of interface issues is still insufficient and the proposed or employed measures are unilateral, which result in unsatisfactory IM performance in construction projects. After establishing IM’s importance in the construction industry, this paper presents a multiperspective approach that systematically explores comprehensive cause factors for various interface issues. From six interrelated perspectives, namely people/participants, methods/processes, resources, documentation, project management, and environment, hierarchical cause factors are identified and presented in a structured way. These cause factors are further converted into a series of interface management and control elements that allow for the development of an object data model and a systematic model-based IM strategy dealing with all interface issues. The multiperspective approach outperforms other research methods that analyze selected interface issues in a loose and isolated way. The findings contribute a holistic view of what causes interface issues as well as provide a solid theoretical basis for practitioners and researchers to seek all-around IM solutions.     

Analytic Network Process Applied to Project Selection

Owing to the complexity of a construction project, the analytic network process (ANP) is helpful to deal with interdependent relationships within a multicriteria decision-making model. This paper demonstrates an example to illustrate how to empirically prioritize a set of projects by using a five-level project selection model. A questionnaire was filled by a group of construction professionals of a medium-sized local developer and scores were computed for prioritizing the potential projects. The paper is relevant to both industry practitioners and researchers. Industry practitioners may adopt the weighted criteria for direct project selection or apply the ANP method to prioritize their own set of selection criteria. Researchers may rely on this paper as a point of departure for exploring other uses of ANP.     

AHP-Based Weighting of Factors Affecting Safety on Construction Sites with Tower Cranes

Aspiring to adopt a nonstatistical quantitative approach to safety assessment, this study implements a multiattribute decision-making tool to elicit knowledge from experts and formalize it into a set of weighted safety factors. The environment addressed is the construction site and the specific factors studied are those affecting safety due to the operation of tower cranes. Nineteen senior construction equipment and safety experts were interviewed and led through the analytic hierarchy process (AHP) to provide their assessments on the relative importance of safety factors obtained in an earlier study. The results accentuate the dominance of the crane operator and general superintendent on the site safety scene and play down the contribution of “classic” site hazards such as power lines. Quantitative measuring of safety, such as reflected in the weights obtained in this study, is important in communicating safety requirements and focusing the limited resources available for safety improvements. These factor weights are also deemed to be a vital component in the development of a comprehensive model that will allow the computation of safety indices for individual construction sites employing tower cranes. It is expected that the methodology can then be adopted for addressing other site safety issues as well.     

Fuzzy Analytical Hierarchy Process Risk Assessment Approach for Joint Venture Construction Projects in China

Research and practice show that construction joint venture (JV) activities in China are opportunities that can bring potential benefits but at the same time may generate many risks. While research has studied these risks and presented useful advice for managing individual risks, the methodologies used to analyze the risks were mainly qualitatively based, and there is a gap in using the quantitative method that can integrate a risk expert’s knowledge to assess the risks associated with JV projects. This paper sets up a hierarchy structure of the risks and then develops a fuzzy analytical hierarchy process (AHP) model for the appraisal of the risk environment pertaining to the JVs to support the rational decision making of project stakeholders. An empirical case study is used to demonstrate the application of the proposed fuzzy AHP model. It is concluded that the fuzzy AHP model is effective in tackling the risks involved in JV projects. The information presented in this paper should be shown to all parties considering JV business opportunities in China, and the proposed approach should be applicable to the research and analysis of risks associated with any type of construction projects.     

Control Over the Innovative Pellet Production Process at TKOM No. 3 at PAO ‘Mikhailovskiy GOK’ Employing the State-of-the-Art Automated Process Control System

The paper article describes the operating experience of a plant employing state-of-the-art production technology with an MOK-1-592 (TKOM no. 3) indurating machine started up in 2015 at PAO Mikhailovsky GOK. The technical and process solutions implemented in the design of a greenfield production complex is discussed, including a state-of-the-art automated process control system ensuring seamless operation of the equipment in the automated mode and improvement of the product quality. The innovative approach to the performance of the traveling-grate indurating machine and the equipment, which is a part of the heatflow diagram (thermal circuit) of the machine, is based on numerical simulation research of heat and weight transfer in an iron-ore pellet bed. Successful execution of the TKOM no. 3 project is a result of the researchbased and scientifically proven selection of control methods for the pellet production process, the use the state-of-the-industry algorithms for control over the operation modes of the entire production line.     

Assignment and Allocation Optimization of Partially Multiskilled Workforce

Multiskilling is a workforce strategy that has been shown to reduce indirect labor costs, improve productivity, and reduce turnover. A multiskilled workforce is one in which the workers possess a range of skills that allow them to participate in more than one work process. In practice, they may work across craft boundaries. The success of multiskilling greatly relies on the foreman’s ability to assign workers to appropriate tasks and to compose crews effectively. The foreman assigns tasks to workers according to their knowledge, capabilities, and experience on former projects. This research investigated the mechanics of allocating a multiskilled workforce and developed a linear programming model to help optimize the multiskilled workforce assignment and allocation process in a construction project, or between the projects of one company. It is concluded that the model will be most useful in conditions where full employment does not exist; however, it is also useful for short term allocation decisions. By running the model for various simulated scenarios, additional observations were made. For example, it is concluded that, for a capital project, the benefits of multiskilling are marginal beyond approximately a 20% concentration of multiskilled workers in a project workforce. Benefits to workers themselves become marginal after acquiring competency in two or three crafts. These observations have been confirmed by field experience. Extension of this model to allocation of multifunctional resources, such as construction equipment, should also be possible.     

A Fuzzy Decision Framework for Contractor Selection

Contractor selection is the process of selecting the most appropriate contractor to deliver the project as specified so that the achievement of the best value for money is ensured. Construction clients are becoming more aware of the fact that selection of a contractor based on tender price alone is quite risky and may lead to the failure of the project in terms of time delay and poor quality standards. Evaluation of contractors based on multiple criteria is, therefore, becoming more popular. Contractor selection in a multicriteria environment is, in essence, largely dependent on the uncertainty inherent in the nature of construction projects and subjective judgment of decision makers (DMs). This paper presents a systematic procedure based on fuzzy set theory to evaluate the capability of a contractor to deliver the project as per the owner’s requirements. The notion of Shapley value is used to determine the global value or relative importance of each criterion in accomplishing the overall objective of the decision-making process. The research reported upon forms part of a larger study that aims to develop a fuzzy decision model for construction contractor selection involving investigating multiple criteria selection tendencies of construction clients, relationship among decision criteria, and construction clients’ preferences of criteria in the contractor selection process. An illustration with a bid evaluation exercise is presented to demonstrate the data requirements and the application of the method in selecting the most appropriate contractor for the project under uncertainty. The proposed model is not intended to supplant the work of decision-making teams in the contractor selection process, but rather to help them make quality evaluations of the available candidate contractors. One major advantage of the proposed method is that it makes the selection process more systematic and realistic as the use of fuzzy set theory allows the DMs to express their assessment of contractors’ performance on decision criteria in linguistic terms rather than as crisp values.     

Resource Management in Construction

Resource plannirtg and management is one of the most important ingredients for competitiveness and profitability in today's construction industry. In order to control costs, equipment and labor should be utilized in the most efficient way possible. This can be achieved by minimizing the total cost of leased resources under the constraint of maximum and most efficient use of owned equipment and contracted labor force. This paper presents a mixed‐integer linear programming model for the management of resources throughout the project life. Based on the Critical Path Method time analysis, the model derives the schedule for equipment rentals and transient resources, as well as the utilization scheme for owned equipment and other available resources. The model can be used as an estimating tool for multi‐project resource planning and sharing, and as a means to implement the most efficient utilization of resources throughout the duration of the whole project.     

Developing ERP Systems Success Model for the Construction Industry

Recently, a significant number of major construction companies embarked on the implementation of integrated information technology solutions such as enterprise resource planning (ERP) systems to better integrate various business functions. However, these integrated systems in the construction sector present a set of unique challenges, different from those in the manufacturing or other service sectors. There have been many cases of failure in implementing ERP systems in the past, so it is critical to identify and understand the factors that largely determine the success or failure of ERP implementation in the construction industry. This paper presents the process of developing an ERP systems success model to guide a successful ERP implementation project and to identify success factors for ERP systems implementation. The paper identifies factors associated with the success and failure of ERP systems, and develops a success model to analyze the relationships between key factors and the success of such systems. The proposed ERP systems success model adapts the technology acceptance model and DeLone and McLean’s information systems success model and integrates those with key project management principles. The goal of the ERP systems success model is to better evaluate, plan, and implement ERP projects and help senior managers make better decisions when considering ERP systems in their organization.     

Strategic-Operational Construction Management: Hybrid System Dynamics and Discrete Event Approach

A significant number of large-scale civil infrastructure projects experience cost overruns and schedule delays. To minimize these disastrous consequences, management actions need to be carefully examined at both the strategic and operational levels, as their effectiveness is mainly dependent on how well strategic perspectives and operational details of a project are balanced. However, current construction project management approaches have treated the strategic and operational issues separately, and consequently introduced a potential conflict between strategic and operational analyses. To address this issue, a hybrid simulation model is presented in this paper. This hybrid model combines system dynamics and discrete event simulation which have mainly been utilized to analyze the strategic and operational issues in isolation, respectively. As an application example, a nontypical repetitive earthmoving process is selected and simulated. The simulation results demonstrate that a systematic integration of strategic perspective and operational details is helpful to enhance the process performance by enabling construction managers to identify potential process improvement areas that traditional approaches may miss. Based on the simulation results, it is concluded that the proposed hybrid simulation model has great potential to support both the strategic and operational aspects of construction project management and to ultimately help increase project performance.     

Modeling Interfirm Dependency: Game Theoretic Simulation to Examine the Holdup Problem in Project Networks

Subcontractor selection strategies used by contractors can significantly affect short-term project and long-term organizational success. Existing research on subcontractor selection strategy implicitly assumes that the evaluation of subcontractors depends on current conditions. We extend this perspective by integrating an agent-based simulation model with game theory to examine whether precontract partner selection strategies that do not consider subcontractor selection as a repeated game may lead to a version of the holdup problem. The holdup problem we investigate focuses on relationship-specific investments in learning after the introduction of an innovation or organizational change across a project network. A minimum total cost strategy may decelerate the rate of adaptation to an innovation or organizational change, thereby proving that the holdup problem can exist in project networks. The findings contribute to subcontractor selection strategy literature by simulating the impact of the holdup problem in project networks, distinguishing task interdependence as a moderating variable, and identifying that the minimum total cost strategy can be a suboptimal strategy for project networks adapting to systemic changes.