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To describe the implementation of the Performance Information Risk Management System (PIRMS) to indefinite delivery indefinite quantity (IDIQ) general contractors in the US Army Medical Command (MEDCOM) 26 sites, 150 projects/year, and $250m/year maintenance and repair construction program.

To test the hypothesis that facility owner management, control, and decision making is a source of risk, and that the transfer of risk and control to the contractors will minimise the risk.

Include minimising construction management by 33 percent, motivated contractors to regulate their own contracts, minimised unresolved issues by 50 percent, minimised contractor generated change orders by 20 percent, and moving from doing quality control to quality assurance.

The authors see no constraints in the implementation of PIRMS in other organisations. This paper reflects the perceptions of the Arizona State University research team, and publicly available test results, and not the views or policy of the USA Medical Command.

Includes the use of dominant performance/risk information from the contractor's weekly risk reports to create accurate performance and risk information on all ongoing projects, the IDIQ contractors, and on the client's/buyer's personnel. Risk information is being used to streamline a large organisation's organisational structure, minimising decision making and transactions, and transferring risk and control to the party who can minimise the technical risk.

Variations due to errors and mistakes have caused cost overruns in building projects. Therefore, it is undeniable that the gravity of such variations will be a critical factor in deciding the success of any building project. In addition, the design stage of a building project is considered the most suitable stage to identify and mitigate the causes of potential variations. However, there are no proper mechanisms to minimise the frequency or gravity of variations. Many researchers experienced the promising essence of Poka-Yoke, a mistake-proofing method aimed at increasing efficiency by early detection and eradication of the causes of potential errors. However, less attention has been paid so far to implement Poka-Yoke principles to minimise variations in the building project. Therefore, this study aims to develop a framework to minimise variations in building projects through the integration of the Poka-Yoke principles.

An interpretivism stance is adopted, and a qualitative research approach is used. The data collection technique adopted is semi-structured interviews with ten experts, and the data is analysed using code-based content analysis through NVivo12.

Research findings revealed 23 causes of variations, categorised under client-originated, consultant-originated, contractor-originated and other variations. The identified causes were then mapped with the Poka-Yoke principles to develop the framework. The research findings could prove useful to researchers, academics, government agencies and construction professionals in developing nations that have demographic/cultural and socioeconomic characteristics such as Sri Lanka.

The findings benefitted the Sri Lankan construction sector by minimising the causes of variations. To the best of the authors’ knowledge, this study will be the first of its kind in the Sri Lankan construction industry, leading to a better understanding of the “Poka-Yoke” principle within the building construction context.

The knowledge management (KM) sharing process plays an essential role in manufacturing under Green Implementation Network (GIN). This study aims to analyze the KM process of adopting a GIN to determine the relative importance of technical risk minimization. The proposed conceptual model was tested by considering two interrelated concepts (GIN and KM process).

Primary data from manufacturing companies in Henan province, China, were collected through 276 questionnaires. PLS-SEM and fuzzy set qualitative comparative analysis (fsQCA) were applied to investigate the configurational path of minimizing the technical risk in the manufacturing process.

The findings showed that the GIN and KM processes minimize the technical risk. The fsQCA reported multiple configurational of GIN and KM processes validated toward technical risk reduction. The study's findings contribute to the existing body of knowledge on technical risk reduction in manufacturing concerns by investigating the complex intersection between GIN and KM process.

This research adds to current GIN and KM literature by focusing on the green process using a resource-based view (RBV) and socio-technical theories. The current study provides practical and theoretical justification for explaining the relationship between GIN and KM processes. Moreover, this study adds to the literature by providing evidence that KM is an essential manufacturing industry enabler in minimizing technical risk.

The self-cleaning properties of nanostructured titanium dioxide facade coatings are useful in Singapore's tropical climate. However, its potential maintenance issues need to be determined right at the design stage. The purpose of this paper is to highlight the development of the design for maintainability tool which is a multicriteria design decision score sheet that evaluates the maintainability potential of nano-facade coating applications on high-rise façades with concrete and stonemasonry finishes and curtain walls.

Quantitative methods (expert and practitioner surveys) are conducted in this research study. Analytic hierarchy process (AHP) and sensitivity analysis were used to develop a robust Design for Maintainability tool.

Safety measures indicator received the highest weighted score by experts, while the maximizing performance, minimizing risk, minimizing negative environmental impact and minimizing consumption of matter and energy were the top ranking main criteria by both experts and practitioners. The top ranked design for maintainability sub-criteria identified by practitioners and experts were risk management, maintenance considerations, climatic conditions, safety measures, lifecycle cost and maintenance access, sun's path, rainfall intensity, biological growth measures and building age profile.

Most researches on the maintainability of nano-façade coatings uses experimentation to test the durability of nano-façade coatings, while this study focuses on design based empirical data such as establishing and ranking the list of design for maintainability criteria or indicators to minimize future defects and maintenance issues. The design for maintainability tool contributes to the maintainability of nano-façade coatings leading to maximizing its performance while minimizing cost, risks, resource consumption and negative environmental impact.

The purpose of this research is to address the complex multiobjective unrelated parallel machine scheduling problem with real-world constraints, including sequence-dependent setup times and periodic machine maintenance. The primary goal is to minimize total tardiness, earliness and total completion times simultaneously. This study aims to provide effective solution methods, including a Mixed-Integer Programming (MIP) model, an Epsilon-constraint method and the Nondominated Sorting Genetic Algorithm (NSGA-II), to offer valuable insights into solving large-sized instances of this challenging problem.

This study addresses a multiobjective unrelated parallel machine scheduling problem with sequence-dependent setup times and periodic machine maintenance activities. An MIP model is introduced to formulate the problem, and an Epsilon-constraint method is applied for a solution. To handle the NP-hard nature of the problem for larger instances, an NSGA-II is developed. The research involves the creation of 45 problem instances for computational experiments, which evaluate the performance of the algorithms in terms of proposed measures.

The research findings demonstrate the effectiveness of the proposed solution approaches for the multiobjective unrelated parallel machine scheduling problem. Computational experiments on 45 generated problem instances reveal that the NSGA-II algorithm outperforms the Epsilon-constraint method, particularly for larger instances. The algorithms successfully minimize total tardiness, earliness and total completion times, showcasing their practical applicability and efficiency in handling real-world scheduling scenarios.

This study contributes original value by addressing a complex multiobjective unrelated parallel machine scheduling problem with real-world constraints, including sequence-dependent setup times and periodic machine maintenance activities. The introduction of an MIP model, the application of the Epsilon-constraint method and the development of the NSGA-II algorithm offer innovative approaches to solving this NP-hard problem. The research provides valuable insights into efficient scheduling methods applicable in various industries, enhancing decision-making processes and operational efficiency.

Scheduling is defined by Baker as, “the allocation of resources over time to perform a collection of tasks”. The term facilities is often used instead of resources and the tasks to be performed may involve a variety of different operations.

The objective of this research study is to formulate and develop a novel optimization model that enables planners of modular construction to minimize the total transportation and storage costs of prefabricated modules in modular construction projects.

The model is developed by identifying relevant decision variables, formulating an objective function capable of minimizing the total transportation and storage costs and modelling relevant constraints. The model is implemented by providing all relevant planner-specified data and performing the model optimization computations using mixed-integer programming to generate the optimal solution.

A case study of hybrid modular construction of a healthcare facility is used to evaluate the model performance and demonstrate its capabilities in minimizing the total transportation and onsite storage costs of building prefabricated modules.

The model can be most effective in optimizing transportation for prefabricated modules with rectangular shapes and might be less effective for modules with irregular shapes. Further research is needed to consider the shape of onsite storage area and its module arrangement.

The developed model supports construction planners in improving the cost effectiveness of modular construction projects by optimizing the transportation of prefabricated modules from factories to construction sites.

The original contributions of this research is selecting an optimal module truck assignment from a feasible set of trucks, identifying an optimal delivery day of each module as well as its location and orientation on the assigned truck and complying with relevant constraints including the non-overlap of modules on each truck, shipment weight distribution and aerodynamic drag reduction.

Planning for increased contractor profits should start at the time the contract is signed because low profits and lack of profitability are the primary causes of contractor failure. The purpose of this paper is to propose an integrated profit maximization model (IPMM) that aims for maximum expected profit by using time-cost tradeoff analysis, adjusted start times of activities, minimized financing cost and minimized extension of work schedule beyond the contract duration. This kind of integrated approach was never researched in the past.

IPMM is programmed into an automated system using MATLAB 2016a. It generates an optimal work schedule that leads to maximum profit by means of time-cost tradeoff analysis considering different activity acceleration/deceleration methods and adjusting the start/finish times of activities. While doing so, IPMM minimizes the contractor’s financing cost by considering combinations of different financing alternatives such as short-term loans, long-term loans and lines of credit. IPMM also considers the impact of extending the project duration on project profit.

IPMM is tested for different project durations, for the optimality of the solutions, differing activity start/finish times and project financing alternatives. In all cases, contractors can achieve maximum profit by using IPMM.

IPMM considers a deterministic project schedule, whereas stochastic time-cost tradeoff analysis can improve its performance. Resource allocation and resource leveling are not considered in IPMM, but can be incorporated into the model in future research. Finally, the long computational time is a challenge that needs to be overcome in future research.

IPMM is likely to increase profits and improve the chances of contractors to survive and grow compared to their competitors. The practical value of IPMM is that any contractor can and should use IPMM since all the data required to run IPMM is available to the contractor at the time the contract is signed. The contractor who provides information about network logic, schedule data, cost data, contractual terms, and available financing alternatives and their APRs can use an automated IPMM that adjusts activity start times and durations, minimizes financing cost, eliminates or minimizes time extensions, minimizes total cost and maximizes expected profit.

Unlike any prior study that looks into contractors’ profits by considering the impact of only one or two factors at a time, this study presents an IPMM that considers all major factors that affect profits, namely, time-cost tradeoff analysis, adjusted start times of activities, minimized financing cost and minimized extension of work schedule beyond the contract duration.

Multi-manned assembly lines are designed to produce large-sized products, such as automobiles. In this paper, a multi-manned assembly line balancing problem (MALBP) is addressed in which a group of workers simultaneously performs different tasks on a workstation. The key idea in this work is to improve the workstation efficiency and worker efficiency of an automobile plant by minimizing the number of workstations, the number of workers, and the cycle time of the MALBP.

A mixed-integer programming formulation for the problem is proposed. The proposed model is solved with benchmark test problems mentioned in research papers. The automobile case study problem is solved in three steps. In the first step, the authors find the task time of all major tasks. The problem is solved in the second step with the objective of minimizing the cycle time for the sub-tasks and major tasks, respectively. In the third step, the output results obtained from the second step are used to minimize the number of workstations using Lingo 16 solver.

The experimental results of the automobile case study show that there is a large improvement in workstation efficiency and worker efficiency of the plant in terms of reduction in the number of workstations and workers; the number of workstations reduced by 24% with a cycle time of 240 s. The reduced number of workstations led to a reduction in the number of workers (32% reduction) working on that assembly line.

For assembly line practitioners, the results of the study can be beneficial where the manufacturer is required to increased workstation efficiency and worker efficiency and reduce resource requirement and save space for assembling the products.

This paper is the first to apply a multi-manned assembly line balancing approach in real life problem by considering the case study of an automobile plant.

Waste minimization strategies and the relative significance of construction waste sources were examined using a survey of 24 construction firms operating in Australia. The results indicated that a sizeable proportion of respondent firms did not have specific policies for minimizing waste. Furthermore, while a majority of firms with specific waste minimization policies made efforts to minimize waste at source, i.e. to avoid generating waste in the first place, this minimization was limited to waste generated by site offices and amenities. Potential scope exists for improving the effectiveness of waste minimization at source by addressing the sources of all waste generated during the construction phase. The survey results indicated that the five most significant sources of construction waste were design changes, leftover material scraps, wastes from packaging and non‐reclaimable consumables, design/detailing errors, and poor weather. Potential opportunities for minimizing the amount of waste generated on construction project sites are identified.