Risk Of Rework Research Articles

An intelligent framework for rework risk identification in prefabricated construction processes based on compliance checking

An intelligent framework for rework risk identification in prefabricated construction processes based on compliance checking

Error Mastery in Alliance Transport Megaprojects

Human error is a major source of rework, with a project's culture setting the tone for its response and how it cooperates and shares information. This article examines how a program alliance's error culture, which forms part of a transport megaproject, mitigates its errors and rework. We undertake a series of semi-structured interviews to make sense of the experiences of alliance participants about why and how rework occurs, its assessment, and if knowledge sharing occurs when it arises. Our analysis reveals that the alliance effectively utilizes elements of an error management culture to communicate and share knowledge. However, we find the alliance's learning capacity is constrained by its inability to capture and analyze rework-related knowledge, preventing it from building resilience to error. Consequently, we propose a collection of principles that an alliance can draw upon to create an error mastery mindset enabling it to manage its rework risks and unexpected events. The benefits of an error mastery mindset are threefold as it provides the ability to: 1) better support people's well-being; 2) anticipate what might go wrong; and 3) adapt and learn about circumstances where errors and rework occur and re-establish work practices after an adverse event.

Fast-and-frugal heuristics: an exploration into building an adaptive toolbox to assess the uncertainty of rework

Performing rework within the production system of construction is the most expensive waste that confronts organisations, with its causation yet to be fully understood in practice. Any effort to assess the risk of rework poses challenges due to limited information about its frequency and causes, rendering the use of statistical models immeasurable. Research has shown that fast-and-frugal heuristics enable epistemic success under conditions of uncertainty and cognitive complexity – they are accurate, fast, and rely on limited information. Thus, this paper proposes the following research question: How can fast-and-frugal heuristics effectively assess the uncertainty of rework in construction? The theoretical framing of ecological rationality provides an environmental structure for bounded rationality to explore this question, enabling a person’s ‘adaptive toolbox’ of fast-and-frugal heuristics tailored for different epistemic and pragmatic decisions to be utilised. Situations during the construction of a transport infrastructure mega-project (>AU$18 billion) where there was profound uncertainty surrounding rework are presented. The heuristics, intuitively drawn from an individual’s adaptive toolbox used to form judgments to assess the uncertainty of rework, are identified. The theoretical and practical implications of the paper are discussed before presenting suggestions for future research to help build a robust adaptive toolbox to be utilised for assessing the uncertainty of rework in construction.

A new uncertain remanufacturing scheduling model with rework risk using hybrid optimization algorithm.

As a resource-conserving and environmentally friendly manufacturing paradigm, remanufacturing with the potential to realize sustainability in production has been extensively investigated. Scheduling plays a significant role in achieving the remanufacturing benefits. However, the remanufacturing process involves intricate uncertainties because it takes end-of-life products with different qualities as workblanks, which increases the risk of rework and complicates remanufacturing scheduling. Though the traditional stochastic optimization methods or fuzzy theory have been employed to address uncertainties in the remanufacturing scheduling problem, they are constrained with the limited historical data which renders it difficult to describe uncertainties accurately and intuitively. Therefore, a new uncertain remanufacturing scheduling model with rework risk is proposed, in which the interval grey numbers are applied to describe the uncertainty clearly and consider the rework risk in remanufacturing process. To solve this model, a hybrid optimization algorithm that combines differential evolution and particle swarm optimization algorithms through an efficient representation scheme is proposed. Besides, this algorithm integrates multiple improvements to maintain the diversity of the population and enhance its performance. Simulation experiments are conducted on 18 sets of instances with different scales, and the results demonstrated that the proposed algorithm obtains a better optimal solution than other baseline algorithms on 17 sets of instances. The main finding of this study is providing a new method for solving uncertain remanufacturing scheduling problem with rework risk practically and effectively.

When ‘less is more’: The rationale for an adaptive toolbox to manage the risk and uncertainty of rework

Determining the risk and uncertainty of rework in construction has received limited attention due to a paucity of information about its frequency and causes. Errors made during construction, which may require rework, can go undetected, manifesting as an engineering failure during an asset’s operation and thus jeopardise system safety. Therefore, this paper addresses the following research question: How can practitioners make better decisions to mitigate the risk and uncertainty of rework during the construction of infrastructure assets and ensure system safety? Using a mega-transport infrastructure asset as a case setting, we adopt an interpretative line of inquiry and examine people's experiences with managing the risk and uncertainty of rework under the auspices of a sense-making lens. Our analysis revealed that heuristics were being used informally to determine rework risks and uncertainties due to the absence of information, resulting in them becoming curiosities as the same mistakes were repeated and learning stymied. We suggest that developing an adaptive-box tool comprising heuristics can provide the much-need theoretical foundation to effectively manage the risk and uncertainty of rework. Such heuristics would be adaptable to different situations as they are fitted to the environment through evolution and/or learning by amending them successively in small steps.

Prefabricated Construction Process Optimization Based on Rework Risk

Prefabricated Construction Process Optimization Based on Rework Risk

Large‐scale semi‐automated migration of legacy C/C++ test code

AbstractThis is an industrial experience report on a large semi‐automated migration of legacy test code in C and C++. The particular migration was enabled by automating most of the maintenance steps. Without automation this particular large‐scale migration would not have been conducted, due to the risks involved in manual maintenance (risk of introducing errors, risk of unexpected rework, and loss of productivity). We describe and evaluate the method of automation we used on this real‐world case. The benefits were that by automating analysis, we could make sure that we understand all the relevant details for the envisioned maintenance, without having to manually read and check our theories. Furthermore, by automating transformations we could reiterate and improve over complex and large scale source code updates, until they were “just right.” The drawbacks were that, first, we have had to learn new metaprogramming skills. Second, our automation scripts are not readily reusable for other contexts; they were necessarily developed for this ad‐hoc maintenance task. Our analysis shows that automated software maintenance as compared to the (hypothetical) manual alternative method seems to be better both in terms of avoiding mistakes and avoiding rework because of such mistakes. It seems that necessary and beneficial source code maintenance need not to be avoided, if software engineers are enabled to create bespoke (and ad‐hoc) analysis and transformation tools to support it.

Subcontracting and Rework Risk Sharing in Engineering-Procurement-Construction Projects

Subcontracting and Rework Risk Sharing in Engineering-Procurement-Construction Projects

Reflections on the Risk and Uncertainty of Rework in Construction

AbstractRework can be a problem in construction projects. While research has contributed to the accumulation of knowledge about rework, there remains limited understanding about its causal mechanis...

Research on the rework risk core tasks in prefabricated construction in China

PurposeThe purpose of this paper is to assess the process of prefabricated construction (PC) and analyze the impacts of rework risk to identify the core tasks for which the rework risk has severe impacts.Design/methodology/approachThe methods consist of a literature review, expert interviews, a questionnaire survey and a rework risk function. The expert interviews and questionnaire survey were administered to experts in the entire process of PC from the dimensions of rework frequency, rework cost and rework time. Descriptive and inferential statistics were employed to analyze the data. The rework risk function was based on the loss expectancy method.FindingsThere are 13 core tasks that have higher impacts than the average level. The core tasks in the design stage account for 100% of the tasks in the stage, those in the manufacturing stage account for 20% and those in the construction stage account for 23.1%. Compared with the other stages, the design stage is characterized by significantly more frequent rework, higher rework costs and longer rework time. The manufacturing stage is characterized by significantly higher rework costs than the construction stage. The manufacturing stage and construction stage are co-reliant, and both are impacted by the design stage.Practical implicationsThe findings provide stakeholders with a clear understanding of the core tasks of the PC process and represent a method for identifying core tasks. Stakeholders can learn from this to focus on the core tasks to reduce rework risk and manage the process with the priority of PC rework management based on the following order: design > manufacturing > construction. The approach is suitable for core task identification in other areas.Originality/valueThis research provides insight into rework risk management and provides a novel analysis method for rework risk and PC management from the perspective of the construction process. The findings are valuable for supporting stakeholders in making effective construction plans to reduce the impacts of rework risk in PC and provide a reference for future research on process optimization.

A DSM‐Based CCPM‐MPL Representation Method for Project Scheduling under Rework Scenarios

Rework risks caused by information flow interactions have become a major challenge in project scheduling. To deal with this challenge, we propose a model integrating the critical chain project management method, design structure matrix method, and max‐plus method. Our model uses a start‐to‐start relationship of activities instead of the traditional finish‐to‐start relationship, which also allows overlaps between activities. We improve the accuracy of the rework safety time in two ways: (1) the overall overlapping effect is taken into consideration when calculating the rework time of an activity arising from the information flow interaction of its multiple predecessors overlapped with it; (2) the rework time arising from activity overlaps, the first rework time, and the second rework time are calculated as components of the rework safety time in our model, while the last one is ignored in traditional methods. Furthermore, the accuracy of time buffers is improved based on the improved rework safety time. Finally, we design the max‐plus method to generate project schedules and appropriately sized time buffers. The empirical results show that the project schedule generated by the proposed method has a higher on‐time completion probability, as well as more appropriately sized project buffers.

Faster or fewer iterations? A strategic perspective of a sequential product development project

Shortening the lead time for Product Development (PD) provides enterprises with a competitive advantage. Given the iterative nature of PD projects, two aspects are regularly considered to shorten the PD lead time, that is, conducting faster or fewer iterations. However, executing faster iterations usually causes more iterations and vice versa. Therefore, suitable coordination between faster and fewer iterations is necessary to minimize the PD lead time. We investigate this coordination from a strategic perspective, whereby a PD project is considered as a sequence of stages and characterized by the design rates and rework probabilities of those stages. We model the coordination as a decision to choose the appropriate design rates for each stage, wherein the rework probabilities are negatively related to the design rates. An absorbing Markov process is applied to calculate the expected lead time of a PD project. Further, we formulate a geometric programming model to determine the optimal design rates of the stages with respect to the minimal expected lead time. Several insights are extracted from the model to provide general guidance on the coordination, including the effect of the acceptance check rate of the project, rework risk of the stages on the optimal design rates, and decomposability of the coordination. Inspired by these insights, an efficient heuristic algorithm is designed. The algorithm performs well in numerical experiments, which in turn validates the insights. Additionally, a field case proves the effectiveness of our model. Compared with the current policy, 12.25% of the PD lead time is saved through appropriate coordination between faster and fewer iterations.

Quality, requisite imagination and resilience: Managing risk and uncertainty in construction

Measuring and determining the risks of rework is critical for determining the reliability of construction and ensuring peoples safety. In this paper we aim to addresses the following question: “How can we anticipate and mitigate the consequences of rework in construction?” We adopted a sense-making approach to tackle this question and in doing so acquired knowledge and an understanding of managerial practices and conditions that contributed to rework in a leading construction organization. Using non-conformances as a measure of quality we analyzed 9088 events that required rework in 210 projects to determine its costs and identify those subcontract trades where it was most prevalent. To garner an understanding of the conditions that hindered the organizations ability to ‘anticipate’ the presence and ‘respond’ to the occurrence of rework in its projects, we conducted a series of interviews and found three issues contributing to this situation: (1) the absence of a homogenous culture; (2) a misalignment of strategy; and (3) organizational amnesia. We develop a novel framework to manage the risk and uncertainty of rework based on the concepts of requisite imagination and resilience. The developed framework can be applied not only to construction, but also form part of an integrated preventative maintenance policy to manage an asset's quality during its operations.

A Critical Design Structure Method for Project Schedule Development under Rework Risks

In order to overcome the difficulty in quantifying rework by traditional project schedule management tools, this study proposes an innovative method, namely improved Critical Chain Design Structure Matrix (ICCDSM). From the perspective of information flow, the authors firstly make assumptions on activity parameters and interactions between activities. After that, a genetic algorithm is employed to reorder the activity sequence, and a banding algorithm with consideration of resource constraints is used to identify concurrent activities. Then potential criticality is proposed to measure the importance of each activity, and the rework impact area is implicated to indicate potential rework windows. Next, two methods for calculating project buffer are employed. A simulation methodology is used to verify the proposed method. The simulation results illustrate that the ICCDSM method is capable of quantifying and visualizing rework and its impact, decreases iterations, and improves the completion probability. In this vein, this study provides a novel framework for rework management, which offers some insights for researchers and managers.

A Novel Method of Developing Construction Projects Schedule under Rework Scenarios

Construction projects have faced serious schedule delays caused by rework risks. However, it appears that traditional methods are of limited value in developing applicable project schedules. This study presents an analysis on construction projects schedule development under rework scenarios by a novel method named the improved critical chain design structure matrix (CCDSM). Research data are collected from a real estate development project in China. As a result, predictions of project completion duration and probability have been made. A reliable schedule considering information interactions has been developed and visualized. Rework impact areas of activities have been examined to quantitatively record the impact on project duration. To meet different demands, the method generates two more schedules setting different rework buffers. Furthermore, these activities have the potential of causing rework and have been quantified based on the calculation of two criticalities, providing an identification of rework-intensive works that should be payed close importance to, which have not be realized by previous methods. The results proved the feasibility and effectiveness of this method in developing a schedule for construction projects disturbed by rework, helping practitioners adopt measures to avoid rework-caused schedule delays and achieve sustainable development of such projects.

Critical Chain Design Structure Matrix Method for Construction Project Scheduling under Rework Scenarios

Rework risks have been a major challenge in the construction industry that constantly affects project schedules and threatens on-time project completion. Traditional project scheduling methods are not capable of modeling rework relationships between activities and mitigating the impact of resulting uncertainties during the development of project schedules. To address this challenge, a critical chain design structure matrix (CCDSM) method is proposed in this paper. The CCDSM method aims to develop construction project schedules that are adaptive to rework scenarios and robust against rework risks. The CCDSM method models and displays large-scale rework relationships among activities and introduces a new rework buffer to quantitatively represent the impact of rework instances in project schedules. A max-plus algorithm is adopted in CCDSM to transform complex logic relationships into simple matrix operations, reducing computational load of schedule generation. A case study was conducted to demonstrate the implementation of the CCDSM method and assess its effectiveness in addressing rework risks. The results showed that the CCDSM is a promising tool to generate schedules, which could improve on-time project completion rate and reduce impacts of varying rework scenarios on project execution.

Monte Carlo simulation for tolerance analysis in prefabrication and offsite construction

Abstract Producing assemblies that experience little to no rework during assembly fit-up is a perennial challenge in offsite construction. While the traditional response has been to solve geometric issues onsite at the expense of large rework costs, manufacturing optimisation techniques can mitigate these issues upstream. Tolerance analysis is one such method that is widely used in manufacturing to predict if problems will occur from the accumulation of tolerances and dimensional variability. This article demonstrates Monte Carlo tolerance simulation on a prefabricated construction assembly, where variations up to 37 mm are identified compared to as-built deviations which range up to 30 mm. Process optimisation is also explored, where risk of rework related to dimensional variability is reduced by 65.6% through selection of alternate fabrication processes. To compare the Monte Carlo method to traditional analysis methods, a simplified 1-D tolerance analysis is used. Compared to an as-built deviation of roughly 11 mm, the Monte Carlo method produces a conservative value of 15.4 mm, while other traditional methods are either overly conservative (worst-case tolerance chain has a deviation of 19.8 mm), or overly ambitious (root sum square tolerance chain has a deviation of 4.6 mm). Tolerance analysis through Monte Carlo simulation is shown to be a proactive design tool with several key advantages for prefabricated and offsite construction. First, complex three-dimensional geometric interactions can be readily modelled using very basic tolerance configurations. Secondly, potential misalignments at key connection points can be identified and quantified in terms of a probability distribution of variation. Finally, design improvements can be achieved by comparing alternate construction processes to mitigate the risk of assembly rework.

Analysis of Rework Risk Triggers in the Nigerian Construction Industry

Abstract The construction industry plays a significant role in the infrastructure development of many countries. Construction projects suffer from a lot of setbacks despite sophistication and advancement in technology and pro­fessionalism. This study, therefore, assessed the factors that triggered the emergence of rework and the benefits derived from eliminating such triggers in the Nigerian construction industry. The study adopted a quantitative survey approach in which a structured questionnaire was adopted as the research instrument. Factor analysis using principal component analysis was adopted to determine the factors that triggered the rework and the pattern of relationship that existed amongst the factors; relative importance index (RII) was used to assess the benefits of eliminating rework triggers. The study concluded that the factors that triggered the emergence of rework were omis­sion and planning issues, change issues, funding and communication issues, and poor workers and resource control. Repeat patronage, higher productivity, and reduced delivery time reduced the rework and waste and improved the employee job satisfaction and morale; they were the benefits derived from eliminating rework trig­gers. It was recommended that there is a need for clarity, effectiveness, and timeliness of instruction and informa­tion dissemination amongst project participants and the participation of contractors, subcontractors, and other stakeholders at the design stages to avoid omissions and construction changes

Rework risks triggers in the Nigerian construction industry: a view of built environment professionals

Rework is systemic and a recurring decimal and It is triggered by several factors, which emergence create scenarios, which degrades project cost, quality and schedule performance, and overall project performance. This study therefore examined the perception of construction professionals on the factors that triggers the emergence of rework in the Nigerian construction industry. This was achieved by determining the predominant rework triggers that affect project performance, identifying rework triggers in which the professionals view varies significantly, and examining the category of rework risks triggers that contribute more to rework incidences. The study adopted a quantitative survey approach in which structured questionnaire was adopted as the research instrument. Mean item score was used in ranking the professionals perception on rework triggers, and Kruskal-Wallis H test was used to identify the variables in which the professionals view varies. The study concluded that: contractor-related and design-related causes are the major categories of rework risks triggers. Unclear instruction to workers, Shortage of skilled supervisors, incomplete and inaccurate information are the predominant triggers of rework. The professionals view varies significantly on nine factors which cut across the four categories of rework triggers. It was recommended that there is need for clarity, effectiveness and timeliness of instruction and information dissemination among project participants, and the use of skilled and experienced professionals, skilled supervisors and proper implementation of quality management practices by both the design consultant and contractor throughout the project’s phases

Design process robustness: a bipartite network analysis reveals the central importance of people

Design processes require the joint effort of many people to collaborate and work on multiple activities. Effective techniques to analyse and model design processes are important for understanding organisational dynamics, for improving collaboration, and for planning robust design processes, reducing the risk of rework and delays. Although there has been much progress in modelling and understanding design processes, little is known about the interplay between people and the activities they perform and its influence on design process robustness. To analyse this interplay, we model a large-scale design process of a biomass power plant with $100+$ people and ${\sim}150$ activities as a bipartite network. Observing that some people act as bridges between activities organised to form nearly independent modules, in order to evaluate process fragility, we simulate random failures and targeted attacks to people and activities. We find that our process is more vulnerable to attacks to people rather than activities. These findings show how the allocation of people to activities can obscure an inherent fragility, making the process highly sensitive and dependent on specific people. More generally, we show that the behaviour of robustness is determined by the degree distributions, the heterogeneity of which can be leveraged to improve robustness and resilience to cascading failures. Overall, we show that it is important to carefully plan the assignment of people to activities.