Additional Project Costs Research Articles

Implementation of CPM and PERT Method in Canteen Development Project CV Super Makmur

Project management is the science and art concerned with planning, organizing, implementing, and controlling projects to achieve predefined goals by utilizing available resources optimally. The CPM (Critical Path Method) method is a deterministic approach that identifies the longest path of activities in a project, while the PERT (Program Evaluation and Review Technique) method is used to plan, estimate and control completion time by considering the uncertainty in each project activity. The goal to be achieved from this research is that the application of the method and implementation of the CPM and PERT methods can optimize project completion by knowing critical activities, operations, estimated time, costs and project resources, as well as reducing the risk of delays and additional project costs. This research adopts a quantitative approach and applies descriptive analysis using the CPM and PERT methods. Based on the analysis results, it is known that there are two critical paths, namely A-C-E-I and B-D-G-K, so accelerating the project time without delaying or waiting for completion in 11 weeks, with a value of Z = 2.27 in the normal distribution table shows the number 0.9984, meaning the probability that the project can be completed during 11 weeks is 99%. because there is an additional fee of IDR 2,588,940 which is an additional acceleration fee. So, the cost of completing a 12-week project is IDR 1,171,739,257 while for 11 weeks it is IDR 1,174,328,197.

Importance and Performance Analysis of Construction Management Activities in Construction Projects in Pulang Pisau Regency Based on Contractor Perceptions

Construction is a system that always involves many parties from the planning, implementation (doing), until controlling which in the process can cause problems that will affect project performance. In the implementation of construction projects, problems often occur, including the extension of work execution time, delays, additional project costs and work results that are not in accordance with the planned quality. This study aims to identify and make instruments measuring the effect of management activities on the performance of construction projects in Pulang Pisau Regency. There are 120 variables used to measure project management performance from two viewpoints of the level of satisfaction/perception and interests/expectations. Then an evaluation using the Importance Performance Analysis (IPA) method is performed. From the results of the analysis by the Importance Performance Analysis (IPA) method it can be seen that project management activity variables are the top priority that need to be improved in order to improve construction project performance, including 12 variables which are divided into 4 variables each at the planning stage, 3 variables at the implementation stage, and 5 variables at the control stage.

Nuclear decommissioning risk management adopting a comprehensive artificial intelligence framework: An applied case in an Italian site

The increase of nuclear sites entering the decommissioning phase has drawn the attention of governments, regulatory bodies, and industries to decommissioning projects. However, despite the high number of uncertainties and risks of these projects, there is a lack of dedicated risk management frameworks beyond the guidelines established by the International Atomic Energy Agency (IAEA) and the Project Management Institute (PMI). This study aims to propose an integrated framework for managing risks in Nuclear Decommissioning Projects. For the development of the framework artificial intelligence algorithms were employed, integrating models derived from the manufacturing sector capable of assessing risks, identifying an optimal set of risk mitigation actions, and predicting the additional project delay or cost based on a quantitative risk analysis. To demonstrate its validity, the model was applied to a nuclear decommissioning project currently underway in Italy, generating a forecast of the final project delay. The results showed to be promising, as the delay prediction for the analysed phase of the project differs from the current one only by an error of 4.7%. The proposed model can help project managers in managing risks and predicting delays or additional project costs during the preliminary phase. In addition, the framework is equally useful for controlling risks in the progress stages of the project by dynamically updating forecasts.

Improving the detection of community smells through socio‐technical and sentiment analysis

AbstractOpen source software development is regarded as a collaborative activity in which developers interact to build a software product. Such a human collaboration is described as an organized effort of the “social” activity of organizations, individuals, and stakeholders, which can affect the development community and the open source project health. Negative effects of the development community manifest typically in the form of community smells, which represent symptoms of organizational and social issues within the open source software development community that often lead to additional project costs and reduced software quality. Recognizing the advantages of the early detection of potential community smells in a software project, we introduce a novel approach that learns from various community organizational, social, and emotional aspects to provide an automated support for detecting community smells. In particular, our approach learns from a set of interleaving organizational–social and emotional symptoms that characterize the existence of community smell instances in a software project. We build a multi‐label learning model to detect 10 common types of community smells. We use the ensemble classifier chain (ECC) model that transforms multi‐label problems into several single‐label problems, which are solved using genetic programming (GP) to find the optimal detection rules for each smell type. To evaluate the performance of our approach, we conducted an empirical study on a benchmark of 143 open source projects. The statistical tests of our results show that our approach can detect community smells with an average F‐measure of 93%, achieving a better performance compared to different state‐of‐the‐art techniques. Furthermore, we investigate the most influential community‐related metrics to identify each community smell type.

Impact of Economic and Financial, Construction Technology and Resources, and Project Organizational Culture on Project Performance Studies at PT. PLN UPP Kitring, Centre Part Borneo-1

Project construction is a dynamic and complex system that involves many parties from the planning stage to the project handover stage. The problems that arise are varied and generally vary from one project to another, but these problems affect project performance. Project performance is assessed from the time of project execution, the quality or quality of the project and the costs used in the construction project. Problems that arise in a project often lead to an extension of the project implementation time, additional project costs and work results that do not match the quality of the agreement. This study aims to determine the influence of the internal and external environment on project performance, especially the electricity system development project in Borneo. Internal and external environmental factors are taken from related studies as well as previous research that has been carried out in various countries and regions. It can be concluded that economic and financial factors (X1), technology factors and construction resources (X2) and project organizational culture factors (X3) are the factors causing project performance problems (Y).

Pipejacking clogging detection in soft alluvial deposits using machine learning algorithms

‘Clogging’ is a common issue encountered during tunnelling in clayey soils which can impede tunnel excavation, cause unplanned downtimes and lead to significant additional project costs. Clogging can result in a drastic reduction in performance due to reduced jacking speeds and the time needed for cleaning if it cannot be fully mitigated. The data acquired by modern tunnel boring machines (TBMs) have grown significantly in recent years presenting a substantial opportunity for the application of data-driven artificial intelligence (AI) techniques. In this study, a baseline assessment of clogging in slurry-supported pipejacking is performed using a combination of TBM parameters and semi-empirical diagrams proposed in the literature. The potential for one-class support vector machines (OCSVM), isolation forest (IForest) and robust covariance (Robcov) to assess the tendency for clogging is then explored in this work. The proposed approach is applied to a pipejacking case history in Taipei, Taiwan, involving tunnelling in soft alluvial deposits. The results highlight an exciting potential for the use of AI techniques to detect clogging during slurry-supported pipejacking.

Exploring Community Smells in Open-Source: An Automated Approach

Software engineering is now more than ever a community effort. Its success often weighs on balancing distance, culture, global engineering practices and more. In this scenario many unforeseen socio-technical events may result into additional project cost or “social” debt, e.g., sudden, collective employee turnover. With industrial research we discovered community smells , that is, sub-optimal patterns across the organisational and social structure in a software development community that are precursors of such nasty socio-technical events. To understand the impact of community smells at large, in this paper we first introduce CodeFace4Smells , an automated approach able to identify four community smell types that reflect socio-technical issues that have been shown to be detrimental both the software engineering and organisational research fields. Then, we perform a large-scale empirical study involving over 100 years worth of releases and communication structures data of 60 open-source communities: we evaluate (i) their diffuseness, i.e., how much are they distributed in open-source, (ii) how developers perceive them, to understand whether practitioners recognize their presence and their negative effects in practice, and (iii) how community smells relate to existing socio-technical factors, with the aim of assessing the inter-relations between them. The key findings of our study highlight that community smells are highly diffused in open-source and are perceived by developers as relevant problems for the evolution of software communities. Moreover, a number of state-of-the-art socio-technical indicators (e.g., socio-technical congruence) can be used to monitor how healthy a community is and possibly avoid the emergence of social debt.

Learning to detect community smells in open source software projects

Community smells are symptoms of organizational and social issues within the software development community that often lead to additional project costs. Recent studies identified a variety of community smells and defined them as sub-optimal patterns connected to organizational-social structures in the software development community. To early detect and discover existence of potential community smells in a software project, we introduce, in this paper, a novel machine learning-based detection approach, named csDetector, that learns from various existing bad community development practices to provide automated support in detecting such community smells. In particular, our approach learns from a set of organizational-social symptoms that characterize the existence of potential instances of community smells in a software project. We built a detection model using Decision Tree by adopting the C4.5 classifier to identify eight commonly occurring community smells in software projects. To evaluate the performance of our approach, we conduct an empirical study on a benchmark of 74 open source projects from Github. Our statistical results show a high performance of csDetector, achieving an average accuracy of 96% and AUC of 0.94. Moreover, our results indicate that the csDetector outperforms two recent state-of-the-art techniques in terms of detection accuracy. Finally, we investigate the most influential community-related metrics to identify each community smell type. We found that the number of commits and developers per time zone, the number of developers per community, and the social network betweenness and closeness centrality are the most influential community characteristics.

Software Architecture Social Debt: Managing the Incommunicability Factor

Architectural technical debt is the additional project cost connected to technical issues nested in software architectures. Similarly, many practitioners have already experienced that there exists within software architectures a form of social debt, that is, the additional project cost connected to sociotechnical and organizational issues evident in or related to software architectures. This paper illustrates four recurrent antipatterns or community smells connected to such architectural social debt and outlines a means to measure the additional project cost connected to their underlying cause: decision incommunicability . Evaluating the results in multiple focus groups, this paper concludes that studying social debt and community smells at the architecture level may prove vital to rid software development communities of critical organizational flaws incurring considerable additional cost.

Beyond Technical Aspects: How Do Community Smells Influence the Intensity of Code Smells?

Code smells are poor implementation choices applied by developers during software evolution that often lead to critical flaws or failure. Much in the same way, community smells reflect the presence of organizational and socio-technical issues within a software community that may lead to additional project costs. Recent empirical studies provide evidence that community smells are often—if not always—connected to circumstances such as code smells. In this paper we look deeper into this connection by conducting a mixed-methods empirical study of 117 releases from 9 open-source systems. The qualitative and quantitative sides of our mixed-methods study were run in parallel and assume a mutually-confirmative connotation. On the one hand, we survey 162 developers of the 9 considered systems to investigate whether developers perceive relationship between community smells and the code smells found in those projects. On the other hand, we perform a fine-grained analysis into the 117 releases of our dataset to measure the extent to which community smells impact code smell intensity (i.e., criticality). We then propose a code smell intensity prediction model that relies on both technical and community-related aspects. The results of both sides of our mixed-methods study lead to one conclusion: community-related factors contribute to the intensity of code smells. This conclusion supports the joint use of community and code smells detection as a mechanism for the joint management of technical and social problems around software development communities.

Hybrid Simulation Framework for Immediate Facility Restoration Planning after a Catastrophic Disaster

AbstractSince the effects of external conditions, such as limited resource supplies and poor working environments in damaged regions, are critical to facility restoration projects after a catastrophic disaster, a lack of understanding regarding restoration conditions may lead to unexpected delays and additional project costs. The fact that various elements of postdisaster restoration conditions interact with each other and vary with a facility’s surrounding damage and recovery situations over time makes many stakeholders’ comprehension even more challenging. To support immediate and appropriate facility restoration planning under changing project conditions, this study developed a hybrid system dynamics (SD)–discrete event simulation (DES) framework. In this hybrid restoration simulation, SD allows for a comprehensive understanding of the dynamic features of various restoration conditions, while DES enables an in-depth examination of facility restoration operations according to external condition changes....

Facilitating feral camel removal in Australia through commercial use

Approximately 16.5% of feral camel removal under the Australian Feral Camel Management Project (AFCMP) was by commercial means, via mustering for transport to abattoir (9.3%) and pet-meating in the field (7.2%). The challenges of commercial use of feral camels as a removal method include: variable density, mobility and distribution of the feral camel population; achieving landholder collaboration; accessibility to remote areas by road; availability of yard infrastructure and trucking capacity; and distance to slaughter facilities and end-markets. However, the AFCMP recognised commercial use as important to some Aboriginal communities, bringing a range of economic and social benefits as well as environmental outcomes in terms of reduced feral camel density. To facilitate mustering offtake, a removal assistance scheme was developed, whereby a formal landholder agreement was entered into with various legal requirements, including animal welfare. The agreement incentivised removal of both sexes: payments were for cow camels received at abattoir, but with a concurrent requirement for approximately equal sexes to be delivered to abattoir in an annual contract period. Additional project costs included contract development and oversight, landholder engagement, training and animal welfare auditing. Pet-meating, by way of ground culling and in-field butchering for meat storage in mobile refrigeration units, was also supported by the AFCMP via measures to increase harvest efficiency such as satellite tracking, aerial spotting and improved road access. However, pet-meating ceased mid-project due to changed industry demands. Post-AFCMP, mustering operations continue to service market demand for camel meat. The camel industry is also looking to camel farming to ensure greater continuity and quality of supply than can be achieved through wild harvest.

Lessons Learned on the Presentation of Scan Data.

Technicians performed a radiological survey of a surplus metal tank to support disposition planning at an Oak Ridge, TN, site. The survey included radiation scans to identify contamination and, if identified, define the boundary and magnitude of contamination. Fixed-point 1-min measurements were also collected at randomly selected locations for comparison against the site's free release limit of 5,000 disintegrations per minute per 100 cm (dpm 100 cm) (0.83 Bq cm). Scan data were recorded using a data logger as a means to document surveyor observation-logged data captured at 1-s intervals and converted to counts per minute (cpm) by the data logger software were presented in the project report. Both the qualitative scan data (in cpm) and the quantitative direct measurements (in dpm 100 cm) were reported for completeness, so stakeholders had all available information to support disposition decisions. However, a new stakeholder-introduced to the project at the reporting phase of work-used the instrument efficiency and background data to convert the scan data from cpm to dpm 100 cm, then compared the converted results to the site limit. Many of the converted values exceeded 5,000 dpm 100 cm. This resulted in delays in tank disposition and additional project costs that could have been avoided if the proper use and interpretation of scan data and implications of radon progeny buildup on oxidized metal surfaces had been better communicated.

Separating project risk from the time value of money: A step toward integration of risk management and valuation of infrastructure investments

The rationale for using heuristics to establish a risk premium that is added to the risk-free rate to obtain the value of an investment is questioned and an alternative method, termed decoupled net present value (DNPV), is proposed. Rather than using utility theory concepts to decrease the value of uncertain cash flows, the risks associated with project cash flows are discretely quantified using insurance and contingent claim valuation concepts. Synthetic insurance premiums are designed to “protect” the value of expected cash flows which are treated as additional project costs. Because identified project risks are quantified in financial terms and treated as a real cost to the project, DNPV allows business executives to evaluate the effect on the value of the project of different risks and select management techniques that are deemed more effective. Hence, DNPV is both a valuation methodology and a risk management tool.

The Proportion of Three Foundation Plant Species and Their Genotypes Influence an Arthropod Community: Restoration Implications for the Endangered Southwestern Willow Flycatcher

AbstractAs part of a restoration project, multiple genotypes of two tree species, Fremont cottonwood (Populus fremontii) and Goodding's willow (Salix gooddingii), and one shrub species, Coyote willow (S. exigua), were experimentally planted in different proportions at the Palo Verde Ecological Reserve near Blythe, California, U.S.A. These common woody plant species are important to the endangered southwestern willow flycatcher, providing perch, nesting, and foraging habitat. We conducted this study to evaluate plant species proportion and plant genotype effects on the arthropod community, the prey base for the endangered southwestern willow flycatcher. Three patterns emerged. First, plant species proportions were important; the arthropod community had the greatest richness and diversity (H′) when Goodding's willow proportion was high and Fremont cottonwood proportion was lower; that is, fewer Fremont cottonwoods are required to positively affect overall arthropod diversity. Second, we found significant genotypic effects, for all three plant species, on arthropod species accumulation. Third, while both planting proportion and genotype effects were significant, we found that the effect of planting proportion on arthropod richness was about twice as large as the effect of plant genotype. This shows that both plant species proportions and genotype should be utilized in restoration projects to maximize habitat heterogeneity and arthropod richness. Similar studies can determine which planting proportion and specific genotypes may result in a more favorable arthropod prey base for the southwestern willow flycatcher and other species of concern. Greater attention to planting design and genotype can result in significant gains in diversity at little or no additional project cost.

A case study on project-level CO2 mitigation costs in industrialised countries: the Climate Cent Foundation in Switzerland

This paper analyses CO2 emissions reduction costs based on project data from the Climate Cent Foundation (CCF), a climate policy instrument in Switzerland. Four conclusions are drawn. First, for the projects investigated, the CCF on average pays €63/ton. Due to the Kyoto Protocol, the CCF buys reductions only until 2012. This cut-off increases reported per ton reduction costs, as the additional lifetime project costs are set in relation to reductions only until 2012, rather than to reductions realised over the whole lifetime. Lifetime reduction costs are €45/t. Second, correlation between CCF's payments and lifetime reduction costs per ton is low. Projects with low per ton reduction costs should thus be identified based on lifetime per ton reduction costs. Third, the wide range of project costs per ton observed casts doubts on the widely used identification of the merit order of reduction measures based on average per ton costs for technology types. Finally, the CCF covers only a fraction of additional reduction costs. Decisions to take reduction efforts thus depend on additional, non-observable and/or non-economic motives. Any generalisation of results has to consider that this analysis is based on prospective costs of a sub-sample of projects in Switzerland.

Lean Processes for Sustainable Project Delivery

Facility owners and project teams often struggle to engage “green” or “sustainable” requirements on building projects and can incur additional project costs as a result. Although “investments” in high performance building features can be paid back through operational savings, the project delivery methods currently adopted by most teams are laden with process waste. Lean production principles have been proven to reduce waste and improve process performance in highly complex development and production environments. Adopting these lean principles, this paper reports a study that identified the presence of value and waste in a sustainable building project. Through an empirical investigation of the Real Estate and Facilities Division of Toyota Motor Sales, Toyota’s capital facility delivery process was mapped to identify both the steps in project delivery critical for success (value) and those that are waste. The investigation focused on the South Campus Facility, which received U.S. Green Building Council’s Leadership in Energy and Environmental Design Gold certification at a project cost equivalent to a conventional facility. Through post hoc process-based analysis, insight about what added value and waste in sustainable project delivery at Toyota was obtained. The results also identify further improvement opportunities to Toyota’s delivery process. For corporate facility owners and the Architecture Engineering Construction industry, the results unearth insights about how to successfully and economically deliver sustainable facilities.

CASE STUDY OF ABORIGINAL INVOLVEMENT AND ISSUES—SOUTH WEST QUEENSLAND PIPELINE

The South West Queensland Pipeline project has set a new benchmark for Aboriginal involvement in corridor project planning and construction in Australia.Before the final pipeline alignment was decided, Tenneco Energy Australia (now Epic Energy), the Queensland Government and the Goolburri Aboriginal Corporation Land Council arranged for Aboriginal Researchers to conduct a foot survey along a 200 in wide corridor for the full 756 km of the pipeline route. The final alignment was selected to avoid all cultural heritage sites identified by the Aboriginal Researchers.At the commencement of the construction phase, a Cultural Heritage Management Plan (CHMP) covering construction activities was developed. Key components were as follows:Goolburri Aboriginal Corporation Land Council engaged as a service provider to provide Aboriginal Researchers, a Cultural Heritage Management Officer (CHMO), and an auditor for the project;Four Aboriginal monitors to be present on the project during clear, grade and trenching activities;An archaeologist to be present on the project to coordinate Aboriginal monitoring and cultural heritage management activities;A cultural heritage management audit to be conducted at the end of each four-week work cycle to identify non-conformances with the CHMP and recommend improvements;Cultural awareness training to be undertaken by the workforce and presented by Aboriginal representatives; andInstant dismissal provisions for serious infringements of the CHMP.The cultural heritage clearance process and the CHMP were probably the most extensive ever implemented for a pipeline project in Australia in terms of the extent and nature of Aboriginal involvement. Despite this, there was ongoing concern about whether the appropriate Aboriginal groups were being involved in the project. Cultural heritage management of the project became linked to the question of traditional association with the land and native title rights. Disparate views about the rights of different Aboriginal groups continually emerged.Of particular note was a tribal boundary dispute which resulted in prematurely closing down the first cycle of construction and leapfrogging the 108 km stretch under dispute to provide Aboriginal groups with time to resolve the issue. This action directly resulted in additional project costs (construction rescheduling and backtracking crews) in the order of $5 million.This case study will look particularly at:the process of cultural clearance and cultural heritage management which evolved for the project;issues associated with establishing appropriate Aboriginal representation for involvement in the project;native title claims; andsuggestions for improving management of native title, cultural heritage and Aboriginal involvement issues for future projects.

Ada compiler selection for embedded targets

Although mainframe Ada compilers have reached execution as well as reliability performance characteristics of languages such as FORTRAN, the same is not true of embedded system compilers. Finding a reliable cross-compiler for widely used and powerful micro-processors such as the Motorola 68000 family is extremely difficult, if not impossible. First quarter '87 cross-compiler users face many tough trade-offs and additional project costs due to time lost developing compiler work-arounds. Although the user community appreciates the technological challenges of building an Ada compiler, it is still faced with trying to use incomplete and somewhat unstable systems while trying to deliver efficient, ultra-reliable code. In order to help both vendors and users alike, this article presents a set of evaluation criteria that may be used in selecting an Ada compiler for embedded system applications. Given the progress made with mainframe compilers, the major focus is on robustness, reliability, run-time system, and cross-compiler tools.

Product Specification Practices and Problems

The technical product specifications of construction contracts and the associated submittal review processes are shown to be involved in a major portion of all serious project disputes. A large number of actual publicly‐funded water and wastewater treatment facility building projects were examined with subsequent analysis of those reviews indicating that these disputes are detrimental in terms of additional project cost, schedule delays, and overall project disruption and loss of goodwill. In particular, the proprietary “brand name or equal” product specification method is seen to be commonly at the heart of these product disputes. Several different solution strategies were expressed as statistical hypotheses and tested for effectiveness. Among other propositions, the managerial strategies of required bid listing of proposed products, timely dispute resolution, and clarifying the submittal review process proved to be realistic and effective tools for reducing both the incidence and severity of product‐related contract disputes. Exact details are put forward along with sensitivity ranges.