Data-driven through-life costing to support product lifecycle management solutions in innovative product development

Innovative product usually refers to product that comprises of creativity and new ideas. In the development of such a new product, there is often a lack of historical knowledge and data available to be used to perform cost estimation accurately. This is due to the fact that traditional cost estimation methods are used to predict costs only after a product model has been built, and not at an early design stage when there is little data and information available. In light of this, original equipment manufacturers are also facing critical challenges of becoming globally competitive and increasing demands from customer for continuous innovation. To alleviate these situations this research has identified a new approach to cost modelling with the inclusion of product lifecycle management solutions to address innovative product development.The aim of this paper, therefore, is to discuss methods of developing an extended-enterprise data-driven through-life cost estimating method for innovative product development

Real Option Valuation of a Portfolio of Oil Projects

Various methodologies exist for valuing companies and their projects. We address the problem of valuing a portfolio of projects within companies that have infrequent, large and volatile cash flows. Examples of this type of company exist in oil exploration and development and we will use this example to illustrate our analysis throughout the thesis. The theoretical interest in this problem lies in modeling the sources of risk in the projects and their different interactions within each project. Initially we look at the advantages of real options analysis and compare this approach with more traditional valuation methods, highlighting strengths and weaknesses ofeach approach in the light ofthe thesis problem. We give the background to the stages in an oil exploration and development project and identify the main common sources of risk, for example commodity prices. We discuss the appropriate representation for oil prices; in short, do oil prices behave more like equities or more like interest rates? The appropriate representation is used to model oil price as a source ofrisk. A real option valuation model based on market uncertainty (in the form of oil price risk) and geological uncertainty (reserve volume uncertainty) is presented and tested for two different oil projects. Finally, a methodology to measure the inter-relationship between oil price and other sources of risk such as interest rates is proposed using copula methods.Imperial Users onl

Risk-Based Decision Making Support for Construction Corporate Resource Management

Competitive bidding typically challenges contractors to stay in business by reducing contingency and limiting profit margin, which imposes more prudent resource utilization and allocation decisions during both planning and construction phases of projects. Many of these decisions must be made considering uncertainties that affect resource production and construction performance through several factors such as weather, managerial practices, job-type, and market conditions, etc. Construction decision makers will therefore have varied approaches to deal with these uncertainties based on their risk utility or perception. This research presents the development of a model for investigating the impact of risk-based approaches on construction network outcomes. The current study contributes to development of a model that enables corporate managers to understand the impact of different resource utilization and sharing policies on the overall outcome of their project and to select among optimum planning solutions that satisfy their profit margin and capital limitations. This research also enables corporate decision makers to have more realistic estimates for the profitability of their company, and understand consequences of their decisions in short and long term. Findings of this research provide decision makers with different solutions for profitability of their corporation based on non-dominated optimal time-cost trade-offs, and also broader perspective on how overall time and budget limitations, as well as risk perceptions, can affect the decision-making process. The model is verified and the results are validated through acquiring data from actual large scale construction projects in South Florida

Status and Future Perspectives for Lattice Gauge Theory Calculations to the Exascale and Beyond

In this and a set of companion whitepapers, the USQCD Collaboration lays out a program of science and computing for lattice gauge theory. These whitepapers describe how calculation using lattice QCD (and other gauge theories) can aid the interpretation of ongoing and upcoming experiments in particle and nuclear physics, as well as inspire new ones.Comment: 44 pages. 1 of USQCD whitepapers

Analog, hybrid, and digital simulation

Analog, hybrid, and digital computerized simulation technique

Development of Simulation Based Approaches for Cost Estimation and Effect Analysis in Industrial and Humanitarian projects, Including System Dynamic Model and Monte Carlo Simulation

Cost management has become an integral part of management fields these days and has acquired great weight in the sector of project management as well. For most beneficiaries in the industry and humanitarian field, the management of projects is synonymous with the management of cost that affects directly the funds they need to mobilize to deliver their scheme. This thesis deals with the development and validation of simulation-based methods in the industry and the humanitarian field. In addition, several novel methods of cost management have been proposed considering the complexity of different factors. In the industry field, construction projects are characterized by great uncertainty. Appropriate risk analysis techniques are required to estimate the adequate coverage level against the occurrence of extra costs to increase the progress of the project in the tenders. The project margin increases when an excessive provision leads to more comprehensive coverage of the risks. Also, an accurate estimation of the contingency reserve is a crucial subject in construction projects to reduce the risk of overruns\u2019 costs to an acceptable level and ensure the competitiveness of the company\u2019s bid. To achieve this goal, a Company\u2019s traditional approach has been applied to a real railway project and then a stochastic Risk Mode and Effect Analysis (RMEA) methodology base on Monte Carlo Simulation compared with the outcome of the company\u2019s traditional approach applied to the same project. Most of the contingency estimation methods are included problems of subjectivity, complex mathematical models, and inaccurate estimation. This research proposes a combination of the Risk Mode and Effect Analysis (RMEA) with Monte Carlo Simulation (MCS) to determine the amount of allocated contingency fund that overcomes other methods\u2019 limitations. The output of the analysis is a cumulative distribution function that demonstrates a coverage level related to the contingency amount to control extra cost and reduce the amount of contingency in projects. The developed method is validated by applying a real construction project and the obtained results are compared with the outcomes\u2019 of the company\u2019s traditional approach, clearly demonstrate the potential and the benefits of the proposed methodology. The result of the proposed method allows the decision-makers to operate with a lower contingency amount and control extra expenses of projects. In addition, a Decision Support System (DSS) approach using Failure Mode Effect Analysis and Monte Carlo Simulation has been discussed in this chapter. Besides, in the humanitarian field, A System Dynamic (SD) model has been applied to a humanitarian project to study the impact of different levels of financial aid paid to beneficiaries for different impact factors and estimate financial aid variation. Natural and man-made disasters seem unpredictable every year, increasing a wide range of universal sufferers. Several people are affected by the direct outcomes of these disasters, and their life depends on disaster relief aid administered by humanitarian organizations. Recently, there has been renewed interest in cash distribution in the humanitarian sector during disaster relief to increase access of vulnerable people to supporting services such as health or education and develop their life\u2019s condition while rising the efficiency of humanitarian organizations committed to the program. The research proposes a casual-loop and system dynamic model to assess multi aspects of related impact factors to provide optimal support of beneficiaries. The model provides a decision-making framework with a high-level overview of the interactions between the education and health aspects of the recipient\u2019s life, provides a system dynamics analysis including interactions that could have led to improving the vulnerable people's condition life. This system dynamics approach can be used to study the significant factors on education and health aspects of refugee crises such as the case of Syrian refugees in Turkey. Reviewing the humanitarian management literature, a causal loop is developed to better understand the health and education variables and their interactions. Then a system dynamic model is proposed and validated by historical data of Syrian refugees in Turkey. The result of financial aid sensitivity shows that more financial aid from humanitarian organizations are significantly improved the general health of refugees and also it is caused higher attendance for children in schools. In addition, enhanced financial aid supports can lead to improving access to water and hygiene facilities and also building more schools for their children

Lessons Learned and Next Steps in Energy Efficiency Measurement and Attribution: Energy Savings, Net to Gross, Non-Energy Benefits, and Persistence of Energy Efficiency Behavior

This white paper examines four topics addressing evaluation, measurement, and attribution of direct and indirect effects to energy efficiency and behavioral programs: Estimates of program savings (gross); Net savings derivation through free ridership / net to gross analyses; Indirect non-energy benefits / impacts (e.g., comfort, convenience, emissions, jobs); and, Persistence of savings

6th International Probabilistic Workshop - 32. Darmstädter Massivbauseminar: 26-27 November 2008 ; Darmstadt, Germany 2008 ; Technische Universität Darmstadt

These are the proceedings of the 6th International Probabilistic Workshop, formerly known as Dresden Probabilistic Symposium or International Probabilistic Symposium. The workshop was held twice in Dresden, then it moved to Vienna, Berlin, Ghent and finally to Darmstadt in 2008. All of the conference cities feature some specialities. However, Darmstadt features a very special property: The element number 110 was named Darmstadtium after Darmstadt: There are only very few cities worldwide after which a chemical element is named. The high element number 110 of Darmstadtium indicates, that much research is still required and carried out. This is also true for the issue of probabilistic safety concepts in engineering. Although the history of probabilistic safety concepts can be traced back nearly 90 years, for the practical applications a long way to go still remains. This is not a disadvantage. Just as research chemists strive to discover new element properties, with the application of new probabilistic techniques we may advance the properties of structures substantially. (Auszug aus Vorwort