Michael R. Duffey

A model for effective implementation of Earned Value Management methodology

Abstract For better implementation of Earned Value Management (EVM) methodology in different types of organizations and projects (e.g. public and private; large and small projects), a model was developed based on a research effort over a 2-year period. The findings include: (1) EVM is gaining higher acceptance due to more favorable views related to both diminishing EVM problems and improving utilities; and (2) a broader approach considering four-factor groups (i.e. EVM users, EVM methodology, project environment, implementation process) together can significantly improve the acceptance and performance of EVM in different types of organizations and projects.

Scrap tires to crumb rubber: feasibility analysis for processing facilities

Crumb rubber can be produced from scrap tires in a wide range of particle sizes and quality levels. Ideally, the revenue stream includes tipping fees paid to receive the raw materials; sales of variously-sized crumb products to different end-user markets; and potential sales of scrap metal and fiber contained within the tires. General demand has been increasing, and submarkets for crumb products are growing in size and variety. However, the optimistic expectations of potential investors and government agencies contrast sharply with the experiences of many current and former producers. Production planning and operation is complex, real-dollar crumb prices have fallen, and many producers recount difficulties finding stable markets and competing against newer, state-subsidized competitors. This paper examines the engineering economics of crumb rubber facilities. Following a literature review and interviews with producers, a financial model of a nominal processing operation was created to aid the analysis of different market, crumb size, and production scenarios. The profitability of a crumb facility appears to be particularly sensitive to crumb rubber prices, operating costs, and raw material availability. Better analysis of market and production impacts on financial viability for proposed processing facilities would aid overall market efficiency.

Statistical dependence in risk analysis for project networks using Monte Carlo methods

Monte Carlo simulation of project networks is increasingly used by engineering firms to analyze schedule/cost risk for bidding purposes. However, one serious methodological flaw of most Monte Carlo simulations is the assumption of statistical independence of activity durations in the network. In this paper, a method is proposed to model and quantify positive dependence between uncertainty distributions of activities. This method inherits the theoretically sound foundations of the rank correlation method, but provides a less cumbersome method to elicit dependency information from project engineers. Details of the methodology are described along with an example of project risk analysis in a manufacturing domain (shipbuilding).

Design for tolerance of electro-mechanical assemblies: An integrated approach

Tolerancing decisions can profoundly impact the quality and cost of electro-mechanical assemblies. Existing approaches to tolerance analysis and synthesis in design entail detailed knowledge of geometry of the assemblies and are mostly applicable during advanced stages of design, leading to a less than optimal design process. During the design process of assemblies, both the assembly structure and associated tolerance information evolve continuously. Therefore, significant gains can be achieved by effectively using this information to influence the design of the assembly. Motivated by this, we identify and explore two goals for future research that we believe can enhance the scope of tolerancing for the entire design process. The first goal is to advance tolerancing decisions to the earliest possible stages of design. This issue raises the need for effective representation of tolerancing information during different stages of design and for effective assembly modeling. The second goal addresses the appropriate, synergistic use of available methods and best practices for tolerance analysis and synthesis, at successive stages of design. Pursuit of these goals leads to the definition of a multilevel approach that enables tolerancing to be addressed at successive stages of design in an incremental fashion. The resulting design process, which we call the design for tolerance process, integrates three important domains: (1) design activities at successive stages of design; (2) assembly models that evolve continuously through the design process; (3) methods and best practices for tolerance analysis and synthesis. We demonstrate major steps of our proposed approach through a simple, yet illustrative, example.

Technology selection and capacity investment under uncertainty

We analyze the problem of technology selection and capacity investment for electricity generation in a competitive environment under uncertainty. Adopting a Nash-Cournot competition model, we consider the marginal cost as the uncertain parameter, although the results can be easily generalized to other sources of uncertainty such as a load curve. In the model, firms make three different decisions: (i) the portfolio of technologies, (ii) each technology’s capacity and (iii) the technology’s production level for every scenario. The decisions related to the portfolio and capacity are ex-ante and the production level is ex-post to the realization of uncertainty. We discuss open and closed-loop models, with the aim to understand the relationship between different technologies’ cost structures and the portfolio of generation technologies adopted by firms in equilibrium. For a competitive setting, to the best of our knowledge, this paper is the first not only to explicitly discuss the relation between costs and generation portfolio but also to allow firms to choose a portfolio of technologies. We show that portfolio diversification arises even with risk-neutral firms and technologies with different cost expectations. We also investigate conditions on the probability and cost under which different equilibria of the game arise.

Formulation of financial valuation methodologies for NASA's human spaceflight projects

The National Aeronautics and Space Administration (NASA) must continually evaluate proposals to upgrade its human spaceflight systems. These proposals may be initiated to enhance safety, improve performance, or provide improved cost value. In the current restrictive budget environment, the cost valuation should be strengthened to ensure the best use of limited funding. NASA has not frequently utilized financial analysis in project consideration, and business case analysis is often lacking during annual budgetary assessments. Some of the reasons inhibiting financial analysis are uncertainty in the projections of long life-cycle costs, gains that may seem intangible and difficult to mone-tize, and the political environment. This paper explores ways in which some financial valuation methods, coupled with reformulation of project cash flows, might enhance NASAs analysis process. Among these methods is real option analysis (ROA), which is discussed in the context of several NASA upgrade projects.

Optimal Capital Structure and Financial Risk of Project Finance Investments: A Simulation Optimization Model With Chance Constraints

We investigate the use of chance constraints in modeling the debt financing decision under conditions of debt heterogeneity and uncertainty. We develop a stochastic financial model that uses simulation optimization to select an optimal mix of fixed-rate debt instruments from different sources, with the objective of maximizing net present value (NPV) while limiting default risk. We then use simulation to evaluate the performance of the resulting debt policy. Numerical results from our model indicate that in a world of uncertainty, project promoters who wish to create bankable proposals for project financing, by limiting the probability of default, should spread debt across different maturities.

A Framework for Financial Analysis of Offshore Wind Energy

The financial viability of an offshore wind project is dependent on many interrelated, site-specific factors. However, existing analysis tools in the public domain are not adequate to comprehensively evaluate proposed offshore projects for involved parties including potential investors, developers, and policy makers. Each site requires unique optimization of the physical design (for turbines, support structures, and farm parameters) to calculate a minimum cost of energy. Also specific to each offshore project are: 1) local deregulated power networks which impact revenues and penalty costs in the bidding process; 2) complex financing structures with multiple participants; 3) monetization of environmental impacts specific to energy sold/generated in a power network, including avoided emissions of displaced generations; 4) uncertain permitting and payment schedules which impact commissioning costs. This paper presents an Offshore Wind Integrated Cost model (OFWIC) that attempts to comprehensively include these factors. It summarizes the model architecture, describes implementation issues, and discusses case study results for a proposed offshore site near Cape Cod, Massachusetts. Because the comprehensive cost calculations can provide insights beyond those of existing, public domain methodologies, further research on this type of model may be warranted.

Requirements, Methods and Research Issues for Modeling the Product Realization Process

This paper presents a bottom up introduction to process modeling requirements for product realization which should drive new methods and computer tools. Though relatively high-level and organizational in scope, these models are attracting interest among design engineers, system engineers and technical managers whose decisions affect the complex downstream task interactions that cross organizational boundaries. A recent study of industrial usage, industrial requirements, and research issues is presented.