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Expansion Planning For Transmission Network Under Demand Uncertainty: A Real Options Framework, Fikri Fucuksayacigil, K. Jo Min 2019 Iowa State University

Expansion Planning For Transmission Network Under Demand Uncertainty: A Real Options Framework, Fikri Fucuksayacigil, K. Jo Min

Kyung J. Min

In recent years, there has been much expectation that transmission expansion planning should address ever increasing demands for transmission services under significant and complex economic and regulatory uncertainties. In this article, toward meeting the aforementioned expectation, we develop and analyze a real options framework that provides the valuation of a transmission owner’s option to expand in his or her network. What distinguishes our framework from the extant literature is that the evolution of the demand follows a geometric Brownian motion process, it explicitly accounts for the physical flow of the electric power economically manifested as the locational marginal prices ...


Transmission Expansion Planning With Transformer Replacement, Mujing Ye, Sarah M. Ryan, James D. McCalley 2019 Iowa State University

Transmission Expansion Planning With Transformer Replacement, Mujing Ye, Sarah M. Ryan, James D. Mccalley

Sarah M. Ryan

Investments in high-voltage transmission facilities require large financial commitments and significantly affect the future reliability and economy of the interconnected power system. Transmission expansion planning is complicated by the potential component unavailability due to forced or scheduled outage. Transformers comprise one important set of system components of which many in current use are reaching an advanced service age. Condition monitoring technologies can help improve predictions of their reliability. We formulate and analyze an optimization model for transmission expansion planning and transformer replacement that accounts for transformer as well as transmission line reliability and solve a small instance in a reasonable ...


Option Pricing Methods For Estimating Capacity Shortages, Dohyun Pak, Sarah M. Ryan 2019 Iowa State University

Option Pricing Methods For Estimating Capacity Shortages, Dohyun Pak, Sarah M. Ryan

Sarah M. Ryan

Uncertain demand combined with a positive lead time for adding capacity creates the risk of capacity shortage during the lead time. Accurate shortage estimation is very important to determine a capacity expansion policy. In this paper, we investigate four kinds of option pricing methods to estimate the shortage during a fixed lead time under the assumption of an exponential trend for demand growth. We compare the effect of the different shortage measures on the optimal parameters for an expansion policy over the long term.


Optimal Solution To A Capacity Expansion Problem, Rahul R. Marathe, Sarah M. Ryan 2019 Iowa State University

Optimal Solution To A Capacity Expansion Problem, Rahul R. Marathe, Sarah M. Ryan

Sarah M. Ryan

For a service provider, stochastic demand growth along with expansion lead times and economies of scale may encourage delaying the start of expansion until after some shortages have been accumulated. Assuming demand follows a geometric Brownian motion, we define the service level in terms of the proportion of demand satisfied, which is then analytically evaluated using financial option pricing theory. Under a stationary expansion policy, an infinite time horizon discounted expansion cost is minimized under the service level constraint, where the expansion timing and size parameters are the decision variables. With the current formulation, the problem seems to be unbounded.


Closed-Loop Supply Chain Network Design Under Carbon Emission Regulations, Nan Gao, Sarah M. Ryan 2019 Iowa State University

Closed-Loop Supply Chain Network Design Under Carbon Emission Regulations, Nan Gao, Sarah M. Ryan

Sarah M. Ryan

This paper considers a closed–loop supply chain (CLSC) network design problem that accounts for the impact of carbon emission regulations. Three regulatory policy settings are considered; namely, (a) firms are subject to mandatory carbon caps on the amount of carbon they emit, (b) firms are taxed on the amount of emissions, and (c) firms can participate in a carbon cap and trade system. Traditional CLSC network design models are extended to account for the carbon emissions caused by transportation under different transportation modes. Model validations are demonstrated via a case study. Through detailed sensitivity analysis, we investigate how the ...


Capacity Expansion For Uncertain Demand With Initial Shortages, Rahul R. Marathe, Sarah M. Ryan 2019 Iowa State University

Capacity Expansion For Uncertain Demand With Initial Shortages, Rahul R. Marathe, Sarah M. Ryan

Sarah M. Ryan

For service providers, uncertain demand for capacity and expansion lead time may create unavoidable capacity shortages, which may be allowed to accumulate before initiating an expansion. For the demand following a geometric Brownian motion process, we assume a stationary expansion policy where the timing and size of expansion are determined as fixed proportions of the capacity position. We define the service level in terms of the capacity shortages, which can be evaluated by applying pricing formulae for barrier options in finance. We observe the relationship between the two policy parameters at different specified service levels and for other model parameters.


Analysis Of Delayed Product Differentiation Under A Conwip Policy, Heedong Kim, Sarah M. Ryan 2019 Iowa State University

Analysis Of Delayed Product Differentiation Under A Conwip Policy, Heedong Kim, Sarah M. Ryan

Sarah M. Ryan

Delayed product differentiation (DPD) increases manufacturers’ competitiveness by enabling faster responses to demand changes and has been shown to require less work in process (WIP) in base-stock systems. We model a system of two products using three CONWIP loops to represent the common processes and the differentiated processes for each product. DPD converts some differentiated processes to common ones. A nonlinear programming (NLP) model can determine kanban counts for each loop to achieve specified throughput bounds. Because these bounds are not tight, a heuristic algorithm starts from the NLP solution and adjusts the kanbans according to simulation. The results indicate ...


Comparison Of Efficient Methods For Solving A Large-Scale Multistage Stochastic Program, Yan Wang, Sarah M. Ryan 2019 Iowa State University

Comparison Of Efficient Methods For Solving A Large-Scale Multistage Stochastic Program, Yan Wang, Sarah M. Ryan

Sarah M. Ryan

We use a rolling two-stage procedure for solving a multistage stochastic program to assess the effects of uncertain fuel costs on optimal energy flows in the U.S. The optimal solution to the largest deterministic equivalent is obtained via Benders decomposition. We apply methods including temporal aggregation and scenario reduction to find approximate solutions which require less computational effort. These methods exploit both the network structure of the model and the multistage nature of forecast revision and uncertainty resolution. We evaluate the approximations based on similarity of the effects of uncertainty on the optimal flows compared to the exact solution.


A New Analytical Evaluation Model For Kanban Controlled Systems With Fork/Join Synchronization Stations, Heedong Kim, Sarah M. Ryan 2019 Iowa State University

A New Analytical Evaluation Model For Kanban Controlled Systems With Fork/Join Synchronization Stations, Heedong Kim, Sarah M. Ryan

Sarah M. Ryan

A nonlinear programming model is developed for analyzing the queuing model of a kanban controlled system with fork/join synchronization stations. The model finds the minimum number of kanbans for a given throughput requirement or the maximum throughput for a given number of kanbans, where servers have different exponential service times. Furthermore, it aids understanding of kanban systems.


Integrated Curriculum To Improve Engineering Problem Solving, John K. Jackman, Sigurdur Olafsson, Frank E. Peters, Sarah M. Ryan 2019 Iowa State University

Integrated Curriculum To Improve Engineering Problem Solving, John K. Jackman, Sigurdur Olafsson, Frank E. Peters, Sarah M. Ryan

Sarah M. Ryan

A series of modules based on realistic problems are being developed for our industrial engineering curriculum. These modules require students to use a variety of information technology skills to access, screen and analyze the data available to them. The modules are also designed to help students build relationships among the courses, which they traditionally treat as isolated bodies of knowledge. Students’ engineering problem solving will also be enhanced by the challenge presented by more realistic open-ended problems that are incorporated into the modules. This paper details the results of the latest module used in a Manufacturing Systems Engineering course.


Applying Alternative Decision-Making Approaches To A Complex Supplier Selection Problem, Paul J. Componation, Michael C. Dorneich, Guiping Hu, Gillian M. Nicholls 2019 Iowa State University

Applying Alternative Decision-Making Approaches To A Complex Supplier Selection Problem, Paul J. Componation, Michael C. Dorneich, Guiping Hu, Gillian M. Nicholls

Michael C. Dorneich

Prior work has been completed on understanding how an organization’s decision-making approach can influence the selection of alternative vendors when setting up a supply chain system. Teams using different decision-making approaches on identical performance data did end with different vendor recommendations. One possible explanation of this result was that the data set on vendor performance was limited to five vendors and four variables; however the decision-making approaches had significantly different cognitive requirements. The team members preferred cognitively simple approaches such as Weighted Sum and to a lesser degree SMART with this relatively limited data set. The more cognitively complex ...


A New Metric For Evaluating Machinability Of A Design, Jocelyn Chay, John K. Jackman, Matthew C. Frank, Frank E. Peters 2019 Iowa State University

A New Metric For Evaluating Machinability Of A Design, Jocelyn Chay, John K. Jackman, Matthew C. Frank, Frank E. Peters

Matthew C. Frank

With the increasing complexity of part model designs and the pressure to reduce time to market, evaluating the manufacturability of conceptual designs can help design engineers avoid part features that create downstream manufacturing problems. For machining processes, reachability of a part surface with a cutting tool plays a major role in determining the machinability of a design. This paper describes a new method to quantify reachability at different locations on the surface of a part model. A mesh representation (STL file) is generated for a part model and a slicing algorithm is used to estimate the reachability for each model ...


The Use Of Sacrificial Support Structures In A Rapid Machining Process, Wutthigrai Boonsuk, Matthew C. Frank 2019 Iowa State University

The Use Of Sacrificial Support Structures In A Rapid Machining Process, Wutthigrai Boonsuk, Matthew C. Frank

Matthew C. Frank

Rapid prototyping techniques for CNC machining have been developed in an effort to produce functional prototypes in appropriate materials. One of the major challenges is to develop an automatic fixturing system for the part during the milling process. The current proposed method, sacrificial support fixturing, is similar to the support structures used in existing rapid processes, such as Stereolithography. During the machining process, the sacrificial supports emerge incrementally and, at the end of the process, are the only entities connecting the part to the stock material. In this paper, we propose methodologies for the design of sacrificial support structures for ...


Visibility From A Slice File For Rapid Cnc Machining, Matthew C. Frank, Richard A. Wysk, Sanjay B. Joshi 2019 Iowa State University

Visibility From A Slice File For Rapid Cnc Machining, Matthew C. Frank, Richard A. Wysk, Sanjay B. Joshi

Matthew C. Frank

A methodology for using CNC machining as a rapid prototyping process is being developed. The method involves cutting complex parts using layer-based machining operations from a plurality of orientations about one axis of rotation. A critical step is to determine the number of and location of those orientations. This paper presents an approach to mapping the visibility of a model about an axis of rotation using a set of model slices taken orthogonal to the axis of rotation.


Probabilistic Methods For Long-Term Demand Forecasting For Aviation Production Planning, Minxiang Zhang, Cameron A. MacKenzie, Caroline Krejci, John K. Jackman, Guiping Hu, Charles Y. Hu, Gabriel A. Burnett, Adam A. Graunke 2019 Iowa State University

Probabilistic Methods For Long-Term Demand Forecasting For Aviation Production Planning, Minxiang Zhang, Cameron A. Mackenzie, Caroline Krejci, John K. Jackman, Guiping Hu, Charles Y. Hu, Gabriel A. Burnett, Adam A. Graunke

Guiping Hu

The aviation industry represents a complex system with low-volume high-value manufacturing, long lead times, large capital investments, and highly variable demand. Making important decisions with intensive capital investments requires accurate forecasting of future demand. However, this can be challenging because of significant variability in future scenarios. The use of probabilistic methods such as Brownian motion in forecasting has been well studied especially in the financial industry. Applying these probabilistic methods to forecast demand in the aerospace industry can be problematic because of the independence assumptions and no consideration of production system in these models. We used two forecasting models based ...


Capacity Planning And Production Scheduling For Aircraft Painting Operations, Xiangzhen Li, Caroline Krejci, Cameron A. MacKenzie, John K. Jackman, Guiping Hu, Charles Y. Hu, Adam A. Graunke, Gabriel A. Bumett 2019 Iowa State University

Capacity Planning And Production Scheduling For Aircraft Painting Operations, Xiangzhen Li, Caroline Krejci, Cameron A. Mackenzie, John K. Jackman, Guiping Hu, Charles Y. Hu, Adam A. Graunke, Gabriel A. Bumett

Guiping Hu

Long-term capacity planning and production scheduling present significant challenges for the aviation industry. Our research has integrated three different modeling methodologies to effectively forecast future demand for aircraft painting and then assess and manage the capacity that is needed to meet these requirements. First, an innovative forecasting approach was developed in which stochastic processes were used to model aircraft demand over a selected time interval. These demand forecasts were used as inputs to an integer programming model, which was used to find optimal monthly aircraft painting schedules. This approach supports for resource allocation that is based on optimal scheduling, rather ...


Applying Alternative Decision-Making Approaches To A Complex Supplier Selection Problem, Paul J. Componation, Michael C. Dorneich, Guiping Hu, Gillian M. Nicholls 2019 Iowa State University

Applying Alternative Decision-Making Approaches To A Complex Supplier Selection Problem, Paul J. Componation, Michael C. Dorneich, Guiping Hu, Gillian M. Nicholls

Guiping Hu

Prior work has been completed on understanding how an organization’s decision-making approach can influence the selection of alternative vendors when setting up a supply chain system. Teams using different decision-making approaches on identical performance data did end with different vendor recommendations. One possible explanation of this result was that the data set on vendor performance was limited to five vendors and four variables; however the decision-making approaches had significantly different cognitive requirements. The team members preferred cognitively simple approaches such as Weighted Sum and to a lesser degree SMART with this relatively limited data set. The more cognitively complex ...


Data Mining For Production Scheduling, Sigurdur Olafsson 2019 Iowa State University

Data Mining For Production Scheduling, Sigurdur Olafsson

Sigurdur Olafsson

Data mining is a fast growing field and many industrial engineering applications generate large amounts of data to which data mining techniques can be applied. In this paper we develop a data mining framework for production scheduling. This involves preprocessing of historic schedules into an appropriate data file, discovery of key scheduling concepts, and representation of the data mining results in a way that enables its use for job scheduling.


Analogies And Comparisons For Stm Data Bodies, Phillip M. Cunio, Brien Flewelling 2019 ExoAnalytic Solutions, Inc.

Analogies And Comparisons For Stm Data Bodies, Phillip M. Cunio, Brien Flewelling

Space Traffic Management Conference

Space Traffic Management (STM) has already demonstrated its potential to be extremely data-intensive. The large number of objects on orbit today, if observed constantly throughout their lifetimes, could produce a staggeringly large number of observations that might in turn generate large numbers of orbits. Orbit data with a lengthy time history can be used to produce estimates of maneuver frequency, susceptibility to natural forces such as drag, and (if combined with photometric data) assessments of behavioral patterns of life.

A future of mega-constellations and a growing number of nations and organizations with assets on orbit would make it likely that ...


Enhancing Suborbital Science Through Better Understanding Of Wind Effects, Pedro Llanos, Diane Howard 2019 Embry-Riddle Aeronautical University - Daytona Beach

Enhancing Suborbital Science Through Better Understanding Of Wind Effects, Pedro Llanos, Diane Howard

Space Traffic Management Conference

This paper highlights the importance of understanding some key factors, such as winds effects, trajectory and vehicle parameters variations in order to streamline the space vehicle operations and enhance science in the upper mesosphere at about 85 km. Understanding these effects is crucial to refine current space operations and establish more robust procedures. These procedures will involve training new space operators to conduct and coordinate space operations in class E above FL600 airspace within the Air Traffic Organization (ATO).

Space vehicles such as Space Ship Two can spend up to 6 minutes in class E airspace above FL600 after launch ...


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