Matching Items (81)

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Adapt or Die: Restaurants in the Modern Era & DLVR Consulting

Description

Customers in the modern world are accustomed to having immediate and simple access to an immense amount of information, and demand this immediacy in all businesses, especially in the restaurant industry. Now more than ever, restaurants are relying on third

Customers in the modern world are accustomed to having immediate and simple access to an immense amount of information, and demand this immediacy in all businesses, especially in the restaurant industry. Now more than ever, restaurants are relying on third party delivery services such as UberEATS, Postmates, and GrubHub to satiate the appetite of their delivery market, and while this may seem like the natural progression, not all restaurant owners are comfortable moving in this direction. Pain points range from not wanting a third party to represent their business or the lack of supervision over the food in transit, and the time it takes to navigate the delivery landscape, to the fact that some food just doesn’t “travel” well. In addition to this, food delivery services can cause increased stress on a kitchen, and dig into the bottom line of an already slim restaurant margin. Simply put, customer reliance on these applications puts apprehensive restaurant owners at a competitive disadvantage.Our solution is simple—we want business owners to be able to take advantage of the huge market provided by third party delivery services, without the fear of compromising their brand. At DLVR Consulting, we listen to specific pain points of a customer and alleviate them through solutions developed by our in-house food, restaurant, and branding experts. Whether creating an entirely new “delivery” brand, menu curation, or payment processing service, we give the customer exactly what they need to feel comfortable using third-party delivery applications. In this plan, we will first take a deep dive into the problem and opportunity identified by both third-party research and first-hand interviews with successful restaurant owners and operators. After exploring the problem, we will propose our solution, who we will target with said solution, and what makes this solution unique and sellable. From here we will begin to explore the execution of our ideas, including our sales and marketing plans which will work in conjunction with our go-to-market strategy. We will explore key milestones and metrics we hope to meet in the coming year, as well as the team which will be taking DLVR from a plan to an implemented business. We will take a look at our three year financial forecast, and break this down further to monthly revenue, direct costs, and expenses. We will finish by taking a look at our required funding, and how we will attempt to gain said funding.

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Created

Date Created
2019-05

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Optimization of a Plug-In Hybrid Electric Vehicle Using Thermal Modeling

Description

Carbon emissions have become a major concern since the turn of the century. This has increased the demand of hybrid vehicles in United States market. Hence, there is a need to make these vehicles more efficient. This thesis focuses on

Carbon emissions have become a major concern since the turn of the century. This has increased the demand of hybrid vehicles in United States market. Hence, there is a need to make these vehicles more efficient. This thesis focuses on creating a thermal model that could be used for optimization of these vehicles. The project was accomplished in collaboration with EcoCar3, and the temperature data obtained from the model was compared with the experimental temperature data gathered from EcoCar's testing of the vehicle they built. The data obtained through this study demonstrates that the model was accurately able to predict thermal behavior of the electric motor and the high-voltage batteries in the vehicle. Therefore, this model could be used for optimization of the powertrain in a hybrid vehicle.

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Created

Date Created
2018-05

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Six Sigma in the Manufacturing Industry

Description

Evidence of Six Sigma principles dates back as far as the 1800s when normal distributions were first being introduced by Friedrich Gauss. Since then, Six Sigma has evolved and been documented into the Define, Measure, Analyze, Improve, and Control (DMAIC)

Evidence of Six Sigma principles dates back as far as the 1800s when normal distributions were first being introduced by Friedrich Gauss. Since then, Six Sigma has evolved and been documented into the Define, Measure, Analyze, Improve, and Control (DMAIC) methodology that is used today. Each stage in the DMAIC methodology serves a unique purpose, and various tools have been developed to accomplish each stage’s goal. The manufacturing industry has developed its own more specified set of methods and tools that have been coined as Lean Six Sigma. The more notable Lean Six Sigma principles are TIMWOOD, SMED, and 5S.

As a case study, DMAIC methodology was used at a company that encourages Six Sigma in all its departments—Niagara Bottling. Ultimately, the company was able to cut its financial losses in fines from customers by over 15% in just a 12-week span by utilizing Six Sigma. In this, the importance of instilling an entire culture of Six Sigma is exemplified. When only a handful of team members are on board with the problem-solving mindset, it is significantly more difficult to see substantial improvements.

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Created

Date Created
2020-05

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Design and Optimization of a Building Integrated Solar Thermoelectric Generator

Description

The main objective of this project was to continue research and development of a building integrated solar thermoelectric generator (BISTEG). BISTEG is a promising renewable energy technology that is capable of generating electrical energy from the heat of concentrated sunlight.

The main objective of this project was to continue research and development of a building integrated solar thermoelectric generator (BISTEG). BISTEG is a promising renewable energy technology that is capable of generating electrical energy from the heat of concentrated sunlight. In order to perform R&D, the performance of different TEG cells and TEG setups were tested and analyzed, proof-of-concepts and prototypes were built. and the performance of the proof-of-concepts and prototypes were tested and analyzed as well. In order to test different TEG cells and TEG setups, a TEG testing apparatus was designed and fabricated. The apparatus is capable of comparing the performance of TEGs with temperature differentials up to 200 degrees C. Along with a TEG testing apparatus, several proof-of-concepts and prototypes were completed. All of these were tested in order to determine the feasibility of the design. All three proof-of-concepts were only capable of producing a voltage output less than 300mV. The prototype, however, was capable of producing a max output voltage of 17 volts. Although the prototype outperformed all of the proof-of-concepts, optimizations to the design can continue to improve the output voltage. In order to do so, stacked TEG tests were performed. After performing the stacked TEG tests, it was determined that the use of stacked TEGs depended on the Fresnel lens chosen. If BISTEG were to use a point focused Fresnel lens, using a stack of TEGs could increase the power density. If BISTEG were to utilize a linear focused Fresnel lens, however, the TEGs should not be stacked. It would be more efficient to lay them out side by side. They can be stacked, however, if the energy density needs to be increased and the costs of the additional TEGs are not an issue.

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Created

Date Created
2017-05

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An optimization model for emergency response crew location within a theme park

Description

Every year, millions of guests visit theme parks internationally. Within that massive population, accidents and emergencies are bound to occur. Choosing the correct location for emergency responders inside of the park could mean the difference between life and death. In

Every year, millions of guests visit theme parks internationally. Within that massive population, accidents and emergencies are bound to occur. Choosing the correct location for emergency responders inside of the park could mean the difference between life and death. In an effort to provide the utmost safety for the guests of a park, it is important to make the best decision when selecting the location for emergency response crews. A theme park is different from a regular residential or commercial area because the crowds and shows block certain routes, and they change throughout the day. We propose an optimization model that selects staging locations for emergency medical responders in a theme park to maximize the number of responses that can occur within a pre-specified time. The staging areas are selected from a candidate set of restricted access locations where the responders can store their equipment. Our solution approach considers all routes to access any park location, including areas that are unavailable to a regular guest. Theme parks are a highly dynamic environment. Because special events occurring in the park at certain hours (e.g., parades) might impact the responders' travel times, our model's decisions also include the time dimension in the location and re-location of the responders. Our solution provides the optimal location of the responders for each time partition, including backup responders. When an optimal solution is found, the model is also designed to consider alternate optimal solutions that provide a more balanced workload for the crews.

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Created

Date Created
2017-12

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Squeezing Out Electricity: Computer-Aided Design and Optimization of Electrodes of Solid Oxide Fuel Cells

Description

Solid oxide fuel cells have become a promising candidate in the development of high-density clean energy sources for the rapidly increasing demands in energy and global sustainability. In order to understand more about solid oxide fuel cells, the important ste

Solid oxide fuel cells have become a promising candidate in the development of high-density clean energy sources for the rapidly increasing demands in energy and global sustainability. In order to understand more about solid oxide fuel cells, the important step is to understand how to model heterogeneous materials. Heterogeneous materials are abundant in nature and also created in various processes. The diverse properties exhibited by these materials result from their complex microstructures, which also make it hard to model the material. Microstructure modeling and reconstruction on a meso-scale level is needed in order to produce heterogeneous models without having to shave and image every slice of the physical material, which is a destructive and irreversible process. Yeong and Torquato [1] introduced a stochastic optimization technique that enables the generation of a model of the material with the use of correlation functions. Spatial correlation functions of each of the various phases within the heterogeneous structure are collected from a two-dimensional micrograph representing a slice of a solid oxide fuel cell through computational means. The assumption is that two-dimensional images contain key structural information representative of the associated full three-dimensional microstructure. The collected spatial correlation functions, a combination of one-point and two-point correlation functions are then outputted and are representative of the material. In the reconstruction process, the characteristic two-point correlation functions is then inputted through a series of computational modeling codes and software to generate a three-dimensional visual model that is statistically similar to that of the original two-dimensional micrograph. Furthermore, parameters of temperature cooling stages and number of pixel exchanges per temperature stage are utilized and altered accordingly to observe which parameters has a higher impact on the reconstruction results. Stochastic optimization techniques to produce three-dimensional visual models from two-dimensional micrographs are therefore a statistically reliable method to understanding heterogeneous materials.

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Created

Date Created
2016-05

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A Reliability Driven Model for Airline Crew Vacation Grid Optimization

Description

The crew planning problem in the airline industry presents a very computationally complex problem of high importance to the business. Airlines must schedule crew members to ensure that all flights are staffed while remaining in compliance with the business needs

The crew planning problem in the airline industry presents a very computationally complex problem of high importance to the business. Airlines must schedule crew members to ensure that all flights are staffed while remaining in compliance with the business needs and regulatory requirements set by entities such as unions and FAA. With the magnitude of operation of the prominent players in the airline industry today, the crew staffing problem proves very large and has become heavily reliant on operations research solution methodologies. An area of opportunity that has not yet been extensively researched lies in the planning of crew vacation. This paper develops a model driven by the idea of system risk that constructs an optimal vacation grid for the time period of one year. The model generates a daily allocation that maximizes vacation offering while ensuring a given level of system reliability. The model is then implemented using data from US Airways and model improvements are provided for practical application in the airline industry based on the output.

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Created

Date Created
2015-05

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Method to Systematically Optimize the Formula Society of Automotive Engineering Race Car

Description

The purpose of this paper is to provide a new and improved design method for the Formula Society of Automotive Engineering (FSAE) team. There are five tasks that I accomplish in this paper: 1. I describe how the FSAE team

The purpose of this paper is to provide a new and improved design method for the Formula Society of Automotive Engineering (FSAE) team. There are five tasks that I accomplish in this paper: 1. I describe how the FSAE team is currently designing their car. This allows the reader to understand where the flaws might arise in their design method. 2. I then describe the key aspects of systems engineering design. This is the backbone of the method I am proposing, and it is important to understand the key concepts so that they can be applied to the FSAE design method. 3. I discuss what is available in the literature about race car design and optimization. I describe what other FSAE teams are doing and how that differs from systems engineering design. 4. I describe what the FSAE team at Arizona State University (ASU) should do to improve their approach to race car design. I go into detail about how the systems engineering method works and how it can and should be applied to the way they design their car. 5. I then describe how the team should implement this method because the method is useless if they do not implement it into their design process. I include an interview from their brakes team leader, Colin Twist, to give an example of their current method of design and show how it can be improved with the new method. This paper provides a framework for the FSAE team to develop their new method of design that will help them accomplish their overall goal of succeeding at the national competition.

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Created

Date Created
2015-05

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Optimal Modeling of Knots in Wood

Description

A model has been developed to modify Euler-Bernoulli beam theory for wooden beams, using visible properties of wood knot-defects. Treating knots in a beam as a system of two ellipses that change the local bending stiffness has been shown to

A model has been developed to modify Euler-Bernoulli beam theory for wooden beams, using visible properties of wood knot-defects. Treating knots in a beam as a system of two ellipses that change the local bending stiffness has been shown to improve the fit of a theoretical beam displacement function to edge-line deflection data extracted from digital imagery of experimentally loaded beams. In addition, an Ellipse Logistic Model (ELM) has been proposed, using L1-regularized logistic regression, to predict the impact of a knot on the displacement of a beam. By classifying a knot as severely positive or negative, vs. mildly positive or negative, ELM can classify knots that lead to large changes to beam deflection, while not over-emphasizing knots that may not be a problem. Using ELM with a regression-fit Young's Modulus on three-point bending of Douglass Fir, it is possible estimate the effects a knot will have on the shape of the resulting displacement curve.

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Date Created
2015-05

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Learning Dynamic Manipulation with Redundant Degrees of Freedom: Sub-Optimal Motor Solution induced by switching tasks

Description

The effect of conflicting sensorimotor memories on optimal force strategies was explored. Subjects operated a virtual object controlled by a physical handle to complete a simple straight-line task. Perturbations applied to the handle induced a period of increased error in

The effect of conflicting sensorimotor memories on optimal force strategies was explored. Subjects operated a virtual object controlled by a physical handle to complete a simple straight-line task. Perturbations applied to the handle induced a period of increased error in subject accuracy. After two blocks of 33 trials, perturbations switched direction, inducing increased error from the previous trials. Subjects returned after a 24-hour period to complete a similar protocol, but beginning with the second context and ending with the first. Interference from the first context on each day caused an increase in initial error for the second (P < 0.05). Following the rest period, subjects showed retention of the sensorimotor memory from the previous day through significantly decreased initial error (P = 3x10-6). However, subjects showed an increase in forces for each new context resulting from a sub-optimal motor strategy. Higher levels of total effort (P < 0.05) and a lack of separation between force values for opposing and non-opposing digits (P > 0.05) indicated a strategy that used more energy to complete the task, even when rates of learning appeared identical or improved. Two possible mechanisms for this lack of energy conservation have been proposed.

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Date Created
2016-05