2023 ISE Senior Design and Undergraduate Research Symposium

Time

Team

Abstract

iRoanoke App QAlert Citizen Request

Team Members: Alec Bradfield, Paul Hanna, Spencer Dennis, Chenyu Xing
Client Contact: Angela O’Brien
Advisor: Dr. Konstantinos Triantis

iRoanoke is a mobile application built by the City of Roanoke, Virginia that provides citizens with an easy way to report service requests to city staff for action and resolution. However, there is a misalignment between various governmental departments and the backend request system QAlert, leading to delays in service request responses. An analysis of the QAlert system capabilities, alongside researching efforts, led to the identification of a multifaceted solution presented in a final whitepaper deliverable. The two main solutions are a Key Performance Indicator (KPI) Analysis which recommends KPIs for departments to track, and an automatic communication audit which explores the current automatic communication settings in QAlert. These approaches are expected to improve the current process flow so that service requests are addressed in a timely manner.

Quality Improvement Through Event Reporting

Team Members: Daniel Ruopp, Emma Hall, Elysia Calderon, Joyce Nam
Client Contact: Justina Pangallo
Advisor: Dr. Konstaninos Triantis

MedStar Health is a high-reliability organization which takes pride in its commitment to maintaining quality and safety throughout its operations. Our project presents an opportunity to improve and standardize how MedStar Health Laboratories reports errors and patient safety events to prevent future errors from occurring. MedStar currently uses RL Solutions to report errors in laboratory procedures, but this system is not standardized, resulting in inconsistencies across their various hospitals. The absence of a standardized medical dictionary, suboptimal user interface, and delayed event reporting in RL Solution contribute to inconsistent event categorization, confusion among reporters, reduced efficiency, and hampered visibility and timely action. Our team worked on three different solution approaches: User Interface Changes, Standardized Data Dictionary, and Education of Frequent Users. The event reporting platform has been improved with a user-friendly interface that facilitates the work of lab employees, a standardized medical dictionary that promotes consistency in event classification, and comprehensive training resources readily available to frequent users, all of which enhance data quality and reliable event reporting at MedStar.

Making Healthcare Sustainability More Efficient

Team Members: Imani Gainey, Elizabeth Hunt, Taylor Strickler, Allison Tieman, Alejandra Vega
Client Contact: Sara Wolford, Marina Sotelo
Advisor: Dr. Sean McGinnis

Carilion Roanoke Memorial Hospital’s nursing units have implemented 10 waste collection sustainability programs to return, reprocess, and recycle the 5 million pounds of waste produced annually. However, these programs were difficult for nursing staff to engage in due to time constraints, competing demands, and inefficient system design. To increase nurse engagement in the waste collection programs, the team has implemented a process improvement solution that integrates the programs into the nurses' everyday work flow. This solution includes nursing education, bin reconfiguration, and updated signage. The implementation of our process improvement is expected to increase hospital savings by $2,000 over the next three years and integrate sustainability into the nurses’ established routes.

Automate a Quality Control Function

Team Members: Pablo Isaza, Hao Dong, Hongrui Shan, Kunth Shah
Client Contact: Antoneta Sevo
Advisor: Dr. Prahalada Rao

ICS Corporation, a direct mail printing company located in the Philadelphia metropolitan area, has challenged the team with reducing errors during the digital printing stage by developing a machine learning model that can detect and correct errors more efficiently and accurately. The team’s objective was to support the ICS Quality Control department by finding errors automatically, reducing the need for manual verification, and saving human resources and time. This was achieved by using Artificial Intelligence Models, as well as cross referencing tools to accurately detect errors, such as mismatched variables, in direct mail samples. Due to the magnitude and complexity of the problem, the team proposed a use-case starting with one specific company, that could then be scaled to its whole clientele base. Overall, this senior design project represents a significant improvement in ICS’s Quality Control Department processes and efficiency capabilities.

Shipping Optimization

Team Members: Will Carlyle, Ashley Girod, Drew Martin, Sam Barnes, Zach Schwinger
Client Contact: David Ryan
Advisor: Dr. Kwok Tsui
Additional Faculty: Dr. Robert Hildebrand, Jamie Fravel

The Devils Backbone brewing facility, located in Lexington, VA, services over one hundred wholesalers primarily on the East Coast through a road freight distribution network. Using a set of standardized shipping rules, decision-makers at the facility determine whether shipments are sent directly to wholesalers or to a distribution center. However, it was unclear whether their outbound shipping costs are minimized using their existing decision-making process. To address this, a linear programming model was developed to reduce network costs while considering the products' shipping destination, timing, and demand. The model was implemented into a Gurobi Python program to generate an optimal shipping plan. The results showed that the current decision-making process was not completely optimized, resulting in 28.02% savings compared to current practices. This cost reduction provides opportunities for alternative investments, such as increased production efficiency and greater storage capacity.

Optimization of CT Imaging Protocol Management

Team Members: Jessica Kaur Aujla, Baasim Kazi, Alejandro Romulo, Ahmad Abu Shamat, Katie Springer
Client Contact: Dr. Ethan Larsen
Advisor: Dr. Joseph Godfrey

The Pediatric Radiology department of the Children’s Hospital of Philadelphia (CHOP) requested an improved computerized tomography (CT) protocol management process. CHOP envisions a structured, efficient workflow in compliance with the American College of Radiology and Joint Commission’s regulations to obtain as low as reasonably achievable (ALARA) radiation levels. Utilizing research the team conducted from fellow pediatric institutions, the team mapped CHOP’s existing processes and brainstormed potential software and workflow solutions. The team curated a change management guide which identified Radimetrics as the protocol management software, proposed a Radiology Governance Board, and defined a complementary workflow. The implementation of these solutions is expected to reduce average protocol updating time by 75% and save CHOP approximately $483,180 in labor and equipment costs.

On Time Outside Image Processing for Patient Transfer

Team Members: Adam Taffel, Isaiah Usher, Mackenzie Gehringer, MaryGrace VanDervort, Maryum Khan
Client Contact: Ethan Larsen
Advisor: Dr. Esra Toy

The Children’s Hospital of Philadelphia (CHOP) often receives transfer patients from external hospitals for specialized pediatric care. The radiology department expressed concern for the extensive delays in processing outside imaging due to patients entering with a physical CD copy of their prior images or requesting the image transfer upon arrival. This has led to unnecessary repeat CTscans which add radiation exposure, as well as delayed care, or faulty decisions based on incomplete information. Our team developed an improved communication process that pulls from a database of external hospitals to send an automated email that requests patient imaging electronically before patients arrive. The database and email system are proactive systems that address the larger need for a more integrated healthcare network to share patient data seamlessly. This implementation is expected to reduce labor, unnecessary CT scans, and improve the timeliness of patient care, saving approximately $80,000 over the next three years.

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Team

Abstract

Manufacturing and Test Utility Database

Team Members: Sarah Corona, Robin Huang, Fayaz Solaiman, Dominic Brazina, Gowtham Ganapaneni
Client Contact: Michael Wurst
Advisor: Dr.Christopher Kwaramba

Northrop Grumman, a defense contractor based in Baltimore, Maryland, develops fundamental electronics systems concepts, as well as being home to makerspaces that foster innovation and creativity for the future. They have issues with storing and retrieving their data on both old and new manufacturing and test equipment, which becomes more of a challenge to find historical requirements to specific pieces of equipment to prepare for relocation within the facility. This causes an increase in cost and schedule delays. We have identified three possible solutions to address this problem: creating a database in AWS GovCloud, using Google Cloud Suite, or utilizing an On-Site Server. The database will be able to hold many file types securely on AWS GovCloud. It will automatically notify administrators of changes made to it via email. Additionally, it will comprise an auto-tagging file system. When fully implemented, the database is expected to reduce costs by about $3.9 million USD over the next three years. Finally, this solution will eliminate the need for outside design firms and reduce materials and labor costs.

Operating Room Stewardship

Team Members: Deepti Aaron, Elizabeth McCain, Paige Pilewski, Matthew Taylor, Kaitlin Walker
Client Contact: Deidre Cahill, Lauren Carpenito, Stefani Dubea, Thomas Davis
Advisor: Dr. Ran Jin

Duke University Health System (DUHS) located in Durham, North Carolina, is one of the top hospitals in the world, caring for 3.5 million outpatients each year. Current operating room utilization rates are low, causing DUHS to lose patient demand and the resulting revenue, losing up to $20,000 per block per day. DUHS does not have a quantitative method to efficiently allocate 400 surgeon schedules to 1340 surgical blocks each month. This project uses data analysis and decision matrices to create standardized stewardship scores for all 400 surgeons and ranks them accordingly. Raw data from the hospital was statistically analyzed to assign a weighted z-score to each surgeon for the nine variables that impact overall block utilization. Each surgeon was assigned three stewardship scores: one based on the data from the entire hospital, one based on the data from their specific department, and one based on the data from their division. The implementation of this project is expected to increase the overall block utilization of the perioperative services sector of Duke University Health by 5%, resulting in an additional $2,500 in revenue per block and 1,325 cases each year.

Revolutionizing Loan Acquisition with Machine Learning

Team Members: Whit Packwood, Jarrett Johnston, Paul Blanco, Patrick Tolley
Client Contact: James Haney
Advisor: Dr. Christopher Kwaramba

Republic Finance is a financial services company based in Baton Rouge, Louisiana that specializes in personal loans. Currently, Republic Finance receives a large portion of its annual origination volume through direct mail acquisition. These prospective customers are targeted using a Response Model; however, the current in-production model is not as accurate as they anticipated. To better predict the likelihood of response, the team built a more advanced response model using a gradient boosting machine. The new model was formed through multiple stages of feature selection and hyperparameter tuning and has an improved response rate of 1.2%. Compared to the current model, the team expects the new model to save Republic Finance $3.7M+ annually by eliminating excess mailing costs.

Manufacturing Variance Tool and Process

Team Members: Theresa Mull, Kevin Polomondo, Will Koeppen, Gabriel Pasos, Amanda Edwards
Client Contact: Vibhor Pandhare
Advisor: Dr. John Shewchuk

Kennametal is a high-end global part manufacturing company that produces many different machine parts. Their Asheboro, NC facility is experiencing suboptimal capacity planning and resource utilization as a result of potentially inaccurate cycle times on grinding machines. Using real-time data from the machines supplied by Internet of Things (IoT) devices, our team developed code that was able to analyze the data and feed a curated output into an interactive dashboard to display key information regarding grinding cycle time variances. This dashboard will be used during daily morning meetings so facility managers and production team members can understand manufacturing floor happenings and make informed decisions regarding processes with high variances. Once cycle times are updated, Kennametal is able to efficiently route their production runs, reduce machine downtime, and have a better understanding of the capacity of their plant in order to keep up with the increasing demand the company has been facing.

High Performance Building

Team Members: Tori Pagliaro, Ryan Kelly, Sam Shomailah, Yuran Wei
Client Contact: Jeffrey Shawver
Advisor: Dr. Brian Klenier

Roanoke City Public Schools (RCPS) is an urban school division located in Roanoke, Virginia that serves a total students and faculty population of over 17,000. Our project focused on the creation of an energy tracking software that can monitor the internal processes of energy expenditures and efficiencies within the entire school district. The development of the energy analysis software aids RCPS in aligning current and future construction projects to the standards of HB ~ 2001, and complying with certification standards of: Leadership in Energy and Environmental Design (LEED), EnergyStar, Virginia Energy Conservation and Environmental Standards (VEES), or Green Globes. The software’s ability to track all electricity, water, gas, and other utilities within the district helps provide feasible recommendations to RCPS on how adjustments to building design can reduce overall costs and expenditures. Further, the outputs generated by the software are monitoring carbon emissions, waste generation, and water consumption, which allows RCPS to extrapolate new information, and make necessary systematic changes that will continue the minimization of energy and waste.

Expansion: Data Organization and KPI Reporting

Team Members: Jonah Anastos, Ashley Fisher, Stu Forsman, Ahan Panchal
Client Contact: Patrick Jackson
Advisor: Tom Winters

VIRESCO is an anaerobic digestion company which transforms food waste into reusable energy through their patented VBC process. The company plans to expand their business by adding facilities but lacked a data management system with the cohesion to support said planned expansion. To help facilitate this planned expansion, our team created monthly Tableau reports and a dashboard to display process efficiency and variables affecting VIRESCO’s anaerobic processes at both the single-plant and multi-plant level. Through this, our team was able to reduce outsourcing costs and highlight KPIs and differences across multiple locations, ultimately helping improve plant processes. Not only does this immediately benefit VIRESCO process engineers with the enablement of the universal data management framework, but it also facilitates future expansion by allowing VIRESCO management to understand problems which may arise at new facilities.

Vendor Spend Portal Enablement

Team Members: Matthew Goncalves, Zain Siddiqui, Palak Varshney, Aushim Mittal
Client Contact: Dave Wood
Advisor: Dr. Kwok Tsui

Coca-Cola Bottlers’ Sales and Service (CCBSS) is a Limited Liability Company that provides one voice for customers and suppliers using value based solutions that leverage the negotiating power of the parent company Coca-Cola. Within the commercial division of the procurement team, procurement specialists previously encountered non-standardized data uploads from suppliers and lacked consistent data visualization. An average of 40 working hours per month were lost to dealing with these issues. The team developed an automated data upload/cleansing and report generating system to eliminate manual data management by procurement specialists. After the completion of this project the CCBSS team will have multiple dashboards for data visualization and efficient key performance indicators (KPI) callouts, saving an estimated 39 hours per month for the next three years. This will translate to a combined estimated savings of $74,000.

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Team

Abstract

Long Pallet Flipper

Team Members: Jaebeum Lee, Owen Keegan, Joseph Spohrer, Joseph Albrigo
Client Contact: Witold Biercz
Advisor: Dr. Michael Madigan

PMG is a company specializing in pallet manufacturing machines. The pallet needs to be flipped during the production process to add nails to each side, but currently there are no machines capable of flipping pallets longer than 96". Our team is creating a pallet flipping machine which would be able to reach a speed of five 72"~122" pallets per minute. Our solution uses barrel roll design, rotating the pallet along its longer axis, saving space and energy. We expect this machine to be able to make PMG a leader in long pallet machinery.

Exploration into Pallet Lettering Options

Team Members: Hamza Almatar, Mohammed Alaa Garada, John Andrew Paul Grose, Alex Pierce
Client Contact: Steven Morrissette
Advisor: Andy Hansbrough

Pallet Machinery Group (PMG) is a company that produces pallet-building machinery to sell to pallet-building companies across America. PMG currently sells a brander-attachment used to label pallets on the production line, but clients also use a handheld stamp off of the production line when necessary. Both of these methods have drawbacks, such as being slow or inconsistent. A fast labeling solution is required to match the production speed of new PMG machines and reduce the amount of rejected batches of pallets. A laser engraver matches our criteria the best, as it has a cycle time of 10 seconds for each label and produces a clearer image on the pallet. This improvement helps PMG’s customers spend less time labeling pallets and increase their full production time. PMG’s profit will also increase approximately $200,000, enabling PMG to expand their company.

Fab Tool Throughput Validation

Team Members: Aaron Hale, Mekias Endale, Michael Havostak, Sanchit Tamboli
Client Contact: Ryan Ott, Connor White
Advisor: Dr. Subhash Sarin

MACOM is a semiconductor manufacturing company that has found a niche in producing four-inch semiconductor wafers. MACOM relies on manual labor to produce their specialized wafers rather than automate their production. Within the wafer fabrication plant, this project addresses inaccuracies between the manufacturing process times that the operators enter in the tracking system and actual process times on the floor. Our solution approach is to capture the true timings of each process based on observations and past data, compare these to the system standard times, and generate accurate processing time updates compatible for MACOM’s manufacturing execution system. The new system is expected to reduce idle time in wafer production, simultaneously reducing the direct production costs and freeing up capacity to meet an increased demand. The financial impact for MACOM includes both an increase in per unit profit margin of up to 10% and overall revenue by saving upwards of $3,000,000 by not purchasing new tools.

Glass Decontamination & Conveyance Design

Team Members: Will Davis, Emily Goulet, Ignacio Morales-Erauzquin, Sagar Thakker, Jameel Wilson
Client Contact: Dominic Benedetto, Joe Benedetto, David Twigg
Advisor: Dr. Joseph Godfrey

Recycling & Disposal Solutions (RDS) is a company that provides residential and commercial recycling services to help create a sustainable environment. This project addresses the company’s Material Recovery Facility (MRF) in Roanoke, Virginia, which struggles to effectively sort glass from other contaminants including paper, aluminum, plastic, and more. To alleviate this concern, our team

1) Performed a decision analysis on general design types to narrow our focus.

2) Applied the Python programming language to compute optimal design attributes.

3) Sourced materials for the design and developed a price quote for RDS.

4) Virtually modeled the solution using Computer-Aided Design (CAD) to ensure on-site construction accuracy.

5) Assessed the design’s financial impact over the next three years.

6) Applied statistical process control to monitor the output of the design.

These tools have allowed our team to develop a solution that reduces glass contamination levels to at most 5% by volume and 1% by sight (eye test). Consequently, this will eliminate the need for RDS to spend $6,000 a month for Strategic Materials, Incorporated (SMI) to transport and further decontaminate the glass. RDS will be able to hold the glass on-site and sell it for a profit when the market value peaks.

Use of Robotics in Manufacturing

Team Members: Phillip Andrews, Joaquin Baquerizo, Meghan Brown, and Joey Russo
Client Contact: Dennis Fish
Advisor: Dr. Sol Lim

ICS is a direct mailing company, which prints, folds, and inserts promotional mail contents into envelopes parcels and mail them on behalf of their customers. ICS experienced persistent staffing issues due to post effects of COVID-19, that were expected to continue into the future. The team determined the most important aspect of the solution was to improve autonomy and predictability of throughput by replacing some of the manual tasks with robot operations, while considering safety as a close third. Final solution was composed of a mail chute at the end of ICS’ existing conveyor belt, with a collection point at the bottom, where a robotic arm collects the parcels to be transported to an angled USPS crate. We developed a scale presentation of concept, a written report with details on the robot, operating metrics, and CAD drawings of the chute and angled loading parts. Our design paired with the selected robot decreased the required manual labor by half, which in turn will improve the operation efficiency and predictability.

Anodized Metals Drying Process

Team Members: Bohan Zhang, Hamda Almahri, Marc Nassar, Shihao Xu
Client Contact: Steve Wachnowsky
Advisor: Dr. Prahalada Rao

Global Metal Finishing is an aluminum anodizing plant in Roanoke, VA. Their production is bottlenecked and part completion is inconsistent due to the current drying process where laborers dry freshly anodized parts with handheld, heated-air blowers. To remedy the issue, Team 17 researched alternative drying methods such as vacuum chambers, infrared ovens, and alcohol rinses. After experimentation, Team 17 concluded that alcohol rinses are the most viable approach under which drying time(s) can be reduced from 13.5 minutes to 8.5 minutes. Team 17 expects the impact of this drying method to completely eliminate bottleneck, improve customer satisfaction, increase yearly profits by 54%, and reduce yearly labor by over 90%.

Process & Root Cause Analysis with Riverbend Nursery

Team Members: Molly Zuidema, Leanna Tarr, Amber Clauss, Dmitry Gartner, Andrew Chicalo
Client Contact: Steve Ronyak, Isaac Brantingham, Eric Sanders
Advisor: Dr. Robert Hildebrand

Riverbend Nursery is a 100-acre plant nursery aiming to expand sales but is discovering roadblocks within its operations. Riverbend has a lack of standardization with decision making and data collection, as these have proven to be their fundamental issues. Team 39 is providing Riverbend with designs of foundational processes to improve operations and to establish a strong continuous improvement mindsets for further expansion. The solution approach was achieved by developing and improving Riverbend’s existing Enterprise Resource Planning (ERP) system with an inventory management report and added both crucial metrics that were not calculated effectively previously and a comprehensive document with Team 39’s recommended changes. These recommended improvements in Riverbend’s communication and reporting processes will help provide visibility, standardization, and centralization to give way for more efficient operations, higher throughput, and greater employee satisfaction.

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Improvement of Electronics Handling Procedures

Team Members: Vincent Carno, Audrey San Cartier, Matt Moschella, Mason Matsuda
Client Contact: Jason Jones
Advisor: Dr. John Casali

Moog Aspen produces a number of high performance brushless motor and control solutions for applications in commercial industries. However Moog Aspen’s Radford facility does not have the proper product and processes in place for handling certain components. The two assemblies in scope, a trapezoidal board and circular board, experienced failure rates of 10% and 40% respectively, due to material handling problems, electrostatic discharge, and poor operator training. The team researched industry standards, best practices, and observed the manufacturing processes to achieve a reduced failure rate. Our goal is to reduce failure rates by 50%, improve failure rate to 5% on board 1 and sub 20% on board 2 via customly designed Kanbans, improved material handling procedures, electrostatic discharge countermeasures, and operator training. These impacts reduce backup inventory, remove excess work-in-progress and are expected to save approximately $207,741.

Process Flow Improvement

Team Members: Erin Agosto, Sam Heslin, Sam Farls, Ashish Patel
Client Contact: Christopher Lafferty
Advisor: Dr. Joe Godfrey

Collins Aerospace, a subsidiary of Raytheon technologies, is a global leader in aerospace and defense products. The current process for deicing aircraft propellers is experiencing inefficient order processing, resulting in subsequent production delays. A revised layout of the physical propellor line was created by the team to improve production flow using simulations backed by past demand data and standard labor times. An improved room layout will both reduce the number of bottlenecks during production while simultaneously creating space for new equipment to further improve production capacities.

Augmented Reality Work Instructions for the Learning Factory

Team Members: Quincy Houk, Annie Meenan, Ana Casciello, Yuyang Han
Client Contact: Ashley Strong
Advisor: Dr. Joseph Gabbard

While working with Northrop Grumman, a prominent aerospace and defense company, the team identified a problem with the assembly process in the company's manufacturing sector, causing delays and inefficiencies. Northrop Grumman previously used printed work instructions in their manufacturing facilities and believed that augmented reality (AR) training would improve production performance. To address this issue, the team developed a solution that involves the implementation of AR work instructions to reduce assembly times. With AR technology, workers can quickly and accurately perform tasks without time-consuming paper-based instructions. Upon completion, the team achieved reductions in assembly times, resulting in increased productivity using the AR technology on the iPad and Hololens by 9% and 15%, respectively. This solution has the potential to have an impact on the manufacturing industry by streamlining processes and improving efficiency.

Secure off-network Device Connection to Digital Thread

Team Members: Ojas Amberkar, Sam Tesema, Pranav Sondhi, Aaron Vickers
Client Contact: Dr. Zach DeSmit
Advisor: Jim Sowder

Northrop Grumman processes a high volume of data throughout their wide array of manufacturing facilities; however, an automated and secure methodology to move this data from off-network devices is yet to be implemented. The team researched a variety of Industry 4.0 technology that could be applied to Northrop Grumman facilities. The objective of the team’s solution is to move data from off-network manufacturing machinery onto a secure server automatically, adding additional layers of security on the data itself. As a result, the team researched and developed a functional prototype which performs this automated, secure movement of data utilizing a Raspberry Pi, localized encrypted server, and an off-network 3D printer. The solution is expected to lead to a reduction of labor, increased process automation resulting in five times faster data transfer, and an undisclosed amount of savings for Northrop Grumman.

Capacity, Capability and Readiness Assessment

Team Members: Alex Orillac, Joe Parodi, Nina Ziu, Shay Wilberger, Supran Poudel
Client Contact: Matt Bailey, Liam Cahalane
Advisor: Tony Kauer

Boeing Space and Defense St. Louis is approaching Low-Rate Initial Production (LRIP) for the MQ-25 Autonomous Refueler and T-7A Red Hawk trainer. Before LRIP implementation, Boeing needs to perform a capability, capacity, and readiness analysis for each production line to identify risks and develop mitigation recommendations. The team completed a high-level labor, facility, and tooling analysis for MQ-25 to pinpoint potential areas of concern. The experience from the MQ-25 analysis was replicated and adapted to complete a thorough evaluation of the T-7A canopy and windshield shop. Utilizing spreadsheet analysis, Arena Simulation Software, and AutoCAD, the team completed the T-7A analysis to identify potential risks and propose recommendations that will improve the shop capacity to successfully meet targeted production rates. In both the MQ-25 and T-7A analysis, the most critical issues were identified and ranked based on their influence on the production capabilities. Similarly, the corresponding recommendations include potential results on the production capabilities. These results and design recommendations will support Boeing in meeting LRIP production rates, which in turn enables Boeing’s customers to meet their mission goals and objectives.

Expediting Manufacturing Picking Process

Team Members: Rachel Hager, Megan Judge, Colin Hagerup, Gregory Balov-Madrid, Nishanth Shetty
Client Contact: Heather Catoe, Kaitlin Byrne
Advisor: Dr. Maury Nussbaum

The Boeing Company, a leading global aerospace manufacturer, has been 50% less efficient in its material integration center’s (MIC’s) warehousing operations since the COVID-19 pandemic. Boeing’s Charleston plant, home of the 787 Dreamliner, sought to decrease the picking cycle time from ~1.5 minutes to ~1 minute. The team redesigned the MIC’s equipment layout to shorten the distance traveled in the U-line. Another countermeasure was replacing Boeing’s current cart markers with fastened, flippable cart toppers to indicate the flow day and shift, which eliminated wasted time from switching markers. For future consideration, the team recommended implementing RFID tracking using Arduino modules. All countermeasures were constructed using root cause analysis and the engineering design process. These solutions reduced each cycle time by 20 seconds and travel distance by 60 feet, saving Boeing $120,000 per 3 year period.

Digitally Connected Manufacturing

Team Members: Jayce Barillaro, Santiago Sun, Nick Swanson, Sanam Patel
Client Contact: Benjamin Moses
Advisor: Mark Seymour

The Association for Manufacturing Technology (AMT) delivers best practices and standards to clients worldwide, including expertise in digital transformation. AMT’s subsidiary organization, MTConnect, developed the MTConnect standard to standardize data processing and formatting for various manufacturing machines; however, legacy machines built without MTConnect in mind require custom adapters in order to translate their internal data to communicate through this standard. The Tormach PCNC 1100 milling center is a popular manufacturing machine that has not yet been adapted to comply with the MTConnect standard, which is the problem our team addressed. Unfortunately, Virginia Tech’s Tormach mill was not operational for the duration of this project, so the team was not able to use the machine to develop or test our solution. Instead, the team analyzed the LinuxCNC virtual controller that the Tormach mill’s operation is based on, and developed a data simulator that should match the data output from a running machine. Once able to simulate a starting point, our team not only adapted a simulated Tormach milling center to the MTConnect data standard, but also built databasing and visualization tools for entire fleets of MTConnect-compatible machinery with MongoDB and Grafana, with a focus on helping machine shops to run leaner operations, generate more accurate reports, and identify recurring issues in quality control. Each AMT member organization that implements some version of this work will be saving over 80 man hours of engineering time, representing a value in the industry of as much as $77,000 or more.

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Streamlining Community

Team Members: Joel Chandler, Lance Weiner, Megan Hebbe, Tara Shorafa, Marah Ghanem
Client Contact: Lee Spiegel
Advisor: Dr. Navid Ghaffarzadegan

Beans and Rice Inc. is a non-profit organization based in southwest Virginia that offers a variety of services under the mission of helping at-risk members of the community with food security, family stability, and youth development. The overarching issue is a lack of income produced by their business projects, causing the organization to fall short in terms of the mortgage payment. To solve this, we evaluated decisions regarding the underutilized space in the Pulaski building and decided to turn it from a current liability into a cash flowing asset. This has been accomplished through the development of a fully customized online rental system where short term bookings can be made.The expected sales impact of this transformation is about $94,500 in revenue over the next three years.

Digital Thread Expansion for the Learning Factory

Team Members: Jared Kern, Andy Waldo, Colin Adams, Kojo Akrong
Client Contact: Dr. Zachary Desmit
Advisor: Dr. Zhenyu Kong

Northrop Grumman is a government contractor that manufactures a broad range of products for military and defense applications. With over five hundred manufacturing facilities, Northrop Grumman incurs considerable costs from lengthy data collection processes, delayed maintenance response times, and inaccurate data reporting. In partnership with Virginia Tech’s Learning Factory, the team researched replicable data solutions that bring digital transformation to traditional manufacturing. The team developed a database to dashboard solution that automates the stream of data collection and ensures real-time visualization of production processes with quality control charts for alerting purposes. After implementing the solution to the Learning Factory machinery, the team provided Northrop Grumman with a step-by-step process for replication in their own facilities. The solution is expected to reduce time spent collecting machine-generated data, increase visibility of different manufacturing processes, and estimate time to machine failure.

Computer Vision System for Beef Cattle

Team Members: Katie Price, Alexis Flick, Jack Zhang, Sumaiya Haque
Client Contact: Gota Morota, Sabrina Amorim
Advisor: Mark Froggatt

The Virginia Tech Animal Science department is automating the process of collecting phenotypic data to expand the scope of their research while contributing to the overall goals of efficiency, profitability, and animal well-being. This project capitalizes on a new, affordable, and accurate depth-sensing camera to estimate the weight of beef cattle. The team developed a Python script and deep learning algorithm to compare different ways to measure body weight factors from the images taken from the depth camera. Using regression analysis, the models will be compared and the best model will be implemented. The implementation of the camera and algorithms is expected to estimate cows’ body weights with a minimum of 80% of estimations within 20 kilograms of the actual weight. This will reduce maintenance costs by 35% and increase the frequency of weigh-ins from once a year to 6 times a year.

VT ISE Virtual Recruiting

Team Members: Mary Pletcher, Atlas Vernier, Jake Pierson, Leanne Shahin
Client Contact: Jacob Kerstiens
Advisor: Dr. Rafael N.C. Patrick

Novel recruitment tools and approaches are needed to sufficiently meet informational needs of current and prospective students while overcoming growing socioeconomic, accessibility, and geographical barriers. The Grado Department of Industrial & Systems Engineering at Virginia Tech is committed to being a leader in diversity, equity, and inclusion. Efforts have been set in motion to develop and implement an accessibly effective virtual reality recruiting platform. The current research and development process seeks to improve an existing virtual reality recruitment platform by engaging in semi-structured focus groups and usability testing with a diverse population of students across general engineering and ISE while specifically seeking feedback from students of underserved and underrepresented populations. Developing and implementing an effective virtual recruitment platform is expected to facilitate continued growth of the department in all aspects of diversity, especially with respect to the student body.

Industry 4.0 - Data Utilization and Visualization

Team Members: Michael Berpong, Nicolas Hernandez, Robert Hodge, Brandon Woo
Client Contact: Joseph Jackson
Advisor: Dr. Xi Chen

InMotion is a manufacturer of motors and components for electric transportation units; the Blacksburg facility has an influx of unutilized quality data being recorded on its motor assembly lines. InMotion noted a need for better utilization and management of this data that would be used to measure daily progress. After researching Industry 4.0 and human-centered design, the team has created an interface using Qlik Sense that updates managers and assembly line leaders on motor line metrics on an hourly basis. The implementation of these dashboards has led to material and labor costs savings, as well as the opportunity to invest in more advanced software in the future.

Earned Value Management System

Team Members: June Sinlapanuntakul, Demi Olajide, Lindsey Butler, Vedant Gandhi
Client Contact: Eric Christoph
Advisor: Dr. Esra Buyuktahtakin Toy

Transformative Management Solutions (TMS) is a consulting company specializing in acquisition lifecycle management and project control support for the Department of Homeland Security and Defense. TMS has received an opportunity from a (classified) US government agency, an IT modernization program, to implement an Earned Value Management System (EVMS) and improve project performance. Using the agile methodology, the team integrated Microsoft Power Platform and Office 365 to develop an EVMS, following the Electronic Industries Alliance (EIA) 748 Standard. As a solution, the team created a visualization dashboard and a system that integrated the work scope, budget, and time to track the contractor’s project progress and forecast costs throughout the project lifecycle. This project aims to help our primary contractor win the intended government bid, granting TMS an increase in revenue of $3 million over the next 3 years.

Frith Live Dashboard

Team Members: Daniel Owusu, Derek White, Mike Zumbaugh
Client Contact: Nick Bedard
Advisor: Dr. Sunwook Kim

The Frith First-Year Makerspace provides access to tools and materials necessary to complete the Foundations of Engineering course at Virginia Tech, required for all engineering undergraduates. The makerspace experiences shortages of consumable materials and is ill-equipped to gauge material needs without an efficient inventory tracking process. Our solution approach integrates an HTML dashboard with a database on the Google Sheets platform via a custom API for posting and displaying data. The solution provides a visual tool that streamlines the inventory tracking process, thus facilitating timely stock replenishment. Frith staff will save a projected four hours per week that may be reallocated to other projects, equating to a $34,800 value in labor saved over three years.

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AI-based Cyber Monitoring for IoT/IoBT Sensors

Team Members: Abhishek Gautam, Daniela Correa, Finnbar Courtney, Hunter Every, Tymon Wansel
Client Contact: Sarah Lukens
Advisor: Dr. Peter Beling

LMI is a consultancy dedicated to improving the business of government and assisting the military in their pursuit of absolute security. LMI would like to use internet of things (IoT) devices with military grade equipment; however, these devices are at high risk of being tampered with. The team has decided to characterize potential cyber risks and their behavioral patterns and create an anomaly detection device to monitor when any kind of attacks occur. The results of this project were a finished anomaly detection algorithm capable of detecting anomalies within IoT devices, as well as a recommendation to further increase IoT network security. The implementation of our solution is expected to create a deeper layer of security for the IoT devices, make the detection of cyber attacks and the IoT management system more efficient, and create a greater confidence in the devices.

Snow Removal Operation Improvements

Team Members: Miranda Brown, Emma LeTellier, Eli Pritchard, Brandon Mahon
Client Contact: Dwayne D’Ardenne
Advisor: Dr. Christopher Kwaramba

The City of Roanoke is responsible for keeping their roadways safe during winter weather. Prior salt alt application cost up to $100,000 per snow event. The City’s salt application strategy did not account for different types of weather events (e.g. sub-zero snow vs. 30° freezing rain) or truck calibration. By measuring and analyzing road salt outputs of the trucks, Roanoke city was found to be over-applying road salt by 66%—which was partially due to truck variances. Team 41 researched best practices in surrounding areas and developed a dashboard that suggests salt application rates based on weather conditions and equipment type. Roanoke City now utilizes a calibration dashboard to ensure all trucks are consistently distributing salt. By optimizing road treatment methods, the city can save up to $500,000 a year. The solution optimizes cost for the company and mitigates negative environmental impacts, all while increasing safety by having more consistent and precise salt distribution.

AC Parts AS/RS

Team Members: Jerry Sun, Jerrard Huang, James Hardy, Tyler Smith, Max Rabil
Client Contact: Steve Kelly
Advisor: Dr. Laura Savage, Dr. Cherbaka

UPS is a world-wide package distributor whose Airline Maintenance division has projected an increase in aircraft parts over the next 5 years due to the introduction of newer aircraft within its fleet. With the increase of parts, UPS faces capacity issues within its automated storage and retrieval system (AS/RS) called Mini-Load. This project addresses the capacity issue by an optimization plan and long term replacement for the current system. The optimization plan seeks to improve in the short term by removing any parts that have not been picked within the last year and replacing them with viable candidates within the UPS warehouse. The replacement seeks to be a sustainable option for replacement of the preexisting Mini-Load allowing UPS to maximize their capacity and create part data necessary for storage and tracking. The implementation of these solutions will increase the capacity by 20% and save for the employees to use.

North Yard Waste Management Optimization

Team Members: Maddie Kidd, Byron Guju, Matt Burch, Ian Cullen, Justin Jones
Client Contact: Leah Colvin
Advisor: Dr. Subhash Sarin

Newport News Shipbuilding consists of 550 acres of industrial space, thousands of employees, and numerous shops for manufacturing and assembling United States naval ships. The shipyard produces large quantities of waste that must be moved from the waste source to the appropriate waste removal facility. This process is not meeting expectations for quick and efficient waste removal from the yard and is consequently creating waste backups and encouraging poor waste management behaviors. This problem is compounded by the surrounding urban space and waterway, causing reduced footprint availability for waste process improvements. The team conducted an on-site analysis of waste management problems and engaged with project stakeholders to determine key factors contributing to waste mismanagement. The project developed a working model and simulation of the North Yard waste management process by completing a problem discovery phase with associated value stream map, modeling current waste management features, and by providing potential process improvements from what-if analysis of the simulation. These products provide Newport News Shipbuilding insight into potential process improvements as well as a tool to simulate these improvements before implementation.

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Designing a Sustainable Internal Audit Process

Team Members: Megan James, Giorgio Saade, Sangmin Kim, Junyi Fu, Steven Dollyhite
Client Contact: Susan Bennett and Lynn Wright
Advisor: Dr. John P. Shewchuk

This project focuses on enhancing the internal audit process at Abbott Nutrition's Altavista, VA plant, specifically targeting the reclosable plastic bottle (RPB) line. The existing process falls short of Abbott's expectations for external audit readiness, primarily due to incomplete or absent audits and a lack of standardization and accountability throughout the process. The proposed solution aims to achieve three objectives: first, to increase the audit completion rate, second, to increase accountability, and third, to reduce the waiting period between audit completion and the initiation of work orders. The design includes a user-friendly Excel worksheet that streamlines audit filing and analysis; and a comprehensive operations plan that ensures audit completion and accountability. Anticipated cost savings over the next three years include $1,137 in material costs, $47,000 in investment savings, and $105,000 in savings from passing OSHA audits, resulting in a total cost impact of $153,137.

Lean Transformation GSM Motor Line

Team Members: Emily Muldowney, Paavan Patel, Advay Sharma, Drake Warren
Client Contact: Joe Jackson
Advisor: Dr. Kimberly Ellis

The Blacksburg Inmotion facility produces electric motors and controls for use in vehicle systems. The launch of one of their newest production lines, the GSM line, was disrupted by The Covid-19 pandemic. Inmotion asked our team to address the lingering problems of disorganization, process waste, and lack of capacity to meet forecasted demand. Our team provided Inmotion with a 5S transformation, process analysis and recommendations to meet forecasted demand, and a package of documentation and sustainment resources to maintain the proposed solutions. These solutions raised The GSM Line’s 5S score from 1.4 to 3.0, and identified cost-effective methods to raise output by 450% over the next four years.

Learning Factory Product Development

Team Members: Joe Baker, Alex Noll, Evan Curtis, Betelhem Demissie
Client Contact: Matt Earnest
Advisor: Todd Ogle

The Learning Factory at Virginia Tech is a small-scale manufacturing space which serves to showcase Industry 4.0 technology in a safe, educational workspace for students. To increase community awareness of the Learning Factory, the Industrial and Systems Engineering Department would like to showcase its capabilities via a family of products manufactured by students. Our team has developed a family of ten prototypes addressing broad stakeholder and community needs and expects these will increase awareness of the Learning Factory, ultimately leading to increased educational value and corporate sponsorship.

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Automation of Material Cutting

Team Members: Joe Mayer, Scott Ratliff, Charlie Ortiz, Sam Jensen
Client Contact: Mark Smith
Advisor: Dr. Blake N. Johnson

Collins Aerospace is an aerospace and defense manufacturer that is a subsidiary of Raytheon Technologies. The team was tasked with converting an inefficient manual cutting process on a thermal insulation element to an automatic cutting process as a means of saving both time and labor costs. The element consists of a thin metal sheet with rubber backing and has a very high production volume at the client’s site in Union, West Virginia. The team performed decision analysis on several potential solutions and elected to make use of the on-site XY cut table with a team-designed alignment mechanism. The team performed a time study on both the old process and the new proposed process and found that the new automated process will save the company 925 labor hours per year for this particular element. The new process was designed to easily accommodate new geometries allowing it to be applied to other elements in the near future—dramatically decreasing labor hours for this type of process.

Solar Electric Vehicle Chargestation

Team Members: Sarah Landy, Leta Anna Elmore, Adam McMorrow, John Bruce
Client Contact: Jonathan Gorbach
Advisor: Dr. Charlie Klauer

Established in June 2022, start-up company Running Fox Solar aims to introduce solar power and electric vehicle infrastructure to the Delmarva Peninsula. With a limited budget and isolated location, our team was able to assist the company in the design and installation of a solar powered EV charging station in order to make the company profitable. Running Fox Solar looks to expand by becoming a solar utility for commercial and agricultural businesses and installing solar panels on existing buildings throughout an underserved area of the country. Our solution approach involves placing solar panels on the roof of an existing building then charging the tenants and EV charger users for electricity, ensuring a constant source of income for the company. This project was completed before the tourist season to expand Running Fox Solar’s revenue stream and footprint in the industry. Areas of impact for this project include customer experience/retention, cost savings, and reducing electric vehicle driver range anxiety in the Delmarva Peninsula.

Cold Chain Unit Load Device Enabling Technologies

Team Members: Ratib Patwary, Mihir Damle, Luis Kruger, Karan Nindra
Client Contact: Soe Wunna
Advisor: Dr. Don Taylor

Boeing is an American aerospace manufacturing corporation, focusing on the production of rockets, satellites, and airplanes. A new area that they want to enter is the Cold Chain Unit Load Device market. They estimated that up to forty percent of goods perish through the transportation process and look to improve efficiency. Boeing wanted to know if this is a profitable market to join, and the best ULD option to ensure customer satisfaction. The team researched the Cold Chain ULD market and ascertained the most efficient ULD configuration and if ULDs should be sold or leased to third party companies. The use of a lithium iron phosphate battery, in conjunction with a frameless polycarbonate exterior, made the ULD both profitable and environmentally friendly. With the completion of this project, Boeing is better equipped to understand the ULD market and if it is a worthwhile investment to build their own ULDs.

Perinatal Mood and Anxiety Disorder Screening

Team Members: Mimi Dang, Tia Farese, Joshua Oswald, Anoushka Rodrigues, Rebecca Tu
Client Contact: Dr. Lamia Soghier
Advisor: Dr. Niyousha Hosseinichimeh

Children’s National Hospital of Washington, D.C. has a startup department, the Perinatal Mood and Anxiety Disorder (PMAD) team, which screens parents of patients for postpartum depression in the emergency department (ED) and neonatal intensive care unit (NICU); the PMAD team sought to increase their patient screening rate of 60%. The student team analyzed their complex system in-person and identified major reparable areas of inefficiency to be a lack of consistent screening space in the ED and inordinate time spent on manual data handling in dated technology among others. The final solution within this scope included an interactive Excel document using macros to sort patient information and to automate the benchmarking process. Through this implementation, Children’s National Hospital is expected to improve screening rates by approximately 21% through the increase in available time.

Incremental Benefit of Medication Reconciliation

Team Members: David Petrulis, Lauren Trepp, Bryan Chong, Jillian Haas
Client Contact: Dr. Gonzalo Bearman
Advisor: Dr. Sait Tunc

VCU Health is a non-profit health service and research system based in Richmond, Virginia. Currently there is no quantifiable method to relate the practice and compliance of medication reconciliation within a healthcare system to the risk of adverse outcomes for patient health. This project addresses this undetermined relationship through the development of a mathematical model to quantify the relationship between medication reconciliation compliance levels and hospital outcomes. The team developed a mathematical model based on a comprehensive literature review, assumptions relating to collected medication reconciliation data, and hospital outcome data regarding the intensive care and emergency clinical services. In terms of solution sustainability, the model was made to be open-source so it can be easily accessed and modified by hospital administrations to improve their medication reconciliation practices. The development of this model provided information to hospitals such as VCU Health so they may better judge their management in medication reconciliation practices.

Incremental Benefit of Hand Hygiene

Team Members: Katie Dodge, Darsh Desai, Michael Kappel, Nicholas Miech-Sams
Client Contact: Dr. Gonzalo Bearman
Advisor: Dr. Deborah Dickerson

VCU Health is an academic medical center based in Richmond, Virginia that utilizes a hand hygiene compliance program in their daily operations and seeks to find improvement within their policy. In order to find the best method to evaluate hand hygiene compliance, the team underwent a series of quantitative, literature-based research and crafted a Markov-based mathematical model to interpret the patient-to-patient contacts within a generic hospital setting. In this mathematical model, we accomplished the analysis of three different hand hygiene program implementations to determine which is most effective in decreasing the rate of hospital acquired infections (HAIs). These implementations include a control group of no implementation, visual observation by an outside hire, and incorporation of hand hygiene badge sensors. Through calculating daily probabilities and the likelihood of compliance with each program, we were able to make a program recommendation to VCU. With the interpretations and assumptions made by the team through the research and model, the data given to VCU health through a manuscript assists VCU Medical Center in improving their own hand hygiene programs and further reducing certain time and cost factors that are associated with a patient's duration of stay.

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Sample Mount Recovery

Team Members: Abbie Hennessy, Ayden Blackwood, Luke Van Hout, Zoë Garvey
Client Contact: Loretta Bell
Advisor: Dr. Laura Savage, Dr. Win Nguyen

The Kennametal Technology Center analyzes tungsten carbide samples for new tooling and machining products. The properties of these samples are evaluated by mounting them into resin. Kennametal wants to recover the carbide from these mounts instead of disposing of it. The team researched the sample mount materials and consulted material specialists to create a safe and improved removal process. The improved process utilizes a hydraulic press and personal protective equipment. Kennametal will obtain 900lbs of tungsten carbide that otherwise would have been thrown away, saving them around $7,400 in material costs compared to buying new material and $120,000 in labor costs compared to their old method.

Lean Production Assembly Improvement

Team Members: Jesse King, Ryan Costanzo, Yannis Chamourikos, Vincent Horne
Client Contact: Jeff Jaycox, Peter Hilker
Advisor: Dr. Myounghoon Jeon

Tabet Manufacturing Co. recently opened a new facility adjacent to their original manufacturing site. This created newly freed space in the old building, thus allowing for a floor plan reconfiguration with improved layout and flow; along with these changes, the opportunity arose to also improve workspaces and tool organization. Our team first reconfigured the layout of Tabet’s old building, specifically the assembly area, to be both expandable and replicable for future growth. We then created an optimal workspace configuration with a primary focus on designing a new workbench to help reduce workplace clutter and improve organization. Finally, we improved tool access by identifying and providing a standard set of tools at each workbench in addition to devising and implementing a storage/check-out system for separate, highly specialized tools. After implementing each of our solutions, we were able to quantify our direct financial impact and provide an estimation of $243,000 in savings over the course of three years.

Optimization Solution for Reusable Shipping Racks

Team Members: Michael Chaney, Anapat Pichetpongsa, Valeria Galdo, Zane Saleeby
Client Contact: Sarah Coleman, Taylor Everson-Jones, Carri Friend
Advisor: Dr. Manish Bansal

Mack Trucks, a truck manufacturing company that outsources its parts, has experienced increased demand in Mack Medium Duty (MMD) trucks at its Roanoke Valley Operations facility. Parts move from third-party suppliers to the facility using reusable shipping racks; this flow of commodity between the plant and supplier is referred to as a “loop”. Mack added a second shift of operation to address increased demand, but required a method to determine the optimal number of racks per loop, and a system to track the racks within each loop. The team developed a simulation model that determined the optimal number of shipping racks for two types of racks: window glass and cab racks. Additionally, the team researched and proposed third-party tracking tools (e.g., GPS, barcode, RFID technology) Mack could implement. The application of the simulation and tracking tool is expected to save the company $1.4 million in operating costs during the lifetime of its second shift of production.

Automated Perf Support Structure

Team Members: Ally Jett, Kewei Cao, Pavan Hemanth, Jessica Goad, Atharva Deshmukh
Client Contact: Johnnie Perry
Advisor: Dr. Xiaowei Yue

Collins Aerospace Company is a Raytheon Industries subsidiary specializing in the manufacturing of aircraft components and materials. Collins Aerospace in Riverside, California focuses on the manufacturing of Internal Fixed Structures (IFSs) for use in commercial aircraft engine assembly. Part of the IFS manufacturing process involves drilling thousands of holes across the surface of the material using an automated multi-head drill (MHD) system. This process requires the use of a support material to avoid denting and delamination of the completed pieces. The current support material takes a long time to prepare for use before the drilling process and is difficult to remove, both from the mounting surface and the completed IFS. This project aims to reduce the application and removal time of the support material in order to save on costs from wasted time by implementing a quick release mechanism solution and a revised application and removal process. This solution will lead to a reduction of support material service time from its current standard of several days to sometimes weeks, down to two to three days with a standardized process.