Every firm has that “job jar” of important projects that just never seem to reach peak priority for the limited resources available. These are exactly the projects that the DCMME Center is interested in assisting you with.
If interested in partnering with the Center to complete a project with your company or to learn more, contact us at dcmme@purdue.edu.
Indiana is among the nation's leading states in auto manufacturing. They don’t plan to fall behind with the rise of EV production. Indiana is planning to be a top competitor in the EV manufacturing space by drawing investments from major auto manufacturers. While the major companies plan to invest in new and exciting technologies, smaller companies are going to be forced to adapt to the new environment or risk being left behind.
This report addresses the industry outlook for Indiana as EV production ramps up throughout the country. This report also analyzes the auto-related companies in Indiana and evaluates the risks that are posed to them based on the products that they are putting out. The report suggests that Indiana auto manufacturing is poised to be in a favorable position entering into the new age of auto manufacturing based off the analysis done by our research.
Three teams of students are working with three clients to create solutions for specific issues within each company.
Manufacturing Readiness Grants Program; This project will study the impact of the MRG program on the manufacturing ecosystem in Indiana and uncover relevant trends among the applications. This project is phase 2 with the next set of companies. The research is intended to identify digital transformation trends, company demographics, investment and use case trends, and other program data that may become apparent during analysis to assess the state-wide dynamics of transformation and program impact. The deliverables culminate in an analysis on the Manufacturing Readiness Grants program across Indiana, as well as an ‘analysis tool’ and strategies and/or recommendations that can enhance the program as it relates to Indiana’s manufacturing ecosystem. They specifically include: A detailed analysis of the program in the form of a report/whitepaper; An analytical tool to assess every application.
The project entails HS code-based data analysis of imports into the US through oceanic routes that help understand the current level of imports into Indiana. The analysis helps OEM companies to explore the possibility of having multiple suppliers by reshoring or finding alternate suppliers that are local to reduce the supply chain risks. Meanwhile it helps identify opportunities for supplier companies to expand/grow their business by supplying to companies that import from outside US. The analysis is also very important to realize manufacturing opportunities in transition of automobile industry from IC engine cars to EV cars.
The project involves analyzing the economic effect of active transportation and association of healthcare industry with transportation. The project entails analyzing the relationship between access to active transportation (walking, bicycling, hiking, etc.) and the region’s economic viability in addition to how the overall transportation features impact the healthcare industry. The goal of the project being understanding what initiatives INDOT can take to make Indiana attractive to advanced industries especially the healthcare industry.
“Where’s my stuff” This team is to develop product prototypes, in the guidance of industry experts, that may have practical values for deployment. The class will be charged to investigate two, possibly three local companies with different problems. They will need to figure out their specific needs and determine where are the common issues between these manufacturers and where are the differences. After these common issues have been identified they will investigate various existing technical and commercially available products on the market as possible solutions.
The project, in collaboration with the Department of Defense (DOD), is divided into several tasks, where Purdue University is responsible for Task 4. The goals of this task are to develop an additive manufacturing (AM) supply chain & sustainment strategy and a digital engineering strategy. The Daniels School team is tasked to develop a simulation model to investigate the benefits of AM and how it can be best used by DOD.
The project involves analyzing the state’s current permit system for overweight freight and it’s impact on Indiana’s road infrastructure and safety. The goal of the project is to understand the current permit fee structure state has in place and review necessary changes to it by providing incentives for the major truck hauling companies.
Development and support of supply chain portal for 10-county WHIN companies. This project will involve keeping updated the relevant information. In addition, the project aims to grow the usage of the portal.
Development and support of educational portal for WHIN company employees to boost knowledge and learning that helps the individual and the company grow.
Expand the existing supply chain tool and the database to include all the 92 counties in the state. The database will include essential information about all the manufacturing companies in the state.
Data Analysis
Student Team: David Ramirez, Joshua Reilly-Grim
With the pandemic in effect, the companies had to ensure to put extra safety measures in place so they could prevent any outbreak of infections and stay open all the while ensuring safe working environment for the workers. Due to this, a lot of companies had to restructure their workspace and Witko was no different. In order to maintain the same efficiency in terms of quality and cost, and to avoid any waste, the team recommended using Value Stream Mapping with Infection mitigation (VSMI) – a variant of VSM, developed by the center team. This entailed the team to identify efficiency limiting steps and waste which would require attention for resolution. The team helped develop steps by revising the system to mitigate infection risk and add value to the bottom line. Students: Colby Phipps, Marissa Cabrera Site Selection – Wabash National Wabash National was trying to select a site/city to explore the notion of expansion/relocation ideas. This required understanding the market in that city which would assist the management to develop a business strategy. The market data was acquired by engaging with companies – potential partners or competitors and cold calling some businesses. This market data was used by the board-level management to decide on investment strategy for one area of the business.
Student Team: Kim Cahoon, Johanna King
Bootmakers is a local company in West Lafayette, which is focused on manufacturing custom made horseback riding footwear and uniform footwear. The main objective of the project was to develop a mobile/web application for order placement and inventory management for their products. It was paramount for Bootmakers to have a digital platform for order placement, which would decrease the time dedicated for order placement by clients and help eliminate possible errors while processing the order on Bootmakers side. Another important capability of the app was an inventory management. Whenever the order will be shipped by Bootmakers, the inventory will decrease for the respective amount of UOM. Additionally, that would help customers be aware of in stock items, while placing an order. The team developed an application using Appsheet, a no code app platform, that let bootmakers’ customers have an easy access to the bootmakers products and place order using the app in addition to providing analytics on orders and inventory for the business.
Student Team: Jane Krasavina, Ana Mendez, Eleanor Didonna
This project was devised to establish a system for tri-lingual tracking of maintenance, relocation tasks to improve management of tasks and the communication between staff with different first-language. The system would need to integrate with both IT and worker resources. Consideration of two leading solutions (incorporating digital app-based communications to reach all involved) led to the choice of Microsoft (MS) ‘PowerApps’ supported by other MS apps. The team set up the instructions and forms for the system to bring the project closer to realization of a working pilot system for appraisal.
Student Team: David Ramirez, Joshua Reilly-Grim, James Grimm
This project will require development of Power BI Dashboards for IIoT data in a SQL database that will be accessed through an O-Data integration layer. The Dashboard will require creating a Star data model, aggregations, multiple visualizations, and ETL layer development using the DAX editor. The Dashboards will be used at both our HTI (Heat Treat) and Small Parts (Metal Forming) operating companies. While the base Dashboard will be the same for both opco's there will be some specialization needed for each once we deploy to users.
Student Team: Rajinder Budhiraja, Vikram Narendra
The project was set up to provide a Three-year, 2021-2021 marketing plan, in collaboration with leading corporate executives in the County in order to foster County growth and enhance the quality of life and economic vitality of businesses. With a low ‘Indiana Counties Livability Ranking’ at 68th out of 91 counties, the potential for improvement was clear. Key goals for impacting on improvement aims were addressed; these focused on 1). ca. doubling childcare capacity, 2). supporting an increase in residential housing, 3). striving to create investment of a new commercial development (including amenities to improve an underserved area of the county) and, 4). a plan to significantly improve and expand the County’s marketing and advertising channels in order to attract talent and so, fill many open job positions in the county.
Student Team: Brian Birdsall, Kayla Veeder, Ryan Melvin
This project aims to reduce inefficiencies within Standard Industrial’s corporate office and shop floors. It aims to promote the usage of Lean 5S methodologies to enable management to make better decisions and anticipate problems prior to occurrence.
This includes maintaining organization and decluttering workstations, eliminating paper redundancies, and labeling items to reduce orientation time within the facility. Furthermore, the development of a backend system that will be utilized maintaining the application and creation of an accessible database for senior management and directors. In this project, we aim to:
Next step is to create a dashboard using Power BI that not only includes the 5S data collected in the no code app but provides a framework to display other production information.
Student Team: Yijia Chen, Wenbo You, Ahmed Ali, Amy David
Student team will research the use of alternative energy at the Lafayette, Indiana production location. Students will determine the viability of energies such as hydro, solar, and wind for the purpose of lowering fossil fuel consumption and reducing carbon emissions. Deliverables will include recommendation of Biomass Direct Combustion System with following benefits:
Biomass O&M costs range from $0.05 to $0.08 per kWh, variation is dependent on fuel availability and costs
Student Team
The Wabash National AME Materials Engineering Group would like to commend Jacob Raspe and Hui Zeng for their excellent work over the Spring 2021 semester on our Plan For Every Part (PFEP) project. During this semester they accomplished the following,
Considering the obstacles of remote work and connectivity to WNC system, Hui and Jacob did an outstanding job. Their work benefited our group immensely by allowing us to focus on other activities related to this project. We are looking forward to working with the DCMME team again over the summer and hopefully into the fall semester.
Student Team: Hui Zeng, Jacob Raspe
The successful completion and deployment of this visual dashboard will help Evonik by achieving the following objectives: 1. Make decisions based on facts and on current data that is periodically refreshed. 2. Make data more valuable by allowing every organization member to gain insights that help them perform their job better. 3. Save time and frustration by having all data analytics on one screen instead of flipping between screens, digging through databases, or signing into multiple analytics applications. 4. Get an easy-to-understand, objective view of current performance that will effectively serve as a foundation for further dialogue and surface metrics relevant to each team in a mutually understandable way. 5. Get an at-a-glance big picture of every critical metric needed to make informed decisions, including metrics and key performance indicators from multiple data sources, markets, and departments. 6. Get insight into possible problem areas so stakeholders can handle challenges proactively.
Student Team: Vikram Narendra, Rajinder Budhiraja, Vincent Hu, Amy David
Student Team: Aadav Srimushnam Sundaranathan, Alec Patrick White, Fatoumata Coumba Niang, Amy David
Kirby Risk is a Tier 1 OEM supplier to organizations such as John Deere and Caterpillar. With an increasing EV market, the firm wants to strategically explore the EV charging station market for retail and commercial use to expand its current business operations. Kirby Risk has relationships with material suppliers, and the electrical and mechanical expertise to manufacture. Therefore, Kirby Risk has the reputation to become the main supplier of an EV charging station brand. Project objectives. Perform a market analysis of EV charging stations and/or batteries
Build a marketing plan based on research to identify potential EV Charging Station OEMs who need a Tier 1 Supplier of the charging unit.
The EV wave is coming and there may be opportunities in the EV Charging station assembly. The challenge is to do the research to find out who in in that space and potential partners.
Project scope included:
Include recommendations of suppliers to develop future partnership
Student Team: Alfred Carandang, Kristin Zalewski, Jason Farmer
Bio town farm has difficulty finding tools that are used through-out farm by workers. They need a process/system to track tools to ensure they are return to maintenance area. Initial phase concluded with recommendation of potential electronic tool tracking system. Next step is to get client approval and initiate a Tiles pilot.
Tiles are Bluetooth trackers than can be connected to the Tile App on both iPhones and other phones. Each tile registered on the app can be given a name for tracking:
It will be much harder to lose an item with multiple people being on the network, and even if it is left behind you will be able track where it last was and hear it
Student Team: Ana Paula Trejo Mendez, Johanna King, Kevin Zeiba
Oscar Winski metal operations process a variety of incoming materials, outgoing materials, and WIP (work in process) daily. Due to space limitations and magnitude of materials being handled and processed daily, materials are often stacked on one another, and moved several times during processing steps. Keeping track of where materials are stored currently is an ongoing challenge. Purdue Students visited and discussed these challenges and concerns with Oscar Winski’s staff and then investigated various technologies and methods for possible solutions. The student team returned to share their findings with management and on several fronts shared some of the very same thoughts which management was considering as possible best solutions, providing Oscar Winski’s staff an independent validation of their possible plans and actions.
Student Team: Rajinder Budhiraja, Vikram Narendra
Build a change management support application that helps an engineer draft an MoC (management of change) document. provide a step-by-step workflow for drafting the change, provide instructions for each step in real time, provide access to sources of data that help draft each step in the change, provide historical examples of similar content to reference during the drafting of the change.
Student Team: David Hoffman, James Schubert, Tyler Mancuso, Noah Mugmon
Hardware for all products is pulled at a single standalone station with several Bins containing every type of hardware. Currently the hardware ticket is scanned than the computer shows the item numbers and quantities. The hardware puller goes to the proper bin, scans the bin and then selects the hardware, packages and labels. The goal of this project would be to develop a grid-based PLC system that lights up a LED light at the appropriate hardware bin combined with a weight scale that allows the computer to ensure the proper quantity of hardware has been pulled.
Student Team: Ethan Haeberle Grant Bolotin, Bora Schrom
'Need all documentation on floor throughout plants to be verified being correct revision, update and proper location to match what is shown through our electronic log 'controlled documents'. If found to be incorrect, the logged information needs to be updated/corrected. If found to be using documents on the floor that are not within the electronic 'controlled document' system, it will need to be added to the 'controlled document' system to match. All forms must be reviewed on an annual basis. This is typically done by printing documents and physically signing them when reviewed and then stored in a binder until the next years review. This method does not 100% prevent undocumented changes or use of a previous version on the floor. In addition to ensuring the correct documents are being used, a student could help design a user-friendly e-system that will document and schedule annual form reviews and changes, and help transition to e-signature approval, e-document control, and e-use of these controlled documents on the shop floor.
Student Team: Kim Cahoon, Cherag Keswani, Colin Lee-Au
The research was conducted for Indiana Department of Transportation (INDOT) as part of a project to assess the potential benefits of constructing conduit infrastructure on right-of-way along state highways. The conduits would be leased to information and communication technology (ICT) companies for fiber-optic cables that expand broadband internet coverage in the state.
Student Team: Anuja Wangnoo, Karthik Sethuraman, Abrar Mohammed, Gopi Manthena
What would it take for an on-demand laundry service provider to be twice as fast as before, switching from a turnaround time of 48 hours to 24 hours?
Could rest areas in Indiana be upgraded to include electric vehicle charging stations, high-speed internet service, interactive touch screen displays and parking lot sensors?
Student Team: Dutt Thakkar, Andrew Colbert, Hannah Pratt
As self-driving or autonomous vehicles become more viable, Indiana Department of Transportation is making plans to accommodate them on its highways. It has collaborated with Purdue University on a study that shows the significant impact that autonomous vehicles could have on Indiana's transportation and manufacturing industries.
Student Team: Anmol Singh, Mihir Bhatia, Sazzadur Rahman
Student Team: Maria Hartas & Ishan Mehta.
Two employees were working in proximity on a packaging line affecting costs and quality ‘due diligence’ when accomplished workers were absent. Value Stream Mapping with Infection mitigation (VSMI) is a variant of Value Stream Mapping for reducing waste and increasing value-added time related to actual product-manufacturing steps/processing. VSMI is an invention by our DCMME team. The project was designed to mitigate infection risks and identify rate-limiting steps and wastes where revised systems would add value to the bottom-line.
Student Team: Marissa Cabrera & Colby Phipps.
This project started as a cobot identification/recommendation process, but very soon needed to embrace further process steps and investment in order to present component parts for access by the cobot End-Of-Arm-Tool (EOAT). All decision-steps that would be required and a single fail-safe business model for purchase, implementation and failure mitigation were established for the company Board.
Student Team: David Ramirez & Josh Reilly-grim.
The objective of this project was to analyze scrap history data to determine which equipment created the highest percentage of scrap and recommend actions that can be taken to reduce scrap rate.
The project required the students to analyze the historical scrap data and create several grafts that showed which machine created the most scrap, identified the most probably reasons, and recommended countermeasures to reduce the scrap.
The results were presented to the Tru-Flex management team which was very appreciative.
Student Team: Mathew Matthew Caleb Gebbie, Abhilasha Satpathy
This study investigates multiple machine learning methodologies that KA Components manager can use to allocate appropriate tasks to suitable workstations efficiently. The motivation of the study is to help operations managers device strategies to improve the efficiency of their operations in assembly lines. With the use of predictive models, our goal is to help them not only understand but also evaluate the capability and performance of each workstation and assign tasks to them accordingly. Within the scope of the study, models have been developed to predict the completion times of incoming tasks so that an apt workstation can be scheduled well in advance for the planned tasks to improve production line efficiency. In addition to this, using machine learning models, various factors, and measures impacting the performance of the production line have been assessed. Also highlighted in this study are the possible features that are missing and could have been influential in this analysis.
By collaborating with a structural building components manufacturer and using their data, we build and assess various analytics models and highlight some of those models which help derive quantifiable insights that operations managers can incorporate to improve their existing processes.
Student Team: Abhishek Bhambhu, Deeksha Goyal, Mengying Sun, Sudarshan Ananthakrishnan, Yang Wang
KA’s production flow involved cutting and preparation of raw materials by job number and placing all of the necessary materials on a cart(s) to be stored in a staging area for assembly. KA would identify the materials by writing the job number on a piece of cardboard place on each cart of material. The problem was that when assembly personnel came to the staging area looking for the next job for assembly, they were spending a great time of time looking for these carted materials, as sometimes there could be 30-40 carts of materials in the area. Purdue Students visited the site and then evaluated a variety of possible solutions, and later presented to KA management the group’s finding and reported on a commercially available and cost-effective technology solution to the problem.
Student Team: Yizhou (Zoe) Fang, Rushabh Gala, Sai Bhargav Nimmagadda, Dutt Thakkar
Visualizing process operating patterns sparks another crucial business insight, which provides decision makers a strong tool to develop an efficient contingency plan when facing critical moments like equipment malfunctioning or project scope revision. Meanwhile, the model recommendation could ensure the anticipatory in process planning, monitoring, and optimizing the utilization of plant resources.
Student Team: Roy Vasher, Mike Gulbranson
Evonik is seeking to optimize the manufacturing sites' production capacity, smooth process schedule and generate strategic planning solutions. The key to the problem is understanding current asset utilization, identifying idle time caused by improvident planning and improving throughout time of process. Low asset utilization is usually known as higher rate of resource waste and production cost, longer production cycle time, and lower productivity. Hard to detect the performance of asset utilization also affects managers' strategic decisions on capital investment, project planning, and risk management.
To develop the process optimization model, the first step is to define variables and parameters for each production process, construct mathematical relationships between each process stages, and identify resources and procedure constraints. Then, our team would utilize optimization tools to fulfill the goal of minimizing process start-to-start time and recommend the most efficient process plan. After exploring past operating data and measuring asset utilization rate at multiple levels, our team would identify the idle time of equipment and the waste in the actual production process. For example, unreasonable equipment running in the operating process flow results in unexpected production energy waste. Further, the model could assist monitoring the asset’s status in each batch, time period and desired level. Such a system supports managers to check asset utilization and process performance more precisely with less human effort.
Visualizing process operating patterns sparks another crucial business insight, which provides decision makers a strong tool to develop an efficient contingency plan when facing critical moments like equipment malfunctioning or project scope revision. Meanwhile, the model recommendation could ensure the anticipatory in process planning, monitoring and optimizing the utilization of plant resources.
Student Team: Luqi Chen, Yi-Chun Ku, Yuchen Li, Yu-Chuang Tsai, ChunXuan Zhang, Yang Wang
The study aims to identify and predict equipment failure, thereby reducing downtime and costs. Evonik has been facing increasing instances of equipment failure, causing a rise in the equipment downtime. This barrier towards complete resource utilization emphasized a need to classify various equipment, identify the bad actors amongst them and predicting when they would fail. We performed LSTM-based auto encoders for anomaly detection and used an Ensemble method of Xgboost, Catboost, Adaboost, Random Forest and Support Vector Classification for failure prediction. Also, we used Deep Neural Networks to predict the probability of failure. We then used hyperparameter tuning and grid search to optimize parameters for the classifier. Using cross-validation, we evaluated our model accuracy to be about 84%.
This resulted in increasing output, reducing downtime, operational and maintenance costs.
Student Team: Medhaa Bangalore, Mankaran Singh Bahri, Medha Gupta, Soujanya Samineni, Yang Wang
The primary objective of the Ohio River Bridges project was to develop a present value analysis by analyzing the funding structure of both INDOT and WVB partners to identify whether the P3 approach of DBFOM is profitable or not. The funding structure includes the toll revenue projection model (reflective of current traffic patterns), operations and maintenance cost of the bridges. We also did a comparative study of Ohio River bridge with other bridges that have similar features (physical, financial, design, policies, etc.).
Project Scope: The key objective of the project was to collect extensive data including employee information, location, skills and core competencies for 270 companies in the 10-county region of Indiana with the goal to develop smart people, smart processes and smart technologies through various resources.
Project Scope: The WHIN Supply Chain Leakage project aims to solve the issue of the Supply Chain Leakage in the Wabash 10-county region by developing a web database which will allow companies to easily access information about each other and take advantage of products and services available within the region itself resulting in reduced supply chain leakage. The database is being populated with information from participating company websites that will serve as a directory.
Project Scope: This project is assisting one of the scientists on finding product/market fit, economic value, and ROI for a new technology to produce synthetic graphite which would have a huge impact on cost of electric vehicle batteries and drive EV sales.
Project Scope: This project is assisting a scientist on Technoeconomic analysis of production and separation of rare earth metals and developing a product roadmap for the technology. The team is also studying purity vs. cost of purification vs. price of Dysprosium, Cerium & Neodymium.
From Trash to Treasure: Electronic Waste Mined for Rare Earth Elements
Project Scope: The team is developing a game to simulate the capacity game and its outcomes based on various constraints on information sharing using ASP, MySQL & HTML and will launch this game to train students.
Project Scope: This project focuses on the identification and tracking of all people in the engagement center. In this project, live video feed from cameras set up in the center was used as input. OpenCV algorithm using tensorflow library identified and tracked people.
Project Scope: In this project we will be leveraging video analytics to perform crowd analysis over visitors in a room. The objective of the project is to detect and count the number of people in a room every 15 minutes. Live feed and images from preinstalled cameras will be processed by the algorithm, providing us the number of people at that instance in the room.
WHIN Education has built a network of company representatives interested in providing research to develop a global epicenter for agriculture and next-generation manufacturing empowered by smart “Internet of Things” platforms. The team is in the early stages of company interviews and has spread the word through interactive group sessions and a WHIN launch event. In April, WHIN offered a pilot training session, where the team helped to address technology and education issues companies may be facing.
The European Union grant offered faculty, students and staff a great opportunity to work with Procter and Gamble on projects that included business continuity planning with suppliers, manufacturing synchronization and container visibility optimization. Each of these projects was driven by detailed data and contracts and focused on generating quantitative estimates of the impact of optimizing the system and maximizing impact to the supply chain. The Business Continuity project was led by Professor Gemma Berenguer. The simulation models for production were led by Professor Olga Senicheva.
The manufacturing synchronization and container visibility projects were led by Professor Ananth Iyer. The goal of the synchronization effort was to produce all required orders on a weekly basis i.e., get to a goal of 100% weekly synchronization. But there were some key issues to consider, from differences in packaging, to differences in formulation to line production constraints to forecast variability. In addition, there were setup times that had to be kept track of as production shifted across products. With intense collaboration with P&G managers, and data at a highly granular level, the team produced a mathematical model to optimize the system that permitted both 100% weekly synchronization as well as a close to 5% projected reduction in capacity required.
The project provided a great learning experience and will appear in various forms, from class exercises to cases to academic papers in future years. The container visibility project involved a visiting faculty member from Turkey, Professor Cagri Haksoz and Ananth Iyer. They applied ideas from their past methodological papers to the estimation of the optimal way to use container visibility to improve the supply chain. Their results suggest that waiting to gather data so that it helps in the choice of contingent actions may be preferred to acting too early. Similarly, the decision of when to get this information may depend on how significant the cost of delay is to the system and how expensive the cost of taking corrective steps to remain on schedule. The container visibility project’s results are expected to be used to understand the economics of different tracking schemes for global container flows.
A second student group worked with Dr. Berenguar and Dr. Iyer on the Proctor and Gamble’s (P&G) laundry pod to accomplish a safety stock and inventory analysis for key components, a JaamSim model to visually and analytically simulate supply chain disruptions for different components, a business continuity and risk planning analysis for each supplier, and an optimization model to determine optimal production plans in a global context. The team began the project by looking at different components and identifying the most critical by delay impact, supplier risk, demand variability, and other factors. From there, the team created a mathematical model to provide recommendations on optimal inventory levels. The next step was a model created in JammSim, a 3D graphic simulation tool, which visually showed how supply chain disruptions lead to manufacturing delays and the financial impact. This simulation model showed the importance of managing risk which transitioned the project into the third stage. Here the team created business continuity plans for each component. This involved conducting a risk analysis of the supplier, the substitutivity of the component, the criticality of the material, and other risk areas. A plan was created for each component of the laundry pods and areas that need to be particularly monitored. The final part was an optimization model that pulled in data from other parts of the project which enabled us to create optimal production plans for day-to-day production as well as when disruptions occur.
Project Scope: The project aimed at documenting the current state and mapping order processes using Visio, identifying and addressing the key gaps in the current state and proposing an anticipated future state for order process by building a Salesforce order queue for the plants located in the US.
Premier Auto Detailing and Wash serves individuals and business owners throughout the Greater Lafayette Community, providing vehicle cleaning, detailing and repair services for all sizes, makes, and models of vehicles. The company was looking to optimize their operations to provide faster and on-time delivery for its services and to use their capacity more profitably. They also wanted to reduce their carbon footprint and become a green business to contribute to the environmental cause. The team from DCMME center made site visits to understand the business problem better. The site visits were also used as opportunity to interview process stakeholders working on-site. Post data collection, the team used various analyses used for solving business problems. As per the AS-IS analysis of the business operations, the following areas for improvements to reduce the carbon footprint of the business were discovered: water usage and treatment, solid waste disposal, power utilization, air emissions, and operational layout. The team listed out the long-term and short-term measures to be taken for each of these areas. The team also summarized the information needed to help Premier get started with Indiana Department of Environmental Management’s Environmental Stewardship program, and the team provided curated information to put a robust Environmental Management System in place.
We are on the verge of the next transformational revolution in transportation and the automobile industry with the introduction of Autonomous Vehicles. As an emerging technology, Autonomous Vehicles have the ability to impact economic value creation as well as enable economic development, with its adoption in the consumer as well as business markets. Indiana Department of Transportation (INDOT) has partnered with DCMME Purdue students to work on developing a business ecosystem around Autonomous Vehicle Infrastructure in Indiana to help support this emerging technology and allow businesses to leverage the benefits that it brings with it. The project team will be evaluating the perception of Autonomous vehicles with the business community and identifying opportunities and key projects for INDOT to embark on. The focus of the partnership is to empower businesses to adopt and implement Autonomous Vehicles and leverage them to develop a competitive advantage.
In the INDOT Economic Development project, the project work is progressing as per the schedule and the team has completed mapping of I-65 and I-70. The mapping includes gas stations, restaurants, rest areas, emergency shelters, truck parking spaces and motels. Moreover, progress has been made on completing the same for I-64 to I-94. Data comparing Federal vs. State owned roads has been compiled. Data on green space from the state tax department has been acquired which will form the base for filtering out state owned green space. This project is in its early stages, and much more data will be compiled in the future.
The focus of the project was to research for new market opportunities, improve operations with the help of new technology, and build a simulation tool for improving bidding accuracy for the contract work services team at JRDS. The proposed solution was designed to help JRDS enhance current operations and establish new business. During the course of the project, the team explored the opportunity for JRDS to pair with French Knot to carry out quality check, packing and billing for their gloves, headband, caps and other products. The other ideas for business development included bundling, packing of school supplies during start of school season, and fruit basket packing and decoration. Technologies like Light Guided Systems, Bar Coding, Microsoft HoloLens, BrainExchange, Video Analytics, and BlueVision were evaluated. These technologies would enhance the productivity of different types of employees in the facility. We proposed Light Guided System and Bar Code technology for streamlining the supply chain and quality test system. Light Guided System can be used to quality inspection, training, sorting, part knitting and sequencing. For simulation purposes, the team used SimQuick spreadsheet and JaamSim simulation software to replicate real life operations at JRDS to help improve the bidding accuracy and reduce the risk of variation from planned and actual costs.
Summer Student Team: Matt Bobrowski, Koji Yamada, Sayan Sinha
Spring Student Team: Joey Meisberger, Taylor Haws, Matt Jung, Gisela Condado, Pablo Martinez, Akshit Bajpai
Project Description: In 2014, American Axle & Manufacturing, Inc., purchased what is now AAM’s Rochester Manufacturing Facility (ROMF), which is a 71,000 square foot facility with various machine tools in Rochester, Indiana. This is the first IN-MaC project grant for the center which emphasizes Indiana economic improvement. The project objective is to model, analyze and evaluate various proposals to maximize the Gross Profits, Contribution Margin and Internal Rate of Return (IRR) to support the utilization planning for the open floor space currently available. Through the adoption of these modeling and analysis capabilities, this project will result in the following outcomes:
Student Team: Linjie Wang, David Windmiller, Xiangyang Song
Faculty Advisor: Sang-Phil Kim
Project Description: CCI is a leading manufacturer and innovator headquartered in Waukegan, IL which produces wire, cable and other electrical products, serving a multitude of channels and industries. CCI categorizes their broad assortment of products into 4 categories; Industrial, Electronic, Assembled and Copper Fabrication. Over the past 40 years, CCI has built the business through a series of strategic acquisitions and organic growth to ensure exceptional performance. The scope of this engagement was to both optimize inventory levels and investigate changes in production quantities for Coleman Cable. The team’s recommendations were presented in a PowerPoint presentation and Excel worksheets, and included suggestions for implementing a (Q, r) inventory control policy, focused on implementing reorder points and levels of safety stock in order to reduce lead time to the fabrication department’s customer. These reorder points and levels of safety stock were suggested according to both normal and Poisson distribution models.
Additionally, optimal production quantities (batch sizes) were proposed for 9 of CCI’s products according to the Economic Order Quantity (EOQ) model.
Student team: : Christine Zhang, Deepika Mokkarala (MSGSCM 2013), Isra Gadri (MSGSCM 2013), Yichen Ding (MSGSCM 2013)
Faculty Advisor: Julia Kalish
Project Description: During the summer semester of the Masters in Global Supply Chain Management program, a team of students worked on a project for Coleman Cable Inc. through the GSCMI center. Coleman Cable, Inc., headquartered in Waukegan, Illinois, is a leading manufacturer and innovator of electrical and electronic wire and cable products for security, sound, tele-communications, electrical construction, retail, commercial, industrial, irrigation, and automotive markets. The team was faced with inventory and supplier issues and acted as student consultants from Purdue for the Coleman Cable Inc. Lafayette, Indiana branch specifically in the rubber raw material department. After Coleman Cable Inc. decided to manufacture the rubber component for their products at their own facility, they were faced with new challenges in vendor and inventory management of the raw materials. The project’s main objective was to avoid shortages in inventory of the raw materials and to bring about a consistent ordering pattern. The team analyzed the data available since the production had begun and provided an excel based inventory model which dealt with the purchasing and maintenance of 45 critical parts coupled with the MRP (Material Requirements Planning) system utilization. This solution helped reduce shortages in inventory. Students also worked towards a vendor management system by which the company could bring about an ordering pattern among 22 different suppliers. They documented the changes in processes and made the solution more flexible for future enhancements. The solution required no investment and slight adjustments were made to the internal processes to accommodate this model which helped the company reduce their production and procurement costs. As students in the Global Supply Chain Management program it was an excellent learning experience for the team to be able to apply classroom lessons to solve industry challenges. The company is currently using this model for purchasing and inventory management and is considering extending this solution to other departments with similar issues.
Student team: : Randall Miao (MSGSCM 2013) Shankar Rajagopalan (MSIA 2013), Sunil Merumu (MBA 2014)
Faculty Advisor: Julia Kalish
Project Description: This project with Coleman Cables Inc. (CCI) was about inventory management and production planning. The project provided understanding on how inventory management works in organizations. During the course of the project, it was evident that even advanced planning systems have drawbacks. This project primarily dealt with made to order items, where there is immense pressure due to lead times and hence such planning is of utmost importance. The team, along with company representatives with able guidance from Dr. Julia Kalish and the GSCMI center, came up with an advanced system to estimate process losses and incorporate losses into the planning system. Traditionally, these losses lead to mismatch in inventory management and often lead to shortages. For a cable manufacturer, shortages can be very troublesome as requirements are in terms of length, and shortages in meeting requirements would mean making the entire cable again. The system developed helped CCI address the issue of matching copper lengths with insulation requirements. Having an opportunity to work with a real life problem gave the students great insights into planning systems and the impacts of how it might affect business and customer relationships in general.
