A project with Indiana Department of Transportation
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 of 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.
WHIN Supply Chain
Project Scope: The WHIN Supply Chain Leakage project aims to solve the issue of the Supply Chain Leakage in theWabash 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: 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.
DOE Project #1
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.
DOE Project #2
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.
DOE Project #3
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.
OPENCV People Tracking
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.
OPENCV Crowd Analysis
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.
Premier Auto Detailing
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.
Proctor & Gamble
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.
Project Part 2
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.
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.
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 econosystem 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.
INDOT Economic Development
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.
Inventory Management, Financial Analysis and Facility Detailing, American Axle & Manufacturing
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:
1. Written proposal and recommendation of various alternatives utilizing a variety of academic methods/tools.
2. Final Project Summary to support the cost justification and project return on investment, implementation plan, etc. Detailed inventory storage management models and multiple plant layouts were recommended. Also included were financial analysis, material flow and SWOT analysis for different plant configuration and optimization of storage space including holding cost analysis.
Inventory Optimization Project, Coleman Cable (2013-2014)
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.
Rubber Raw Materials, Coleman Cable
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 specifi cally 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 diff erent suppliers. They documented the changes in processes and made the solution more fl exible 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.
Inventory Management & Production Planning, Coleman Cable
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 aff ect business and customer relationships in general.
Spare Parts Inventory Management, Evonik
Student team: Ana Romero, Joshua Kwak(MBA 2013), Sutapa Paul(MBA 2013), Roshan Picardo(MBA 2013), Susana Restrepo (MBA 2013)
Faculty Advisor: Qi Annabelle Feng
Project Description: Evonik is one of the largest specialty chemical companies. It is headquartered in Germany and does business globally. It has its presence in more than 100 countries and operates production plants in 24 countries. The employee strength is approximately 33,000. The core business is focused on high-growth megatrends such as health, nutrition, efficiency and globalization. In regards to performance (2011), Evonik generated sales of €14.5 billion and operating result of €2.8 billion.
Evonik acquired the Tippecanoe Laboratory from the previous owner Eli Lilly, as a strategic investment to enlarge their presence in the pharmaceutical industry. This purchase augments Evonik’s exclusive business of synthetics in America and adds capacity for additional market growth. Evonik’s exclusive Synthesis & Amino Acids Business Line - part of the company’s Health & Nutrition Business Unit - focuses on the customized production of pharmaceutical intermediates, active pharmaceutical ingredients, amino acids, and high-quality derivatives. The data analysis part of this experiential learning process entails understanding of diverse machinery and their spare parts in the T2C fermentation unit of the Tippecanoe labs.
Production Planning at Verallia (Phase I)
Student team: Aniesh Aravin (MBA 2013), Ivan Banchs (MBA 2014), , Pedro Gerum (IE Undergraduate 2013) , Stephen Masters(MBA 2013), Vijay Sachdeva(MBA 2013)
Faculty Advisor: J. George Shanthikumar
Project Description: Verallia, a subsidiary of Saint-Gobain Company is number three glass packaging manufacturing company in the world contributing to 9% of Saint-Gobain’s FY 2011 sales. Given that packaging is a very challenging business where growth is qualified by the substitute products; as a result – Verallia is looking to gain competitive advantage by measures such as cost-savings so as to bring more efficiencies at the table.
Demand uncertainty is one of the major operational challenges at Verallia. The focus of this project was to help identify some of the areas which could be improved in such a situation which could better the demand prediction and planning thereby improving the production output rates, cost of production and reduce manual intervention.