This thesis project provides practitioners with a new mathematical model to estimate an appropriate number of production planners required for the supply chain planning department of a company in the consumer packaged goods industry. Using bivariate correlation and multiple regression analyses, we explored whether a relationship exists between the required...
As the recession and global competition threaten profitability, firms are increasingly turning to their procurement function of the supply chain to achieve significant cost reductions and maintain a competitive edge. When procuring unique, highly-engineered components, the price is often negotiated with suppliers. Our project explored ways to estimate a procured...
Scheduling dispatchers in the Rail industry is difficult because of training requirements, unplanned employee absences, and the nature of shift work. This project uses past data on absences to build a model to predict unplanned absences. It also uses Monte Carlo simulation to evaluate the tradeoffs among extra staff, the...
By conducting semi-structured interviews and developing a value chain map, we identified and quantified the business costs of each actor in the distribution chain of pharmaceuticals in Zambia and Zimbabwe. We then estimated how these costs translate into the mark-ups of two essential medicines, M1 and O1. These calculations are...
This project explored what factors affect tender rejection, a frequent and consistent problem in the truckload (TL) transportation industry. We examined geographical pattern, length of haul, and variability of volume as the key factor. We used ordinary least squares (OLS) regression analysis to quantify the effect of those factors. Author...
This project explores how we can develop a Demand Signal Repository (DSR) to better predict demand. We devised a methodology, collected and cleansed the data, and built more than 240 models before we arrived at models that could improve forecast accuracy. The models explained 85%+ of weekly demand per customer...
This project uses a stochastic linear programming (LP) model to evaluate the capacity of the five United Nations Humanitarian Response Depots (UNHRDs) to respond to a single potential disaster: what expected percentage of people affected may receive emergency relief items and in what period of time? The model also recommends...
This project reviews the characteristics and uses of spot-market rate indexes in the US truckload transportation industry. It examines factors that influences rates and determines that multiple indexes of the spot market are required, each specified to a particular geography and range of tender lead times. Author: Andrew Bignell Advisor...
This project explores the dynamic between experts and users of complicated optimization models that are used in planning global supply chains. After conducting a comprehensive literature review on optimization modeling, communication methods, and data visualization, we surveyed a group of solver application users from our sponsor company to determine where...
This research project analyzes the current state of a typical Aerospace and Defense (A&D) support supply chain, and envisions a desired state with better integration. Finally the research proposes the +Add Model as an easy to understand and deploy roadmap to bridge the gap. The “+Add” Model stands for Aggregate...
This research examines key aspects of ethanol including its material characteristics, supply chain, and government legislation that affect its market demand and availability. In addition, it discusses the social and environmental impacts of the growing biofuel industry stemming from government mandates. The goal of the project was to investigate existing...
This project explores the benefits of establishing and operating Foreign Trade Zones (FTZs) and Bonded Warehouses (BWs) for luxury goods in North America, using the case of Ralph Lauren Corporation’s (RLC) distribution network. With over 3 million square feet of warehousing facilities in the U.S., the company wants to explore...
Through our study we have attempted to address the focal issue of sustainability for chemical supply chains. The meaning of the word sustainability itself is quite subjective and there is both uncertainty and ambiguity related to how this crucial parameter will impact future business decisions. Currently, there is a dearth...
A systematic approach including seven steps to build indicators for scenario monitoring was developed. Factor analysis was used to assign weights to individual indicators. And then individual indicators were aggregated linearly to build composite indicator. Next, the composite indicators were used to assess the changes in the driving forces so...
By using a Southeast Asian multi-purpose port as a case study, this project enhances the investment decision-making process for port infrastructure. Two existing methodologies are successfully applied and modified, leading to the development of both an investment tool and a framework for selecting an optimal investment strategy to address capacity...
In the agrochemical industry, balancing supply with extremely seasonal demand has been a struggle for most companies due to their capacity constraints. Stocking enough inventory ahead of the peak seasons and increasing the production capacity are two ways of resolving the issue. Our research examines an approach to achieve the...
For fresh produce, product freshness is very critical in satisfying customers and reducing obsolescent cost. While network nodes in a supply chain add more “touch” of inventories, they also reduce safety stock through a risk pooling effect. Our project studied relevant factors and created a predictive model to quantify the...
Outbound transportation collaboration is the act of cross-company consolidation of shipments originated from and destined to a common area. It can reduce transportation cost depending on the level of synergies that exist between companies’ supply chains. For companies who are interested in tackling collaboration on their own (DIY), this research...
This project determines appropriate inventory modeling approaches for externally sourced medical products. The authors identify the key drivers of inventory, highlight gaps in the current inventory modeling approach, and recommend inventory targets through the use of simulation or an appropriate safety stock formula. Authors: Nichole L. Hillstrom and Renato A...
This research project studies the global supply chain network flow of a low volume low margin industrial chemical product. It presents a network optimization model to minimize the total cost-to-serve (C2S). It also includes three scenarios to compare C2S when supply capacity shifts. Authors: Fred Dacha and Li Jin Advisor...
This project explores whether the readily available data in agriculture, published by various sources such as USDA, universities and weather stations, can be used in conjunction with the manufacturer’s private data to better forecast the demand of agricultural products (chemicals). We analyzed certain variables such as corn price, acres harvested...
Most companies aim for perfect on-time delivery from suppliers, since late deliveries cause supply disruptions. But some companies incur direct costs in maintaining supplier delivery performance. Our empirical research looked at a company that invests in suppliers to help them achieve a desired performance level. We developed a framework that...
Analysis of e-luxury from a systems-thinking perspective can give companies valuable insights into how to organize their supply chain and align their operations to capture demand. In the South Korean market, the luxury retailer that can simultaneously elevate its brand, segment its products and services, and unify the online and...
In this research, we investigate how carrier assignment methods impact available capacity and pricing. In the lane robustness study we examine how shipment volumes on specific lanes affect price escalation. We also study the role of brokers and asset based carriers in capacity creation process. In addition, we examine lane...
This research aims to improve the accuracy of individual freight train run time predictions. A regression model is proposed utilizing a broad selection of explanatory variables. The performance of the proposed regression model is compared against a baseline simple historical averaging technique. The proposed regression model offers substantial improvements in...
