Thesis: M. Eng. in Logistics, Massachusetts Institute of Technology, Supply Chain Management Program, 2016. / Cataloged from PDF version of thesis. / Includes bibliographical references (pages 66-70). / Recent advances in technological capability and economics have opened up a new world of capability known as the Internet of Things (IoT). The Internet of Things is the concept that all machines can be connected to the internet, and be remotely monitored through an infrastructure of interconnected software and hardware. Many companies are just beginning to explore the economic value that the Internet of Things can unlock, with much of the initial focus on remote diagnostics and predictive maintenance, particularly in application to industrial machines. This research tests various scenarios of predictive failure accuracy, creating spare parts forecasts based off of varying predictive forecast parameters. We compare these scenarios and their respective outputs to a regular time-series forecasting scenario, inserting each type of forecast into a periodic review (R, S) inventory system. We measure the output of each forecast put into the system in terms of spare parts inventory levels and in-stock service performance. We find that as long as the true positive rate (TPR) and false positive rate (FPR) have different values, our model is able to hold a lower average inventory while providing a higher level of service. Additionally, as the difference between the two values increases, the average amount of inventory held decreases, while the level of service provided increases. A more detailed summary of the results found and the implications on service supply chain were developed, and further areas of research are discussed. / by Michael Patrick Brocks and Renzo Eliseo Trujillo Castaneda. / M. Eng. in Logistics

Thesis: M. Eng. in Logistics, Massachusetts Institute of Technology, Supply Chain Management Program, 2016. / Cataloged from PDF version of thesis. / Includes bibliographical references (pages 72-73). / As supply chains become more global and complex, it increases the importance of end-to-end visibility into the material, information, and financial flows of a firm. This work covers various aspects of supply chain visibility such as current status, its benefits, and the benefit-enabling mechanisms, traced through multiple stages of research, including a survey, round- table, and detailed interviews. Specifically, we developed a multi-case study analysis of supply chain visibility solutions (SCVS) and analyzed its effect on key supply chain processes. A qualitative "with and without SCVS" framework was employed to understand the changes observed in key business processes at several companies that recently implemented SCVS. This was combined with a cross-case study analysis to evaluate the effect of SCVS on the efficiency and effectiveness dimensions of process performance. We found that SCVS has a direct positive effect on data management processes via benefit-enabling mechanisms such as automation, standardization, and better raw data. Key operational processes, such as shipment and inventory management, risk management, and procurement and partner collaboration, were affected positively by SCVS via the antecedent data management process. The strength of impact of SCVS on key operational processes varies by company characteristics and the stage of implementation of SCVS. This research is most useful to companies considering implementing an SCVS to understand the potential benefits of SCVS and the underlying mechanisms. Managers can increase the relevance and robustness of results by extending the case-study analysis to include more companies with similar operating characteristics. / by Anna Stanchik. / M. Eng. in Logistics

Thesis: M. Eng. in Logistics, Massachusetts Institute of Technology, Supply Chain Management Program, 2016. / Cataloged from PDF version of thesis. / Includes bibliographical references (pages 90-91). / Multi-stop truckload has been gaining importance in recent years as part of a shift away from Less-than-truckload freight. In our research, we sought to understand how the price and carrier behavior vary as the number of stops increases. Rational economic theory says that these shipments will be more expensive, and experience shows that in practice they also tend to get rejected more often. This thesis tested these two likely results together with other factors known for affecting price and rejection rates, such as lead time, clustering of the stops, etc. We used logistics regression to predict the acceptance ratio and ordinary least squares regression to model the price based on historical data. We found that there is an inherent cost associated with multi-stops, which depends on the number of stops and whether the stop is a pick or a drop. The proximity of these stops as well as the stop-off charge can also impact the price. Carrier acceptance and routing guide depth depends on the price structure and load characteristics. As the number of stops increases, it takes longer for a tender to be accepted and the shipment performance also deteriorates with an increased likelihood of late delivery especially if the initial pickup is late. Therefore, companies need to be aware of the hidden costs associated with multi-stop truckloads as they plan their transportation network. / by Xiaojia (Amy) Chen and Shang Lin (Peter) Tsai Yang. / M. Eng. in Logistics

Thesis: M. Eng. in Logistics, Massachusetts Institute of Technology, Supply Chain Management Program, 2016. / Cataloged from PDF version of thesis. / Includes bibliographical references (page 50). / The United States has one of the safest drug supply chains in the world. However, its security is threatened by new challenges such as counterfeit, diverted, and illegally imported drugs. To counter the new challenges, the Drug Supply Chain Security Act (DSCSA) was signed into law by President Obama on November 27, 2013, with a 10-year implementation timeframe. As a result, companies in the U.S. pharmaceutical industry, including drug manufacturers, distributors, and dispensers, are challenged to fully comply with the DSCSA by 2023. The compliance with the DSCSA will enable companies to operate and manage the risks of their supply chains more efficiently. Industry consortiums, such as the Healthcare Distribution Management Association (HDMA), and the industry leaders have recommended various interoperable data exchange models for the implementation of the compliance. However, domestic and international complexities make it difficult to pick the optimal model for the industry. In this research, we start with categorizing the known data exchange models that can be potentially used by the U.S. pharmaceutical industry. Second, we develop a scorecard methodology based on a framework that considers various factors across the entire supply chain. Next, we examine the categorized models using this scorecard methodology. Lastly, we conclude with recommendations on the data strategy decision for the U.S. pharmaceutical industry. / by Peter Wontae Chung and Tao Zhang. / M. Eng. in Logistics

Thesis: M. Eng. in Logistics, Massachusetts Institute of Technology, Supply Chain Management Program, 2016. / Cataloged from PDF version of thesis. / Includes bibliographical references (page 40). / For many manufacturing facilities, process improvement efforts are a luxury when faced with heightened competitive pressures and a fast-paced work environment where fires are constantly being fought. This need for speed is even more important for startup companies who are racing against time to get their product to the market. Continuous improvement and Lean projects typically span from trial-and-error experiments to changes based on lengthy analyses. Biotech startup Company XYZ has felt the effects of these forces and launched a new effort to improve its operations via continuous improvement and Lean, ultimately reducing costs and improving productivity of operations. This thesis examines one example of a process improvement effort at Company XYZ's pre-clinical manufacturing facility. This project involved characterizing the cycle time and process flow, leading to targeted actions to increase the throughput and reduce the amount of time and effort to manufacture their drugs. Tools and ideas from Lean and Six Sigma were applied and a recommendation and next steps were presented to the company. This thesis also provides a broader demonstration of how such continuous improvement efforts can fit into the pharmaceutical and biotechnology industries. / by Mimi L. Tsai. / M. Eng. in Logistics

Thesis: M. Eng. in Logistics, Massachusetts Institute of Technology, Supply Chain Management Program, 2016. / Cataloged from PDF version of thesis. / Includes bibliographical references (pages 94-97). / The craft brewing industry in New York State has grown rapidly over the past five years helped in part by New York State legislation called the Farm Brewery Act of 2012. The act imposes agricultural stipulations for breweries desiring to file for a Farm Brewing license. The hop industry will have to grow in kind to meet the Farm Brewery Act requirements. The level of growth that needs to be achieved was determined through the use of system dynamics modeling. Production volumes were calculated based on survey results from brewers and farmers. Currently, the state's hop industry is producing a surplus of hops and will be able to supply short-term brewery growth over the horizon of the next three years. It was discovered, however, that the industry is vulnerable to demand shifts and prudent action should be taken to become resilient to changes in buyer regulations and preferences: increasing the economy of scale and building collaborative relationships through farm clustering will improve the longevity of New York's hop industry. / by Nathan D. Stempel. / M. Eng. in Logistics

Thesis: M. Eng. in Logistics, Massachusetts Institute of Technology, Supply Chain Management Program, 2016. / "June 2016." Cataloged from PDF version of thesis. / Includes bibliographical references (pages 83-85). / The company sponsoring our project is a leading chemical manufacturer, supplying a wide range of products on a global scale. One of the most interesting lines of business the company operates is to supply specialty chemicals in faraway places on few weeks' notice. The nature of these supply chains is project- driven, or, in other words, unique, non-repeatable and established for the sole purpose of fulfilling a single project. The company faces the challenge of operationalizing the set-up of such supply chains in order to reduce the amount of time and effort devoted to each supply and maximize learning from each project. This thesis seeks to address the conundrum of setting up project-driven supply chains in a more efficient, effective and easily repeatable way. Through interviews with company personnel, we identify eleven challenges and subdivide them into three categories: Business-Specific, Cross-Border, and Last-Leg. Next, through literature review and interviews with experts, we identify seventeen possible solutions to the above issues, which have the potential to improve planning and execution of project-driven supply chains in the chemical industry. Recognizing that cross-learnings from supply chains in humanitarian and military supply chains are valuable, our interviews include military and humanitarian practitioners, with the aim of increasing the variety of solutions. Using the research data as a basis, we formulate a project-driven supply chain mobilization template aimed at including most critical areas required in setting up project-driven supply chains. This template could be used as both a guideline for planning the mobilization of a supply contract, and as a validation tool to confirm the mobilization process has been thoroughly completed. The adoption of the mobilization template and process via integration with managerial and approval processes is expected to drive a more efficient and effective mobilization of project-driven supply chains for companies within the chemical industry and beyond. / by Sze Xin Mok and Ruggero Moretto. / M. Eng. in Logistics

Disruptions in the supply chain are becoming more common as supply chains become more complex, and supply chain managers of warehouse distribution centers need strategies to minimize the impact of disruptions. In this study, the focus of the research questions was on strategies supply chain managers could use to mitigate the impact of disruptions. The conceptual frameworks for this study were the resource dependence theory and the normal accident theory, which link supply chain disruptions with resource availability and the inability to eliminate disruptions. An exploratory case study involved exploring how supply chain managers of a warehouse distribution center in Jacksonville, Florida, successfully used strategies to mitigate the impact of a disruption after it occurred. Data came from responses to semistructured interview questions from these managers (n = 6) and archival documents related to policies, procedures, and business continuity planning of a warehouse distribution center in Jacksonville, Florida. I analyzed the data by using Atlas.ti qualitative analysis software. There were 6 themes that emerged: collaborating to minimize the impact of disruptions, disruptions precursors, identifying and assessing impact of disruptions, resources used to minimize impact of disruption, strategies to mitigate disruptions, and supplier relationships. The results could contribute to social change by minimizing the negative effects disruptions have on an organization's profitability and performance. Social change can come from business leaders who are able to maintain and sustain their businesses after a supply chain disruption has occurred.

As adaptive clinical trials (ACTs) receive growing attention and exhibit promising performance in practical trials during last decade, they also present challenges to drug supply chain management. As indicated by Burnham et al. (2015), the challenges include the uncertainty of maximum drug supply needed, the shifting of supply requirement, and rapid availability of new supply at decision points. To facilitate drug supply decision making and the development of mathematical analysis tools, we propose two trial supply chain optimization problems that represent different mindsets in response to trial adaptations. In the first problem, we treat the impacts of ACTs as exogenous uncertainties and study important aspects of trial supply, including drug wastage, resupply policy, trial length, and costs minimization, via a two-stage stochastic program. In the second problem, we incorporate the adaptation rules of ACTs with supply chain management and numerically study the impact of joint optimization on the trial and drug supply planning through a mixed-integer nonlinear program (MINLP). For solution approaches to the problems, we use progressive hedging algorithm (PHA) and particle swarm optimization (PSO) respectively, and take advantages of the problem structures to enhance the solution efficiency. With case studies, we see that the proposed models capture the features of ACT drug supply and the mechanisms of trial conduction well. The solutions not only reflect the impact of trial adaptations but also provide managerial suggestions, e.g. the prediction of needed production amount, storage capacity at clinical sites, and resupply schemes. The joint optimization also suggests a new angle and research extension in the field of ACT design and supply.

Supply chain disruptions are more prevalent in Ghana as businesses develop and become more complex. While business leaders recognize the importance of reducing the exposure to disruptions, 83 % of companies still suffer a form of disruption. Using the systems theory as the conceptual framework, the purpose of this qualitative case study was to explore strategies supply chain managers in Ghana use to reduce disruptions in the supply chain. The data collection was through face-to-face, semi-structured interviews from 12 supply chain managers who gave tape-recorded interview responses to 8 questions. Transcript evaluation, member checking, and methodological triangulation ensured reliability and strengthened the credibility of the data collected. Data analysis revealed 6 themes, which included identification of disruptions before they occur, information sharing and collaboration between partners, management strategies to mitigate supply chain disruptions, inventory optimization, availability of human capital, energy, and finance problems. The identification of disruptions was important to participants because they believed if they identified potential disruptions they might prevent them from happening. The collaboration between partners was important because participants believed that the speed at which stakeholders work together after a disruption determines the extent of the cost and the recovery period. Business leaders could apply the findings to provide insight to businesses to reduce disruptions, improve best practices, and increase business profits. Implications for social change include the enhancement of company profits given efficiencies in the supply chain. Such increase in profits leads to increases in taxes, which contributes to the overall betterment of the local communities.