The current Solid-State Electrolyte (SSE) used in Li-ion batteries are limited by their current production methods (i.e., die-pressing; tape casting), planar geometries and random porosities. This constrains their use for mass production in manufacturing plants. 3D-printing of SSEs, however, is a new, highly-researched method that shows promise in expanding beyond the laboratory to more large-scale industrial production as rapid prototyping takes place. Indeed, laboratory studies to date suggest that SSE technology is safer than current production methods and provides a safe high energy solid-state battery. For SSE technology to become a reality though, it must be scalable and financially feasible. Therefore, this thesis aids to bridge the gap between laboratory studies and commercialization by examining the financial feasibility of adopting this technology for a hypothetical battery manufacturing plant. In doing this, I develop a model of the incremental net cash flows, and subsequently the Net Present Value (NPV), from such an enterprise. If the present value of future cash flows from the enterprise are anticipated to be greater than the investment costs, the NPV is positive and the investment in this new technology would be considered instantaneously value enhancing and thus financially feasible. However, future cash flows are highly uncertain, which brings into question financial feasibility in a risky environment. To address the riskiness of future cash flows, I model three risk factors: the cost of raw materials, the potential growth in battery sales, as well as the potential mark-up (profit margin) of the SSE enterprise. Using Monte Carlo simulation (MCS) I model the incremental cash flows considering these risk factors and derive probabilistic assessments of NPV. My analysis suggests that despite the uncertainty caused by the volatility of raw metal prices, assumptions on price mark-up, and uncertain market demand for Li-ion batteries, there is a high probability of an investment in SSE batteries being financially feasible. Future research should consider the value of real options (optionality embedded in tangible investments) as traditional NPV analysis may underestimate the potential value of an investment in the presence of uncertain cash flows, especially if management has the ability to respond to the uncertainty.

Purpose: This paper serves to illustrate the risks that affect multinational organizations during this new era of global production and increased supply chain complexity. This paper also strives to showcase the benefits of conducting a Network Optimization analysis on a firm’s logistics system including but not limited to reducing the impact of supply chain market and operational risk, improving efficiency, and increasing cost savings across the organization. Approach: This paper will have two main sections beginning with an in depth look into the theory supporting supply chain logistics network optimizations. Through this literature review, the best practices in the industry will be compared to risk mitigation methodology to determine an analytical process that can be applied to companies considering conducting a network optimization. The second stage of this paper takes a clinical look at the aerospace industry and the implementation process of a Logistics Network Optimization at an industry leader to ultimately recommend additional considerations they should implement into their process. Recommendation: To ensure the effective adoption of a network optimization in the aerospace industry, and other manufacturing industries, the maintenance of logistics data and creation of long term 3PL partnerships are needed for success. It is also important to frame a network optimization not as an operational project, but rather a critical business process aimed to mitigate risk within the supply chain though a four-stage risk identification process.