Massachusetts Institute of Technology
Streamlining Financial Analysis for Novel Robotics Concepts
Abstract
dc:description.abstractOver the past decade e-commerce shipment volumes have risen dramatically, and online retailers,lead by Amazon, have invested significantly in robotics technologies to meet capacity needs. Before making these investments, firms consider both operational and financial feasibility in order to ensure that the technology meets requirements and earns a return on investment. In this work, we present Robotics Concept Modeler (RCM), a software program that streamlines and standardizes financial analysis process for novel robotics concepts at Amazon. RCM augments Amazon’s existing process of sequentially evaluating operational and financial feasibility, a governor on the company’s pace of robotics innovation. We outline the needs of the stakeholders involved in the financial analysis process, discuss how those needs shaped our development process, and give an overview of the final functionality of the developed software, including an exploration of the innovative graphical model construction methodology that drives many of RCM’s benefits. We show that using RCM introduces significant time savings in preparing financial analysis, expands the userbase of individuals that are capable of this analysis, and reduces ambiguity and variation in analysis structure.
Degree
thesis:*- Name thesis:degree_name
- Master
- Department dc:contributor.department
- Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
- Grantor dc:publisher
- Massachusetts Institute of Technology
- Year dc:date.issued
- 2022
Author and committee
dc:creator, dc:contributor.*- Author dc:creator
-
- Livingston, Timothy
- Advisors dc:contributor.advisor
-
- Welsch, Roy E.
- Davis, Randall
Rights
dc:rights- Statement dc:rights
-
- In Copyright - Educational Use Permitted
- Copyright retained by author(s)
- Licence dc:rights.uri
Identifiers
dc:identifier.*- Handle dc:identifier.uri
- https://hdl.handle.net/1721.1/146698
- OAI identifier oai:identifier
- oai:dspace.mit.edu:1721.1/146698