ASCI 530 Module 2 Research: Overweight Crop-dusting UAS

In the role of a systems engineer, my first course of action when approaching a design conflict is to focus on the requirements and constraints of the initial project. In the given example, the navigation, payload, and safety groups are at odds with their given constraints. However, systems engineers are tasked with determining implementation of system functions. In the example of the overweight agricultural spray application UAS, the payload (spray equipment and capacity) are constrained by promises to customers and the overall requirement of the aircraft. The project requirements should “bring the most value to the customer and help the business improve innovation” (IBM, 2013). Timeline and budget should also be considered, but in this example, the highest priority would be improvement of the navigation and control system.

In order to carry the determined payload of spray application equipment and tank capacity (without lowering fuel load), either the navigation and control system needs to lose weight, or the overall lift and endurance of the aircraft must be increased. There are a multitude of potential technical solutions, including selection of an improved power plant, improved aerodynamics, or a lighter navigation system altogether. For each of these options, there should be a risk assessment conducted to determine the cost and benefit of each implementation. Since each technical option has the potential of bringing a new vendor/subcontractor to the design process, external partners can be utilized to fill the execution “gaps” present in the aircraft design (Terwilliger, Burgess, & Hernandez, 2013). Feasibility, schedule, and budget should be weighed to assess risk to the overall success of the design project.

In this particular design problem, a recommended technical solution would be to remove some of the onboard navigational processing equipment and replace it with a wireless sensor network (WSN). UAS application of agricultural chemicals can be achieved through implementation of a ground-based network of sensors that provide feedback to a computer that determines and commands the performance of the aircraft and sprayer payload in varying wind conditions. A 2012 paper by F.G Costa (et. al) predicted a 10-22% reduction of wasted pesticide through corrections provided every 15 seconds to a UAS via ground-based WSN and control loop algorithm.

A WSN solution brings added cost and complexity to the product, but it adds two important benefits. First, it performs the dual function of reducing the weight of the aircraft by removing some of the necessary sensors and processors to perform corrections on-board. Second, and more importantly, using a WSN increases efficiency by a large margin, which aids the success of meeting a capacity and endurance requirement. The solution also aids the business in future aircraft development by providing a path to swarm technology through mobile ad-hoc networking (MANET). 

References

Costa, F. G., Ueyama, J., Braun, T., Pessin, G., Osório, F. S., & Vargas, P. A. (2012, July). The use of unmanned aerial vehicles and wireless sensor network in agricultural applications. In Geoscience and Remote Sensing Symposium (IGARSS), 2012 IEEE International (pp. 5045-5048). IEEE.

IBM Corporation, Software Group. (2013). Ten steps to better requirements management. Somers, NY: Author. Retrieved from http://public.dhe.ibm.com/common/ssi/ecm/en/ raw14059usen/RAW14059USEN.PDF

Terwilliger, B., Burgess, S., and Hernandez, D. (2013). ASCI 530 Module #2 global system design concepts, requirements, and specifications overview [PowerPoint slides]. Retrieved from https://erau.instructure.com/courses/39651/files/6702704/download?wrap=1