The Line of Least Resistance

From ESE205 Wiki
Revision as of 17:38, 25 September 2016 by Devon.essick (talk | contribs) (Challenges)
Jump to: navigation, search

Project Overview

Research has shown that many of the typical methods for queueing customers are incredibly inefficient [1]. Many attractions choose to utilize time slots rather than the proven-inefficient first-come, first-serve process, but this process can still be less than ideal when delays are introduced. We aim to create an "consulting" app that allows businesses, particularly tourist attractions, to input various data (e.g. weather conditions, average number of customers, minimum time between slots, minimum/maximum number of staff, time needed for each person to go through security, hours of operation, etc). The app will output recommendations based on the inputs that provide businesses with suggested set-ups for the day (e.g. how far to space time slots, how many staff members to have, estimated time until boarding). We will base our app on a simplified version of the St. Louis Arch, and then expand it to be applicable to similar systems. The goal is to minimize delay time/maximize predictability.

Team Members

  • Devon Essick
  • Andrew Sweren
  • Kjartan Brownell (TA)

Objectives

Note: Each objective depends on the success of the previous one and proximity to the demo.

  • Create a "consulting" application that accurately suggests how to most efficiently (in terms of minimal delay time) set up queues on a given day at a tourist attraction.
  • Expand the application in order to be useful to other companies that aim to minimize delay time (not just tourist attractions).
  • Expand the application to be able to make suggestions based on real time data (e. g. delay caused by security lines being understaffed).
  • Expand application to be able to solve problems other than minimizing delay time (e. g. minimizing wait time).
  • Expand the application to take into account different methods of payment when determining how to maximize profits.

Challenges

  • Learning simulation software
  • Learning how to code an app
  • Making sure the app is realistic for an array of systems by taking into account myriad variables (e.g. understanding the challenges that come with a large system that may not be present with a smaller system, and vice versa)
  • Making sure the app has the most important inputs so that the recommendations are realistic
  • Accounting for changes disrupting the way the business operates (e.g. would adding an online purchase option affect the type of customer?)
  • Limitations due to security and safety concerns (e.g. eliminating security lines could diminish delay time, but at what cost?)

Budget

  • Monitor and peripherals for demo (available from Urbauer 015) - $0
  • Coding software (provided by school) - $0

Total: $0

Gantt Chart

EssickGantt.png

Design and Solutions

Results