Difference between revisions of "IS480 Team wiki: 2012T1 Bumblebee Project Overview"
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Revision as of 14:12, 16 August 2012
Home | Project Overview | Project Documentation | Project Management | Learning and Growth |
Project Description | X Factor | Stakeholders | Motivation | Deliverables and Scope |
Contents
Project Description
Project Description |
Singapore Airport Terminal Services (SATS) is the leading provider of the gateway services and food solutions in the region. It has a staff of 800 to handle more than 35 airlines. Every year, there are two major airline flight schedule change - summer (April) and winter (November). Each change can be a drastic one and has great impact on staff roster. One of SATS’s goals for its staff roster is to meet all its airlines’ requirements. However, there are many uncertainties such as staff members falling sick, staff resigning and flight delay, that cause the roster planned to be ineffective. Thus, Duty Manager in SATS often has to make last minute changes to the rosters and incur costs such as Staff Recall Cost, Over-Time cost and Meal Allowance Compensation (MAC). To help improve the efficiency involving various costs and consequences of the planned staff roster, our project aims to create a Staff Deployment Simulation Software (SDSS) which will first deploy staff based on flight schedule, flight requirements, staff records and staff roster and then simulate the roster plan by taking into account all the various uncertainties and forecast the various costs that the management would have to incur. Understanding the cost and consequences of a given roster, SATS would then be able to make necessary adjustments to avoid high expenses to the company. The diagram below explains the flow of the software. To predict the uncertainties, we will take in the mean and standard deviation of the listed simulation parameters in diagram above(MC Rate, Flight Delay Rate, Staff Resign Rate, etc). Having those values, our software will then generate a normal distribution of each uncertainty. After such, we will be applying the uncertainties at the planned roster plan such as removing staff from the roster plan if he/she is taking MC. The software will also try to mimic the actions of Duty Manager who does the necessary adjustment to the staff roster to fulfill the airlines requirements i.e. to imitate human decision making process to come out with an optimal staff roster. At the end of the day, our software will generate a management report which will reveal the cost and consequences of implementation of a given roster. The output given will be Total Staff Working Hours, Flight Demand Coverage, Meal Allowance Compensation (MAC), Over Time (OT) Cost, OT hours, Staff Utilization Rate, Unproductive Hours, Recall Cost and Recall Hours. Understanding the cost and consequences of a given roster, SATS would then be able to make necessary adjustment to avoid high expenses and thus, increase cost savings to the company. |
X Factor
X Factor |
Efficiency Our system is able to handle a highly complex, huge domain size, scheduling problem efficiently in comparison to SATS’ current manual scheduling process. Optimal Scheduling We provide our client an optimized staff schedule to effectively reducing their overheads from non-optimal scheduling practices. In essence, we developed an optimal scheduling algorithm to maximise SATS’ resources to meet all airline requirements. Probabilistic Simulation Our system gives our client a clear perspective of cost loss profile from human resource planning uncertainties. And we would provide recommendation for minimizing additional cost effectively. To be specific, we use normal distribution and Kolmogorov-Smirnov test to forecast the uncertainties which SATS could face. After which we run a simulation to plot our client’s cost profile. To understand the complexity and the abundance in probabilities of scheduling, try to solve this:
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Stakeholders
Stakeholders |
The BeesSponsors
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Motivation
Motivation |
There are 2 main motivations for working on this project:
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Deliverables and Scope
Deliverables and Scope | ||||||||||||||||||||||||||||
Please refer to use case description for greater details. | ||||||||||||||||||||||||||||