Complete one question from the project.

Jubail Industrial CollegeDepartment of Business Administration
Semester 452
Project part 1 & 2
Course Code:
MIS 305
Course Title:
Intelligent Support System in Business
Section:
No.
Student ID
Student Name
1
431200362
Rozah albuainain
2
421200523
Rahaf albuainain
3
4
5
6
7
List of contacts:
Proposed Project Title: …………………………………………………………………………………………………..
3
Introduction: …………………………………………………………………………………………………………………. 3
Business Entity and Roles:
…………………………………………………………………………………………….. 3
General background for our DSS project:
……………………………………………………………………… 3
Key Roles ………………………………………………………………………. 4
Products Offering: …………………………………………………………………………………………………………
4
Intelligence phase …………………………………………………………………………………………………………..
5
Data founded: ………………………………………………………………………………………………………. 5
How is it relevant to our DSS project business entity?
……………………………………………. 5
General description of the decision situation : ………………………………………………………..
5
Decision classification: ………………………………………………………………………………………….. 5
Type of decision and why ……………………………………………………………………………………… 5
Problem Statement ……………………………………………………………………………………………….. 6
Design Phase …………………………………………………………………………………………………………………. 6
Decision Variables: ………………………………………………………………………………………………. 6
Results Variables (Performance Metrics): …………………………………………………………….. 6
Uncontrollable Variables (External Factors): …………………………………………………………
7
Principles of Choice: …………………………………………………………………………………………….. 7
proposed model: …………………………………………………………………………………………………… 7
Long-term Impact: ……………………………………………………………………………………………….. 7
High-level Choices: ………………………………………………………………………………………………. 7
Consideration of Multiple Factors: ……………………………………………………………………….. 8
Evaluate the risk / uncertainty levels: ……………………………………………………………………. 8
Work Breakdown Structure: ………………………………………………………………………………… 8
Conclusion: …………………………………………………………………………………………………………………. 10
References : ……………………………………………………………………….. 11
Proposed Project Title:
Airplane company
Problem: flight delays date
Introduction:
Flight delays are a significant issue within the aviation industry, affecting
millions of passengers globally each year. These delays not only diminish
passenger satisfaction but also disrupt airline operations and lead to
increased costs. As airlines strive to maintain high levels of service,
understanding the underlying causes of delays and developing predictive
models can play a crucial role in enhancing operational efficiency and
improving the passenger experience
Business Entity and Roles: Definition
Flight delays happen when flights are not on time. This affects many
passengers around the world every year. Delays can make passengers
unhappy, disrupt airline schedules, and increase costs for airlines. To tackle
these problems, airlines work to understand why delays happen and use tools
to predict and prevent them, aiming to improve both efficiency and passenger
satisfaction.
General background for our DSS project:
Flight delays are a common issue in the aviation industry, occurring when flights
do not adhere to their scheduled departure or arrival times. These delays affect
millions of passengers globally each year, leading to increased frustration,
disrupted travel plans, and an overall reduction in passenger satisfaction.
Additionally, delays can cause significant disruptions to airline schedules and
contribute to higher operational costs for airlines.
Several factors contribute to flight delays, including:
Weather:Adverse weather conditions such as storms, fog, or heavy snow can
hinder flight schedules and lead to delays.
Air Traffic: Congestion in the airspace and at airports can slow down the
movement of aircraft, leading to extended wait times.
Late Arrival of Aircraft: When an aircraft arrives late from a previous flight, it can
cause subsequent delays in its scheduled departures.
Gate Congestion:Delays can occur if there are not enough available gates to
accommodate arriving aircraft promptly.
Maintenance:** Unforeseen maintenance issues or required repairs can delay
aircraft from departing on time.
Technical Issues: Problems with onboard systems or equipment can necessitate
additional checks and delays.
To address these challenges, airlines are increasingly relying on advanced
Decision Support Systems (DSS) to better understand the causes of delays and to
implement strategies to mitigate them. These systems use a combination of data
analysis, predictive modeling, and real-time monitoring to enhance operational
efficiency and improve passenger satisfaction. By identifying patterns and
predicting potential delays, airlines can make informed decisions to minimize
disruptions and streamline their operations.
In the Intelligence phase ensure:
What data did you find?
how is it relevant to the chosen business entity?
Providing a general description of the decision
situation, i.e., what is the
decision circumstances in which the decision is made?
How could you
classify this decision?
What type of decision and why?
Hint: The phase should end with a clear problem
statement.
Design Phase
1. Decision Variables
Decision variables are the factors that decision-makers can control and adjust to
influence the outcome of flight schedules and minimize delays. In the context of
flight delays, the key decision variables might include:
– Scheduling Adjustments:** Modifying flight departure or arrival times based on
predicted delays.
– Resource Allocation:** Adjusting the allocation of gates, ground staff, and
aircraft maintenance crews.
– Air Traffic Management:** Implementing changes to flight routes or altitudes to
reduce air traffic congestion.
– Maintenance Scheduling:** Rescheduling or prioritizing maintenance activities
to prevent delays.
2. Results Variable**
The results variable represents the outcome that the DSS aims to improve or
achieve. For this project, the primary results variable is:
– Flight Delay Duration:The amount of time by which a flight is delayed from its
scheduled departure or arrival time.
3. Uncontrollable Variables
Uncontrollable variables are factors that affect flight delays but cannot be
directly controlled or adjusted by the decision-makers. These include:
– Weather Conditions:Natural events such as storms, fog, and heavy
precipitation.
– Air Traffic:External traffic conditions and regulations managed by air traffic
control.
– Airport Infrastructure:Limitations in airport facilities, such as gate availability
and runway capacity.
– Technical Failures:Unexpected equipment or system malfunctions that occur
without prior warning.
4. Principles of Choice
The principles of choice guide the decision-making process in the DSS. These
principles include:
Minimization of Delays: Prioritising strategies that lead to the shortest possible
delay times for passengers.
Cost Efficiency: Balancing delay reduction efforts with associated costs to ensure
that interventions are economically viable.
Passenger Satisfaction:Ensuring that decisions contribute to higher levels of
passenger satisfaction and less frustration.
Operational Efficiency: Enhancing overall airline operations, including schedule
adherence and resource utilization.
5. Proposed Model
The proposed model for this DSS project could be a “Predictive Analytics Model”
combined with a Simulation-Based Optimization Model.
Predictive Analytics Model:Utilizes historical data, weather forecasts, air traffic
patterns, and maintenance records to predict potential delays and their likely
impact. This model helps in forecasting delays before they occur and allows for
proactive decision-making.
Simulation-Based Optimization Model:Tests different scenarios and strategies to
find the optimal solutions for scheduling adjustments, resource allocation, and
maintenance planning. This model simulates various conditions and assesses the
impact of different decisions on minimizing delays.
Justification for Choice:
Predictive Analytics : provides foresight and helps anticipate issues before they
arise, allowing for proactive measures.
Simulation-Based Optimization evaluates the effectiveness of different strategies
under various scenarios, leading to data-driven and optimized decision-making.
6. Risk / Uncertainty Levels
Weather Uncertainty:Weather conditions can be unpredictable and may change
rapidly, affecting flight schedules and delay predictions.
Air Traffic Variability:The volume and flow of air traffic can fluctuate, impacting
the accuracy of air traffic-related delay predictions.
Technical Failures:Unexpected technical issues can arise, making it difficult to
predict and manage their impact on flight schedules.
Operational Constraints:Changes in airport infrastructure or regulations can
introduce new risks or uncertainties that affect the DSS’s effectiveness.
Evaluation of Risk / Uncertainty Levels:
Sensitivity Analysis:Conduct sensitivity analyses to understand how variations in
uncontrollable variables affect the results.
Scenario Planning:Develop and test various scenarios to account for different
levels of risk and uncertainty, ensuring the DSS can handle a range of possible
situations.
Continuous Monitoring:Implement real-time data collection and monitoring to
adjust predictions and strategies as conditions change.