Based on the theories of professional Campus Cafeteria, how do I solve crowding problems using high school rigs and technology?
Introduction
Long queuing times and overcrowding in school cafeterias are known to be serious problems faced by students.
This issue has been well-documented in previous studies that have emphasized the impact of poorly designed cafeterias on student satisfaction, waiting times, and the overall dining experience.
Surveys conducted at our school have shown that many students are dissatisfied with the current cafeteria setup, citing overcrowding and long wait times as major annoyances.
However, no one has fully explored why these issues persist after years of improvement or how specific factors - such as cafeteria layout, queuing systems, and crowding during peak hours - contribute to the problem.
If we can identify the root causes of inefficient cafeteria operations, we can not only improve the dining experience but also optimize space usage and human resources.
This study aims to investigate the root causes of cafeteria crowding by analyzing queuing dynamics, conducting simulations, and exploring potential improvements.
By identifying and addressing these issues, we hope to reduce queue times, increase student satisfaction, and improve overall operational efficiency.
Data Collection
Observation
The data for this study came from field observations in our school’s cafeteria, and data were collected from December 2 to December 5, 2024, and December 9 to December 12, 2024 (8 days in total).
Data collection under each schedule lasted for four days due to the school’s schedule of one cycle every two days.
The data primarily covered the third and fourth periods which are lunch periods, and the peak hours.
Specifically, it includes the number of students entering/leaving the cafeteria during each period, the service time of each window, and the number of windows.
Methodology
Data collection was performed through the cafeteria’s monitoring system during the daytime hours, which recorded the timestamp of each student’s entry into the cafeteria.
The specific time period for data collection was from 11:50 to 13:35 each day.
During this time period, the number of students entering the cafeteria was recorded by manual count, and simple observations recorded the service time of each service window.
The mean value of the window service time is the average value obtained by several manual timings.
Queueing theory
Queueing theory is the mathematical study of waiting lines. It examines how customers arrive, wait, and receive service in systems with limited resources. Each system is defined by arrival patterns, service processes, and queue rules (e.g., first-come-first-served). Common models, like M/M/1 or M/G/1, use probability to predict metrics such as waiting time, queue length, and system utilization. Widely applied in telecommunications, computer systems, healthcare, and operations research, queueing theory helps optimize performance and manage congestion in complex, service-based environments.