---
title: "Improving Campus Dining Operations Using Capacity and Queue Management: A Simulation-Based Case Study"
type: source
tags: [discrete-event-simulation, dmaic, six-sigma, capacity-management, queue-management, service-operations, case-study, hospitality, marginal-fit-to-bpm]
authors: [Kambli, Ashish; Sinha, Akhouri Amitanand; Srinivas, Sharan]
year: 2020
venue: "Journal of Hospitality and Tourism Management 43: 62–70 (Elsevier). DOI: 10.1016/j.jhtm.2020.02.008"
kind: paper
raw_path: "raw/Predictive process monitoring/2020-kambli-campus-dining-simulation.pdf"
doi: "10.1016/j.jhtm.2020.02.008"
sources: []
key_claims:
  - "Application of DMAIC (Define–Measure–Analyze–Improve–Control) integrated with Discrete Event Simulation (DES, Simio software) to a real all-you-can-eat campus dining service (CDS) with ~500,000 annual student visits across 8 stations."
  - "Baseline simulated average waiting time 23.24 min (validated against 20-min observed). Bottlenecks identified at Grill and On-Stage (MTO) stations through fishbone root-cause analysis."
  - "Five process-redesign scenarios evaluated: (S1) workforce reallocation → 16.45 min (-29%); (S2) reusable check-sheet queue management → 14.65 min; (S3) S1+S2 → 12.74 min; (S4) Arduino-Uno kiosk-based queue mgmt → 12.43 min; (S5) S1+S4 → 11.41 min (-51%)."
  - "All three hypotheses supported with paired t-tests, p < 0.001: capacity reallocation reduces waiting time; queue management reduces waiting time; combined reallocation + queue management dominates either alone."
  - "Robustness check: alternatives outperform baseline under 5%, 10%, 15%, 20% demand growth — combined strategies more resilient than capacity-only."
  - "Method is a transferable DMAIC + DES template for service-operations redesign — adoptable to fast food, fine dining, retail, hospital outpatient flows."
created: 2026-05-11
updated: 2026-05-11
---

# Kambli, Sinha & Srinivas 2020 — Improving Campus Dining Operations

Service-operations case study published in *Journal of Hospitality and Tourism Management*. Authors are based at the University of Missouri (Marketing + Industrial and Manufacturing Systems Engineering). **NOT a process-mining or predictive-process-monitoring paper** despite its placement under `raw/Predictive process monitoring/`. Its relevance to the BPM wiki is methodological: a clean worked example of the **DMAIC + Discrete Event Simulation** pattern as a process-redesign vehicle.

## What the paper does

Applies the **DMAIC** six-sigma improvement cycle integrated with **discrete event simulation (DES)** to a real campus dining service (CDS) — an all-you-can-eat university facility serving ~500,000 student visits per year through 8 stations (4 MTO + 3 pre-cooked + 1 beverage). Customer complaint: ~32% of students unhappy with waiting time; 15% defected to off-campus restaurants. Baseline simulated waiting time: **23.24 min**.

The DMAIC phases map onto the paper's structure: Define (customer voice, problem identification, layout + process flow), Measure (observation, time studies, distribution fitting — Poisson arrivals with time-varying mean, uniform service times per station), Analyze (fishbone root-cause across People/Method/Environment/Staffing/Material/Measurement), Improve (5 scenarios, simulation, hypothesis testing), Control (cost-benefit + sustainability ranking + managerial recommendation).

## Methodology specifics worth borrowing

- **Process flow diagram** of the customer journey through entry → station selection → queue → meal → re-queue or exit (Fig. 3 in paper).
- **Fishbone root-cause analysis** across 6 categories for waiting-time anomaly (Fig. 4).
- **DES model construction in Simio** with distribution-fitted arrival and service times, 50 replications + 1-hour warm-up; validated via t-test between baseline simulation arrivals (412) and observed arrivals (400).
- **Five redesign scenarios** evaluated on a common simulation basis; pairwise t-tests + 95% CI for waiting-time differences.
- **Multi-criteria evaluation** of alternatives along cost, ease of implementation, responsiveness improvement, sustainability — not just waiting-time minimisation.

## Results table

| Scenario | Waiting time (min) | Δ vs baseline | Fixed cost ($) | Annual cost ($/yr) |
|---|---|---|---|---|
| Baseline | 23.24 | — | — | — |
| **S1** Workforce reallocation | 16.45 | -29 % | 200 | 0 |
| **S2** Check-sheet queue mgmt | 14.65 | -37 % | 0 | 420 |
| **S3** S1 + S2 | 12.74 | -45 % | 200 | 420 |
| **S4** Arduino kiosk queue mgmt | 12.43 | -47 % | 8200 | 3100 |
| **S5** S1 + S4 | **11.41** | **-51 %** | 8400 | 3100 |

All differences vs baseline and pairwise differences among scenarios significant at p < 0.001.

## Why this is in the BPM wiki — and where it actually fits

The paper has **marginal fit** to the wiki's core PPM/process-mining/APM threads:

- It is **not process mining** — no event log analytics, no discovery, no conformance.
- It is **not PPM** — no prediction of running cases.
- It is **DMAIC + DES** — service-operations redesign methodology applied to a hospitality case.

Where it *does* connect:

- **Method-level reference** for [[methods/process-simulation]] — clear, applied DES + DMAIC integration example.
- **Concrete worked example** of the [[concepts/devils-quadrangle]] — five scenarios show cost-vs-time-vs-(implicitly)-quality trade-offs.
- **Real-world testbed** for process-redesign heuristics ([[concepts/bpr-heuristics]], [[sources/2005-reijers-limanmansar-best-practices-bpr]]) — particularly the *Resource Reallocation* and *Customer Decoupling/Untethering* heuristics.
- **Inter-case queueing** intuition — campus dining is a queueing system; complements the [[concepts/inter-case-ppm]] thread which formalises queue-state features for PPM.

## Limitations

- **Single facility** — generalisability is asserted but untested.
- **Single criterion focus** (responsiveness / waiting time); food quality, employee training, customer satisfaction not directly modelled.
- **Capital investment estimates** are point estimates without sensitivity analysis.
- **Online ordering** (an obvious extension that would change the queue topology) flagged as future work.

## Connections

**Concepts:**
- [[concepts/devils-quadrangle]] — explicit cost-time trade-off illustrated.
- [[concepts/bpr-heuristics]] — workforce reallocation + customer untethering as concrete heuristic applications.
- [[concepts/inter-case-ppm]] — queueing-system perspective; relevant precedent for PPM features incorporating queue state.

**Methods:**
- [[methods/process-simulation]] — DES + DMAIC integration as a worked-example reference.
- [[methods/process-redesign-heuristics]] — multi-criteria evaluation pattern transferable.

**Sources:**
- [[sources/2005-reijers-limanmansar-best-practices-bpr]] — heuristics catalogue this case study implicitly validates.
- [[sources/2018-dumas-fundamentals-of-bpm]] — DMAIC + DES are textbook BPM lifecycle techniques.