Login | Register

Peel Pack Planning Using Clustering and Decomposition Approach


Peel Pack Planning Using Clustering and Decomposition Approach

Wang, Yixuan (2023) Peel Pack Planning Using Clustering and Decomposition Approach. Masters thesis, Concordia University.

[thumbnail of Wang_MSCM_F2023.pdf]
Text (application/pdf)
Wang_MSCM_F2023.pdf - Accepted Version
Restricted to Repository staff only until 1 August 2025.
Available under License Spectrum Terms of Access.


In order to improve the operational efficiency in the Operating Room, hospitals customize surgical trays for each surgical procedure. Since, surgical procedures involve a variety of patients and surgeons, the usage of surgical instruments (in terms of quantity) differs from case to case. This poses a significant challenge as the variability in instrument usage makes it difficult to determine the optimal quantity for each instrument for each procedure. In this study, we address the issue of excessive waste in surgical trays by proposing the implementation of custom peel packs. These peel packs could be used (in place of a new surgical tray) if the surgical tray ran out of the instruments. Our objective is to reduce waste by designing custom peel packs associated with multiple surgical procedures while ensuring that all the necessary instruments are available during the procedure without opening a new main tray. We present one decomposition approach to finding the exact solution and a simplified fast approach based on clustering and mathematical programming to find the near-optimal solution in a fractional time compared to the exact approach. Numerical experiments demonstrate the performance of the presented approaches. The findings indicate that the proposed K-means based clustering method is very effective in configuring peel packs.

Divisions:Concordia University > John Molson School of Business > Supply Chain and Business Technology Management
Item Type:Thesis (Masters)
Authors:Wang, Yixuan
Institution:Concordia University
Degree Name:M.S.C.M.
Program:Business Administration (Supply Chain and Business Technology Management specialization)
Date:7 August 2023
Thesis Supervisor(s):Chauhan, Satyaveer.S
ID Code:992667
Deposited By: Yixuan Wang
Deposited On:17 Nov 2023 15:01
Last Modified:17 Nov 2023 15:01
All items in Spectrum are protected by copyright, with all rights reserved. The use of items is governed by Spectrum's terms of access.

Repository Staff Only: item control page

Downloads per month over past year

Research related to the current document (at the CORE website)
- Research related to the current document (at the CORE website)
Back to top Back to top