author Nasution Ninan 
2nd author Moon Philjun,
Dweekat Abdallah
Park Jinwoo 
presenter Nasution Ninan 
info  
year 2017 
category IC 
start / end date 02.08 / 02.09 
city / nation Seoul 
학회 SICEAS 
keywords Container Loading Problem, Depth Camera, Size Measurement, Computer Vision 
abstract Minimizing inventory cost in supply chain management has becoming important research field in supply chain area. One of the researches is space utilization when loading the logistics inside the container. Inefficient container loading could result an unnecessary additional costs. For instance, Parcel Delivery Company receives different boxes with different shapes and sizes every single day. In that case, the way how to stack the parcel boxes inside the container are not same for every day and become unpredictable. Many research papers tried to solve this problem theoretically using both exact and heuristic algorithms, (Bortfeldt & Wäscher, 2013). In this paper, authors are trying to address these unpredictable scenarios and propose a new approach that can handle this situation in real life.
In the proposed solution, measurement is the key important part of the solution. In the beginning, the new system will measure the size: width, height and depth of packaging boxes in real time using depth camera. When the system recognized available boxes with their size, the data will be processed for the next purpose. Problem arises when boxes are going to be loaded into the container. What is the best way to stack the heterogeneous boxes inside the container so that wasted spaces are minimized? With placing the depth camera to scan the container environment, system will know the real-time condition of the container, and the dimensions of the coming boxes and then calculate the best way to stack after the camera learned the environment. 
Minimizing inventory cost in supply chain management has becoming important research field in supply chain area. One of the researches is space utilization when loading the logistics inside the container. Inefficient container loading could result an unnecessary additional costs. For instance, Parcel Delivery Company receives different boxes with different shapes and sizes every single day. In that case, the way how to stack the parcel boxes inside the container are not same for every day and become unpredictable. Many research papers tried to solve this problem theoretically using both exact and heuristic algorithms, (Bortfeldt & Wäscher, 2013). In this paper, authors are trying to address these unpredictable scenarios and propose a new approach that can handle this situation in real life.
In the proposed solution, measurement is the key important part of the solution. In the beginning, the new system will measure the size: width, height and depth of packaging boxes in real time using depth camera. When the system recognized available boxes with their size, the data will be processed for the next purpose. Problem arises when boxes are going to be loaded into the container. What is the best way to stack the heterogeneous boxes inside the container so that wasted spaces are minimized? With placing the depth camera to scan the container environment, system will know the real-time condition of the container, and the dimensions of the coming boxes and then calculate the best way to stack after the camera learned the environment.

번호 category 학회 제목 author presenter year
35 IC  Asian eBiz  Applying Negotiation Patterns in Supply Chain Planning based on Self-integrating Environment file Yuncheol Kang    2005 
34 IC  CIE  Decision support system for preliminary cost estimation with case based reasoning file Jonghan Kim    2004 
33 IC  SCSC  Performance Evaluation of Alternative Designs for the Car Recycling System Using Simulation Analysis file Eoksu Sim    2004 
32 IC  GECCO  A Generic Network Design for a Closed-loop Supply Chain Using Genetic Algorithm file Eoksu Sim    2004 
31 IC  AsiaSim  Vendor Managed Inventory and its value in the various supply chain Sungwon Jung    2004 
30 IC  AsiaSim  Performance Analysis of Alternative Designs for a Vehicle Disassembly System using Simulation Modeling file Eoksu Sim    2004 
29 IC  AsiaSim  Reorder decision system based on the concept of the order risk using neural networks Sungwon Jung    2004 
28 IC  CIE  Information Strategy Planning for the Korean Postal Address Database file Tai-Woo Chang    2004 
27 IC  e-Biz  Design of Information System for e-Logistics Kitae Shin    2004 
26 IC  IBERC  An Ontology-Based Framework for e-Business Integration file Tai-Woo Chang    2003 
25 IC  ICPR  Combined production and distribution planning using demand based mixed Genetic Algorithm in a supply chain file Sungwon Jung    2003 
24 IC  ICMA  Machine-Understandable e-Business Modeling with Ontology Tai-Woo Chang    2002 
23 IC  Asian eBiz  A Systematic Approach for Ontology-based e-Business Modeling Tai-Woo Chang    2002 
22 IC  SCSC  Performance Improvement Methodology for a Manufacturing System using Petri Nets and Simulation Analysis Kichang Lee    2002 
21 IC  SCSC  Inventory Management in a Supply Chain using Neural Networks file Sungwon Jung    2002 
20 IC  PAIS  Knowledge Acquisition using Neural Network and Simulator Kitae Shin    2001 
19 IC  SeoulSim  Design for a Hybrid System of Integration Kanban with MRPII Taeyoung Song    2001 
18 IC  GECCO  A Study on the Resource Allocation Planning for Automated Container Terminals Yangja Jang    2001 
17 IC  ICPR  Development of a Decision Support System for the formulation of Manufacturing Kichang Lee    2001 
16 IC  ICRA  An On-Line Production Scheduler using Neural Network and Simulator based on Manufacturing System State file Kitae Kim    2001