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
95 IC  Asian eBiz  Applying Negotiation Patterns in Supply Chain Planning based on Self-integrating Environment file Yuncheol Kang    2005 
94 IC  APMS  A study on Active Information Sharing for Organizing Effective Collaborative Manufacturing Yuncheol Kang    2008 
93 IC  IFORS  A Closed-loop Supply Chain Coordination Model Considering the Effect of Regulation Alternatives Youngwoo Kim    2011 
92 IC  APMS  Designing an Integrated Data System for Remanufacturing with RFID Technology Youngwoo Kim    2012 
91 IC  APMS  A Lifecycle Data Management System Based on RFID Technology of EPCC1G2 Youngwoo Kim    2014 
90 IC  EURO  Multiperiod Hybrid Manufacturing/Remanufacturing Planning Under the Internet-of-Things Scenario file Young-woo Kim  Young-woo Kim  2015 
89 IC  SISE  Impact of Information Visibility of Quality and Physical Flow on the Closed-loop Supply Chain file Young-woo Kim  Young-woo Kim  2016 
88 IC  GECCO  A Study on the Resource Allocation Planning for Automated Container Terminals Yangja Jang    2001 
87 IC  ICMA  Machine-Understandable e-Business Modeling with Ontology Tai-Woo Chang    2002 
86 IC  Asian eBiz  A Systematic Approach for Ontology-based e-Business Modeling Tai-Woo Chang    2002 
85 IC  IBERC  An Ontology-Based Framework for e-Business Integration file Tai-Woo Chang    2003 
84 IC  CIE  Information Strategy Planning for the Korean Postal Address Database file Tai-Woo Chang    2004 
83 IC  SeoulSim  Design for a Hybrid System of Integration Kanban with MRPII Taeyoung Song    2001 
82 IC  SCSC  Inventory Management in a Supply Chain using Neural Networks file Sungwon Jung    2002 
81 IC  ICPR  Combined production and distribution planning using demand based mixed Genetic Algorithm in a supply chain file Sungwon Jung    2003 
80 IC  AsiaSim  Vendor Managed Inventory and its value in the various supply chain Sungwon Jung    2004 
79 IC  AsiaSim  Reorder decision system based on the concept of the order risk using neural networks Sungwon Jung    2004 
78 IC  ISPIM  Open Innovation in SMEs - The Case of KICMS Sungjoo Lee    2008 
77 IC  IEOM  Designing an effective scheduling scheme considering multi-level BOM in hybrid job shop Sumin Han    2012 
76 IC  APORS  A study on makeshift recovery planning in emergency logistics considering disaster scene's risks and uncertainties file Sumin Han  Sumin Han  2015