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  ICIMSA  Internet of Things-Enabled Supply Chain Performance Measurement Model file Abdallah J. Dweekat  Abdallah J. Dweekat  2016 
94 IC  ICPR  Business Process Modeling for developing a performance measurement system using the Internet of Things file Gyusun Hwang  Jinwoo Park  2015 
93 IC  CIE  A batch splitting heuristic for dynamic job shop scheduling problem Hanil Jeong    1996 
92 IC  CIE  A decision support model for the initial design of FMS Hosub Shin    1996 
91 IC  ICARCV  A Discrete Control Approach to Robotic Cell Operating System Design Jonghun Park    1996 
90 IC  PCM  An Intelligent Batch Splitting method for Schedule Improvement in MRP Environment Hanil Jeong    1996 
89 IC  PCM  FMS Scheduling Strategies in a Distributed Coordination Environment Jonghun Park    1996 
88 IC  ICPR  A Study on FMS Scheduling Problems Based on Priority Functions Generated by Genetic Programming ChangUk Kim    1997 
87 IC  ICPR  A Scheduling Algorithm considering Subcontract cost in MRP Environment Kichang Lee    1997 
86 IC  IFAC on IMS  A Weighted Load Balancing Heuristic that Minimizes Makespan in Alternative Routing and Machine Environment Kidong Kim    1997 
85 IC  APIEMS  An Integrated Approach for Loading and Scheduling of a Flexible Manufactureing System Sangbok Woo    1999 
84 IC  APIEMS  A Study on Developing a Scheduling System in Alternative Routing and Machine Environment Kidong Kim    1999 
83 IC  IW on IMS  Maximally permissive adaptive control of an automated manufacturing cell Sangkyun Kim    1999 
82 IC  ICPR  An Algrorithm for Job Shop Scheduling Problem with Due Date Constraints Considering Operation Subcontract Daeyoung Chung    2000 
81 IC  INFORMS-KORMS  Hybrid Algorithms in Integrated Quality Design & Scheduling Jonghan Kim    2000 
80 IC  INFORMS-KORMS  Development of capacitated event-driven MRP components using object oriented method Seunghyun Yoon    2000 
79 IC  PAIS  Knowledge Acquisition using Neural Network and Simulator Kitae Shin    2001 
78 IC  SeoulSim  Design for a Hybrid System of Integration Kanban with MRPII Taeyoung Song    2001 
77 IC  GECCO  A Study on the Resource Allocation Planning for Automated Container Terminals Yangja Jang    2001 
76 IC  ICPR  Development of a Decision Support System for the formulation of Manufacturing Kichang Lee    2001