"Container load optimization reduces the number of shipping containers and lowers the logistics cost"

Overview

• Build a logistics information system to standardize the packaging and automate the load planning
• Use CubeMaster™ to enable the load optimization of electronics goods such as refrigerator, air-conditioner, washing machine and vacuum cleaner
• Generate instruction reports including the packing list and loading map to help the shipping
• Share the reports over World Wide Web with logistics, sales and R&D departments

Background

• Demand for solution of loading containers with multi-products
• Claims for poor quality of packaging and loading
• Hardness for determination of the package design

Lack of communication channel within the related departments for specification changes

• Increasing demand for cost reduction of over-seas logistics area
• Increased transport cost decreases the profit of the company
• Always more number of containers are used than the actual amounts

Demand for increasing the customers satisfaction

• Customers complain for the empty containers
• Unstable stacking and low volume utilization increases the cost of delivery

Objective

Three main goals should be implemented;

• Package design for the R&D department
• Automatic FCL (Full Container Load) calculation for the sales department
• Container load plan of mixed products for the logistics department

Features

Three main features should be implemented;

Package Design

• Finding the best measurement of new product and carton

Container Load Plan

• Order Size Optimization
• Simulation of loading containers with customer’s order
• Finding the minimum number of containers required for the orders
• Finding new order quantities for making FCL

Container Load Optimization

• Simulation of loading containers with delivery orders
• Finding the minimum number of containers and the layout of loaded containers
• Generating the easy-to-follow reports for the shipping

Benefits

• Reduced number of shipping containers by the increasing volume utilization by 13.5%
• Reduced average shipping cost by 9.2%
• Reduced time by 2 hours to process loading and shipping