What is it about?
The purpose of this study is to find the best strategy for products distribution network in terms of response time reduction. The decision making is based on the carriage capacity of the cars relative to the transportation time and cost records. The response time for the service delivered in the manufacturing company is not optimum and customers are always in complaint. Thus, due to high transportation cost and long time delivery, the institutional customers of the company were also influenced by response time to get the products on time. Optimum transportation time and cost has improved company’s competitive strategy during last decades undoubtedly. As premises of this, transportation cost and times are the two variable used to determine the best strategy among the alternatives. A lot of mathematical models have been applied to do optimization on supply chain networks, but supply chain dynamics, such as uncertainty in production demand and transportation, are not present in most of them. As a result, to handle this variation, simulation can be a powerful tool. In this study, an arena simulation tool is used to analyze system performance using transportation cost and time as the performance parameters. In addition, based on the generated transportation time and cost, a simple mixed integer linear programing (MILP) was developed and Win QSB software has been used to solve and select the best network configuration Finally, the study resulted in strategy 2 has a minimum time and cost. By considering current situation this strategy is able to save the time by nearly 6.5 hours in 30 days.
Featured Image
Why is it important?
Finally, the study resulted in strategy 2 has a minimum time and cost. By considering current situation this strategy is able to save the time by nearly 6.5 hours in 30 days.
Perspectives
Read the Original
This page is a summary of: Response Time Reduction in the Leather Products Manufacturing Industry Using Arena Simulation Method, January 2015, Springer Science + Business Media,
DOI: 10.1007/978-3-319-13572-4_22.
You can read the full text:
Contributors
The following have contributed to this page