- Supply chain & logistics
- Fort Smith, Arkansas, United States
- Project goals
- Optimize dock operations and manage completion times
Achievements with Simul8
Accurate forecasting of how the changes will improve operations
Ability to test many scenarios resulted in a number of solutions
About the project
From its origin as a small local carrier in 1923, ABF Freight System, Inc. has been transformed into one of North America's largest and most experienced motor carriers. With a forward thinking approach to quality improvement, ABF's mission is to deliver value to its customers by developing and implementing customized solutions to global logistical challenges.
ABF's industrial engineers were tasked with finding the most efficient and economical system to optimize dock operations and manage completion times.
For this project the team needed to coordinate available manpower, forklifts and open bays to handle incoming and outgoing shipments in the most efficient manner. Additionally, union regulations brought further elements of consideration, requiring solid justification for personnel schedule changes and shift patterns.
A simulation of the dock operations process was created to mimic the current system. ABF's forward thinking approach to quality improvement means they hold data on every area of the business.
Using Simul8's Excel connections feature, ABF imported existing data to give a minute-by-minute analysis of the company's dock operations. This allowed the team to validate the simulation against the real life process.
Using the simulation, the team then began to experiment with their ideas for improvement in a risk-free environment and with no detrimental impact on the current system. The Industrial Engineering team tested various scenarios to improve the completion times including; changing resource shift patterns, changing the number of open bays, and increasing the number of forklifts.
"I've been extremely happy with the results we've had using Simul8. It was easy to use, and the program was able to synthesize the massive amounts of data we plugged into the models."