Truck set-up scheduling for the Elgin , IL facility

1. Truck set-up scheduling for the Elgin, IL facility Vijay Viswanathan, Graduate Student Dr. Jaejin Jang, Associate Professor Department of Industrial Engineering

2. Overview of Presentation • Introduction • Detailed Problem Description • Objective of Project • Assumptions • The Scheduling Algorithm • Simulation Input • Summary of Results • Conclusion

3. Introduction • Wisconsin Lift Truck corporation sells, rents, services trucking equipment like… • Aerial lift and construction equipment • Cranes • Lift Trucks • Industrial Cleaning Equipment • Loaders • Pallet Trucks • Personnel Carriers

4. Introduction • They have seven locations in Wisconsin and two locations in Illinois • Our contact for this project is • Kristine Rauch • Industrial Engineer, WLT, Brookfield, WI

5. Receive Truck Stock Sold to Customer WIP Inventory Schedule for Set-Up Schematic of the NTSU facility Set-Up (Bay Area) Stage Delivery (Corp run or Branch truck)

6. Problem Description • Bay has maximum capacity of 25 • 5 stations with capacity of 5 trucks each • 4 are considered WIP • 1 truck is being worked on • 5 techs available for scheduling • one tech assigned to each of the 5 bays

7. Problem Description Cont’d • 4 set-up types • 19-Used Truck Setup • 3 types of New Truck Setups • 20-N.T SET-UP • 36-NEW RTL SET-UP • 76-I/C NT SETUP

8. Schematic of the Truck Set-up Bays Tech 1 Tech 4 Tech 5 Tech 2 Tech 3

9. Scheduling Objective • Minimize the time it takes for stock and new customer truck set ups to get from WIP to the delivery area • Minimize tardiness to ensure timely delivery of trucks to customers as much as possible

10. Assumptions There will be no preemption during setup, once a job is started, it is completed If we cannot finish a truck without stopping in the middle of processing, we do not start the truck Once a tech has completed a setup they will start the next set up right after Both stock and customer trucks are taken together as number of stock trucks is negligible 6 hour work day Receive Truck Schedule for Set-Up Set-Up (Bay Area) Truck set for delivery

11. Scope for scheduling • 2 areas where scheduling can be done • When picking trucks from the infinite arrival area into one of the 5 WIPs • When selecting one truck for set-up in each bay station

12. Raw Data Analysis • Data From: Jan 2005 – May 2006 i.e.; 16 months • Job Type 76 – 515 jobs • Job Type 36 – 43 jobs • Job Type 19 – 97 jobs • Job Type 20 – 449 jobs • Total Significant Jobs: 1104 • % of Job Type 76 – 46.65% • % of Job Type 43 – 3.89% • % of Job Type 19 – 8.79% • % of Job Type 20 – 40.67% • Total No. of Trucks - 1974 • No. of Stock Trucks [IMH RENTAL] - 89 [4.5%] • No. of Sold Trucks – 1885 (95.5%)

13. Simulation Input Data • Setup times for each job type • Total labor $$ billed on each truck available • Tech billed at $97 per hour • Distributions for inter-arrival times, by job type • Used ARENA Input Analyzer module to fit each of these into standard probability distributions

14. More Simulation Inputs.. • Due dates were assigned as an attribute to every job arriving • Due date distribution also determined from invoice data • Results were used to design an ARENA simulation so that different scheduling algorithms could be implemented and their performance evaluated.

15. Scheduling LOGIC • Experimented with 4 different hybrid scheduling algorithms. • Scheduling Algorithms used are a simple combination of standard algorithms with modifications made to suit this problem. • LST and SPT • Process trucks in both WIP and bay queues in order of lowest value of the sum of Slack time and Processing time. • In doing so, we anticipate minimizing flowtime as also reducing slack. • LST OR SPT • A modification of the above algorithm where incoming trucks are processed as per the least slack time, if (slack >0), else SPT is used to select trucks from the queues.

16. Scheduling Logic • EDD With Priority • Modification of the EDD algorithm to incorporate a priority mechanism for new truck types over old truck types • Selection rule is – least value of (due date/priority), where priority is “50” for a new truck type and “10” for a used truck type (type 19) • Shortest Processing Time • Plain ol’ SPT in least order of processing time

17. Simulation run Parameters • Replication Length – 180 Days • Hours/day – 6 hrs • Warm up period – 10 Days • Number of Replications -4

18. Simulation Results [ALL UNITS DAYS]

19. Conclusion • The combination of LST and SPT works best to minimize overall flow time (but not tardiness). • If either LST/SPT is used depending on whether the job is slack or not, this leads to a significant reduction in max. lateness, compared to using LST + SPT in all cases. • SPT scheduling yields the least max. lateness. • A priority based scheme predictably decreases the avg. lateness for new truck set-ups. • Future Work Idea • An Intelligent scheduler that can decide on the right scheduling algorithm based on a reasonable guess of whether incoming jobs will be late or not.

20. Thank you! Questions/Comments?