1. Case Study 6: Concentrate Line at Florida Citrus Company
Mike Seide
Chris Chesla
Tony Niemczyk
Sean McCauley

2. Introduction Flow Line Process consisting of 5 operations
Cans are depalletized 360 at a time and sent down a conveyor to the Pfaudler Bowl
The Pfaudler Bowl fills 36 cans at a time with concentrate
The cans are then sealed, washed and grouped into batches of 4 at Stage 1
The batch is sent to Stage 2 which accumulates 6 batches to organize for shipping
The Packmaster places the 24 cans in a box, seals the box, and sends the boxes to the palletizer
The Palletizer loads boxes 3 at a time onto the pallet. The pallet formation is 9 boxes per single layer, 10 layers high.

3. Conceptual Analysis
Increase throughput by identifying and reducing bottlenecks
Determine frequency of arrivals, batch sizes, and down time percentages
NEEDS ONE OR TWO MORE THINGS

4. Building the Model Modeled as a basic flow line production
Used StatFit to determine the best probability distribution to model percent downtime, label change time, and flavor change over time
Black boxed similar operations into stages
Used the entity “cans” as a group of 4 cans
Used a batch size of 5 pallets

5. The Model

6. Experimentation – Initial Model
Built to determine capacity and maximize production, no downtimes incorporated
Ran 10 replications of an 8 hour shift
Production capacity of 22,900 cans per 8 hour shift
Table 1: Operating Times without Downtimes
Equipment Description
Operating/Observed Speed
Pfaudler Bowl
672 cans/min
Seamer
600 cans/min
Packmaster
694 cans/min
Palletizer
Depalletizer
Bundler
550 cans/min

7. Experimentation – Second Model
Modeled with downtimes to determine the actual capacity of the concentrate line
Production capacity of cans per day, a 28.3% decrease in production capacity over initial model
Table 2: Operating Times with Downtimes
Equipment Description
Operating/Observed Speed
Pfaudler Bowl
360 cans/min
Seamer
600 cans/min
Packmaster
Palletizer
672 cans/min
Depalletizer
Bundler
550 cans/min

8. Table 2: Pros and Cons of Alternatives
Distributions
Used a pros vs. cons chart to determine the best approach to model the downtimes
Table 2: Pros and Cons of Alternatives
Alternative
Pros
Cons
One distribution for change time and downtime
Simple.
Data not in correct format.
No batches.
Not accurate for long simulation runs.
Probability distributions
Contained Batches
Utilized the ranges of the data.
Too many changes of batches.
Animation did not show accuracy to actual system.
Multiple distributions
Contained batches
Utilized data
Modeled downtimes.
Animation fit the actual system.
Assumptions made to batch size.
Assumptions made to downtime frequency.

9. Packmaster Down Time(%)
Distributions Cont’d
Used StatFit to determine multiple distributions to model the label change time, the flavor change time, and the individual downtimes for the Pfaudler Bowl and Packmaster
Packmaster Down Time(%)
16.96
31.25
6.68
22.16
14.95
28.27
13.79
34.25
48.6
23.65
78.38
21.24
24.84
31.17
35.93
38.41

10. Experimentation – Optimizing the Model
Created a Macro to vary the arrival frequency and arrival quantity to optimize total throughput by using SimRunner
Tested the parameters of arrival frequency from 1-10 minutes and arrival quantity of 50 – 150 cans
It was determined that an arrival frequency of 1-5 minutes produced the most throughput, anything more would be leftover WIP in the system
By performing this analysis it was determined that the arrivals do not create a sizable impact on total throughput

11. Experimentation – Optimizing the Model Cont’d
Next SimRunner tested the effect of downtime on the system
It was determined If the frequency between downtimes was high, then the line produced more full pallets, while if the frequency was small then they produced much less pallets in a given day.
These results were used to better understand the correlation between the length and frequency of downtime during production to try and optimize the model Not sure if this statement is totally correct….

12. Results – Reducing the WIP
One of the team’s tasks was to reduce the WIP, this can be achieved in two ways:
To increase the amount of time between arrivals of empty cans
Or to decrease machine down times
Increasing the amount of time between arrivals mainly affects the amount of cans on the empty can conveyor since the next location on the line is a bottleneck (the Pfaudler bowl).
By making the time between arrivals 8.1 minutes, then the output is still 8 full pallets, while the maximum amount of cans on the empty can conveyor is 1113.
Increasing the amount of time between to more than 8.1 minutes decreases the amount of full pallets that can exit the system in one day.

13. Results – Reducing the WIP
LOOKS kind of full ANY IDEAS?
Results – Reducing the WIP
The final step to maximizing the throughput of the concentrate line with the current equipment is to develop a plan to eliminate the downtime from the bottleneck locations.
The historical data from this line states that Pfaudler bowl is down 22.16% of the time and the Packmaster is down 28.51% of the time.
This downtime is due to poor maintenance, lack of communication between workers, lack of attention by the workers, inefficient layout of the concentrate line, and bad machine design.
Some of these factors are difficult to handle, but there are a few that can be eliminated to improve the efficiency of the line.
Downtime
Average Throughput
Historical Downtime
7.00 Full Pallets
5% Decrease from Historical Downtime
8.30 Full Pallets
10% Decrease from Historical Downtime
9.65 Full Pallets
Table 4: Throughput with Improved Downtime

14. Recommendations
To alleviate the problems the concentrate line is facing a number of things should be done:
The Pfaudler Bowl should be running at all times to alleviate the bottleneck at this station
FCC should try to eliminate the downtime associated with the Pfaudler Bowl
To increase throughput, downtime for other machines should also be reduced. Our model shows a 10% decrease in downtime would increase productivity by roughly 38%.
The amount of time between arrivals should be no greater than 8.1 minutes to prevent production under 8 full pallets
Better employee utilization can be gained by work sharing and flexible work assignments to increase throughput

15. Questions ?