Free Essay

Cranberry Case Operation Study

In: Business and Management

Submitted By krazed
Words 1650
Pages 7
OPNS D30 Operations Management
National Cranberry Cooperative

1. Process flow diagram and bottleneck operations
For the process flow diagram, see Exhibit 1. The bottleneck operation is Drying (rate: 600 bbls/hr).
Let’s consider the wet and dry processing separately: * Wet processing: RP1 can dechaff up to 3,000 bbls/hr, but only dry 600 bbls/hr. Thus, the bottleneck operation of wet processing is drying, and the bottleneck rate is 600 bbls/hr. * Dry processing: RP1 can destone 4,500 bbls/hr, but only dechaff 1,500 bbls/hr. The bottleneck operation is dechaffing, and the bottleneck rate is 1,500 bbls/hr.
So taking wet and dry processing together, the maximum capacity of processing (destoning, dechaffing and drying) is 1,500 + 600 = 2,100 bbls/hr. Thus, if the plant was running at maximum capacity for both wet and dry processing, the activity with the lowest throughput rate would be quality grading, with a rate of 1,200 bbls/hr. However, 70% of the berries processed by RP1 are supposedly wet berries. RP1 can store up to 4,000 bbls solely with the bins 1 to 16, which can hold only dry harvested berries; on the other hand, it can store a maximum of 1,200 bbls with the bins that are designed only for wet harvested berries (25 to 27). Thus, all the hybrid bins will have to be used to store wet harvested berries in order to cope with the rate of wet berries being received. All in all, RP1 will be able to store up to 3,200 bbls of wet harvested berries; this is less than 70% of the total storage capacity, so RP1 will have to process wet berries in priority to unload the bins. Also, because it should avoid storing wet berries overnight, RP1 will have to process wet berries in priority, which means the 600 bbls dried every hour will all need to go through quality grading – thus limiting the amount of dry berries going though quality grading to 600 bbls/hour.
At the end of the day, the bottleneck operation is the drying of wet harvested berries, and the bottleneck rate is 600 bbls/hour.

2. Trucks queue and overtime a) Two main reasons explain why trucks have to wait. First of all, the trucks start unloading 4 hours before the plant starts processing (7AM vs 11AM); because of that, berries accumulate very fast in the holding bins, especially in the wet holding bins. On a busy day, the latter can get full even before RP1 starts processing, which already forces trucks to wait (see Exhibit 2). Moreover, the bottleneck rate is 600 bbls/hr (drying; see Exhibit 1), while the unloading rate of the wet berries is up to 2100 bbls/hr. This causes the wet berries in holding bins to fill up faster than the dryer can process. As a result, the trucks have to wait up to 3 hours before they can empty their wet berries.
Note: unloading normally takes 5 to 10 minutes, i.e. 7.5 minutes on average; the average truck load is 75 bbls, and 5 trucks can be unloaded simultaneously on the 5 Kiwanee dumpers. So the maximum unloading rate (if trucks were coming in constantly) is 60/7.5 x 75 x 5 = 3,000 bbls/hr. Because the percentage of wet berries is 70%, wet berries can be unloaded at a maximum rate of 2,100 bbls/hr. b) Overtime is necessary because, as explained in Q1, wet berries should preferably not be held overnight and the bottleneck rate is too low to enable RP1 to process all the berries within the regular hours. This forces the workers to finish processing during the night.

3. Inventory build-up
See Exhibit 2. There is no inventory build-up for dry berries. Actually, dry berries never need more than 45% of the dry berries holding bins capacity (between 10am and 11am).
On the other hand, wet berries delivery (1,050 bbls/hr) tops up holding capacity (3,200 bbls) before processing even starts. Trucks start waiting after 3,200/1,050 = 3.0476 hours i.e. at 10:03 am.
Trucks stop waiting 400 / 600 = 0.6667 hours after 2 am, i.e. at 2:40 am.
That is, there is a waiting line during 16 hours and 37 minutes.
The holding bins are empty at 8am the next morning.
The operating time is 25 hours, which is impossible because of the 2 hours required for cleaning and maintenance. Moreover, the plant would already have started receiving the next day berries, and would again start building up inventories. The plant would have to shut down at 5am and set aside 1,800 bbls. 4. Start processing earlier
See Exhibit 3. If RP1 starts processing at 7am: * Inventory would increase much slower. * Trucks would start waiting later (at 2:07pm) and the waiting line would end up earlier (at 10:40pm). The waiting line would thus last 8 hours and 33 minutes, which is a lot less than in the previous case. * RP1 would be able to empty the holding bins at 4am the next morning.
Moreover, the dry holding bins would be used as transit only and would not build-up inventory, which could allow for cost reduction.
Comparing the overtime tables of Exhibits 2 and 3 also shows that starting processing at 7 am would enable RP1 to save costs on overtime. However, estimating the costs is not easy because it is not known how many workers would work overtime on each activity. 5. Recommendations
First of all, RP1 should start processing at 7am. This can be achieved immediately and, on the short term, will enable RP1 to benefit from the effects explained in Q4.
(See Exhibit 4) Moreover, despite Walliston’s advice, RP1 does not need to convert its dry holding bins; buying one additional dryer would solve most of RP1’s problems. On the long run, this additional capacity (800 bbls/hr instead of 600) combined with processing starting at 7 am would: * Enable RP1 to never exceed its holding bins capacity, which means that trucks will not have to wait anymore. * Enable the workers to finish emptying the holding bins at 11pm; this would strongly reduce the overtime required to process all berries (see the first workforce scheduling graph and overtime table of Exhibit 4).
Moreover, RP1 could implement 2 shifts instead of one for the activities requiring an amount of overtime hours equal to the duration of a shift (8 hours): see the second workforce scheduling graph and overtime table of Exhibit 4. This would certainly reduce labor costs at RP1.
Finally, we recommend NCC to monitor the berries production trend closely and to convert the number of holding bins accordingly. Indeed, between 6 and 7pm, the wet berries holding bins are close to full; thus, if the production was to increase, the storage capacity would not be enough for wet berries. Converting one or several dry bins to hybrid bins could solve the issue.

Receiving
Receiving
Gross & empty weights recording
Gross & empty weights recording
Berries pre-grading
Berries pre-grading
Take 2 samples
Take 2 samples
Temporary holding
Temporary holding
Wet processing
Wet processing

Dechaffing
2 units
3,000 bbls/hour
Dechaffing
2 units
3,000 bbls/hour
Wet
Wet
Dry processing
Dry processing
Or
Or

Destoning
3 unitS
4,500 bbls/hour
Destoning
3 unitS
4,500 bbls/hour
Hybrid
Hybrid
2,000 bbls
2,000 bbls
Total capacity of processing (sum of the bottleneck rates of wet and dry processing): 2,100 bbls/hour
Total capacity of processing (sum of the bottleneck rates of wet and dry processing): 2,100 bbls/hour
5 dumpers & 27 holding bins
5 dumpers & 27 holding bins
4,000 bbls
4,000 bbls
Processing
Processing
Exhibit 1 - Process flow diagram
Exhibit 1 - Process flow diagram

Drying
3 units
600 bbls/hour
Drying
3 units
600 bbls/hour

Waiting
Waiting

Trucks arrival
Trucks arrival
1,200 bbls
1,200 bbls

Unloading
Unloading
Dechaffing
1 unit
1,500 bbls/hour
Dechaffing
1 unit
1,500 bbls/hour

5-10 min/truck
5-10 min/truck
Dry
Dry

Capacity of quality grading: 1,200 bbls/hour
Capacity of quality grading: 1,200 bbls/hour
Quality grading
Quality grading
Bulk trucks loading
2 stations
Bulk trucks loading
2 stations
Bagging / Bulking
3 conveyors for 10 stations
Bagging / Bulking
3 conveyors for 10 stations
Bagging
4 stations
Bagging
4 stations
Bulking
4 stations
Bulking
4 stations
Bailey Mill
2nd level quality
1,200 bbls/hour
Bailey Mill
2nd level quality
1,200 bbls/hour

3 separator lines
1,200 bbls/hour

3 separator lines
1,200 bbls/hour

Exhibit 2 – Build-up diagrams (processing starts at 11am) 1) Delivery, storing & processing figures
Receiving: 18,000 bbls a day, 70% of which are wet harvested.
Rates: wet berries = 12,600 bbls/day i.e. 1,050 bbls/hr (12 hours) dry berries = 5,400 bbl/day i.e. 450 bbls/hr
Max storage: from Q1, 3,200 bbls of wet berries and 4,000 bbls of dry berries.

The orange row marks the last hour of the regular working time; afterwards starts overtime.

2) Inventory diagrams on the two next pages

Exhibit 3 – Build-up diagrams (processing starts at 7am) 1) Delivery, storing & processing figures

2) Build-up diagrams on the next 2 pages

Exhibit 4 – Consequence of buying one more dryer

Because the throughput rate of quality grading is 1,200 bbls/hr, RP1 can only process 400 bbls/hr of dry berries as a compliment to the 800 bbls/hr of wet berries.
Workforce scheduling

Workforce scheduling: make 2 shifts when overtime equals an entire shift in duration

Overtime - two shifts (hours) | Receiving | 4 | from 3 pm to 7 pm | Processing | 0 | No overtime | Control room | 0 | No overtime |

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