National Cranberry Cooperative A Case Study Solution submitted in partial fulfillment of the course – Manufacturing Strategies “
”
To
Prof. Prasad Chakrabarty On January 23rd, 2013
By Arthi Kumar (E027) Devakshi Garg (E012) Megha Agarwal (E001) Russell Rebello (E046) Sandhya Patil (E042) Sourabh Dhawan (A018)
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Contents Ques 1 What are the sources of variability in the NCC case? ....................................................................... 3 Sources of Variability ................................................................................................................................ 3 Ques 2 What are the problems NCC is experiencing that should be addressed? ........................................ 4 Problems ................................................................................................................................................... 4 Solution ..................................................................................................................................................... 4 Ques 5: How would you assess converting some dry bins to wet? .............................................................. 5 Ques 8: How would you deal with the distribution of wet/dry and volume over the days of the season? . 5 Assumptions: ............................................................................................................................................. 5 Case 1 ........................................................................................................................................................ 5 Analysis ..................................................................................................................................................... 6 Case 2 ........................................................................................................................................................ 6 Adding one dryer ...................................................................................................................................... 6 Analysis ..................................................................................................................................................... 6 Payback Period Estimation........................................................................................................................ 6 Case 3 ........................................................................................................................................................ 7 Adding 2 dryer ........................................................................................................................................... 7 Adding 1 dryer and required bins ............................................................................................................. 7 Payback Period for 2 dryers ...................................................................................................................... 8 Scheduling of workforce and another shift .............................................................................................. 9
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Ques 1 What are the sources of variability in the NCC case? Sources of Variability Trucks arrived at random throughout the day.
The absence of a schedule for the arrival of trucks led to huge waiting lines. It usually took 510min to back a truck onto a Kiwanna dumper, empty its contents and leave the platform. At times some trucks had to wait up to 3 hours before they could empty their contents. This wait occurred when the holding bins became full and there was no place in the receiving plant to temporarily store berries before further operations.
Bulk trucks were loaded with anywhere between 20 to 400 bbls. There was no minimum load weight for a truck, so trucks came with highly varying weights. Hence the number of trucks carrying the load would increase. Present average weight was 75 bbls. Even if this is increased to 100bbls the number truck reduces by 25%.
Employee Absenteeism This problem caused NCC to carry more employees on payroll than really needed. Higher than expected absenteeism often resulted in overtime. For the 1970 season, the process fruit operation at RP1 utilised about 22000 man-hours of straight-time direct labour and about 12000 man-hours of overtime.
Colour Grading of Berries At the time the truck was weighed the truckload of berries was grade according to color. Using the color pictures as a guide, the chief berry receiver classified the berries as Nos 1, 2A, 2B or 3 from poorest to best. Whenever any question about whether the or not a truckload was No. 2B or No. 3, the chief berry receiver chose 3. When these berries were used only 50% of them were found to be No. 3's.
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Ques 2 What are the problems NCC is experiencing that should be addressed? Problems Long Waiting time for Trucks
The absence of a schedule for the arrival of trucks led to huge waiting lines. It usually took 510min to back a truck onto a Kiwanna dumper, empty its contents and leave the platform. At times some trucks had to wait upto 3 hours before they could empty their contents. This wait occured when the holding bins became full and there was no place in the receiving plant to temporarily store berries before further operations.
Overtime This problem is seen in the peak months of September through October. During these months the workers required are 53 instead of the usual 27. However despite carrying higher number of workers than necessary, the shifts run into overtime because of absenteeism. Also, in order to prevent the wet fruit from getting spoilt the labourers need to work the extra hours in the peak months.
Limited room to process water harvested berries Water harvesting is the latest method for harvesting cranberries. The bogs are filled with water and then the berries are mechanically shaken from the bushes, the berries then float to the surface. Water harvesting leads to 20% higher yields, however it reduces the shelf life of the fruit. The water harvesting method is being increasingly used thereby increasing the necessity to increase capacity at NCC. This year too wet harvested berries will form 70% of the total produce.
Solution Scheduling needs to be improved. This includes not just the operations but also the delivery
time and amount of berries. A smoother schedule will ensure less waiting time. A standard minimum weight will ensure that less number of trucks are used to transport the produce, thereby further reducing waiting time.
The absenteeism is directly related to employee payroll. The management can try to find an optimum pay during the peak months to tempt more seasonal labourers so as to ensure that absenteeism too has minimum effect.
Finally, increasing capacity is NOT a solution. The capacity should be increased when present capacity cannot handle the workload after everything has been tried out. The planned capacity increase should be allowed only after everything else has been tried.
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Ques 5: How would you assess converting some dry bins to wet? Ques 8: How would you deal with the distribution of wet/dry and volume over the days of the season? Assumptions: There is a cost associated with trucks waiting to be unloaded and it is $5 per hour.
We have not considered per hour operating cost of plant
Overtime for both regular and part time worker has been taken to be $6.50 per hour.
In calculating the payback time, the same cost saving will occur every day. It is given in case that wet berries will make 70 % of total berries and that normal running hours
for plant is 11 (12-1) hours. Case 1: 10000 bbl/day
Wet Berries (WB) 7000 bbl/day Dry Berries (DB) 3000bbl/day Total Time = 11 Hrs WB feed=7000/11 = 637 bbl/hr DB feed= 3000/11 = 273 bbl/hr Minimum processing rate for WB is at dryers, which is = 600 bbl/hr Minimum processing rate for DB is = 1500 bbl/hr Hence, after 11 hours total accumulation of WB = (637-600)*11 = 407 bbl Overtime = 407/600 = 0.7 hrs Now, assuming this is not a peak season, we have considered only 27 workers. Since plant is working suboptimal level during overtime , only two-third of the work force will be working on wet berries drying process. =2/3 work force = 20*(2/3) = 12 Savings per day = 12 * 6.5= 78 Savings for season = 78* 90 = 7020 If we add another dryer, to save overtime cost, cost will be = 40000
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Analysis Considering the cost of depreciation and cost of investment in dryer(8-10%) it will not be economical to
buy another dryer. Case 2: 15000 bbl/day Wet Berries (WB)= 10500 bbl/day
Dry Berries (DB)= 4500bbl/day Total Time = 11 Hrs WB feed=10500/11 = 950 bbl/hr DB feed= 4500/11 = 410 bbl/hr Minimum processing rate for WB is at dryers, which is = 600 bbl/hr Minimum processing rate for DB is = 1500 bbl/hr Hence, after 11 hours total accumulation of WB = (950-600)*11 = 3850 bbl Overtime = 3850/600 = 6.5 hrs
Adding one dryer Feed capacity = 800+400=1200
Accumulation of WB in 11 hrs = (950-800)*11 = 150*11 = 1650 Overtime = 1650/800 = 2 hrs Analysis Adding another dryer will create bottleneck at separator. Payback Period Estimation Overtime saved in receiving = 12.16-11 = 1.16 hrs
Workers = 15 Cost saved = 15*1.16*6.5= $113 Overtime saved in Processing = 6.5 – 2 = 4.5 hrs Workers = 36 Cost Saved =36*4.5*6.5=$1053 Cost connected to truck weighting period= $ 600 Total cost saved = $1766 per day 6
Payback Period = 40000/1766 = 22.7 days Case 3: 20000 bbl/day
Wet Berries (WB)= 14000 bbl/day Dry Berries (DB)= 6000bbl/day Total Time = 11 Hrs WB feed=14000/11 = 1270 bbl/hr DB feed= 6000/11 = 550 bbl/hr Minimum processing rate for WB is at dryers, which is = 600 bbl/hr Minimum processing rate for DB is = 1500 bbl/hr Hence, after 11 hours total accumulation of WB = (1273-600)*11 = 7403 bbl Overtime = 7403/600 = 12.34 hrs Adding 2 dryer Total feed = 1000+200
Accumulation of WB in 11 hrs (1270-1000)*11 = 2970 Accumulation of DB in 11 hrs (550-200)*11 =3850 Overtime = (2970+3850)/1200 = 5.7 hrs Adding 1 dryer and required bins WB feed = 800
Accumulation = (1270-800) * 11 = 5170 Holding Capacity = 3200 Capacity of a bin = 250 Cost of a bin = 7500 We’ll have to convert dry bins to wet bins, number of bins needed to be converted = (5170-3200)/250
=8 Total Cost = 8* 7500 = 60000 This is more than the cost of adding one more dryer (40000).
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Payback Period for 2 dryers Saving in overtime for receiving process = 18-11 = 7
Workers = 15 Cost saved = 15*7*6.5 = $682.5 Cost of Trucks Weighting $3500 Processing Hours = 12.34-11 = 1.34 Worker= 36 Cost saved = 36*1.34*6.5 = $313.5 Total cost saved = 682.5+3500+313.5 =$4496 per day Payback period = 80000/4496 =17.8 days The chart displaying the initial scenario in all three cases – 10000, 15000, 20000 bbls/day – has been provided below:
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The chart displaying the new scenario in all three cases – 10000, 15000, 20000 bbls/day – with additional dryers (as applicable), has been provided below:
Scheduling of workforce and another shift In the case of 10,000 bbl per day, overtime is minimal so another shift is not needed.
In the case of 15000 bbl per day, overtime is about 2 hrs which is not enough to schedule another shift. Moreover, since it is almost a continuous process, we can start all the processes at same time. At most De-stoning, De-chaffing, Milling and shipping can start one hour after receiving and control room operator has started working.
In case of 20000 bbls per day, overtime is approximately 6 hrs, which means that we can schedule another shift of part time workers on busy or peak days. All the operations will have to start at same time otherwise if we wait one hour, holding bins (both dry and wet) will be full and trucks will have to wait.
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