Cranberry Case

Reflecting on the simulation one of the things that should have changed would have been changing the interval of the trucks so more of the product could have been transported from the

Thus, from the above calculation, it can be exhibited that trucks have to wait to unload after 10.03 am for total 256.5 truck hours. The maximum number of trucks that will wait in a day will be 14.

* Wet berries have to also be dried. This adds an hour to the total processing time as it takes one hour to dry 200 bbls per dryer. However, since there are only 2 steps to each process (dry: dechaff, destine; wet: dechaff, dry) there really is no time added to the whole process

2. At a steady state we'd be able to produce 6 (process capacity) x 4 (hours) = 24 dozen per night. At a starting state, assuming that 1st dozen takes 26 minutes, and we move into a steady state of production, we

I declare that the work contained in this assignment is my own, except where acknowledgement of sources is made.

Sandra Enright of Techtronics Inc., an electronics supply firm, has been examining the times required for stock pickers to fill orders requested from inventory. She has determined that individual order-filling times approximately follow a normal distribution with a mean value of 3.2 minutes and standard deviation of 68 seconds.

Addition of two new dryers implies the increased capacity for the drying station. They add an additional capacity of 2*200bbls wet berries per hour.

At receiving plant no. 1 (RP1), trucks would arrive randomly throughout the day, with a random amount of berries, anywhere from 20 to 400 bbls. In order to utilize transport vehicles more effectively, there should be crews scheduled differently on peak days. It only takes 5 to 10 minutes to unload a

With the bottleneck occurring so early in the process, it is critical that the early steps become more efficient. Hiring more personnel for this step would help ease the back up here but more staff would also increase expenses at a time when the company is trying to reduce costs. An alternative fix would be schedule regular pick ups and deliveries to reduce the uncertainty and efficiency of the way drop offs are occurring. Additionally, if pickups were scheduled, costs could be reduced as LAA could rely on their six trucks to make 4 scheduled pick up/deliveries and could eliminate the need to outsource to a private company. Another thought to address this step is to completely outsource the pick ups, thereby eliminating the cost of truck fuel, maintenance and other expenses. The major problem with the current delivery system in place is that drop offs can occur at any time during a 16-hour work day.

* Last truck arrived (1140min) – First truck arrived (411min) = 729min (=1140 - 411) → 729min/60 = 12.15hrs (Total receiving time)

In order to remedy the backlog at the Dryer area, it is recommended that one (1) extra Dryer be purchases, and not two (2) as was suggested by Will Walliston. Since the Separators (capacity of 1,200 bbls) are too big and expensive to improve upon or replicate, NCC should increase the capacity of the Dryer process so 1,200 Wet Berries (double) can be passed on to the Separators instead the current 600 bbls (filling up its capacity with Wet berries is ideal since Dry Berries can sit overnight).

Secondly, purchasing one additional dryer would cost $60,000. Then, the process capacity would increase to 800 bbls/hr. The dry berries (375bbls/hr) and the wet berries (800bbls/hr) would now sum up to 1175 bbls/hr, which will increase the utilization rate of separators to 97.91%. The resulting increase in flow rate could reduce the overtime labor as much as $78,000 (assuming 12,000 over time hours of all workers * $6.5/hr) and the return on the investment would be 0.3 (18,000/60,000).

Approximately 25% of the shipments to the plant arrive in farmer-owned trucks. These shipments vary in size from 50 to 200 hogs. The farmer’s scheduled delivery affects the overall hogs supply, and the plant is heavily dependent on the farmers schedule accuracy.

According our estimation from day 640 to 730, we had the mean 14.098 drums. Hence, we set the capacity number to 15 and let the production non-stop by adjusting higher order number and 200 quantity per truck. Let’s summary our work as the following: Our process: figure out whether we should build factory and warehouse in specific region. estimate the demand of four region and Fargo region, change capacity, adjust order point, quantity, and priority order, check and adjust parameters from time to time

The main problem in this case is maximizing capacity utilization. An offer for 60 additional reservations to be accepted or not is the question to which Snow, the reservation manager has though of examining the problem through Snow’s technique. One is to have a good forecast of the pickup ratio, which can be multiplied to the Tuesday bookings to get the estimate of the demand. One has to obtain the forecast of adjusted pickup ratio, which can be multiplied, to the Saturday DOW Index to obtain the unadjusted pickup ratio. Here is is trying to eliminate the DOW effect that exists and average the demand through the week (Weatherford & Bodily,1990). Then the