Consider a peak harvest day having 18,000 barrels of berries unloaded, with 70% being wet harvested. The 18,000 bbls. is consistent with the Sep. 23 data in case Exhibit 1. The 70% wet harvested relates to anticipated trends in wet vs dry harvesting (with wet harvesting becoming increasingly more popular). For calculations, assume that trucks arrive uniformly over a period of 12 hours; i.e., if, on average, 20 trucks arrive in an hour, then one truck arrives every 3 minutes and successive trucks are spaced exactly 3 minutes apart. In the language of waiting lines, the truck interarrival times are always 3 minutes with no variability note that this case is on process analysis, not on variability or waiting lines.

1. Bottlenecks:Identify the primary and secondary bottlenecks in the process. FYI, the primary and secondary bottlenecks have, respectively, the highest and second-highest implied utilization; primary bottleneck restricts process flow rate the most. What is the use of identifying the primary and secondary bottlenecks? Notes: The bottleneck is a resource, not a product (some students made this mistake in the Ex.1 PQ problem). To answer this question, you likely need to have answered question 2 (unless you have good intuition on bottlenecks), because implied utilization of process step = demand / step capacity.
2. Peak day duration, overtime: When would processing be completed on a peak day? What amount of this day duration will be overtime? Explain your reasoning for each answer. Note: A good approximation is to use Processing Duration = Amount of flow units to be processed / Flow Rate. This ignores time to fill an empty system or time for the first unit to flow through, but that is OK for this continuous flow cranberry line.
3. Wet berry inventory: Draw a plot (or provide a data table) of total wet berry inventory over time in the system for a peak day. Briefly explain how this plot (or table) tells you how much wet berries must be in trucks waiting to unload? Note: It suffices to use a time unit of an hour as most segments of the graphs are linear. Also, either assume that every truck delivers 70% wet and 30% dry berries or a 100% dry truck goes into separate line for dumping and storage than a 100% wet berry truck. Notes: Before you start this plot, think carefully about when you should start processing berries on a peak day and why. A legible scan of a hand-drawn graph is acceptable if it indicates slope and key inventory values. Excel is an easy way to draw this plot.
4. Last-truck wait time: When would the last truck unload and how long would it have waited? Note: It is useful to ponder why the last truck must wait. FYI, the last truck will arrive close to 7 PM, so all you need to figure out is at what time the last truck will be able to unload. The plot or table in part iii above can enable an answer.
5. Average truck waiting time cost: Estimate the average cost of waiting trucks on a peak day. One way of answering the question is to look at your plot of wet berry inventory in the system and then figure out what of this inventory is not in the storage bins. This gives you a profile over time of wet berry inventory in trucks. Next you determine the average # of trucks that your profile is equivalent to, and what the appropriate waiting time is. Then, the required average cost will be average # of trucks x waiting time in hours x cost rate of a waiting per truck per hour. Please contact the instructor if interested in knowing more.