Table:

Meaning of words:

CT = CYCLE TIME

TH = THROUGHPUT

WIP = WORK IN PROGRESS

FORMULA FOR WIP = TH x CT

ML Models - Refers to Machine Learning Models

2. (25 Pts.) Consider the modeling of production dynamics according to Little's Law. Knowing that experience with continuous improvement reduces CT, and that when CT is reduced, WIP will also reduce while TH is kept constant, explain: a. What happens when TH has to be increased by 20% for this factory? Illustrate your answer numerically. (You can use the example in Table 3, pg. 10, or your own example.) b. What happens to CT and TH in your above illustration) when WIP is kept constant? When if ever might it make sense to operate with such a production strategy? c. Of the four different ML models we discussed, which can, and which cannot be useful for monitoring, learning and predicting CT, TH, and WIP in a production enterprise? Explain your answer. Table 3 Example factory information Station No. 1 # of machines 1 Processing time (hour) 2 5 WIN HYY 10 4 3