the Final Exam Question 45, 8.2 .63 Points: 0 of 1 To manufacture an automobile requires painting, drying, and polishing. Epsilon Motor Company produces three types of cars, the Detta, the Beta, and the Sigma Each Deita requires 13 hours for painting. 3 hours for drying, and 5 hours for polishing. A Beta requires 33 hours for painting, 8 hours for dyying, and 6 hours for polishing, and a Sigma requires 8 hours for painting, 1 hour for drying, and 1 hour for polish If the company has 331 hours for painting, 69 hours for drying, and 71 hours for polishing per month, how many of each type of car are produced? Select the correct choice below and fill in any answer boxes within your choice. A. The Epsilion Motor Company produces \( \square \) Deitas, \( \square \) Betas, and \( \square \) Sigmas in a month. (Simplify your answers.) B. There are infinitely many combinations of each type of car that can be produced. Using ordered triplets, the solution can be written as \( ((\mathrm{P}, \mathrm{B}, \mathrm{S}) / \mathrm{D}=\mathrm{D}, \mathrm{B}=\mathrm{D}, \mathrm{S} \) any real number). \( \square \) \( \square \) (Simplify your answers. Type expressions using \( S \) as the variable as needed.) C. There is no possible combination of each type of car that can be produced that meets the criteria.
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Bonus Knowledge
Did you know that the automotive assembly line revolutionized car manufacturing? Thanks to Henry Ford's implementation of assembly line techniques in the early 20th century, production speeds soared, allowing more people to afford cars. This has a direct impact on mass production methods, where efficient time management is crucial, much like the time allocations you’re dealing with here for painting, drying, and polishing! Now, reflecting this problem into real-world application, companies today still struggle with optimizing resources. Understanding how to distribute limited hours across multiple tasks while producing various products is essential in manufacturing. Analyzing constraints—the painting, drying, and polishing time—is similar to how businesses manage schedules and allocate resources to maximize output and efficiency. It’s a classic optimization problem in operations management!