In addition to prototyping, Powder Bed Fusion (PBF) AM processes have lately been more widely used to manufacture end-use parts. These changes lead to necessity of higher requirements to quality of a final product. Optimization of process parameters is one of the ways to achieve desired quality of a part.
In addition to prototyping, Powder Bed Fusion (PBF) AM processes have lately been more widely used to manufacture end-use parts. These changes lead to necessity of higher requirements to quality of a final product.
Optimization of process parameters is one of the ways to achieve desired quality of a part. Finite Element Method (FEM) and machine learning techniques are applied to evaluate and optimize AM process parameters. While FEM requires specific information, Powder Bed Fusion Machine Learning is based on big amounts of data. This paper provides a conceptual framework on combination of mathematical modelling and Machine Learning to avoid these issues.
Learn more about Powder Bed Fusion here
brainly.com/question/28322914
#SPJ4
Answer:
2. Limited supply would increase the price
Explanation:
In the given case the vendor sells in advance four thousand units for $300. While the installed capacity of the factory being to produce 1000 smartphones every month.
Expected sales being 500 units per month.
During the first few months, since the seller has already successfully sold 4000 smartphone units, high demand for the smartphones is evident.
Since the supply is limited to 1000 units only in a month and the quantity demanded being more as is evident by 4000 units being pre sold, during the initial phase, this would create a high demand.
And since the supply is limited, the seller will have to increase the price as the demand is lot more.
Answer:
a) process
Explanation:
The P's are Product, Pricing, Place, Promotion, People, Process and Physical Evidence and for Traditional Marketing is Product, Pricing, Place and Promotion
The answer is total compensation.
