Answer:
obstacles - provide a challenge
Answer:
The net savings changed the most, and this is because of the extra money coming in via total income. An extra $290.00 was added to the category.
Explanation:
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
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Answer:
Annual depreciation= $7,996
Explanation:
Giving the following information:
Purchase price= $42,000
Useful life= 5 years
Salvage value= $2,020
<u>To calculate the annual depreciation under the straight-line method, we need to use the following formula:</u>
Annual depreciation= (original cost - salvage value)/estimated life (years)
Annual depreciation= (42,000 - 2,020) / 5
Annual depreciation= $7,996
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