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Michelin Interview Questions and Answers

Updated 23 Dec 2024
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Q1. What is the Definition of Topography Survey ? And Explain it!

Ans.

Topography survey is a detailed mapping of the natural and man-made features of a piece of land.

  • Topography survey involves measuring and mapping the elevation, contours, and features of a land area.

  • It helps in understanding the terrain, drainage patterns, and existing structures on the land.

  • Topography surveys are essential for construction projects, land development, and environmental assessments.

  • Surveyors use specialized equipment like total stations and GPS to collect accur...read more

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Q2. What is difference in Dumpy level, auto level, and digital level?

Ans.

Dumpy level, auto level, and digital level are all types of surveying instruments used for measuring horizontal and vertical levels.

  • Dumpy level is a basic surveying instrument with a telescope and bubble level for measuring horizontal and vertical angles.

  • Auto level is a more advanced version of a dumpy level that automatically adjusts the line of sight to be horizontal.

  • Digital level is a modern surveying instrument that provides digital readouts of measurements for increased ...read more

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Q3. How to work the Total Station? And how to layout any area by Total Station it explain!

Ans.

Total Station is a surveying instrument used for measuring angles and distances to accurately layout areas.

  • Set up the Total Station at a known point with a clear line of sight to the area to be surveyed.

  • Calibrate the instrument by leveling it and inputting the necessary parameters such as height and angle.

  • Measure distances and angles to various points in the area to create a detailed map or layout.

  • Use the data collected to mark out boundaries, structures, or other features in...read more

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Q4. How to calibrate a control valve

Ans.

Control valve calibration involves adjusting the valve to ensure it operates within specified parameters.

  • Determine the valve's operating range and desired set points

  • Use a calibration bench or in-line calibration equipment to adjust the valve's position and response time

  • Verify the valve's performance using a flow meter or pressure gauge

  • Document the calibration process and results for future reference

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Q5. How to prepare google KMZ file? And Explain it!

Ans.

A KMZ file is a compressed version of a KML file used for displaying geographic data in Google Earth.

  • Create or download a KML file with geographic data

  • Compress the KML file using a tool like 7-Zip or WinZip

  • Change the file extension from .zip to .kmz

  • Open the KMZ file in Google Earth to view the geographic data

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Q6. What is your current CTC per month and year

Ans.

My current CTC per month is $10,000 and per year is $120,000.

  • Current CTC per month: $10,000

  • Current CTC per year: $120,000

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Q7. How to distribute an error in any Point?

Ans.

Error distribution in a point can be achieved by considering the uncertainty in measurements and applying statistical methods.

  • Consider the uncertainty in measurements to determine the range of possible values for the point.

  • Apply statistical methods such as standard deviation to distribute the error around the point.

  • Use error propagation techniques to calculate the overall error in the point based on the errors in individual measurements.

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Q8. What is the Traverse?

Ans.

The Traverse is a method used in surveying and navigation to move through an area by taking a series of connected measurements and directions.

  • Traverse involves measuring distances and angles between points to create a connected path.

  • It is commonly used in land surveying, construction, and navigation.

  • Traverse can be closed or open depending on whether it returns to the starting point.

  • Example: A land surveyor uses a traverse to map out the boundaries of a property.

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Q9. What is RL?

Ans.

RL stands for Reinforcement Learning, a type of machine learning where an agent learns to make decisions by interacting with an environment.

  • RL involves an agent learning to take actions in an environment to maximize some notion of cumulative reward.

  • It is based on the idea of trial and error learning, where the agent learns from the consequences of its actions.

  • Examples of RL algorithms include Q-Learning, Deep Q Networks (DQN), and Policy Gradient methods.

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