Applying stats in the field of Rice Mill:

This has given me a wonderful opportunity to understand how to implement all that we learned in a working business model.

Using Statistics in the field of Rice mill:

This is an end to end module where millers procure the paddy at right time, Store it for about a year (After drying); processed paddy is converted to Rice and sold to whole sellers. Paddy cultivation in Tamilnadu is seasonal, accurate cost prediction during a bad/ bitter season is an important factor influencing the ability of manufacturing firm to survive in today’s competitive markets.

Let me brief you in short by illustrating the Flow of Rice mill: 

Building a predictive model to increase the performance of the Rice Mill.

Variables considered for predictive modeling:

  • Machinery and Equipment
  • Productivity of workers
  • Performance of Rice Mill

Prescriptive Analytics:

How to improve the operational capability?

  •  The analysis of the correlation between the production volume and the efficiency of machinery and equipment.
  • The production volume was considered to be the result of an interaction of the efficiency of machinery and equipment to the objectified work.
  • The analysis of correlation between the production volume and the productivity of workers. 
  • It shows the strength and direction of the relationship between the production volume and productivity of workers.

 Multiple Co-relation & Regression:

  • Find the Co-relation between the efficiency of machinery/ equipment and the productivity of workers and its effect on the performance.
  • Thus, the level of the applied technology and engineering and the degree of their utilization by the undertaking will be determining the work of employees, and thereby the size and structure of employment.

Therefore, by using these simple techniques I can find the factors influencing the operational capability in the field of Rice Mill.

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