A Company Produces Three Types Of Switches - S1, S2, And S3 - And Supplies Them To A Retailer - Data Analytics Assignment Help

Assignment Task

Requirements for Project.

A company produces three types of switches –S1, S2, and S3 – and supplies them to a retailer. It is contractually obligated to meet the demands of the retailer for each type of switch. Because of limited capacity the company may not have sufficient machining, assembly, andfinishingtime available to satisfy the entire demand in each period through in-house production alone. Contractual obligation requires the companyto make up the shortfall in production by procuring it from an external supplier at higher costs. The company aims to meet the retailer’s demands at minimum cost.

LP Formulation:

Task 1:  
Formulate a linear programming (LP) model that may be solved to identify the optimal production and procurement plan for the company in each time period.

Specifically, you must define the decision variables, objective function, and constraints in your LP model using the following parameters: 

In each time period, for each product i∈(1,2,3):
D_iis the demand (number of units required) for product i.
C_i Pis the cost (in dollars) for producing each unit of product i.
C_i Sis the cost (in dollars) for procuring each unit of product ifrom the external supplier.
t_i mis the machining time (in minutes) required to produce each unit of product i.
t_i ais the assembly time (in minutes) required to produce each unit of product i.
t_i fis the finishing time (in minutes) required to produce each unit of product i.
Further, assume that:
300hours of machining time are available for regular run.
 240hours of assembly time are available for regular run.
 240hours of finishing time are available for regular run.
LP Parameter Estimation:
You must now use available data to estimate the parameters of the LP formulated in Task 1.

Estimation of t_i m, t_i a, t_i f, andC_i P:
The CSV file “production.csv” contains 15,000 records with6 columns: SerialNo,ProductCode, MachineTime,    AssemblyTime, FinishTime, and Cost. SerialNois a unique identifier assigned to each unit produced by the company; ProductCode specifies the product type; MachineTime,AssemblyTime, and FinishTime specify the time (in minutes) taken by each process (machining, assembly, and finishing) to produce a unit; the last attribute, Cost, specifies the cost (in dollars) of producing the unit in-house.

Task 2:
Use the data from the “production.csv”  file to estimate the average machining time, assembly time, finishing time, and cost per unit for each product type as estimates of the parameters t_i^m, t_i^a, t_i^f, and C_i^P of the LP model.

Estimation of demandD_i
The CSV file “demand.csv” contains the retailer’s sales data for the three switches over the last 52 time periods. For example, the first row shows that 463 units of S1 were sold in time period 1, and the last row shows that 629 units of S3 were sold in time period 52. 

Task 3: 
Use the data from the “demand.csv” file to predict the demands D_i in time period 53 for each product. Discuss the prediction method that you chose and justify your choice.

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