BUS606: Operations and Supply Chain Management

An Indian Company is manufacturing/assembling product A and B as per the bill of material shown in Figure 2. The company is 40 km away from the railway station and well connected with other cities by road. Considering fluctuation of market demand of product A and B, company is seeking effective procurement strategy for their ATO production system. The company has assembling unit in Punjab and retailers in different parts of India. Base product is manufactured as per the forecast and stored at the central warehouse shown in Figure 1. After receiving the customer order, the base product is brought to retailer shops in 15 to 20 days. Auxiliary parts/components/sub-assemblies are manufactured or assembled at the retailer site. It is assumed that material handling cost is 10% of procurement cost from each supplier. The aggregate demand for raw material to produce base product in the planning horizon is 4,900 tones. Senior members of different departments such as Finance, Marketing, Design and Manufacturing are asked to form a team of decision makers to select the right supplier for the company. Initially, a supply base is formed based on their industrial certifications such as ISO, TUV etc, material test data and ability to supply within the lead time. Based on the above information supplier's data sheet, is prepared, and shown in Table 2. Distance and mode of transfer mentioned in Table 2 is used further to calculate cost of emission for inbound transport.

Linguistic terms, shown in Table 3, are used to prepare supplier's reliability measurement data sheet, shown in Table 4. Arithmetic mean of each IFN, shown in Table 4, is used to calculate reliability of each supplier, shown in Figure 5.

Table 3 Linguistic terms.

Linguistics terms	IFNs	Linguistics terms	IFNs	Linguistics terms	IFNs
Excellent	[1.00;0.00;0.00]	Good	[0.7;0.2;0.1]	Bad	[0.4;0.5;0.1]
Very good	[0.85;0.05;0.1]	Moderate	[0.5;0.5;0.00]	Very bad	[0.25;0.6;0.15]
				Extremely bad	[0.0;0.9;0.1]

The normal hamming distance of each supplier is measured from ideal IFN (1.0;0.0;0.0). Complement of the normal hamming distance is considered as the overall reliability of each supplier. Cost-Emission-Decision Matrix is prepared with Table 5 and Table 6, shown in Table 7. Cost coefficient and emission coefficient from Cost-Emission-Decision Matrix is used to prepare transportation cost and GHG emission objective function, mentioned in Equation 11 and Equation 14, respectively. Local supplier performance matrix is prepared further with Table 3 and Table 8, shown in Table 9. Supplier's data sheet for auxiliary product and demand of products at retailer's site, shown in Table 10 and Table 11, are prepared to select and to distribute order to the selected suppliers at retailer's site as per stochastic demand.

Table 8 Linguistic terms.
Table 9 Local Supplier Performance Matrix.
Table 10 Supplier's data sheet for auxiliary product.