Page 11 - Steel Tech India eMagazine Volume January 2023

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Vendor Evaluation – Analytical Hierarchy

Process

Partha S. Ghose, Director
Kalyani Steels Ltd, INDIA

Introduction considering all possible parameters, quantitative and
With a challenging target to create 300 MTPA qualities that may impact the facility and the additional
steelmaking capacity in India as per the National Steel associated risks.
Policy 2017 and a subsequent remarkable initiative There are simple vendor selection matrices with simple
undertaken by the Indian steel sector backed by strong score card with discrete values and weighted score
support by Government, India has already started card with weighted values, Pugh analysis etc. However,
experiencing the huge surge in steel project initiation. in a Multiple Criteria Decision Problem (MCDP) with

Reaching to 300 MTPA from the present ~154 MTPA tangible and intangible parameters involved in the
crude steel capacity, there are hindrances and GHFLVLRQ SURFHVV ZLWK FRQÀLFWLQJ LPSDFWV WKHUH DUH
challenges galore for the entire lifecycle of each project, operations research tools available to deal with the
most of which are going to be in the ‘large’ or ‘mega’ same like Multivariate Analysis of Variance (MANOVA),
FDWHJRULHV VSHFL¿FDOO\ LQ WKH DUHD RI ODQG DFTXLVLWLRQ Fuzzy Statistical approach, Analytic Hierarchy Process
and project execution resources like equipment or AHP etc.
manufacturing and construction. In this article we shall elaborate Analytic Hierarchy
In the area of metallurgical machine manufacturing, Process with a real life example.
India is still a net importer and one of the major source of A. Analytic Hierarchy Process (AHP) 1,2,5
import of metallurgical machineries, the manufacturing Analytical Hierarchy Process (AHP) developed by R.
hub China, is not as accessible as it used to be few W. Saaty (1987) can conveniently deal with complex
years ago, the resource gap in steel plant machineries analytics and multiple-criteria decision problems
is going to be phenomenal to meet the 300 MTPA target (MCDP), where some or all of the criteria are not
by 2030-31. The National Capital Goods Policy 2016, represented by discrete numbers and are subjective
rolled out several measures to boost the sector but due
to the massive pandemic impact and extreme market or perception based.
ÀXFWXDWLRQV WKH VHFWRU LV QRW SURMHFW UHDG\ WR FDWHU WR For example, let us consider the vendor selection
supply heavy and critical steel plant machineries to meet decision problem for a steel plant with three
the challenge. Therefore, manufacturers from other shortlisted vendor alternatives – Vendor 1 (V1),
industry sectors, not so conversant with technological, Vendor 2 (V2) and Vendor 3(V3). The major criteria
functional and quality requirements of steel plant could be as under:
and some second tier manufacturers shall have to 1. Product quality guarantee as per RFP (C1)
come forward to share the manufacturing load. This 2. Delivery commitment as per RFP(C2)
phenomena will trigger several issues related to design,
technological requirement, equipment quality to deliver 3. Optimal pricing (C3)
predetermined product quality, delivery commitment 4. Market reputation and references (C4)
to match the project schedule etc. and hence, the 5. Adherence to requirement (C5)
vendor selection process has to be very meticulous
and stringent to make a decision on the right vendor As can be seen from the listed criteria, for criteria C1,

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