Developing the Tool for Vendor Selection in Power Sector using Cost of Quality

International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395-0056
Volume: 04 Issue: 07 | July -2017 www.irjet.net p-ISSN: 2395-0072
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Developing the Tool for Vendor Selection in Power Sector Using Cost of
Quality
Sahil Bhardwaj *1 , R M Belokar 1
1 Department of Production & Industrial Engineering PEC University of Technology Chandigarh
----------------------------------------------------------------------***---------------------------------------------------------------------
Abstract - Today the cost of quality has become most
important tool as per strategic and economic importance
is concerned. The cost of quality analysis trigger changes
and provides the need to be made to improve and
maintain the financial position of an organization which is
being directly correlated to the quality improvements. This
paper presents the cumulative impact of cost of quality on
the product duly taking the case of power distribution
sector. There are number of factors which are effective in
improving the quality such as leadership, customer focus,
supply chain management, product and process
management etc. The cost of poor quality places a basic
role to make the product cost efficient and competitive.
Keeping in view of the various factors causing poor quality
are highlighted in order to take preventive steps as well as
control. Moreover the process of supplier selection in any
organisation plays a significant and important role in
procuring the equipments. Tata Power Delhi Distribution
Ltd Delhi has a vision to analyse suppliers’ historical
quality performances and integrate this data into future
supplier selections. a constructive research approach has
been adopted further empirics and theories have been
studied in an iterative process to identify their cost drivers
in order to fulfil the purpose of developing a tool.
1. Introduction
Power Quality (PQ) related issues are of most concern
nowadays. The widespread use of electronic equipment,
such as information technology equipment, power
electronics such as adjustable speed drives (ASD),
programmable logic controllers (PLC), energy-efficient
lighting, led to a complete change of electric loads
nature. Along with technology advance, the organization
of the worldwide economy has evolved towards
globalisation and the profit margins of many activities
tend to decrease. The increased sensitivity of the vast
majority of processes (industrial, services and even
residential) to PQ problems turns the availability of
electric power with quality a crucial factor for
competitiveness in every activity sector. The most
critical areas are the continuous process industry and
the information technology services. When a disturbance
occurs, huge financial losses may happen, with the
consequent loss of productivity and competitiveness.
The cost of poor quality is accounted as the annual
monitory loss of an industry on its balance sheet.
Apparently the cost of poor quality is not concerned with
quality only but cost of waste associated because of poor
performance and process along with serious impact on
companies market reputation and good will. Cost of poor
quality is widely not measured in companies, even if
there are many hidden failure costs affecting profitability
of companies. As per PAF model the quality costs are
commonly categorized in prevention-, appraisal- and
failure costs . There are different interpretations of the
general PAF-model, which facilitate the quality
awareness within an organization (Juran and De Feo,
2010; Gryna, 1999; Harrington, 1999; Giakatis et al.,
2001). However, since each organization is unique with
individual requirements it is difficult to know how to
measure Cost of poor quality. Further, Krishnan (2006)
uses the traditional metaphor “Cost of Quality Iceberg” to
illustrate visible and hidden quality costs within an
organization. It illustrates that the visible costs are more
often taken into considerations while the hidden costs
are not prioritized (Krishnan, 2006). The majority of the
identified Cost of poor quality are visual costs since
those are easier to measure than the hidden costs.
According to Bergman and Klefsjö (2010) it is important
to work towards high quality already in development
and service, since it is less costly to change a product’s
characteristics in early stage of a product value than it is
in the production stage or, even worse, on the market.
Even though early research concludes that there is a
need to spread the knowledge for Cost of poor quality
throughout the organization.
Today the suppliers are very important to a company
due to the fact that they most likely are contributing to
the company’s core business. The relationship with the
suppliers is thereby crucial and most necessary is that a
great deal of trust is built between the parties. This
makes the process of selecting suppliers central. Many
parameters can be included and taken into consideration
in order to make as correct decisions as possible. One
problem is that the gathering of relevant information
connected to involved suppliers takes a lot of time.
Thereby, companies use various evaluation criteria in
their selection. The company chooses the criteria they
believe will have greatest impact when selecting
appropriate suppliers to their company. Potential
criteria to include in the supplier selection are purchase
price, ability to supply the required quantity,
maintenance of quality standard and financial standings
(Kumar and Suresh, 2009).

As expected, poor quality cost measured with new Cost
of poor quality model were much higher than before,
when also hidden costs became visible. It is pertinent to
mention here that Cost of poor quality model itself can
be used for evaluating quality and spotting targets for
improvement, when cost structure model for delivery
chain helps develop knowledge of delivery operations.
Overall poor quality and its costs seems to be like
domino blocks which are falling more blocks further this
chain reaction proceed with bigger mess and
consequences. Thus prevention of quality faults before
they even exist should be the primary importance.
The criteria regarding quality is important, but can be
hard to estimate. The difficulties lie in the complexity of
knowing the real outcome caused by poor quality. In
some cases it might be more beneficial and profitable to
choose a supplier with somewhat lower quality in front
of one with a higher purchase price as well as it can be
more profitable in the long run to pay extra for higher
quality. Despite the complexity in quantifying quality, it
is important to have a comprehension of the possible
effects from high and low quality. Poor quality can lead
to major costs later on in the production process and the
later in the production process the faults are discovered
the more expensive it will be (Sörqvist, 2012). An even
worse scenario is if the faulted products actually reach
the customers.
The objective was to provide more comprehensive view
of quality costs in deliveries for support managerial
work. This research design was a single case study and it
is limited to cover performance of distribution
transformers a in one year observation period. Data for
the study was collected through interviews as well as the
record available. Poor quality activities and costs caused
were categorized in internal and external failure costs,
and allocated to each responsible cost object.
2. The case study at TATA Power Delhi Distribution
Ltd.
Tata Power-DDL has been the frontrunner in
implementing power distribution reforms in the capital
city New Delhi and is acknowledged for its consumer
friendly practices. It is a joint venture between Tata
Power and the Government of NCT of Delhi with the
majority stake being held by Tata Power Company. Tata
Power-DDL distributes electricity in North & North West
parts of Delhi and serves its registered consumer base
of 1.51 million and a peak load of around 1764 MW (May
2016), the company's operations span across an area of
510 sq kms. Since privatization, the Aggregate Technical
& Commercial (AT&C) losses in Tata Power-DDL areas
have shown a record decline. AT&C loss is a measure of
overall efficiency of the distribution business which is
the difference between units input into the system and
the units for which the payment is collected. Today, AT
& C losses still stand at 8.88% which is an
unprecedented reduction of around 82% from an
opening loss level of 53% in July 2002. On the power
supply front too, Tata Power-DDL areas have shown
remarkable improvement. When choosing supplier at
TATA Power Delhi Distribution Ltd. costs of, lead--‐time,
legal aspects and commercial aspects especially
purchase price are analyzed. In some supplier selections
the Supplier Quality Engineering department gives
indications of poor quality delivered from a supplier. The
Strategic Buyer listens but don’t know how much the
poor quality will cost the company in the long run and
can consequently not motivate a selection of a more
expensive supplier. The quality aspect is thereby today
mostly based on intuitions, which make it difficult to
include in supplier selections.
TATA Power Delhi Distribution Ltd. has paid more and
more attention to this problem and has a wish to
integrate the Costs of Quality into the selection process.
This piece of research work will make an attempt to
contribute by introducing a perspective of how to
integrate historical supplier quality performance into
future supplier selection.
3. Methodology
Since the purpose of this research work was to develop
a tool for identification of Cost of quality and assigning
tool for selection of vendor using Cost of quality, this
proposed research work follows a case study design,
which is complemented by expert and specialists
interviews. A case study allows the researchers to get
input from a company and also to practically verify the
tool. The term case study that focuses on describing,
understanding, predicting and controlling the individual
(i.e. process, organization, group, industry, culture or
nationality) (Woodside, 2010). According to Bryman
and Bell (2011). The case study includes a detailed and
intensive analysis of a single case. A single case is
appropriate to use when the researcher want to test and
establish a theory (Ghauri and Grønhaug, 2010). The
authors explain research design as a framework for
collection and analysis of data. It can be stated that in-
depth case studies are the best way to understand the
interaction between a phenomenon and its context. One
weakness discussed by Dubois and Gadde (2002) is the
outcome from a case study. Case study research tends to
describe things clearly but the readers have to draw
their own conclusions from it. This research paper
present a single case study as a strength, since it gives a
deep understanding regarding the subject. However, it is
known that it is weakness for just describing things
without drawing the conclusions. That is why the
empirical study consists of interviews with quality
experts and specialists in their field. The interviews gave
in-depth insight of which CoPQ parameters that are
important to consider for the organization and how they

can be quantified. Furthermore, the tool that has been
developed on basis of conclusions drawn from both the
case study and the interviews with quality experts and
specialists.
The empirical study of this work has been divided into
several parts. First, interviews were done with quality
expert and specialists in their field. These interviews
increased the knowledge about CoPQ. The workshops
were organised by the organisation focused on cost
parameters within procurement department. Next step
in the research process was a single case study within a
company. In the case study, interviews as well as
observations and reviews of documentation were
included. The different parts will be explained more in
detail below. Interviews with quality expert- and
specialists as interviews are often considered as the best
method for collecting data. It is a process of
communication. Several interviews were held with
quality specialists working within TPDDL . Each of the
interviews was conducted face-to-face during one to two
hours. One example is the question: Which CoPQ
parameters are most critical? The question is open and
the interviewee had the possibility to decide upon which
cost parameter he/she found most critical.
4. Result and Discussion
The process within TPDDL is presented for pre dispatch
processes so as to ensure proper quality materials are
procured from vendors as per the specification ,
subsequently the process starts with the selection
process of venders so as to purchase materials required
and after that inspection is done which is divided into
two parts one is pre-dispatch inspection and issue of
MDCC and second one is for pre dispatch inspection and
external agencies
4.1 Development of Supplier Quality Performance
Tool
Our research work has been concerned with collection of
field observations in the form of data its analysis and
interpretation in the light of tool of Total Quality
Management. The objective of work has remained to
interpret the data for characterization of cost of poor
quality. A new tool has been designed which describes
the cost drivers which is gathered from the data
In order to apply the costs to the theoretical framework,
the cost related to the specific cost drivers is
summarized into the total Cost of Quality(component) by
the formula:
While the Total Cost of Quality(supplier) is estimated by
the formula :
The Total Cost of Quality is subsequently divided by the
total amount of purchased components and finally added
to the purchase price.
To achieve the objective of this research paper data was
examined and consider for costly equipments purchase
by TPDDL during FY”2016-17” . During the survey and
consulting the in charge of different divisions as well as
the technical experts we identified the equipments that
has more importance and relevance in the operation of
the power distribution to north and north west Delhi.
Table -1 Costly Equipments Procured by Procurement
Department
S.No Class A equipment’s
1 66 kv & 33 kv LA, CT, PT, Bushings, Isolators
2 EHV & HT Underground Cables
3 Distribution Transformers
4 Capacitor banks
5 Switchgear and Relay Panel Banks including
Automation Panel
6 All kind of meter (single phase, 3 phase, pre-
paid , CT based , HT meters)
We have considered the analysis of rejection of
transformer as our case study because the magnitude of
rejection and losses were found maximum so in this
regard various observations were collected
Table -2 The factor of rejection of distribution
transformer during FY 2016-17
D.T
REC
EIV
ED
AT
STO
RE
D.T
REJEC
TED
FOR
ANY
REAS
ON
D.T
CORRECTI
ON ISSUE
D.T
SENT
BACK
D.T
(TRANS
PORTA
TION
ISSUE)
D.T
QUAL
ITY
CHEC
KS TO
IMPR
OVE
461 319 Minor
issues for
lift
68 35 33
Breather
not found
SI. No not
found

461
319
68 35 33
Fig-1 Rejection of distribution transformer during the FY
2016-17
The table and figure that out of 461 distribution
transformer received at store out of which 319 were
marked as faulty at the initial inspection later on 68
distribution transformer were rejected and finally sent
back as 35 got damaged during transportation while
remaining 33 were found faulty as they were not
meeting the specifications mentioned in the orders
The department Procurement Quality has recommended
a checklist for checking the physical parameters for
equipments which contains : Less clearance if any ,
Quality of gasket , Rusting, Leakage, Damage due to
transportation , and Missing components
If this procedure for inspecting the physical parameter
for distribution transformer would have been adopted
than the result would have further changed and failure
rate would have be controlled to a large extent
4.2 External Failure of Distribution Transformer
While surveying in the field it was observed that 6
distribution transformer were found not working as they
failed during operation though the transformers were
under warranty. Due to the non operation of this
distribution transformer the power supply could not be
continued and as a result there were losses to company
and reliability of power supply were affected. It was also
observed that these distribution transformer that failed
were under warranty period
It is evident that the losses are maximum due to the
failure of distribution transformer with capacity 630
KVA so we have considered this Transformer for the
vendor selection. Due to the failure of distribution
transformer while operation the financial losses were
estimated using the formula:
Mu(million unit) losses x time(hours) x 106 x cost per
unit
During FY 2016-17 a loss of 1,87,500 has been estimated
during to the failure of 630 KVA D.T which is quite
significant
Table -3 Existing Process for Evaluation Parameter of
TPDDL
S.
No.
Evaluation Parameter Maximum
Allowable
Score
A Timeliness 70
A.1. (70 – 0.5 x No. of days for
delay beyond scheduled
time period)
70
B Quantity 30
B.1. (30 – 0.30 x % quantity
remaining undelivered)
30
4.3 Modified Process for Vendor Selection
The selection of vendor for any equipment has a
significant role in day to day working of an organisation.
It has been observed that the criteria being used for the
selection of vendors in TPDDL does not contain Cost of
Quality. It is proposed that the formula for the vend or
selection need to be further modified by introducing Cost
of Quality as additional factor. The modified formula is
as follows
Calculating Cost of Poor Quality for the 630 KVA
Distribution Transformers
The under mentioned formula has been used for the
estimation of calculation of cost of poor quality for
distribution transformer:
Internal failure + External failure
Table -4
INTERNAL FAILURE
COST
EXTERNAL FAILURE
COST
RE-
WORK(item
sent Back)
DOWNTIME
Rs
6,47,241
Nil
EQUIPMEN
T FALIURE
WITHIN
WARRANT
Y PRIOD
UNITS LOSS
Rs
6,47,241
Rs
1,87,500
Using the above formula the coast of poor quality
workout for 630 kva distribution transformer : Internal
failure + External failure = Rs 14,81,982

Calculating the Cost of Good Quality for 630 KVA
Distribution Transformer:
The cost of maintenance of good quality for the
distribution transformer can be estimated by using
formula:
Prevention Cost + Appraisal Cost
Table -5
PREVENTION
COST = Nil
APPRAISAL COST =
INSPECTION COST + VENDOR
COST = Rs. 58,829
Calculating Cost of Quality for 630 KVA Distribution
Transformer
Cost of Poor Quality + Cost of Good Quality = Rs
8,93,570 Rs
4.4 Vendor Selection
Keeping the above facts into consideration the criteria
for vendor selection need to be further modified by
introducing Total Cost of Quality as additional factor. In
terms of purchase cost the vendor selection can be done
in a significant way by adding Total Cost of Quality in it .
In this manner the total cost of 630 KVA Distribution
Transformer work out as follows
Hence in making the selection of the vendors Total Cost
of Quality plays a significant role the vendors with the
lower prize should be considered for purchase of items
5. Conclusion
The efficient material and supply chain management is a
very significant and crucial for the success of any
organisation better material management methods and
decision models are required to improve the current
practices which increase the efficiency and minimises
the cost. For organizations with a large supply chain
network, the Cost of quality of individual suppliers
participating within a supply chain has a cumulative
effect on the overall revenue of the organization. As a
result, it would do well if work is done proactively with
suppliers to reduce Cost of poor quality. Many
organizations are also implementing supplier charge-
backs (or cost recovery) process, wherein the supplier is
charged for any additional costs incurred due to non-
conforming components and materials, as well as late
deliveries. An effective charge-back system can help keep
track of all the metrics related to suppliers’
performance, along with ensuring business discipline
and accountability throughout the supply chain.
The research presented in this paper emphasize on
designing an integrated system for poor quality cost and
integrated approach for material procurement that
provides better decision on vendor selection . Future
research will be needed to develop a more complete
framework integrated with other decision needed in
areas such as vendor selection, preliminary material
scheduling during the pre-fabrication phase a fully
integrated approach will further improve
communication and minimise gaps in information flow.
Acknowledgement:
Author Sahil Bhardwaj is thankful to Tata Power Delhi
Distribution Ltd. New Delhi for extending the financial
and administrative support for this study.
6. References
Axsäter S. (2006). Inventory Control. Springer, Vol. 2.
Benyoceuf, B., Hongwei, D., Xiaolan, X. (2003). ”Supplier
selection problem: selection criteria and
methods”. Institut National de Recherche en
Informatique et en Automatique (INRIA).
Bergman, B. and Klefsjö, B. (2010) Quality - from
Customer Needs to Customer Satisfaction.
Lund: Studentlitteratur. 3rd edition.
Bryman, A. and Bell, E. (2011) Business research
methods. Oxford University Press, Oxford.
3rd edition.
Burt, D.W. (2003). World Class Supply Management The
Key to Supply Chain Management. The
McGraw Hill , p. 492, 495.
Campanella, J. (1999). “Principles of quality costs:
Principles, Implementation and Use”. ASQ
Quality Press, p. 3-‐‐5.
Cooper, R. , Kaplan, R. S. (1992). Activity based systems:
Measuring the costs of resource usage.
Accounting Horizons.
Degraeve, Z. & Roodhoft, F. (1999a).“Effectively selecting
suppliers using Total Cost of Ownership”,
published in Arlbjørn J.S, Zachariassen F.
(2009). Total Cost of Ownership: A
differentiated Approach. Department of
Entrepreneurship and Relationship
Management, University of Southern
Denmark.
Ellram, L. (1993). “A Framework for Total Cost of
Ownership”. The International Journal of
Logistics Management, Vol. 4 No.2, p. 49-
-‐59.
Ellram, L. (1995). “Total Cost of Ownership, An analysis
approach for purchasing”. International
Journal of Physical Distribution & Logistics,
Vol. 25 No. 8, p. 4-‐‐23.

Ellram, L. , Siferd, S.P. (1993). “Purchasing: The
cornerstone of the Total Cost of Ownership
concept”. Journal of Business Logistics, Vol.
14 No.1, p. 163-‐‐184.
Ferrin, B.G., Plank, R.E. (2002). “Total Cost of Ownership
models: The journal of Supply Chain
Management, p. 18-‐‐29.
Ghauri, P., & Gronhaug, K. (2010). Research Methods in
Business Studies: A Practical Guide. (Fourth
Edition ed.) FT-Pearson
Giakatis, G., Enkawa, T. and Washitani, K. (2001) "Hidden
quality costs and the distinction between
quality cost and quality loss", Total Quality
Management, vol. 12, no. 2, pp. 179190.
Gryna, F. M. In Juran, J.M. and Godfrey, A.B. (1999)
Juran’s Quality Handbook.
Hansen, D.R., Mowen, M.M. (1997). Cost accounting;
Activity--‐based accounting; Managerial
accounting. South Western College Pub.
Harrington, H.J. (1987) Poor-quality cost. New York:
Decker.
Humphreys, P., Mak, K.L., Yeung, C.M. (1998). “A just-‐‐in-
‐‐time evaluation strategy for international
procurement”.
Hoque, Z. (2003). Strategic Management Accounting.
Pearson Prentice Hall, p. 179.
Höst, B.R. (2006). Att genomföra examensarbete. Lund:
Studentlitteratur, p. 29-‐‐42.
Juran, J.M. and De Feo, J.A. (2010) Juran’s quality
handbook: the complete guide to
performance excellence. New York:
McGraw Hill. 6th edition.
Krishnan, S.K. (2006) "Increasing the visibility of hidden
failure costs", Measuring Business
Excellence, Vol. 10 Iss 4 pp. 77-101.
Kumar, S.A., Suresh, N. (2009). Operations Management.
New Age International (P) Limited,
Publishers, p. 180.
Levary, R.R. (2007). “Ranking foreign suppliers based on
supply risk”. Supply Chain Management: An
International Journal, Vol. 12 No. 6, p. 392 -
-‐ 394
Ljung, L., Glad, T. (1991). Modellbygge och simulering.
Studentlitteratur.
Lukka, K. (2003). “The Constructive Approach, in Ojala, L.
and Hilmola, O-‐‐P. (2003). Case Study
Research in Logistics”. Publications of The
Turku School of Economics and Business
Administration, Serie B 1, p. 83-‐‐100.
Saaty, T.L. (2008). “Decision making with the analytic
hierarchy process”. International Journal
Services Sciences, Vol. 1 No. 1, p. 83-‐‐98.
Sánchez-‐‐Rodriguez, C., Hemsworth, D., Martinez-
‐‐Lorente, A.R. (2004), Quality Management
Practices in Purchasing and its Effect on
Purchasing’s Operational Performance and
Internal Customer Satisfaction.
International Journal of Logistic: Research
and Applications, Vol. 7 No 4, p. 325-‐‐344.
Saunders, M. (2009). Research Methods for Business
Students. Pearson.
Svensson, B.S.G. (1994). Kvalitativ metod och
vetenskapsteori. Lund: Studentlitteratur.
Sörqvist, L. (1998). Kvalitetsbristkostnader, Ett
hjälpmedel för verksamhetsutveckling.
Tsai, W.H. (1998).“Quality cost measurement
under activity based costing”.
International Journal of Quality & Reliability
Management, Vol. 15 No 7 p. 719-‐‐752.
van Weele, A.J. (2010). Purchasing and Supply Chain
Management. South-‐‐Western Cengage
Learning, p. 238-‐‐239, 241-‐‐242.
Wei-‐‐Ning, P. (2005). “Supplier evaluation and selection
using Taguchi loss functions”. International
Journal Adv Manuf Technol, p. 155-‐‐160.
Xinxing, L., Chong, W., Rosenberg, D., Barnes, D. (2009).
“Supplier selection in agile supply chains:
An information-‐‐processing model and an
illustration”. Journal of Purchasing & Supply
Management, Vol. 14, p. 249-‐‐262.

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