Risk Assessment For A Blast Furnace Paper

IJRET: International Journal of Research in Engineering and Technology eISSN: 2319-1163 | pISSN: 2321-7308
Volume: 03 Special Issue: 11 | NCAMESHE – 2014 | Jun-2014, Available @ http://www.ijret.org 27
R. Suresh1
, M. Sathyanathan2
, K. Visagavel3, M. Rajesh Kumar4
1PG Scholar, Department of Mechanical Engineering, KIOT, Tamil Nadu, India
2Associate Professor, Department of Mechanical Engineering, KIOT, Tamil Nadu, India
3Professor and Head, Department of Mechanical Engineering, KIOT, Tamil Nadu, India
4PG Scholar, Department of Mechanical Engineering, KIOT, Tamil Nadu, India
Blast furnace is a tall reactor to process iron ore into pig iron, modern day blast furnace size range varies from 70 to 120 feet.
Blast furnace iron making process is a complex task it has potential hazards like fire and explosion, co poisoning, hot metal
sparks, heat stress, emission of air contaminants like particulate matter, sulphur dioxide and nitrogen oxides etc. Organization
need to take necessary steps to manage the hazards and its consequences to perform work safely. Various reliability engineering
and risk assessment techniques are applied to improve the blast furnace safety to prevent the blast furnace workers from
accidents. This paper aims to provide the necessity of risk assessment techniques for implementing safety in an integrated steel
plant. Risk assessment using failure mode effect analysis was carried in an existing steel plant blast furnace capacity of
0.6MTPA(Metric Ton Per Annum) which produce around 1000 ton of hot metal called pig iron daily. Failure mode effect analysis
one of the systematic risk assessment technique is applied to the each activity of the blast furnace operation to find out the
potential failure modes and its effects with detection. Risk priority number, severity, detection, occurrence are the factors
determined in this work are used to suggest the safety precautions. Risk priority number helps to find out the highest hazardous
activities which need more attention than the other activities. Safety precautions suggested in this paper can prevent the
occurrence of failures and protect the blast furnace workers from fatal accidents and injuries.
Keywords: Blast furnace, Failure mode effect analysis, Risk priority number, and Safety.
Blast furnace plays a vital role in an integrated steel plant
for producing pig iron which is then converted into various
grades of steel in an electric arc furnace. Raw materials like
iron ore, coke, limestone are charged at the top of the blast
furnace through skip car system. Coke is almost pure carbon
act as a fuel as well as reduces the iron ore into pig iron. Hot
air from stove is blasted in to the furnace making the coke
burn much faster than the normal and temperature rises to
1200 degree Celsius. Pulverized coal is injected through
tuyeres at the velocity of 160 to 240 m/s to furnace to reduce
the fuel consumption. Due to temperature rise various
chemical reactions take place inside the blast furnace carbon
monoxide reacts with unburned coke to form carbon dioxide
that reduces the iron oxides in ore. The molten iron is very
dense so its runs to the bottom of the furnace. Impurities are
removed by the lime stone used as the one of the raw
material .slag is an impurity which is lighter stays above the
molten metal used for various purposes outside the plant.
Blast furnace gas produced from the process is cleaned in
and used as a fuel in captive power plants,
Vacuum decomposing boiler. Excess blast furnace gas is
burn using flaring system. Molten iron and slag is removed
from at regular intervals. Operation in
blast furnace exposes workers to wide range of hazards that
would cause fatal accidents. In past blast furnace explosion
has shown many tragic and fatal accidents, so controlling the
blast furnace operation is a complex task for the blast
furnace workers and safety professionals. To prevent the
accidents and unnecessary failures an effective risk
assessment is important.
From the literature survey it is clear that some researches on
FMEA have been carried out by previous researchers on the
other hand still a lot of applied research in the above field is
required as to explore the fruitful application of the FMEA
technique in the area of blast furnace process. Some of the
past research work are discussed as under. Arun chauan et
al. (2011) conduct a case study and implement failure mode
effect analysis in a casting industry to identify the potential
failure modes and its effects along with the prevention
measures. Prevention suggested in this paper decrease the
loss of cost and time. Hoseynabodi et al. (2010) applies
failure mode effect analysis method to wind turbine systems
with aid of reliability analysis tool software and compare the
result between FMEA and reliability field data. These
results are useful for future wind turbine systems design to
prevent failures at the design stage. Narayanagounder et al.
(2009) addressed the limitation in traditional FMEA and
proposed a new approach to overcome these limitations. The
risk priority code was used to rank failure modes, when two
or more failure modes have the same RPN. They proposed a
new method to rank failure modes. An analysis of variance
was used to compare the means of two risks priority number
values when there is a disagreement in ranking scale of
severity, occurrence and detection. H.shiroyehzad et al.
(2010) applied FUZZY-FMEA preventive technique to
decrease the failure rate in ERP implementation with the
IJRET: International Journal of Research in Engineering and Technology eISSN: 2319-1163 | pISSN: 2321-7308
Volume: 03 Special Issue: 11 | NCAMESHE – 2014 | Jun-2014, Available @ http://www.ijret.org 28
failure cause and effect by implementing fuzzy number.
Burlikowskwa et al. (2011) describes about a new approach
about production development and cost reduction using
failure mode effect analysis. Popovic et al. (2010) describes
about the implementation of risk analysis parameter into the
FMEA method and inconsistencies of the traditional
method. Huges et al. (1999) stated that the traditional
qualitative methods for modeling mechanical system are in
appropriate for automated mechanical production.
Failure mode effect analysis was originally developed by
NASA to improve and verify the reliability of space
program hardware. FMEA is one of the most important and
widely used tools for reliability analysis. It is intentional to
be a proactive action process carried out in advance
implementing new or changes in products or process ideally
FMEA are conducted in the design or process development
stages, although conducting it an existing products and
processes may possibly have benefits in effective FMEA
identifies corrective actions required to reduce failures to
assure the highest possible yield safety and reliability.
Failure mode effect analysis is four types system, design,
process, service. System FMEA focus on systems and sub
systems in early concept stage to demonstrate balancing
among the operational components. Design FMEA
minimizes the effect of failures in sub and main assemblies
it maximizes the design quality and reduces cost. Process
FMEA identifies the deviation in the process flow,
materials, methods, people and environment. Service FMEA
maximizes customer satisfaction through quality and
reliability. Even though it is widely used reliability
technique it has some limitation in prioritizing the failure
modes and output may be large for even simple systems,
may not easily deal with time sequence, environmental and
maintenance aspects.
3.1 Risk Priority Number
Risk priority number methodology is a technique for
analysing the risk associated with potential failures during a
FMEA analyses. To calculate risk priority number severity,
occurrence, and detection are the three factors need to
RPN= Severity Occurrence Detection
3.2 Severity (S)
Severity is the seriousness of the effect of potential failure
modes. Severity rating with the higher number represents
the higher seriousness or risk which could cause death. An
example rating for severity is given in the table 1.
Table -1 Example table of Severity
The severity rating given in illustration is the representation
of operability of a machine.
3.3 Occurrence (O)
Occurrence ratings for FMEA are based upon the likelihood
that a cause may occur based upon past failures and
performance of similar system in similar activity.
Occurrence values should have data to provide justification.
An example rating for occurrence is given in the table 2.
Table- 2 Example table of Occurrence
3.4 Detection (D)
Detection is an assessment of the likelihood that the current
controls will detect the cause of failure mode. An example
for detection rating is as shown in the table 3.
IJRET: International Journal of Research in Engineering and Technology eISSN: 2319-1163 | pISSN: 2321-7308
Volume: 03 Special Issue: 11 | NCAMESHE – 2014 | Jun-2014, Available @ http://www.ijret.org 29
Table- 3 Example table of Detection
3.5 Steps in FMEA
To conduct FMEA there are some necessary steps as to
Fig 1 Step in FMEA
Figure 1 shows step by step process to conduct FMEA.
Review team first collects all the component data with the
help of process flow diagrams, P&ID. With that information
review team finds the potential failure mode and its effects.
Next step is to find the failure occurrence with its severity
rating. List the to rate detection,
with the help of severity, occurrence and detection rating
calculate RPN. Give the control measures to prevent the
occurrence of failure and finally document and follow up the
FMEA report.
Case study is conducted and FMEA technique is applied to
the blast furnace in an integrated steel plant. Blast furnace is
used for the production of pig iron for steel making in steel
plant. Blast furnace is manufactured by CERIS technology
china capacity of 0.6 MTPA. Failure mode effect analysis is
executed by a multidisciplinary team of experts in blast
furnace operation with the help of the
analysis team identifies the components in process. For the
analysis break down details; accident reports for the past
five years are taken. Criteria of ranking of severity,
occurrence and detection are selected suitably by analyzing
the past failure records of the furnace. Using values of
severity, occurrence and detection number risk priority
number is calculated.
4.1 Sample Calculation
Sample calculation for cold blast process in blast furnace is
shown below. Cold blast in iron making refers to were the
air from the environment is blown into the stoves for
preheating at the pressure 100 to 280 kpa. In cold blast
process the potential failure mode is increase or decrease in
pressure if the pressure decrease it does not cause accident
only effects the process but if the pressure increase the safe
limit it leads to explosion in stove.
4.2 Steps to Calculate RPN
Step1. Potential failure mode of cold blast process found.
Step2. Potential effect of failure found with severity. Failure
not only stops the process it also causes serious accident.
Step3. From the table values of severity, occurrence,
detection values are calculated and tey were obtained as 4,1
and 8 respectively.
Step4. RPN value calculated as RPN = S O D
Considering S = 8, O= 1 and D= 2
RPN = 8 1 2 = 16
Table- 4 FMEA chart
Failure mode Failure
Failed to
Explosion Corrosion Reliable
10 2 3 60 Periodic
IJRET: International Journal of Research in Engineering and Technology eISSN: 2319-1163 | pISSN: 2321-7308
Volume: 03 Special Issue: 11 | NCAMESHE – 2014 | Jun-2014, Available @ http://www.ijret.org 30
Conveyor feed
Friction Fire Improper
Belt sway
8 2 2 32 Lubricate the
rotating parts
Skip car rope
for charging
injury Overloading Weighing 3 4 1 12 Calibrate load
Cold blast
Flow pressure
Rupture in
Failure of
Flow meters 8 1 2 16 Interlock
Hot blast
Stove shell
Fire &
Thermocouple 9 1 2 18 Periodic
Blast furnace
gas injection
Co Poisoning Over
Detectors 10 2 2 40 Provide
detectors with
alarm system
Fire &
Detectors 10 2 2 40 Provide
detectors with
alarm system
Cooling water
supply pump
Pump failure Explosion No power
power supply
10 4 2 80 Check the fuel
level of diesel
Tapping hose Oxygen hose
Fire Ageing Reliable
8 4 4 128 Change hose
Hot metal
lifting by crane
Hot metal
ladle falls
Overloading Safe working
load are marked
9 3 2 54 Interlocks
with alarm
Gas cleaning
filter bags
Filter bags
Improper gas
4 3 3 36 Regular
Lancing hose Tuyere
Burns Ageing Reliable
5 4 4 80 Check defects
before use
Water spraying
Pin holes Gas
Monitors 7 3 1 21 Check the
water level for
every 5
Butterfly valve
to regulate flow
Co poisoning Dust Air line
9 3 2 54 Periodic
Steam injection Pipelines
Burns Excess
Line inspection 7 2 3 42 Display
4.3 Risk Priority Graph
The following graph chart-1 shows the top five risk priority
number values.
Chart-1.RPN graph
Higher value of risk priority number was obtained for tapping
process. Detailed safety audit should be conducted on the
cast house to reduce accident rates. Proper housekeeping,
awareness should be given to the workers involving in cast
house activities. Barriers, shields should be arranged to
prevent cast house workers from molten metal sparks. Proper
training should be given to all operators and workers; this
will reduce risk priority number value.
The present work deals with the basic process of blast
furnace. With the help of FMEA a risk assessment tool all
possible failure modes are evaluated with their severity value
and the causes are calculated with occurrence value. Finally,
the RPN for each process was calculated and the preventive
control measure were suggested for each and every process,
IJRET: International Journal of Research in Engineering and Technology eISSN: 2319-1163 | pISSN: 2321-7308
Volume: 03 Special Issue: 11 | NCAMESHE – 2014 | Jun-2014, Available @ http://www.ijret.org 31
the safety precaution suggested in this paper would help to
reduce the down time failure and its effects.
[1]. Narayanagounder,s and Gurusami,k 2009- A New
Approach for Prioritization of Failure Modes in Design
FMEA using ANOVA, Journal of word Academy of science
(Engineering and Technology), Vol.49,2009,pp.524-532.
[2]. Hughes, N., Chou, E, Price, C.J and Lee, M.1999,
Automating mechanical FMEA using functional models,
Proceeding of the Twelfth international Florida AI Research
Society Conference, (AAAI Press, Melno, CA), pp.394-398.
[3]. Shirouyehzad, H, Badakhsian, M, Dabestani, R,
Panjehfoulan, H. 2010 FMEA Analysis for Identification
and Control of Failure preferences in ERP Implementation,
The journal of Mathematics and Computer Science, Vol.1
No.4 (2010) pp.366-376.
[4]. Arabian-Hoseynabadi, H, Oraee, H, Tavner, P.j. 2010
Failure Modes and Effect Analysis (FMEA) for Wind
Turbines, International Journal of electrical power and
energy system.32 (7), pp-817-824.
[5]. Arun chauhan, Raj Kamal Malik, Gaurav Sharma,
Performance Evaluation of casting Industry by FMEA,
International Journal of Mechanical Engineering Application
Research. Vol 02, issue; pp.113-121.
[6]. Valdimir Popovic, Branko Vasic, Miloj Petrotic, 2010,
The possibility of FMEA method Improvement and its
Implementation into Bus Life Cycle, Journal of Mechanical
engineering 56 (2010) 3.pp.1-7.
[7]. Rhee, s. and k.ishli, Life Cost- Based FMEA Using
Empirical Data, Proceeding of the ASME 2003 DETC/CIE
Conference, Illinios, pp.48-50.
R. Suresh is a PG scholar in the
department of Mechanical Engineering,
Knowledge Institute of Technology. He
holds a degree in Electrical and
Electronics Engineering. His are of
specialization is Industrial safety
M. Sathyanathan is an associate
professor of Mechanical Engineering,
knowledge Institute of Technology. He
is a member of MISTE. He has about 10
year of teaching experience, He His area
of specialization is Manufacturing
Dr. K. Visagavel is a professor and Head
of Mechanical Engineering, Knowledge
Institute of Technology. He presented
many research papers in various
international journals and conference.
His area of specialization is Thermal
M. Rajesh Kumar received the B.E.
degree in Electronics and
Communication Engineering He is
currently pursuing the M.E. degree in
Industrial Safety Engineering at
Knowledge Institute of Technology,
Salem, Tamil Nadu, India

Place your order
(550 words)

Approximate price: $22

Calculate the price of your order

550 words
We'll send you the first draft for approval by September 11, 2018 at 10:52 AM
Total price:
The price is based on these factors:
Academic level
Number of pages
Basic features
  • Free title page and bibliography
  • Unlimited revisions
  • Plagiarism-free guarantee
  • Money-back guarantee
  • 24/7 support
On-demand options
  • Writer’s samples
  • Part-by-part delivery
  • Overnight delivery
  • Copies of used sources
  • Expert Proofreading
Paper format
  • 275 words per page
  • 12 pt Arial/Times New Roman
  • Double line spacing
  • Any citation style (APA, MLA, Chicago/Turabian, Harvard)

Our guarantees

Delivering a high-quality product at a reasonable price is not enough anymore.
That’s why we have developed 5 beneficial guarantees that will make your experience with our service enjoyable, easy, and safe.

Money-back guarantee

You have to be 100% sure of the quality of your product to give a money-back guarantee. This describes us perfectly. Make sure that this guarantee is totally transparent.

Read more

Zero-plagiarism guarantee

Each paper is composed from scratch, according to your instructions. It is then checked by our plagiarism-detection software. There is no gap where plagiarism could squeeze in.

Read more

Free-revision policy

Thanks to our free revisions, there is no way for you to be unsatisfied. We will work on your paper until you are completely happy with the result.

Read more

Privacy policy

Your email is safe, as we store it according to international data protection rules. Your bank details are secure, as we use only reliable payment systems.

Read more

Fair-cooperation guarantee

By sending us your money, you buy the service we provide. Check out our terms and conditions if you prefer business talks to be laid out in official language.

Read more
Need assignment help? You can contact our live agent via WhatsApp using +1 718 717 2861

Feel free to ask questions, clarifications, or discounts available when placing an order.
  +1 718 717 2861           + 44 161 818 7126           [email protected]
  +1 718 717 2861         [email protected]