Background

A realistic goal for underground 

mines trying to reduce the incidence 

of miner injuries associated with 

roof falls is to assess the conditions 

that pose a roof fall risk. If mine 

operators properly assess roof fall 

hazards, they can better reduce roof 

fall risks with appropriate engineering and administrative controls. Any 

methodology that helps attain this 

goal can be thought of as a roof fall 

risk-assessment method. An effective roof fall risk-assessment method 

includes the ability to observe variable roof conditions and assess how much these conditions represent the potential for a roof fall capable of 

injuring miners. This methodology should rank the risks 

associated with varying conditions, should be reasonably 

reproducible and should clearly indicate roof fall risk to 

all mine personnel responsible for the design, approval 

or installation of controls that either stabilize the roof 

or lessen the exposure to roof falls. This paper focuses 

on the risk-assessment issues, leaving the roof fall riskmanagement process, where controls are designed and 

used to reduce risk, to another discussion. 

One of the most important safety issues at any mining 

site is the need to identify the location and nature of roof 

fall hazards. The mining law requires that roof falls be 

reported to enforcement agencies by Form 7000-1. Roof 

fall locations are to be displayed on mine maps and made 

available to miners or their representatives. The Code of 

Federal Regulations, Title 30 Part 50 Section 2, defines a 

reportable roof fall as “an unplanned roof fall at or above 

the anchorage horizon in active workings where roof 

Methods for determining roof fall risk 

in underground mines

bolts are in use” or as “an unplanned 

roof or rib fall in inactive workings 

that impairs ventilation or impedes 

passage” (Anon, 2005). In general, 

roof fall reporting requirements 

consist of time and date, location information, mining method involved, 

equipment involved and a narrative 

that fully describes the conditions 

contributing to the roof fall and that 

also quantifies the damage. The standard also requires the operator to 

take steps to prevent a recurrence. 

The mining law, however, does not 

specifically require that information 

about hazards that could cause roof falls be displayed on 

mine maps or communicated to mine workers. 

Why is a roof fall risk-assessment method 

important for improving miner safety? 

The potential for roof falls in underground mines is 

a significant danger for mine workers. In 2006, 10 fatal 

ground fall injuries occurred (Table 1). Also, during the 

10-year period from 1996 through 2005, 7,738 miners 

were injured from roof falls in underground coal, metal, 

nonmetal and stone mines (MSHA, 2005). Coal mines 

had the highest rate, 1.75 roof fall injuries per 200,000 

hours worked underground (Table 2). While this rate 

dropped over this period, there were still 581 recorded 

roof fall injuries in 2005, with many classified as severe. 

Fatal injury trends from 1996 to 2005 were equally troubling, with 100 roof fall fatalities. While coal mining had 

the highest number with 82, metal mining had the highest rate with 0.03 fatalities per 100,000 miners (Table 1). 

These statistics attest to the seriousness of this safety 

issue, although roof fall injuries decreased from 1.71 in 

1996 to 1.19 in 2005 per 200,000 hours worked (Table 

2). Clearly, progress in miner safety has been made, but 

further improvement is possible. It is imperative that new 

safety techniques and methodologies continue to be developed, so this downward trend in roof fall injures can 

be maintained. 

Most safety decisions in the U.S. mining industry are 

guided by company policy and the requirements of state 

and federal regulations. These decisions have been successful in reducing roof fall injuries (Table 2). For this 

study, the author’s underlying assumption is that incorporating risk-assessment and risk-management methods to 

the existing decision-making process will help to further 

reduce miner injury rates.

A. IANNACCHIONE, L. PROSSER, 

G. ESTERHUIZEN AND T. BAJPAYEE 

A. Iannacchione, member SME, L. Prosser, G. Esterhuizen, 

member SME, and T. Bajpayee, member SME, are principal 

research engineer, research scientist, senior research fellow and 

lead reasearch engineer, respectively, with the National Institute for 

Occupational Safety and Health (NIOSH), Pittsburgh Research Laboratory, Pittsburgh, PA. Paper number TP-06-047. Original manuscript 

submitted online Dec. 2006 and accepted for publication June 2007. 

Discussion of this peer-reviewed and approved paper is invited and 

must be submitted to SME Publications Dept. prior to Feb. 29, 2008.

Abstract

Reducing the number of roof fall injuries is a goal of the 

NIOSH mine safety research program. Central to this effort is the development of assessment techniques to help 

identify the nature of the risks associated with working 

under potentially hazardous roof conditions. This paper 

discusses a method to determine the roof fall risk using 

a qualitative risk-analysis technique. The ability to determine roof fall risk has been a long-standing goal of safety 

professionals and could provide the kind of information 

needed by on-site personnel responsible for worker safety 

to mitigate roof fall injuries.
What is the state-of-practice for minerals 

industry risk assessment?

The International Organization for Standardization 

(ISO) and the American National Standards Institute 

(ANSI) produce standards and guidelines that define 

the use of risk-assessment and risk-management methods. When applied to a particular industry, the issues 

unique to that industry require special approaches. For 

example, the environmental and health sciences have 

long used risk-assessment and risk-management methods to identify the highest environmental and occupational health and safety risks and to develop controls 

specific to their operational and regulatory environments (National Research Council, 1983, 1994, 2006).

Risk-assessment and risk-management methods for 

the mining industry are more prevalent in countries 

with safety standards that emphasize duty-of-care, i.e., 

Australia, Canada, United Kingdom and South Africa, 

rather than the prescriptive health 

and safety regulations, i.e., the United 

States. Duty-of-care in these countries 

is defined in legislation that requires 

employers, suppliers and employees 

to provide, design for and adhere 

to reasonable activities that ensure 

workers are cared for. In Australia, an 

ISO has been specifically developed 

(Anon, 2004) to enable organizations 

to implement environmental management systems (EMS) for continuous 

improvement in their operations. 

In the mid-1990s, Australia’s mineral industry became heavily involved 

in risk-management methods that typically consisting of structured, teambased exercises to review potential 

problems carefully with new or existing mining methods, new equipment or other operational problems (Joy, 

2001). Joy estimates that at least 80 percent of all Australian coal mines have performed some form of structured, team-based risk assessment/risk management. 

Tools used in these exercises include HAZOP (Hazard 

and Operability Analyses), FMECA (Failure Modes, 

Effects and Criticality Analysis), WRAC (Workplace 

Risk Assessment and Control) and the BTA (Bow Tie 

Analysis). All of these tools and techniques are defined 

in a framework by Joy (2006) to explain the management of risk in the minerals industry. Lastly, the Minerals Industry Safety and Health Center (MISHC) Web 

site is an excellent source for information on Australia’s 

diverse risk-assessment/risk-management approaches 

(www.mishc.up.edu.au). 

Examples of risk assessment applied 

to ground control issues

In the early 1990s, the United Kingdom (UK) developed a code of practice (now referred to as Industry 

Guidance) for rock bolt use as roadway supports that 

included geotechnical assessment, initial design, design 

verification and routine monitoring (Arthur et al., 1998). 

Cartwright and Bowler (1999) provided a UK example 

of a procedure to assess the risk associated with potential failure or overloading of rock-bolt support systems. 

In the mid-1990s, South African mines developed codes 

of practice to combat rock fall and rock burst accidents, 

as required by its 1996 Mine Health and Safety Act 

(Gudmanz, 1998). Swart and Joughin (1998) discussed 

the importance of rock engineering in developing this 

code of practice. Van Wijk et al. (2002) developed a riskassessment method for use in South African coal mines. 

This risk-assessment method aims to optimize resources 

and focuses attention on the areas where it is most required. Lind (2005) demonstrated an integrated riskmanagement method that required a basic assessment 

of physical parameters such as coal seam characteristics, 

depth below surface and mining conditions.

The Minerals Council of Australia (MCA) helped 

produce a national guideline for the management of 

roof fall risks in underground metalliferous mines 

(MOSHAB, 1997). Potvin and Nedin (2003) published 

a “Reference Manual” in support of the MCA guidelines meant as a collection of techniques and examples 

FIGURE 1

Flow diagram depicting the generalized structure of roof 

fall risk assessment activities and its relation to risk 

management activities.

Date Mine Company State

1/10/06 #1 Maverick KY

1/29/06 Aberdeen Andalex UT

2/1/06 #18 Tunnel Long Branch WV

2/16/06 HZ4-1 Perry County KY

3/29/06 #4 Jim Walter AL

4/20/06 #1 Tri Star KY

10/6/06 #2 D & R KY

10/12/06 #7 Jim Walter AL

10/20/06 Whitetail 

 Kittanning Alpha Natural Resources WV

12/17/06 Prime #1 Dana Mining WV

Table 1

Fatal roof fall injuries in underground coal mines during 2006.
of good roof control practices.

Roof fall hazard-assessment 

techniques

Risk-assessment methods provide 

a systematic approach to identifying 

and characterizing risks, especially 

those associated with low-probability, 

high-consequence events such as roof 

falls. The first step in utilizing a roof 

fall risk-assessment method requires 

identification of the potential roof 

fall hazards. Because local geologic, 

stress and mining conditions interact to create varying roof conditions, 

commodity-specific or activity-based 

hazard-assessment techniques and associated risk-analysis techniques are 

needed to locate potential risk within workplaces throughout the mine. 

Many hazard-assessment techniques 

generally can be classified into one 

of the following three groups: hazard 

maps, rock-mass classification systems 

and monitoring data. While all three 

techniques are useful in hazard assessment, they have had only limited 

application when applied to roof fall 

risk assessment.

To help improve the link between hazard assessment 

and risk assessment, NIOSH developed a tool called the 

roof fall risk index (RFRI) to systematically identify 

roof fall hazards. The RFRI is specifically developed for 

underground stone mine and is mentioned here as an 

example that could be adapted to mining conditions. The 

RFRI focuses on the character and intensity of defects 

associated with specific roof conditions and attempts 

to incorporate some of the characteristics discussed 

in the other hazard assessment techniques (Iannacchione et al., 2006; 

Iannacchione et al., 

2007). The defects 

measured within the 

RFRI can be caused 

by a wide range of 

local geologic, mining and stress factors and are equated 

directly to changing 

roof conditions causing roof fall hazards. 

A significant range 

of defects found at 

underground stone 

mines are classified 

into 10 categories 

(known as defect 

categories), each of 

which is assigned 

an assessment value 

ranging from 1 to 

5, with the numerical value increasing 

with the severity of 

the defects. To calculate the RFRI, one must determine 

the assessment value for each defect category, multiply 

by an assigned weight (either 1 or 2), add all category 

values together and multiply by 1.11. Ideally, values 

approaching zero represent safer roof conditions, while 

an RFRI approaching 100 represents a serious roof fall 

hazard.

The RFRI is a hazard-assessment technique that 

can be used as both a training tool and a communication tool. This technique requires that roof fall hazards 

be mapped and the spatial distribution within the unFIGURE 2

(a) RFRI values for the 226 measurement area that comprised the study area 

and (b) histogram of RFRI frequency.

Coal Metal Nonmetal Stone Total

 Injury Fatal Injury Fatal Injury Fatal Injury Fatal Injury Fata

Year rate rate rate rate rate rate rate rate rate rate

1996 1.8 0.029 2.08 0.016 0.36 0.0 0.58 0.116 1.71 0.028

1997 1.9 0.02 2.12 0.032 0.43 0.0 0.5 0.055 1.8 0.022

1998 2.03 0.033 2.07 0.052 0.44 0.0 0.52 0.0 1.89 0.032

1999 1.89 0.031 1.82 0.061 0.59 0.0 0.92 0.051 1.77 0.033

2000 1.98 0.011 1.63 0.023 0.4 0.0 0.45 0.0 1.79 0.011

2001 1.79 0.03 1.01 0.09 0.31 0.0 0.52 0.0 1.58 0.032

2002 1.75 0.011 0.94 0.0 0.31 0.0 0.59 0.0 1.55 0.009

2003 1.51 0.009 0.86 0.0 0.3 0.0 0.43 0.0 1.34 0.007

2004 1.5 0.008 0.68 0.0 0.25 0.0 0.31 0.0 1.31 0.007

2005 1.34 0.023 0.81 0.0 0.33 0.0 0.24 0.0 1.19 0.019

Total 1.75 0.021 1.51 0.03 0.38 0.0 0.5 0.021 1.6 0.021

Injury rate = Roof fall injuries (Degree of Incident, Class 1-6) per 200,000 hours worked underground.

Fatal rate = Roof fall fatalities per 100,000 miners.

Table 2

Roof fall injury and fatality rates over then 10-year period from 1996 to 2005 for 

underground mines.
derground workplace determined. The RFRI strives 

to assess roof conditions over large, continuous areas, 

producing a comprehensive assessment of changing 

roof conditions than was previously possible. 

Moving from hazard assessment 

to risk assessment

Hazard assessment in conjunction with the mine’s 

individual roof control plans can be thought of as an implicit form of risk assessment. Ideally, a hazard-assessment technique should be capable of ranking the various 

hazards and communicating these hazards to the persons 

or groups in need of this information. The outcome of this 

process can aid in establishing minimum roof support 

standards for a mining operation where a general class of 

hazards is being addressed. The focus of this roof fall riskassessment approach is on identifying areas of highest 

risk so that additional controls can be applied. 

These controls can range from additional 

monitoring to supplemental roof support.

Identifying areas of highest roof fall risk is 

accomplished through standard risk-analysis 

methods, where the probability of occurrence 

and its consequence are determined using

Risk = Probability of occurrence x Consequence (1)

Of the many different risk-assessment 

methods discussed in the literature, only a few 

risk analysis techniques apply to the roof fall 

problem. For example, when determining the 

probability of occurrence, two very different 

approaches are available: qualitative assessment and quantitative assessment. This paper 

focuses on a qualitative risk-analysis technique 

using a risk matrix as shown in Table 3. 

For a roof fall event, the Probability of occurrence term in Eq. (1) consists of two factors: 

the probability of a roof fall occurring and the 

potential for a miner being injured by this roof 

fall. Roof fall probability in this analysis can be 

estimated with the RFRI, while injury 

potential is estimated by the miner’s 

exposure to hazardous roof conditions. 

Miner exposure is dependent on the 

frequency of an activity within an area 

versus the percentage of the workforce involved in that activity (Table 

4). The activity frequency can range 

from many times per shift to once per 

month, while the percentage of the 

workforce involved in that activity can 

range from many (>50 percent) to few 

(<5 percent). Roof fall probability and 

miner exposure can be determined for 

all areas of the mine accessible by the 

miner. 

The consequence term in the risk 

equation typically refers to the severity of the event. When a miner is injured from a roof fall, some medical 

attention is required. For example, of 

the 7,738 miners injured from roof falls 

between 1996 and 2005, 1.3 percent resulted in a fatality, the rest required medical attention 

(Table 2). For most of the nonfatal injuries, the rock that 

struck the miner was probably relatively small. Because 

it is beyond the author’s abilities to forecast the size of 

a roof fall, it was assumed that any roof fall could seriously injure a miner. Therefore, the consequence should 

always be considered severe and assigned a unit value of 

1. This effectively takes away the consequence term from 

this analysis. Therefore, a more appropriate definition for 

roof fall risk is

Roof fall risk = Roof fall probability x Miner exposure 

to roof falls (2)

Qualitative approach to measure roof fall risk

A qualitative approach allows for estimations of roof 

fall probability and miner exposure. Roof fall probabil-

 Probability of occurrence

Consquences High value Medium value Low value

High value High risk 

Medium value Moderate risk 

Low value Low risk

Table 3

A generalized risk matrix used in many qualitative risk-analysis 

techniques.

 Frequency 

Percent of Many times/shift 1/day 1/week 1/month 

workforce 

Most >50% A A B C

Many – 30% A B C D

Several – 10% B C D E

Few <5% C D E E

Table 4

Exposure of miners within a particular work area.

FIGURE 3

Miner activity (fictional example) and related miner exposure for the 226 measurement areas.
ity can be qualified by calculating the 

RFRI over regions of an underground 

mine and by grouping RFRI values to 

appropriate roof fall probability categories that range from very unlikely 

to very likely. RFRI values approaching 0 represent low defect conditions 

typically associated with stable roof 

conditions and imply a very unlikely 

roof fall probability. Conversely, RFRI 

values approaching 100 represent excessive defect conditions typically associated with unstable roof conditions, 

implying a highly likely roof fall probability. Intermediate RFRI values fall 

into the unlikely, possible and likely 

roof fall probability category.

The other input for calculating roof 

fall risk, miner exposure, requires an 

estimation of miner activity through 

these same measured areas used in the 

RFRI analysis. These estimated parameters are used within a risk matrix 

(Table 5) to assign the relative roof fall 

risk for any accessible area within a 

mine. As roof conditions and patterns 

of miner activity change within a mine, 

roof fall risk changes accordingly. The ultimate utility of 

the risk rankings, shown in Table 5, lies in ones ability to 

identify areas with the highest risk and to design controls 

that mitigate risk in a logical and thoughtful fashion. 

Characteristics of a roof fall 

risk-assessment method

The process to assess risk and implement controls to 

manage risks can be thought of as a series of steps (Fig. 

1). The first step is to recognize and rank defective roof 

conditions within active portions of the mine. By doing 

this, hazards are identified and some attempt can be made 

to rank these hazards from low to high. The next step uses 

a wide variety of risk-analysis techniques to determine 

roof fall probability associated with specific conditions. 

Miner exposure, a key element in assessing risk, is next 

determined by estimating the amount of time miners are 

expected to occupy the different locations within the active underground workings. Combining the probability of 

roof falls with the estimations of miner exposure yields a 

FIGURE 4

(a) Ranked risk for roof fall injuries over the 226 measurement areas comprising 

the study area and (b) histogram of roof fall risk categories. The study area is a 

fictional case presented here as an instructional example.

series of roof fall risk levels tied to changing roof conditions. Because risk can be ranked throughout the mine, 

risk-management methods can be used to determine how 

to mitigate the risk.

Demonstration of a roof fall 

risk-assessment method

The intention of the following example is to detail 

a comprehensive risk-analysis method and to apply it 

to an experience at a mine setting. In a previous paper 

(Iannacchione et al., 2006), the RFRI values at an active 

underground stone mine were calculated and placed on 

a mine map (Fig. 2 (a)). The study area was divided into 

226 measurement areas that ranged in size from that of a 

15 x 15 m (50 x 50 ft) intersection to the 15- to 30-m- (50 

to 100 ft-) long entries between intersections. The RFRI 

frequency distribution is shown in Fig. 2 (b). Roof fall 

probability is implied directly from the RFRI values and 

divided into five categories: very unlikely, unlikely, possible, likely and very likely.

This analysis uses logically assumed miner exposure 

data that replicated a main 

haulage route 

running norths o u t h i n t h e 

center of the section, a secondary 

haulage route 

running along 

t h e w e s t e r n 

portion of the 

section, active 

d e v e l o p m e n t 

faces along the 

southern perimeter of the sec-

 Roof fall probability

Risk 

exposure Highly likely Likely Possible Unlikely Very unlikely

(From Table 5) (RFRI > 50) (RFRI 41 to 50) (RFRI 31 to 40) (RFRI 21 to 30) (RFRI < 21)

A 1 2 4 7 11

B 3 5 8 12 16

C 6 9 13 17 20

D 10 14 18 21 23

E 15 19 22 24 25

Table 5

A risk matrix comparing roof fall probability with miner exposure. The exposure period used for 

this example could range from one to six months.
tion, an idle 

section behind the faces 

and between 

the haulage 

routes, and 

restricted areas to the east 

(Fig. 3). The 

main haulage route in 

a stone mine 

i s t h e a r e a 

o f h i g h e s t 

miner activity, where most of the workforce is in that 

location many times per shift. Therefore, using Table 4, 

an exposure value of A is assigned. The secondary haulage route and the development faces are assigned an 

exposure value of B, because approximately 30 percent 

of the shift workforce is in these areas at least once per 

day. Idle sections away from the haulage routes and the 

development areas are assigned an exposure value of C 

where approximately 10 percent of the shift workforce is 

in these areas once per day. The restricted area, and the 

escapeway that services this section, is assigned the lowest exposure value of E.

It is now possible to use the 5 x 5 risk matrix shown 

in Table 5 to estimate the risk associated with each of the 

226 measurement areas within the study area. Twenty-five 

risk rankings are identified ranging from 1, the highest, 

to 25, the lowest (Table 5). Within these rankings, five 

risk categories are subjectively assigned, ranging from 

high to low (Table 6). Seventy-five percent of the study 

area measurement areas are within the moderate-to-low 

risk categories. A potential correlation between the risk 

ranking and the action taken to manage risk are given 

in Table 6. Clearly, a risk ranking method such as this 

allows the mine operator to focus attention on high-risk 

areas in the main haulage and development entries where 

proactive tactical and strategic controls to mitigate these 

hazardous conditions can be applied. To ensure effective 

implementation of these controls, it is necessary that the 

mine operator strive to: 

• understand how roof falls occur,

• decide how to deal with crucial roof fall warning 

signs,

• develop triggers to action,

• specify what kind of actions are mandatory and who 

is responsible for taking action and

• put decisions in writing along with reasons.

Summary and conclusions

In practice, unstable roof and the risks it presents 

within the underground workplace are often only partially known. Because risk-assessment and risk-management methods rely on hazard recognition practices and 

controls that either reduce the risk of the hazard or lower 

worker exposure, they have the potential to increase roof 

fall hazard recognition efforts and make it possible to 

address the highest risk roof fall hazard. When risks are 

ranked, mine operators have the opportunity to: 

• investigate strategic or tactical controls; 

• monitor the performance of the controls; and 

• modify them as needed, in an iterative process, thus 

continually addressing the highest roof fall risk areas. 

These methods help to rule out the option of doing 

nothing by introducing required actions in certain situations through structured decision-making.

There are four basic steps to the roof fall risk-assessment method used in this paper:

• Recognize and rate defective roof conditions that 

represent roof fall hazards: This is accomplished with 

the RFRI hazard assessment technique.

• Determine the roof fall probability for specific roof 

conditions: This is accomplished using qualitative 

analysis techniques where RFRI values were grouped 

into logical probability categories.

• Evaluate the exposure of miners to roof falls in the 

study area. 

• Rank the roof fall risk for all active workplaces within 

the mine using a risk matrix: Rating or ranking roof 

fall risks helps to identify what areas should be monitored most closely by the mine operators and miners 

alike. It is also critical for prioritizing the areas where 

administrative and/or engineering controls are needed 

most to reduce these risks. 

This paper demonstrates how roof fall risk can be assessed by appropriately designed hazard assessment and 

qualitative risk-analysis techniques. These techniques 

help to rate hazards, rank roof fall risk over a mine property, provide a means to communicate information with 

all levels of the mining operation, track changing conditions as the mine develops, train less-experienced miners 

to recognize hazardous conditions and develop controls/

plans that are the hallmark of a proactive approach to 

mitigate risk to miners. ■

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