ASCI 638 Assignment 7-6

Operational Risk Management

The object of this document to review Operational Risk Management (ORM) as applies to small Unmanned Aircraft Systems (sUAS).  ORM as defined by the FAA is a “…decision making tool to systemically help identify operational risks and benefits and determine the best course of action for any given situation” (FAA, 2000, pg. 15-2).  In simpler terms it is a structured method to mitigate operational risk.  ORM can be applied to any industry or field of endeavor from banking to combat operations but for this discussion we will relate ORM to the safe operation of the MLB Super Bat DA-50.

The MLB Super Bat DA-50 is a commercially available sUAS marketed as an ideal tool for surveillance, monitoring, force protection and agricultural and wildlife uses (MLB Company, 2015).  A slightly smaller and less capable version, the Bat, was used by the Washington State Department of Transportation as a test mule to assess the viability of UAS for long term UAs use in road and avalanche control, including the dropping of explosives to trigger controlled avalanches (McCormack, 2008).  The Super Bat DA-50 is bungee launched and lands autonomously in a 100 by 40 meter area and can safely operate in winds of up to25 knots.  Various sensor packages are available dependent upon need.  An overview of characteristics is presented below in Table 1.

Table 1.  MLB Super Bat DA-50 characteristics.

Wing span	8.5 feet	Payload	6 lbs.
Fuel capacity	11.5 lbs.	Data link	2.4 GHZ video downlink, 900 MHZ spread spectrum 2 way modem w/ optional long range data link
Endurance	10 hours	Speed range	40-70 knots
Fuel range	450 miles	Operational ceiling	15,000 feet

Table 1  

         Prior to reviewing the ORM process several basic terms must be defined

 (FAA, 2000):

·      Risk: The likelihood of loss from exposure to a hazard.

·      Identified risk:  Risk that has been determined to exist.

·      Unidentified risk:  Risk of which the participants in activity are unaware or risk that is otherwise unidentified.

·      Total risk:  A combination of identified and unidentified risk.

·      Acceptable risk:  The likelihood of loss deemed tolerable after implementation of controls.

·      Unacceptable risk:  Risk that must be eliminated and is not deemed tolerable.

·      Residual risk:  The level of risk remaining after implementation of controls.

  The ORM process utilizes several tools in a logical sequence beginning with the preliminary hazard list/analysis (PHL/A).  The methodology listed below was obtained from Introduction to Unmanned Aircraft Systems, chapter 8  (Shappee, 2012).  The PHL is a tool used to catalog and categorize hazards associated with the task at hand.  Additionally the PHL/A will list mitigating actions and be used to assign a numerical identifier to the level of risk.  While there is no set format for a PHL/A several basic categories should be included; a tracking number used for rapid identification, a description of the hazard, mitigation steps, the probability of the hazard occurring, and the risk level both before and after mitigation.  MIL-STD-882D/E, refer to appendix A, provides a method of identifying and quantifying these categories.  Figure 1 is a typical PHL/A.

Figure 1.  Typical PHL/A form.  Note.  Image retrieved from Introduction to unmanned aircraft systems, p. 128, by E. Shappee, 2012, Boca Raton: CRC Press

The PHL/A shown in figure 2 has been filled out with five significant hazards that are possible with the sUAS operation described.  Each is categorized in accordance with MIL-STD-882D/E and mitigation actions described.  The residual risk factor is then determined and documented.  This tool enables decision makers to reduce the possibility of injury, loss of asset, and damage to public and private property prior to the aircraft ever being launched.  Note that each mitigation action receives its’ own hazard number, this allows for easier tracking.  The pro-active methodology ensures the greatest likelihood for safe mission accomplishment. 

Figure 2.  PHL/A with risks categorized and noted as required.

The next step is an operational hazard review and analysis (OHR&A).  OHR&A provides a method to continually track, evaluate, and monitor hazards throughout the lifecycle of the task and is useful tool for providing feedback relating to the effectiveness of mitigation efforts and methods (Shappee, 2012).  A typical OHR&A form is shown in figure 2.  As with the PHL/A no set standard exists for the form however they generally contain the same information with the exception of the OHR&A having a category for action review.  As with the PHL/A, MIL-STD-882D/E provides a useful matrix of category definitions and ratings.  It should be noted that any change to the system should drive a new review and an update to the PHL/A and OHR&A (Shappee, 2012).

Upon operational evaluation and testing the OHR&A is used to track the effectiveness of mitigating actions.  Actions that are successfully mitigated should be monitored and actions that are not successfully mitigated will be reviewed and updated as needed.  Occasionally during testing or operations additional hazards may present themselves, these hazards should be added to the OHR&A.

Figure 3.  Typical OHR&A form.  Note.  Image retrieved from Introduction to unmanned aircraft systems, p. 128, by E. Shappee, 2012, Boca Raton: CRC Press

Figure 4.  OHR&A with updates. 

            The last major step in ORM is to develop a risk assessment tool that is used to aid in the decision making process relative to the safe conduct of the mission or task.  The risk assessment tool can be complicated or simple and should be able to be tailored to the specific operation and equipment.  Using the tool shown in Figure 3 identify the mission type and go down the column on the left assessing each category, place the numerical score in the column on the far left and upon completing the assessment compare the total score to the categories listed on the bottom of the form.  This will provide the operator with a quantifiable determination of the level of risk involved for the particular mission, a decision can then be as to the feasibility, form a safety perspective, of the mission.  The MLB Super Bat DA-50s capabilities, and specifications meld ideally with the risk assessment tool presented in figure 3 and this would be a very suitable tool for its’ intended purpose. 

            In this case, the pilot of the sUAS will utilize the risk assessment tool prior to each flight and using the procedures described above categories the safety viability of the proposed mission.  For our hypothetical scenario we will assume a support mission, clear weather with no mitigating factors, line of sight observation, winds less than 10 knots, all pilots current and no modifications to the aircraft.  As this is a group 2 sUAS the final score would be 23 indicating a low risk level categorization, consequently the flight can be conducted with a low risk level.  Changing the responses to a few of the categories can affect the decision making process, for example if the pilot is not current, the tool would present a no fly scenario.  The benefit of this method is the aircrew and other decision makers are presented with a quantifiable risk assessment which relies on fundamental categories and agreed upon standards to assist in a critical decision making process.

Figure 3.  sUAS risk assessment tool.  Note.  Image retrieved from Introduction to unmanned aircraft systems, p. 128, by E. Shappee, 2012, Boca Raton: CRC Press

           

.

References

FAA.  (2000, December 30).  Operational risk management.  Retrieved from https://www.faa.gov/regulations_policies/handbooks_manuals/aviation/risk_management/ss_handbook/media/Chap15_1200.pdf

McCormack, E.  (2008, June).  The use of small unmanned aircraft by the Washington State Department fo Transporation.  Retrieved from http://www.wsdot.wa.gov/research/reports/fullreports/703.1.pdf

MLB Company.  (2015).  Products: Super Bat DA-50.  Retrieved from

http://mlbuav.com/products-super-bat-da-50/

Shappee, E. (2012).  Safety Assessments in R. Barnhart, S. Hottman, D. Marshall, & E. Shappee (Eds.), Introduction to Unmanned Aircraft Systems (pp. 123-135).  Retrieved from http://site.ebrary.com.ezproxy.libproxy.db.erau.edu/lib/erau/reader.action?docID=

                                                             Appendix A

MIL-STD-882D/E severity and probability charts