Helicopter Terrain Awareness Warning System (HTAWS) - What Next?HTAWS began to be fitted to the newer generation of helicopters, such as the S92, H225 and AW139 when they were introduced into the market. At the time, the principle HTAWS available was the Honeywell Enhanced Ground Proximity Warning System (EGPWS) MKXXII. The thinking behind the fitting of HTAWS was that rotary wing operations could benefit from the use of this equipment that had been so successful in fixed wing operations.
However, a direct read-across is probably not valid as aeroplanes operate from airfields where the local terrain in well mapped in the TAWS database and so the Ground Proximity element can be desensitised to reduce false alerts. The FAA saw a need for improved terrain warning for helicopters, in particular for HEMS operations where a number of well publicised accidents occurred in the USA. I was a member of RTCA Special Committee 212 which had the mandate to produce MOPS for a Class B HTAWS, i.e. a system without a radio altimeter input which derived altitude information from GPS: DO 309 was the resulting standard. For offshore operations, a different approach was needed to warn crews of an unsafe descent rate or proximity to the surface as accident had occurred which had not been, or in the case of legacy helicopters would not have been, prevented by the extant HTAWS warning envelopes. A UK CAA group was formed using industry funding to further enhance the capabilities of HTAWS for offshore operations. As well as Flight Data Monitoring (FDM) and accident data, we had some AAIB recommendations to consider. UK AAIB issued a number of Safety Recommendations regarding H-TAWS:
We were ready to finalise our recommendation in 2013 when the accident to G-WNSB occurred during at approach to Sumburgh airport. During our analysis we confirmed that our new envelopes would not have provided a sufficient alert to the crew and so further analysis was conducted. During this additional analysis we obtained FDM data on several serious incidents where a loss of airspeed had been the precursor to a loss of control. Using data from over 100,000 approaches on various helicopter types we produced a new warning envelope which alerts the crew to a lack of power applied to maintain airspeed. In early 2017 the CAA issued CAP 1538 and CAP 1519 which document the work undertaken and the proposed offshore warning envelopes. CAP1538 - http://publicapps.caa.co.uk/modalapplication.aspx?appid=11&mode=detail&id=7887 CAP1519 - https://publicapps.caa.co.uk/modalapplication.aspx?appid=11&mode=detail&id=7886 HeliOffshore has been supportive in aligning the equipment and airframe manufactures, as well as the operators and oil companies. It is intended that the first aircraft to be fitted with the new certified warning envelopes will be in early 2018. Of course, generating the alerts is only part of the story, as the crews must also perceive the warnings and react appropriately. For example, the incident where G-WIWI nearly came to grief during a night approach to a private house at Peasmarsh in Sussex. Phase 2 of this project, funded by HeliOffshore, is looking at the optimum way to warn the crew. This work has been undertaken by experts from Cranfield University and Royal Holloway University and should report soon. So, what is next? EASA is likely to start a EUROCAE group to address the issues raised and the CAA recommendations – we are meeting EASA on the 26th October to discuss the next steps.
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How Knowledge Can Drive Safety ImprovementsHelicopter operators are increasingly data rich, but how much of it is producing value to safety, efficiency and effectiveness? Aeroplane manufactures and airlines have been using their data to improve efficiency, reduce costs and have attempted to improve the passenger experience for a while. How can the major helicopter operators catch-up and what are the benefits? Whilst the offshore helicopter industry has pioneered the use of Health and Usage Monitoring System (HUMS), other areas have not advanced as far. Too often we see that data is held in silos without being readily accessible to other systems. So what are these system silos? Apart from HUMS, operators will have a safety reporting system, engineering and supply chain system such as SAP, aircraft Tech Log data, Flight Data Monitoring, flight planning tools, crewing and rostering records. Measuring drives behaviour as it indicates where problems exist. What operators lack is a mechanism to find the Rumsfeldian “unknown unknowns” and the unusual patterns or outliers in their data. Flight Data Monitoring (FDM) is an example of a data rich system which is mainly used for compliance and yet it has the capability to do so much more. As well as having fixed thresholds to identify errors in the flight profile, the data can be used to identify “Normality” and anything outside those parameters might be an issue. For example, are the outliers evenly distributed across the operations or are they more prevalent at certain locations, at certain times of day, on certain aircraft or with certain crews? Using this methodology, issues with approaches to problematic locations, fatigue issues, with certain aircraft types or with training can be identified for further investigation by specialists. An example of using FDM data to identify normality is an ongoing UK CAA project to define enhanced HTAWS warning envelopes for offshore operations[1] . Using FDM as a compliance tool tends to treat each event as a singular event with little widespread learning. Further analysis of the FDM data can be used to map turbulence around a helideck. Mapping the turbulence environment will provide a feedback loop to the Helideck Landing Limitations and CFD/wind tunnel modelling done when the installation or ship was commissioned. The military spend large amounts of money on Ship Helicopter Operating Limitations (SHOL) trials, which are by necessity a snap-shot of conditions over the period of the trial. Using FDM data provides the equivalent of an ongoing SHOL which captures all conditions over the life of the vessel with minimal additional cost. FDM can be used to record systems faults or inappropriate combinations of autopilot modes. One operator recorded autopilot faults and found that crews had only reported around 10% of the dropouts, indicating that they had normalised the issue. By comparing recorded faults to the safety reports submitted about those issues gives a good indication of the reporting culture in that organisation. The reporting rate versus events captured in FDM should be a KPI for every operator. Measuring the way that autopilot modes are used can indicate the compliance rate with SOPs, which has been a factor in both aeroplane and helicopter automation related accidents. By additional analysis of the FDM data the actual risks the operations encounter can be quantified, providing a feedback loop to the organisation’s Safety Management System (SMS). In the example of the autopilot faults above, the actual failure rate was many times higher than that assumed in the Predictive Risk Assessment and so the true risk to the organisation was much higher than initially assessed and needed action. Operational data provides a means to optimise operations. How many operators measure their operations against KPIs such as seat cost per mile? With the offshore helicopter market under such tight cost pressures are they sure that their aircraft are being operated in an efficient and effective way? By optimising the departure times of the flights, cruise altitude and airspeed savings can be made. Some fleets such as the S92 have a large variation in their Declared Operating Mass of greater than a 1,000 lbs between old aircraft and the newer heavier versions. Are the lighter aircraft being used on the longer flights where they can maximise the client payload? Tech Log and Supply Chain data can be used for component reliability modelling. Most operators leave it to the OEMs, but smart customers will be able to resolve issues quicker if they identify problems at an early stage rather than sitting back and waiting for OEM action. Part M requires organisations to “assign responsibility for co-ordinating action on airworthiness occurrences and for initiating any necessary further investigation and follow-up activity to a suitably qualified person with clearly defined authority and status”, but how many do it effectively with no room for improvement? Safety Reports can provide a wealth of information, but how well are they analysed? Tools such as Cluster Analysis can draw out areas for further investigation by specialists. Of course there is a worry that Big Data = Big Cost, but this need not be the case. The additional analyses discussed above are not mandated and are about gaining extra insight into the company data, it does not have to run in real-time or be safety critical. Start small and gradually build up a capability. After all simple Machine Learning and Text Mining can be done in Excel, Open Source tools in languages like Python can also be extremely powerful and yet low cost, running on a stand-alone laptop with analyses being run every few weeks; after all the hidden trends are not likely to change quickly. Virtually all standard systems can export data as flat files in formats such as csv which Open Source tools exploit. However, any company wanting to start this process will have to work with their IT Department, where the first barrier to innovation is likely to be met. Large IT Departments love “Enterprise Systems” which allegedly reduce risk to the business, whilst in reality they initially reduce risk to the IT Department as they can buy in a system and contractors to do the work. Start the analysis as a trial using free tools and when the benefits are seen, by all means upgrade to a full Business Intelligence system, but it is not necessary to spend a lot at the outset. Of course smarter use of data is not a silver bullet. However, improved insight of what data is telling a company should help the specialist improve their areas, where complex patterns are often missed due to workload or insufficient visibility of the underlying trends. British Cycling has dominated the last few Olympic Games by the “aggregation of marginal gains”. If everything you do is improved by 1% then those small gains add up to remarkable improvement (and lots of gold medals). So try breaking down those data silos and aggregate the gains that will come from improved information and insight. [1] http://publicapps.caa.co.uk/modalapplication.aspx catid=1&pagetype=65&appid=11&mode=detail&id=7887 |
AuthorSome reflections on the aviation industry by Mark Prior. I will aim to produce regular blogs covering areas where we think our company can make a real difference for our clients. Archives
May 2024
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