Wednesday, 24 August 2016

Modelling the Effects of Maintenance Engineering Errors in Air navigational Aids

Case of Instrument Landing Systems in Kenya

Instrument Landing System (ILS) is a ground-based instrument approach system that provides precision guidance to aircrafts approaching and landing on a runway using combinations of radio signals. The problem of monitoring the ILS signal has been investigated for a number of years. Both experimental and theoretical studies have yielded information about system performance, but little has been done to model effects of maintenance engineering errors in the ILS localizer. The composite signal from the ILS localizer operates in a manner to maintain stable equilibrium by ensuring that its courseline information is in tandem with the runway centerline. However, errors due to drifts in electronic component values have the tendency to destabilize this equilibrium. The bearing of drift errors on parameters of signal quantities and their subsequent effects on lateral courseline information has significant impact on approaching and landing aircrafts. The purpose of this study is to conduct a test experiment based on linear continuous-time state equations and develop models for analyzing ILS localizer maintenance engineering errors. The second purpose is to design a MATLAB tool to be used in predicting the effects of these errors on aircrafts approaching Kenyan airports. It will be ascertained that this study shall contribute in enhancing the design process of instrument flight approach procedures for air traffic control services and thus reducing the number of aircraft accidents that occur within airport zone boundary.

1.1  Background       
As the worldwide air transportation traffic volume grows rapidly, safety in aviation becomes a burning problem over many countries today. Aviation accidents may result in human injury or even death. It influences the reputation and the economy of the air transportation industry of a country. According to Mineata (1997), when the accident rate is applied to the traffic forecast for 2015, the result would be the crashing of an airliner somewhere in the world almost every week.Braithwaite and Faulkner (1998) stated that in order to achieve safety and reduce accident rate, risk must be quantified and balanced with appropriate safety measures.

Accident statistics based on International Civil Aviation Authority (1997-2006) show that 51% of air accidents occur during final approach, landing and take-offs of an aircraft (Kebabjian, 2008). It is indicated that final approach, landing and take-offs are the periods when the flight maximizes usage of Air Navigational Aids (Navaids).  When an aircraft is about to make an approach and landing on an airport during bad weather conditions, there is need to radiate navigational information to carter for lost visibility. Navaids are used for this purpose. One of the Navaids systems used is the Instrument Landing System (ILS).

An ILS is a ground-based instrument approach system that provides precision guidance to an aircraft approaching and landing on a runway, using a combination of radio signals. With reference to Greenwell (2000), ILS consists of two independent sub-systems, one providing lateral guidance (localizer) and the other providing vertical guidance (glide path) to aircrafts approaching a runway. A modulation depth comparison of two radio signal beams radiated strategically from the localizer (LOC) and received by the ILS receiver in the aircraft provides course-line information (runway centre-line) while a similar comparison from the glide path (GP) provides the slope information (inclination angle). Air navigational aids must keep a certain degree of accuracy set by International Civil Aviation Organization (ICAO).  Accuracy standards are enforced by flight inspection organizations which periodically check critical parameters using properly equipped aircrafts to calibrate and certify ILS precision.

ICAO annex 10 (2000) presents some of the engineering errors that occur in ILS localizer as a result of momentary drifts in critical parameters due to geographical factors, human manipulations and design constraints. The three types of errors are; parallax errors, multipath propagation errors and Maintenance Engineering Errors (MEEs). Maintenance engineering errors come as a result of difference in the signal parameters received on the runway centerline due to drift in value of circuit components. MEEs can also be caused by maladjustment of signal levels that lead to deviation of ILS courseline from runway centerline. The worst case of these errors is the provision of false ILS information that misguides the aircraft to miss the runway centerline and crash outside or within the airport. This proposal is focused to study the effects of MEEs on ILS signal using modeling and simulation. Huschem (1994) experiment found that ILS signal could be suitably modeled along linear continuous-time state model equations. These findings were later enhanced by the research conducted by Tromboni (2010).

1.2 Problem Statement
The signal from the ILS localizer operates to maintain stable equilibrium by ensuring that its courseline information is in tandem with the runway centerline. The drifts in electronic component values have the tendency to destabilize this equilibrium and thus creating a window for aircraft accidents. Air navigational aids and aircrafts operate in real-time domain that involves human life and expensive equipment. This constraint makes the study of effects of maintenance engineering errors risky and probably unattainable in real time. The purpose of this study is to conduct a test experiment using linear time-invariant state equations to develop models for analyzing ILS localizer maintenance engineering errors. Another purpose is to design a MATLAB tool to be used in predicting effects of these errors on aircrafts approaching Kenyan airports.

1.3 Objectives
The broad objective of this study is to analyze and predict the effects of maintenance engineering errors in air navigational aids using modeling and simulation.
The specific objectives;
1)      With reference to state model equations for linear continuous-time systems and ILS localizer signal equations, develop canonical state variable model for localizer systems in Kenya.
2)       Perform experiments to determine matrix constants for the ILS localizer state variable model.
3)      Using ILS localizer state variable model design a MATLAB program to simulate maintenance engineering errors and predict the magnitude of their effects on landing aircrafts.


The Current status of OJT in MIA
The following describes the current state of OJT in Mombasa station as described by the local MANSOPS:
The designated training officer is responsible for the organization and supervision of programs for new officers as well as Industrial attachment students. He is required to have knowledge of the CNS/ATM systems and application of ICAO CNS/ATM documents. He is expected to keep and update database of all equipment manuals (operations and maintenance) and training documentation.Compiles, keeps and updates records of training for engineering officers.
The designated training officer is to: Liaise with the HR training unit via CANS in arranging programs to orientate new members of staff. Liaise with respective equipment heads at ANSP headquarters and the Engineer–In-Charge at the station to formulate and implement On Job Training (OJT) programs covering all equipmentEnsure that a continuous program is in place to ensure competence of maintenance staff on equipment to which they have been deployed.
Once deployed to MIA Station, officers undergo initial three months’ induction training in all Equipment. Thereafter officers get attached for OJT to Equipment units that they have more interest in. The preliminary equipment induction covers basic theory and fundamental operations including practical observation and maintenance operation of the facilities. During this period officers also get introduced to all the functional sections within MIA Station in order to familiarize themselves with operations in the station. Officers are encouraged to update themselves through continuous training, refresher courses and to use internal and external avenues to upgrade their academic and professional levels and competence.
Why MIA OJT is not the Recommended ATSEP Training
1)   It is not Competence Based Training (CBT) -it lacks defined competences that one would expect in the outcomes, it has no specific objectives, no standardized competence assessment methods and no feedback criteria.
2)   It is not Evidence Based Training (EBT) -there is no immediate visible or enumerated show-me outcomes. The trainees take long to independently practise their acclaimed competences mainly because the trainers are mean with practical tasks and partly because the practical tasks are not standardized.
3)   On-Job-Training Instructor/Assessor -There is need to impart the trainers with skills that can help them be practical instructors and assessors. Lack of proper training forces many OJT instructors to resort to classroom instructional techniques which achieve little in terms of CBT.
4)   EASA and Field Training must be synchronized -Many a times EASA is out of phase with technology in the field. It is therefore difficult to align the training at school and the field. This poses a major challenge in OJT delivery to trainees from EASA who join the field.

In order that we steer ATSEP training effectively we need to start from EASA on three fronts i.e.
1)   ATSEP training documentation
2)   ATSEP training personnel
3)   ATSEP training equipment

ATSEP Training Documentation
The following documents will be essential in the delivery of ATSEP competence based training.
1.   Course outline/curriculum/syllabus (ATSEP training Doc 01) -this should be derived from ICAO doc 7192-part E (ATSEP training Manual), doc 9868, doc 8071, doc 9995 and the awaited doc 10057. Required competences need to be defined for each learning objective and expected outcomes stated clearly.
2.   Course Book (ATSEP Training Doc 02) -this should be prepared to contain all CNS subject matter. The depth of material should be moderated and guided by ATSEP training Doc 01. Subject matter expertise is required here.
3.   PPT lessons book (ATSEP training Doc 03) -these are PPT pre-prepared lessons generated from the course book. The purpose is to standardize course delivery modules and make them independent of the instructor.
4.   Practical Tasks Book (ATSEP training Doc 04) -this book will contain a series of practical tasks for each lesson. It will be derived from Doc 03. Subject matter expertise shall be required here.
5.   Lesson Plans (ATSEP training Doc 05) -the lesson plans need to be pre-prepared. This is necessary in order to standardize time of course delivery, costing and course management. Lesson plans shall be derived from Doc 03 and Doc 04.
6.   Assessment Plans (ATSEP training Doc 06) -the assessment methods should be standardized and fair. A bank of exam questions and answers should be prepared in advance and updated as often as possible. Multiple choice questions are recommended though structured questions are also allowed. A results analysis and feedback mechanism should be included.
7.   ATSEP progression guidelines (ATSEP training Doc 07) -the trainees will be required to learn how they expect to progress professionally. Whereas it is the responsibility of the ANSP regulators to provide licenses, it is important that ATSEPs understand this process right from system rating, certification and licensing.
8.   Instructors Manual (ATSEP training Doc 08) -this manual contains all what instructors need to know, monitor, follow and evaluate in a CBT environment. It includes elements of CRI, OJTI and OSTI.
9.   Assessors Manual (ATSEP training Doc 09) -ATSEP training philosophy discourages a scenario where an instructor is also an assessor for same trainees. This manual therefore contains what assessors need to know, monitor, follow and evaluate in a CBT environment. It includes elements of CRA, OJTA and OSTA.

ATSEP Training Personnel
1.   Classroom Instructor (CRI) -course delivery in classroom environment has its uniqueness that such an instructor will require training to deliver on CBT objectives.
2.   Laboratory/Workshop instructor (LWI) -this is expected to be 100% practical oriented instructor who requires training to manage trainees so as to deliver on CBT objectives.
3.   On Site Training Instructor (OSTI) -this is a field instructor trained to instruct on the site of specialized equipment due its uniqueness. He will require training to deliver CBT objectives.
4.   On Job Training Instructor (OJTI) – He organizes and manages training in work areas. He instructs all right from orientation, equipment, safety, routine maintenance, personnel teamwork etc. He will require training to deliver in a CBT environment.
5.   Assessors – they will conduct assessment in classroom, laboratory, workshops, equipment site and job areas. Assessors will be trained for various assessment functions to be able to deliver in competence based training environment.
6.   Quality Assurance Officer – there will be need to reflect and measure the quality of training being offered in a CBT environment. It is an ATSEP training requirement that the process of quality assurance should be continuous and therefore some personnel is required to constantly monitor this quality.