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This paper aims to show the current situation and additional requirements for the aircraft automation systems based on the lessons learned from the two 737 MAX crashes.

In this study, the Swiss cheese model was used to find the real root causes of the 737 MAX accidents. Then, the results have been compared with the actions taken by the manufacturers and authorities. Based on the comparison, the necessary improvements to prevent such accidents are defined. Regarding the faulty sensor that forms the accidents, a synthetic sensor was developed using an aerodynamic model.

It has been proven that the safety-critical automation systems should not be designed by relying on a single set of sensor data. Automation levels should be defined in a standard way. Depending on the defined automation level, the system must be designed as either fail-safe or fail-operational system. When designing backup systems, it should be decided by looking at not only whether it has power but also the accuracy of the incoming signals.

Aviation certification requirements related to automation systems need to be revised and improved. With this context, it was revealed that the certification processes for automation systems should be re-evaluated and updated by aviation authorities, especially Federal Aviation Administration and European Union Aviation Safety Agency.

Task sharing between automation system and pilot based on the classification of automation levels and determining certification requirements accordingly has been brought to the agenda. A synthetic Angle of Attack sensor was developed by using an aerodynamic model for fault detection and diagnosis.

The purpose of this paper is to develop an automated engine health monitoring system (AEHMS) for commercial aircraft.

The AEHMS is developed by using fuzzy logic. The input of the fuzzy logic is engine performance parameters gathered from aircraft for every flight during cruise. The fuzzy rule inference system for different engine faults is based on expert knowledge and real life data in the Turkish Airlines fleet. The very smallest is used for defuzzification, since it provides a more meaningful result than others. The complete loop of engine health monitoring (EHM) is automatically performed by the programs and Fuzzy Logic Toolbox in MATLAB. The system produces output values between 0 – faulty and 1 – not faulty for every fault or deterioration on a time series. The program triggers an alert if any output exceeds a specified value. Finally, the method is utilized for monitoring the engines in the Turkish Airlines fleet.

Health monitoring has been a very popular subject to increase aircraft availability with the minimum maintenance cost. Fuzzy logic is a very useful method for automated health monitoring strategies.

It does not provide long‐term engine maintenance decisions such as scheduling overhaul times, predicting the remaining life of the engine components.

The paper provides a robust method for EHM with the application to real aircraft data. The AEHMS can greatly simplify the EHM system for airlines and minimizes its drawbacks, such as extra labor hours, human error and requirement for engineering expertise.

In retail industry, it is very important that companies start to own an omnichannel approach in order provide an integrated experience. This approach is recognized as a key to have sustainable growth for companies and brands. In this study, it is aimed to examine the application of omnichannel decisions in different marketing channels and the contributions of this approach in the strategic plans of companies to create an overall customer experience in Turkey. For this purpose, a thorough literature review was provided on different marketing channel approaches, especially retailing and wholesales. In-depth interviews with companies showed that companies in Turkey are underway to include omnichannel approach in their short-term plans to improve their sales volume, and these companies also use this approach as a positioning by creating an integrated customer experience through customer relationship management.