Human Performance Contributions to Safety in Commercial Aviation

In the commercial aviation domain, large volumes of data are collected and analyzed on the failures and errors that result in infrequent incidents and accidents, but in the absence of data on behaviors that contribute to routine successful outcomes, safety management and system design decisions are based on a small sample of non- representative safety data. Analysis of aviation accident data suggests that human error is implicated in up to 80% of accidents, which has been used to justify future visions for aviation in which the roles of human operators are greatly diminished or eliminated in the interest of creating a safer aviation system. However, failure to fully consider the human contributions to successful system performance in civil aviation represents a significant and largely unrecognized risk when making policy decisions about human roles and responsibilities. Opportunities exist to leverage the vast amount of data that has already been collected, or could be easily obtained, to increase our understanding of human contributions to things going right in commercial aviation. The principal focus of this assessment was to identify current gaps and explore methods for identifying human success data generated by the aviation system, from personnel and within the supporting infrastructure

Development and Application of an Integrated Approach toward NASA Airspace Systems Research

The National Aeronautics and Space Administration's (NASA) Airspace Systems Program is contributing air traffic management research in support of the 2025 Next Generation Air Transportation System (NextGen). Contributions support research and development needs provided by the interagency Joint Planning and Development Office (JPDO). These needs generally call for integrated technical solutions that improve system-level performance and work effectively across multiple domains and planning time horizons. In response, the Airspace Systems Program is pursuing an integrated research approach and has adapted systems engineering best practices for application in a research environment. Systems engineering methods aim to enable researchers to methodically compare different technical approaches, consider system-level performance, and develop compatible solutions. Systems engineering activities are performed iteratively as the research matures. Products of this approach include a demand and needs analysis, system-level descriptions focusing on NASA research contributions, system assessment and design studies, and common systemlevel metrics, scenarios, and assumptions. Results from the first systems engineering iteration include a preliminary demand and needs analysis; a functional modeling tool; and initial system-level metrics, scenario characteristics, and assumptions. Demand and needs analysis results suggest that several advanced concepts can mitigate demand/capacity imbalances for NextGen, but fall short of enabling three-times current-day capacity at the nation s busiest airports and airspace. Current activities are focusing on standardizing metrics, scenarios, and assumptions, conducting system-level performance assessments of integrated research solutions, and exploring key system design interfaces

Project ambidexterity: case of recovering schedule delay in a brownfield airport project in India

Planning deficiencies and consequent execution delays are likely to persist in infrastructure development projects. However, recovery of schedule delay is a less researched area. This case research, using a two-stage inquiry modeled on the grounded theory, studied the schedule delay recovery during the execution phase of a brownfield airport construction project. The analyses generated contextual evidence and ambidexterity was found to be the key underlying phenomenon for successful recovery measures. The empirical learning was validated with literature and can be used by practitioners looking to institute schedule recovery measures

Integrated and joint optimisation of runway-taxiway-apron operations on airport surface

Airports are the main bottlenecks in the Air Traffic Management (ATM) system. The predicted 84% increase in global air traffic in the next two decades has rendered the improvement of airport operational efficiency a key issue in ATM. Although the operations on runways, taxiways, and aprons are highly interconnected and interdependent, the current practice is not integrated and piecemeal, and overly relies on the experience of air traffic controllers and stand allocators to manage operations, which has resulted in sub-optimal performance of the airport surface in terms of operational efficiency, capacity, and safety. This thesis proposes a mixed qualitative-quantitative methodology for integrated and joint optimisation of runways, taxiways, and aprons, aiming to improve the efficiency of airport surface operations by integrating the operations of all three resources and optimising their coordination. This is achieved through a two-stage optimisation procedure: (1) the Integrated Apron and Runway Assignment (IARA) model, which optimises the apron and runway allocations for individual aircraft on a pre-tactical level, and (2) the Integrated Dynamic Routing and Off-block (IDRO) model, which generates taxiing routes and off-block timing decisions for aircraft on an operational (real-time) level. This two-stage procedure considers the interdependencies of the operations of different airport resources, detailed network configurations, air traffic flow characteristics, and operational rules and constraints. The proposed framework is implemented and assessed in a case study at Beijing Capital International Airport. Compared to the current operations, the proposed apron-runway assignment reduces total taxiing distance, average taxiing time, taxiing conflicts, runway queuing time and fuel consumption respectively by 15.5%, 15.28%, 45.1%, [58.7%, 35.3%, 16%] (RWY01, RWY36R, RWY36L) and 6.6%; gated assignment is increased by 11.8%. The operational feasibility of this proposed framework is further validated qualitatively by subject matter experts (SMEs). The potential impact of the integrated apron-runway-taxiway operation is explored with a discussion of its real-world implementation issues and recommendations for industrial and academic practice.Open Acces

BARCH: a business analytics problem formulation and solving framework

The BARCH framework is a business framework that is specifically formulated to help analysts and management who want to identify and formulate a scenario to which Analytics can be applied and the outcome will have a direct impact on the business. This is the overarching public work that I have used extensively in various projects and research. This framework has been developed initially in the banking sector and has evolved progressively with successive projects. The framework’s name represents five aspects for the formulation and identification of an area that one can use Analytics to answer. The five aspects are Business, Analytics, Revenue, Cost and Human. The five aspects represent the entire system and approach to the identification, formulation, understanding and modelling of Analytic problems. The five aspects are not necessarily sequential but are interrelated in some ways where certain aspects are dependent on the other aspects. For example, revenue and cost are related to business and depend on the business from which they are derived. However, in most practices involving Analytics, Analytics are conducted independent of business and the techniques in Analytics are not derived from business directly. This lack of harmony between business and Analytics creates an unfortunate combination of factors that has led to the failure of Analytics projects for many businesses. In intensely practising Analytics and critically reflecting on every piece of work I have done, I have learned the importance of combining knowledge with skills and experience to come up with new knowledge and a form of practical wisdom. I also realize now the importance of understanding fields that are not directly related to my field of specialization. Through this context statement I have been able to increase the articulation of my thinking and the complexities of practice through approaches to knowledge such as transdisciplinarity which further supports the translation of what I can do and what needs to be done in a way that business clients can understand. Having the opportunity to explore concepts new to me from other academic fields and seeking their relevance and application in my own area of expertise has helped me considerably in the ongoing development of the BARCH framework and successful implementation of Analytics projects. I have selected the results of three projects published in papers that are listed in Appendices A-C to demonstrate how the model can be applied to solve problems successfully compared to other frameworks. The evolution of the model involves a continual feedback loop of learning from each successive project which contributes to the BARCH model being able to not only continuously demonstrate its applicability to various problems but to consistently produce better and more refined results. The majority of analytical models applied to the many problems in the business environment address the problems only superficially (Bose, 2009; Krioukov et. al., 2011), that is without understanding the impact on the business as a whole. Many Analytics projects have not delivered the promised impact because the models applied are overly complicated (Stubbs, 2013) to solve the root causes of the business problem. This situation is compounded by an increasing number of analysts applying Analytics to business problems without a proper understanding of the context, technique and environment (Stubbs, 2013). While many experts in the field interpret the problem as a multidisciplinary problem, the problem is in my opinion transdisciplinary in nature