Dr Mahmoud Efatmaneshnik


Dr Mahmoud Efatmaneshnik a PhD in Complexity management of Design Process (2009), and a ME in manufacturing engineering (2005) both from UNSW. He has a BE in aerospace (1999) from Tehran Polytechnic university. Mahmoud is active member of INCOSE and holds a number of committee positions in Systems Engineering Society of Australia. He is author of over 70 book chapters, journal papers, and refereed conference papers. 

His resaerch interests are:

  • Systems Engineering
  • Systems modeling and analysis
  • Complexity modeling and complexity measures
  • Decision support system for design and engineering
  • Design decision analysis and Risk management
  • Capability modelling and acquisition model development

He currently has a number PhD projects in several general areas including:

Risk and Complexity Management in Systems Engineering

  1. Investigating Application of Possibility theory to Systems Engineering Risk Management

Complex systems are characterized by many future possibilities each with a tiny probability. The traditional risk analysis that considers probability versus impact might not be helpful when the number of futures is too many. This project aims at finding parallel risk management methods based on possibility theory rather than probability theory. This project is highly mathematical and is a suitable for a candidate with deep understanding of probability, fuzzy set and possibility theories.

  1. Investigation of Failure Propagation Mechanisms in Complex Systems

The aim of this project is to characterise failure propagation in various kinds of systems such as enterprises (human systems), software and hardware systems, mechanical systems and heterogeneous systems such as system of systems. The models are then used to characterise the fragility and robustness of these systems. The generated models are then put into the more general context of resilience engineering where various resilience engineering mechanisms are validated against characteristics of system responses to failure propagation.

  1. Probabilistic Systems Engineering Model: Synthesis and Validation

The aim of this project is to synthesize building blocks of a Probabilistic Systems Engineering Model and its validation. The model would be based on probabilistic success in execution of systems engineering task and resulting rework. Four basic systems engineering tasks are considered initially:

  1. Problem identification
  2. Solution Synthesis
  3. Integration
  4. Test

For each of these tasks will be characterized with a set of probability measures that will indicate the success or failure. Then these measures are applied to a network view the system. One major task in this project is the identification of an appropriate solver for the network such as Bayesian network, Petri Net, Generalized Networks or other models based random graph theory. The solver must be able to identify lead time, rework and quality of the constructed system.

Systems Architecture Optimisation

  1. System Architecture Evaluation and Optimization at Early Conceptual Design Stage

Defence systems acquisition is fraught with all sorts of financial, technical and political risks. The most effective way of mitigating risks associated with acquisition of complex systems is through identification of these risks as early as possible. This project’s aim is to facilitate optimal decision making for multi stakeholder system design.

This project sets to examine an architectural selection model based on minimal information at early stages of conceptual design. The system architecture, determined by integration and test plans is a key factor in management of the uncertainties associated with technology, processes and tests. This project will examine and categorise these uncertainties and will investigate ways of evaluating competing system architectures based on the identified risks, such as through estimation of the likely values and variances of project cost and time associated with each architecture.

  1. An Integrated Stakeholder Preference Modelling and Tradespace Evaluation Framework

This project’s aim is to facilitate optimal decision making for multi stakeholder system design. This study will investigation all available preference modelling methods and asses their utility for integration with Tradespace exploration techniques.

  1. Creating and Managing System Modularity: A Trade off and Optimality Analysis

Modularity as a system property has many benefits for different lifecycle stages of a system. This project is an investigation of a complete set of these benefits as well as a search for optimum formation of the modules for maximum benefit to all or some the identified benefits, at early design stages.

  1. Investigation of Methods and Methodologies for Systems Engineering of Non-functional Requirements

Systems Engineering methodology applies aptly to functional design of systems. However, for non-functional requirements, the current methodology does not have a lot to offer and there is a lack of concrete methodologies for non-functional systems engineering. Specific modularization of systems elements is a powerful tool for the design of the non-functional requirements into the systems. This project investigates ways that modularization can be integrated into the standard systems engineering process. It also may involve creation of a complete taxonomy for non-functional requirements and their ontology.

Human Systems Engineering

  1. Investigating Best Practices in Human-Systems Integration and Engineering Methodologies

This project aims at identifying current state of the art human systems integration techniques and creation of framework for an overarching or generalized human system integration framework that can be substantiated for different kinds of systems. Human systems integration practices are very domain specific for example healthcare, defence, aerospace etc. However, there is no agreed upon methodology that can be instantiated for any kind of systems. This project takes step back to the principles of human systems integration and based on those principles creates a methodology for human systems integration. The project will include an Investigation of the Role of Human Systems Integration in Engineering of Complex Systems

  1. Investigation of Competency Model Integration with Project Management

This project is part of a much larger vision to measure complexity of projects from subjective views for task and resource allocation purposes. Several competency models have been proposed and used in defence. The project aims at:

  1. Identifying usability of competency frameworks with task complexity measurement.
  2. Integration of competency frameworks with task complexity measure.
  3. Investigation of optimality and validity of system selection for minimum complexity given set of available resources and their competency models and set of problem space elements.