Construction Dispute Mitigation: Quantitative and Qualitative Analytic Approach with a Focus on Bidding, Out-of-Sequence Work, and Contract Analysis

The complexity of today’s construction projects deems conflicts and disputes unavoidable. The mere presence of disputes leads to productivity losses, schedule overruns, cost overruns, and quality decline. Moreover, failure to resolve disputes in a quick manner ripples these impacts and prevents successful completion of projects. Accordingly, preventing disputes prior to taking place is always better than resolving them after the fact. There are several factors that cause disputes. However, this dissertation focuses on those related to bidding, out-of-sequence (OOS) work, and contract administration of owner’s obligations, due to the significant knowledge gaps that were identified in their research streams.The goal of this research is to cover the identified knowledge gaps by providing various effective quantitative and qualitative means of dispute mitigation at the different stages of the project’s lifecycle. To this end, the research has four main objectives; each corresponding to one of the identified major knowledge gaps. The objectives are: (1) develop an advanced model for construction bid price estimation that is able to draw sound statistical inferences even in cases of data incompleteness and dynamic behaviors of competitors; (2) present contract administration guidelines for utilizing employer’s obligations clauses under the most widely used national and international standard forms of design-build contracts; (3) identify the causes and early warning signs of OOS work and their characteristics, as well as the best practices to avoid and mitigate its impacts, and (4) develop an advanced systematic model for analyzing the dynamics of OOS.The objectives were achieved through multiple analytical quantitative and qualitative methods; utilizing Bayesian statistics, decision theory, contractual examinations, surveys and meetings, statistical analysis, decision support systems, and system dynamics simulation. The research has various intellectual merits as it tackles important research areas that have not been explored before and improves areas which needed improvement. The research also has practical merits as it provides project stakeholders with models and tools that are used in multiple stages of the project cycle to mitigate disputes. The intellectual and practical outcomes of this research will partake in further understanding construction projects, minimizing disputes at different stages, and promoting healthier contracting environments

Reliability of multi-channel IEC 61850 mission-critical substation communication networks based on Markov process incorporating linear dynamical systems and calculus inferences.

Doctoral Degree. University of KwaZulu-Natal, Durban.IEC 61850 based Substation Communication Networks (SCN) enable substation processes to be digitalised to fulfil the most sought substation monitoring, protection and control of electrical systems. The standard enables peer-to-peer communication of mission critical messages, aided by onboard diagnostic capabilities to ease the identification of system faults. The implementation of Safety-Related Systems in industrial facilities comprising sensors, logic solvers and final elements in power distribution centres necessitate compliance to IEC 61508 standard, where circuit breakers act as final elements to isolate electrical machines. In recent times, combinatorial methods such as the Reliability Block Diagram have been used to evaluate the architecture of IEC 61850 based SCN reliability and availability due to the simplicity of the approach. These methods, however, assume that all system faults are identified and fully repaired, which is not the case in practice. In this thesis, the reliability of a repairable multi-channel IEC 61850 based SCN architecture is modelled using a structure function and the Markov process while Systems Thinking integrates imperfect repair factors into the model. Thereafter, a novel eigenvalue analysis method based on Markov partitions and symbolic dynamics in the context of linear dynamical systems is used to investigate the impact of imperfect repairs on the system's reliability based on the number of mean state transitions and dynamical behaviour. The eigenvalue method is then advanced by a complimentary analysis technique based on the absorbing Markov Chain process and matrix calculus methods to determine the system's responsiveness to repair factors. The case studies results demonstrate that imperfect repairs cannot be ignored for mission-critical applications because the simplifying assumptions of combinatorial analysis methods greatly over-state the system's reliability performance. The results also indicate that common causes of failure coupled with imperfect repairs significantly negatively impact the system's performance. Moreover, system performance is highly dependent on the diagnostic coverage of the individual subsystems than their repair efficiencies for high diagnostic coverages at 90% and 99% based on ISO 13849-1. Hence, the results demonstrate that emphasis should be more on the system diagnostic coverage for the fact that it is embedded in the system design itself that cannot easily be changed once the system is commissioned and operational

On Engineering Risks Modeling in the Context of Quantum Probability

Conventional risk analysis and assessment tools rely on the use of probability to represent and quantify uncertainties. Modeling complex engineering problems with pure probabilistic approach can encounter challenges, particularly in cases where contextual knowledge and information are needed to define probability distributions or models. For the study and assessment of risks associated with complex engineering systems, researchers have been exploring augmentation of pure probabilistic techniques with alternative, non-fully, or imprecise probabilistic techniques to represent uncertainties. This exploratory research applies an alternative probability theory, quantum probability and the associated tools of quantum mechanics, to investigate their usefulness as a risk analysis and assessment tool for engineering problems. In particular, we investigate the application of the quantum framework to study complex engineering systems where the tracking of states and contextual knowledge can be a challenge. This study attempts to gain insights into the treatment of uncertainty, to explore the theoretical implication of an integrated framework for the treatment of aleatory and epistemic uncertainties, and to evaluate the use of quantum probability to improve the fidelity and robustness of risk system models and risk analysis techniques

Context Awareness for Navigation Applications

This thesis examines the topic of context awareness for navigation applications and asks the question, “What are the benefits and constraints of introducing context awareness in navigation?” Context awareness can be defined as a computer’s ability to understand the situation or context in which it is operating. In particular, we are interested in how context awareness can be used to understand the navigation needs of people using mobile computers, such as smartphones, but context awareness can also benefit other types of navigation users, such as maritime navigators. There are countless other potential applications of context awareness, but this thesis focuses on applications related to navigation. For example, if a smartphone-based navigation system can understand when a user is walking, driving a car, or riding a train, then it can adapt its navigation algorithms to improve positioning performance. We argue that the primary set of tools available for generating context awareness is machine learning. Machine learning is, in fact, a collection of many different algorithms and techniques for developing “computer systems that automatically improve their performance through experience” [1]. This thesis examines systematically the ability of existing algorithms from machine learning to endow computing systems with context awareness. Specifically, we apply machine learning techniques to tackle three different tasks related to context awareness and having applications in the field of navigation: (1) to recognize the activity of a smartphone user in an indoor office environment, (2) to recognize the mode of motion that a smartphone user is undergoing outdoors, and (3) to determine the optimal path of a ship traveling through ice-covered waters. The diversity of these tasks was chosen intentionally to demonstrate the breadth of problems encompassed by the topic of context awareness. During the course of studying context awareness, we adopted two conceptual “frameworks,” which we find useful for the purpose of solidifying the abstract concepts of context and context awareness. The first such framework is based strongly on the writings of a rhetorician from Hellenistic Greece, Hermagoras of Temnos, who defined seven elements of “circumstance”. We adopt these seven elements to describe contextual information. The second framework, which we dub the “context pyramid” describes the processing of raw sensor data into contextual information in terms of six different levels. At the top of the pyramid is “rich context”, where the information is expressed in prose, and the goal for the computer is to mimic the way that a human would describe a situation. We are still a long way off from computers being able to match a human’s ability to understand and describe context, but this thesis improves the state-of-the-art in context awareness for navigation applications. For some particular tasks, machine learning has succeeded in outperforming humans, and in the future there are likely to be tasks in navigation where computers outperform humans. One example might be the route optimization task described above. This is an example of a task where many different types of information must be fused in non-obvious ways, and it may be that computer algorithms can find better routes through ice-covered waters than even well-trained human navigators. This thesis provides only preliminary evidence of this possibility, and future work is needed to further develop the techniques outlined here. The same can be said of the other two navigation-related tasks examined in this thesis

Untangling hotel industry’s inefficiency: An SFA approach applied to a renowned Portuguese hotel chain

The present paper explores the technical efficiency of four hotels from Teixeira Duarte Group - a renowned Portuguese hotel chain. An efficiency ranking is established from these four hotel units located in Portugal using Stochastic Frontier Analysis. This methodology allows to discriminate between measurement error and systematic inefficiencies in the estimation process enabling to investigate the main inefficiency causes. Several suggestions concerning efficiency improvement are undertaken for each hotel studied.info:eu-repo/semantics/publishedVersio

Safety and Reliability - Safe Societies in a Changing World

The contributions cover a wide range of methodologies and application areas for safety and reliability that contribute to safe societies in a changing world. These methodologies and applications include: - foundations of risk and reliability assessment and management - mathematical methods in reliability and safety - risk assessment - risk management - system reliability - uncertainty analysis - digitalization and big data - prognostics and system health management - occupational safety - accident and incident modeling - maintenance modeling and applications - simulation for safety and reliability analysis - dynamic risk and barrier management - organizational factors and safety culture - human factors and human reliability - resilience engineering - structural reliability - natural hazards - security - economic analysis in risk managemen