A novel compliant surgical robot: Preliminary design analysis

A robotic surgical system capable of performing minimally invasive surgery (MIS) is proposed in this paper. Based on the requirements of MIS, a compliant, seven- degrees of freedom (7-DOF) pneumatically actuated mechanism is designed. A remote center of motion (RCM) as a parallelogram mechanism for holding the laparoscopic camera is also developed. The operating workspace of robotic surgical system is determined considering the physical constraints imposed by mechanical joints. The simulation results show that the robotic system meets the design requirement. This research will lay a good foundation for the development of a compliant surgical robot to assist in MIS

INTEGRATED RISK ASSESSMENT IN RAMP HANDLING OPERATIONS: RISK MAPPING FOR TURKISH AIRPORTS

Ramp handling acts a vital role in sustainable airport operations. The ramp related services provided to aircraft and their passengers at the airports are related to the landing, take-off, unloading and loading of the aircraft. Human resource is a key component in ramp handling operation and errors by employees cause significant accidents or incidents. The main purpose of the current study is to prioritize critical risk factors in ramp handling operations by using an integrated risk management approach and optimizing human performance while minimizing both failures and errors by employees. In this study, an integrated qualitative and quantitative risk assessment method is carried out by considering the factors that affect the possibility of ramp handling personnel errors. Initially, 113 risk factors are identified by using the academic literature, documents prepared by international organizations, and then by consulting expert opinions. Subsequently, a prioritization by professionals working on the ramp handling operations, based on the principles of the Analytic Hierarchy Process (AHP) method resulted in the final selection of the 41 most important risks. Then, a risk assessment approach is applied by designing a matrix, based on three dimensions; probability, severity (impact) and relation ratio which ultimately resulted in risk index generation and a risk map model is developed. Finally eleven (11) risk factors are identified as they have higher probabilities to occur and possible higher negative consequences. Thanks to the integrated risk assessment applied in this study, it is aimed to ensure that all systems of the organization operate in a safe way and that an efficient safety culture is formed. Allocating a single resource to many risks, instead of facing the risks of the ramp personnel one by one, leads to more efficient use of resources and higher performance of ground handling companies

Multi crteria decision making and its applications : a literature review

This paper presents current techniques used in Multi Criteria Decision Making (MCDM) and their applications. Two basic approaches for MCDM, namely Artificial Intelligence MCDM (AIMCDM) and Classical MCDM (CMCDM) are discussed and investigated. Recent articles from international journals related to MCDM are collected and analyzed to find which approach is more common than the other in MCDM. Also, which area these techniques are applied to. Those articles are appearing in journals for the year 2008 only. This paper provides evidence that currently, both AIMCDM and CMCDM are equally common in MCDM

Risk factors affecting the ability for earned value management to accurately assess the performance of infrastructure projects in Australia

Purpose – The purpose of this paper is to investigate a set of risk-related factors influencing the earned value management (EVM) concept as an assessment technique in evaluating the progress of modern sustainable infrastructure construction projects. Design/methodology/approach – A qualitative research approach has been adopted for identifying risk-related factors influencing EVM concept from a literature review and through interviewing industry personnel, followed by an inductive process to form sets of key factors and their measuring items. Findings – EVM is a common method for assessing project performance. A weakness of this approach is that EVM assessment in its current form does not measure the impact of a number of project performance factors that result from the complexity of modern infrastructure construction projects, and thus does not accurately assess their impact in this performance. This paper discusses and explains a range of potential risk factors to evaluating project performance such as sustainability, stakeholder requirements, communication, procurement strategy, weather, experience of staff, site condition, design issues, financial risk, subcontractor, government requirements and material. In addition, their measuring items were identified. Practical implications – This research assists projects managers to improve the evaluation process of infrastructure construction performance by incorporating a range of factors likely to impact on that performance and which are not included in current EVM calculations. Originality/value – This research addresses the need to include in the EVM calculation a range of risk factors affecting the performance of infrastructure projects in Australia and therefore makes this calculation a more reliable tool for assessing project performance

Intelligent optimisation system for airport operation: Hajj Terminal in Saudi Arabia

This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University London.Airport operation level of service (LOS) and performance management are among the major concerns by any airport authority. Two aspects considered in that kind of measurement: passengers prospective and operators prospective. This thesis tries to combine both in its produced optimisation system. This study was carried out in the Hajj terminal of the King Abdul-Aziz international airport and classified the processing time among the most important measures affecting the users’ observation of the level of service. Produced survey has helped to generate performance measure upon passengers prospective. On the other hand a simulation model of the process flow is utilised to formulate driven data model of the terminal process flow operations. The model built on Arena software and correlation study is made from the multiple “what if” scenarios of the model. Then a linear regression is used to generate a model for each variable. Levenberg–Marquardt (LM) algorithm is used after to carry out better regression model then Neuro-Fuzzy (NF) model found to be more efficient as it is picked and used to generate a best observed prediction. The system is optimised through the generated Neuro-Fuzzy (NF) logic model using both Particle Swarm Optimization (PSO) and Genetic Algorithm (GA). A validation in addition to the testing made in the optimisation system. Analysis shows a great deal of improvement in predictions using fuzzy logic instead of linear regression for all dependent variables. PSO and GA optimisations are carried out and compared to the actual results gathered from the Arena simulation report

Customer Service in Aviation Industry – An Exploratory Analysis of UAE Airports

Customer satisfaction is given top priority by all service-oriented industries. The civil aviation industry is no exception. The highly competitive global aviation arena causes various airlines to vie for the top position with lot of importance being given to the customer service. The aim of this study is to analyze the methods and tools used by the United Arab Emirates’ (UAE’s) federal government and the various local governments in the country to improve the customer satisfaction with regard to the aviation industry in the country. This paper develops a framework to assess customer service in the aviation sector in the UAE and uses the framework to analyze and compare the three main airports in the UAE based on the feedback of passengers. This study used a multi-pronged approach to collect data. In all, 78 travelers were chosen at random and they were administered a structured and a semi-structured questionnaire. Responses to the former were used to perform Chi-square test and establish the differences between the three airports; the latter were used to gain deeper insight and gauge a more in-depth opinion of the respondents. Through the analysis of the data, this study was able to learn more about the public view with regard to the innovations and ideas implemented by the government of the UAE. A new customer service model has been developed to compare the three airports in UAE and gain more insights into opportunities for improvement

RANKING TRAVEL AND TOURISM ENABLERS IN INDIA USING A FUZZY APPROACH

This paper seeks to review the enablers for the Travel & Tourism (T&T) industry in India and to rank these factors. The paper aims to introduce a fuzzy TOPSIS approach for this purpose. The paper begins with a literature review to investigate the significant enablers in the T&T sector. The research was conducted among the tourists in the northern state of Uttarakhand, India which is a famous tourist destination both for adventure and pilgrimage. Fuzzy TOPSIS approach is used to meet the objectives of the study. Required information was gathered through a questionnaire. The results show that Safety & Security, Price, Transport and Infrastructure are the most important factors in Indian context.The paper will be helpful in enabling the T&T industry policy makers to identify the key service factors in the sector and take the improvement measuresThe concept of ranking T&T enablers using a Fuzzy TOPSIS is a new approach. The study is the unique application of a fuzzy approach to examine and rank customer expectations of the T&T enablers in Indian context

Polarization and opinion analysis in an online argumentation system for collaborative decision support

Argumentation is an important process in a collaborative decision making environment. Argumentation from a large number of stakeholders often produces a large argumentation tree. It is challenging to comprehend such an argumentation tree without intelligent analysis tools. Also, limited decision support is provided for its analysis by the existing argumentation systems. In an argumentation process, stakeholders tend to polarize on their opinions, and form polarization groups. Each group is usually led by a group leader. Polarization groups often overlap and a stakeholder is a member of multiple polarization groups. Identifying polarization groups and quantifying a stakeholder\u27s degree of membership in multiple polarization groups helps the decision maker understand both the social dynamics and the post-decision effects on each group. Frameworks are developed in this dissertation to identify both polarization groups and quantify a stakeholder\u27s degree of membership in multiple polarization groups. These tasks are performed by quantifying opinions of stakeholders using argumentation reduction fuzzy inference system and further clustering opinions based on K-means and Fuzzy c-means algorithms. Assessing the collective opinion of the group on individual arguments is also important. This helps stakeholders understand individual arguments from the collective perspective of the group. A framework is developed to derive the collective assessment score of individual arguments in a tree using the argumentation reduction inference system. Further, these arguments are clustered using argument strength and collective assessment score to identify clusters of arguments with collective support and collective attack. Identifying outlier opinions in an argumentation tree helps in understanding opinions that are further away from the mean group opinion in the opinion space. Outlier opinions may exist from two perspectives in argumentation: individual viewpoint and collective viewpoint of the group. A framework is developed in this dissertation to address this challenge from both perspectives. Evaluation of the methods is also presented and it shows that the proposed methods are effective in identifying polarization groups and outlier opinions. The information produced by these methods help decision makers and stakeholders in making more informed decisions --Abstract, pages iii-iv

An evaluation methodology for the level of service at the airport landside system

A methodology is proposed for evaluating the level of service within an airport landside system from the passenger's point of view using linguistic service criteria. The new concept of level of service for a transport system, particularly within the airports indicates that there must be strong stimulation in order to proceed with the current stereotyped service standards which are being criticised due to their being based on, either physical capacity/volume or temporal/spatial standards that directly incorporates the perception of passengers, the dominant users. Most service evaluation methodologies have been concentrated on the factors of the time spent and the space provided. These quantitative factors are reasonably simple to measure but represent a narrow approach. Qualitative service level attributes are definitely important factors when evaluating the level of service from a user's point of view. This study has adopted three main evaluation factors: temporal or spatial factors as quantitative measurements and comfort factors and reasonable service factors as qualitative measurements. The service level evaluation involves the passenger's subjective judgement as a perception for service provision. To evaluate the level of service in the airport landside system from the user's perception, this research proposes to apply a multi-decision model using fuzzy set theory, in particular fuzzy approximate reasoning. Fuzzy set theory provides a strict mathematical framework for vague conceptual phenomena and a modelling language for real situations. The multi-decision model was applied to a case study at Kimpo International Airport in Seoul, Korea. Results are presented in terms of passenger satisfaction and dissatisfaction with a variety of different values