Search results

This study aims to identify the present research trends and streamline future research possibilities in luxury brands by a systematic review of the existing literature.

A portfolio of 552 articles published between 1996 and 2020 in the luxury brands domain is collected from the Scopus database and analyzed using an integrated approach comprising bibliometric and content analyses.

A comprehensive review of the available literature was done by identifying emerging topics, keywords and research themes. The study's findings indicate that the luxury brand is an exponentially growing theme; seven representative research clusters are identified and analyzed.

This study enriches the literature of luxury brand by presenting a holistic view of the academic literature using an integrated research methodology comprising bibliometric and content analysis techniques.

This paper proposes an integrated methodology for process design to guide decision making under uncertainty by combining life cycle assessment (LCA) with multi‐criteria decision‐making tools.

Cleaner and greener technologies for process and product selection and design have gained popularity in recent years. The LCA is a systematic approach that enables selection of cleaner and greener products and processes. Recently, significant progress has been made for the use of LCA for product/process evaluation and selection. However, its use in process design and environmental decision making has not been fully exploited. The proposed methodology GreenPro‐I is a systematic approach to estimate environmental risks/impacts associated with life cycle of products, processes and services. It evaluates environmental burdens by quantifying energy and materials used and waste released into the environment. It identifies and evaluates opportunities, which affect environmental improvements. The assessment includes the extraction/excavation and processing of raw materials, manufacturing, transportation and distribution, use, recycle, and final disposal.

GreenPro‐I overcomes many of the problems faced in the conventional approaches and establishes a link between the environmental risks/impacts, cost, and technical feasibility of processes.

GreenPro‐I provides a comprehensive decision‐making tool for designers, regulatory agencies, business organizations and other stakeholders.

The aim of this paper is to propose a robust robot fuzzy logic proportional-derivative (PD) controller for trajectory tracking of autonomous nonholonomic differential drive wheeled mobile robot (WMR) of the type Quanser Qbot.

Fuzzy robot control approach is used for developing a robust fuzzy PD controller for trajectory tracking of a nonholonomic differential drive WMR. The linear/angular velocity of the differential drive mobile robot are formulated such that the tracking errors between the robot’s trajectory and the reference path converge asymptotically to zero. Here, a new controller zero-order Takagy–Sugeno trajectory tracking (ZTS-TT) controller is deduced for robot’s speed regulation based on the fuzzy PD controller. The WMR used for the experimental implementation is Quanser Qbot which has two differential drive wheels; therefore, the right/left wheel velocity of the differential wheels of the robot are worked out using inverse kinematics model. The controller is implemented using MATLAB Simulink with QUARC framework, downloaded and compiled into executable (.exe) on the robot based on the WIFI TCP/IP connection.

Compared to other fuzzy proportional-integral-derivative (PID) controllers, the proposed fuzzy PD controller was found to be robust, stable and consuming less resources on the robot. The comparative results of the proposed ZTS-TT controller and the conventional PD controller demonstrated clearly that the proposed ZTS-TT controller provides better tracking performances, flexibility, robustness and stability for the WMR.

The proposed fuzzy PD controller can be improved using hybrid techniques. The proposed approach can be developed for obstacle detection and collision avoidance in combination with trajectory tracking for use in environments with obstacles.

A robust fuzzy logic PD is developed and its performances are compared to the existing fuzzy PID controller. A ZTS-TT controller is deduced for trajectory tracking of an autonomous nonholonomic differential drive mobile robot (i.e. Quanser Qbot).