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Introduction to Computational Automation in Water Quality Management
No full textThis article is index by ScopusComputational automation in water quality management has emerged as a critical tool in ensuring sustainable and safe water resources. This chapter discusses the integration of advanced computational techniques, including machine learning, artificial intelligence, and sensor networks, to enhance the monitoring, analysis, and management of water quality. The discussion includes the development and application of automated systems for real-time data acquisition, processing, and decision-making. By applying computational automation, water quality management can achieve higher precision, efficiency, and responsiveness, addressing challenges posed by environmental changes and increasing water demand. This chapter provides a comprehensive overview of the current state of computational automation in water quality management, its technological fundamentals, case studies of successful implementations, and future directions. The aim is to show these technologies can be utilized to secure water quality and ensure public health and environmental protection
DEVELOPMENT OF MAGNETORHEOLOGICAL ELASTOMER LINEAR ACTUATOR
No full textNowadays, the piezoelectric actuator is commonly used in micro-scale precision systems. However, the use of piezoelectric material is limited to a certain degree of motions because this material has a high tendency to fracture when prolonging exposure to vibrant environments. In contrast, magnetorheological elastomers (MRE) material has high elasticity properties which could capable to withstand this environment. Thus, this project aimed to use MRE in the development of the linear actuator system and observed its displacement responses. The MRE specimens were fabricated using silicon rubber and magnetic particle with the composition of 70/30, 60/40, 50/50, 40/60, and 30/70 percent by its weight percentage (wt%) using compression moulding technique. The surface morphologies were performed to observe the distribution of the particles. Then, the vision-based measurement system was developed in order to perform a displacement test on the MRE specimens. Besides that, the system is also acting as displacement feedback for MRE linear actuator closed-loop control system. System identification approach was adapted to estimate an MRE linear actuator plant model and then used to tune a proportional integral derivative (PID), controller. Prior testing, a sample of the linear actuator was designed and simulated using SOLIDWORKS 2016 x64 Edition and Finite Element Magnetic Method (FEMM) 4.2, respectively in order to observe the magnetic field. It is observed that magnetic particles distributed on the specimen surface similar to the isotropic types. Besides, the vision-based positioning system developed was reported having an accuracy of up to 0.0025 μm. Furthermore, the highest displacement span was 84 μm, which obtained from composition 50/50 silicon rubber: magnetic particles by its wt%. The experimental result shows that the PID controller successfully reduces a steady-state error (7 μm) and settling time (12s) for MRE linear actuator. According to the finite element analysis, the maximum magnetic density observed at plunger with the value of 1.8 tesla. MRE plant model was successfully developed by 85% fitted to real experimental data. Besides, the PID values for Kp, Ki, and Kd were tuned to 5.26, 5.25 and 0, respectively. As a conclusion, the MRE using silicon rubber and magnetic particle were successfully developed and 50/50 by wt% composition had optimum displacement response. Furthermore, the displacement response for MRE based actuator design used in this research was comparable to the existing linear actuator. The vision-based positioning system developed also can be used as measurement and control the displacement in the actuator application
RATIONAL DECISION MODEL FOR SELECTION OF IMPROVEMENT INITIATIVE USING EXPERT MAPPING STUDY
No full textThe rapid interest growth for the adoption of Improvement Initiative (IMI) indicates
the importance of improvement to sustain the business and to remain competitive. This
phenomenon contributes to the extensive evolution of IMI introduced throughout the
recent decades compared to its initial introduction. However, the existence of a bundle
of IMI has caused difficulties to organizations to select the most suitable improvement
initiative to be adopted. In addition, the failure in the deployment of IMI in numerous
organizations has been frequently reported to be associated with a poor selection. In
the absence of explicit key decision criteria, decision makers highly depend on
subjective judgements which are biased to the experience and which tend to follow the
fashion setting. This study aimed to fill the research gap by proposing the rational
selection for IMI adoption based on the phenomena and developing a theory of
selection by bringing all influential criteria together in one comprehensive model. This
study incorporated cross-paradigm (Constructivism & Positivism) as a research
paradigm and adopted a mix method research, including quantitative and qualitative
to meet its objective. Based on rigorous systematic literature review (SLR) steps, a
total of 164 publications were used to extract and synthesize the information. The
information from the SLR enables the development of an empirical model for the
selection of IMI through the provision of wide angles selection criteria which provide
holistic decision supports for decision makers. The quantitative research approach was
adopted to ensure generalization of the model, highlighted as limitations by previous
researchers with a total of 241 respondents’ feedback from various organizations. The
reflective-formative hierarchical model was analyze using structural equation
modelling through Smart PLS software in order to develop rational selection model
for IMI. Upon validation of the model, six selection views with 33 attributes were
decided to be considered by decision makers prior making decisions on the most
suitable IMI to be adopted in their organizations. The development of intelligent
decision support system for IMI selection was derived from the mapping of IMI with
selection criteria based on experience and knowledge of experts. The functionality of
the system was tested through Black Box Testing prior measuring the practicality of
the system to help the decision makers by using a structured case study protocol. The
results from Kendal Coefficient of Concordance analysis indicate that, the system is
able to perform well to help decision makers to select the most suitable IMI to be
implemented in their organizations. As a conclusion, this empirical study provides
rational decision making for the selection of IMI by providing wide angle selection
criteria which avoid subjective judgements which could lead to the failure of
improvement in the organizations. The rational selection model enables organizations
to manage and carefully select improvement initiatives to ensure effectiveness of the
selection and a successful implementation of IMI
A review of recent developments in polymeric materials for battery energy storage
No full textThis article is index by ScopusThis review explores the innovative role of polymer electrolytes in energy storage systems, emphasizing their characteristics, fabrication methods, and practical applications in advanced electrochemistry. It begins by outlining various types of polymeric material, including conductive polymers, redox-active polymers, and polymer electrolytes, that improve the lifetime, efficiency, and capacity of energy storage devices. A comprehensive review of polymeric electrochemistry is provided, focusing on how polymers maintain electrical insulation and enable ion transport, two essential functions for devices such as supercapacitors and batteries. Advanced fabrication techniques, including solution casting, melt processing, electrospinning, and in-situ polymerization are emphasized for tailoring polymer electrolytes to achieve optimal microstructural and electrochemical properties. The study further explores the electrochemical characteristics of polymer electrolytes, focusing on the electrochemical impedance spectroscopy technique. By offering a thorough understanding of both the theoretical and practical aspects of polymer electrolytes, this study contributes to the development of more effective and long-lasting energy storage systems. This discussion aligns with the global trend toward innovative and eco-friendly energy technologies while advancing the field of materials research
Magnetic bead catalyst for photocatalytic phenol degradation in wastewater
No full textThis article is index by ScopusModern advances in semiconductor photocatalysis, particularly increased turnover on degradation of phenolic compounds from industrial wastewater. Phenolic compound is a major environmental threat considering their hazardous effects and recalcitrance. This study focused on the development of high efficiency magnetic bead catalyst with photocatalysis technology as a solution to phenolic compound obstacles in industrial wastewater. The magnetic bead catalyst underwent bead casting process by encapsulating a polymer matrix of sodium alginate and crosslinking it with epichlorohydrin, which enhancing its hydrophilicity, durability, rigidity, selectivity, permeability, and longevity, thereby achieving superior photocatalytic performance. Characterisation techniques including Fourier-transform infrared spectroscopy (FTIR) and X-ray diffraction (XRD) were employed to analyse the structural and chemical properties of these catalyst. The photocatalytic efficiency of the magnetic bead catalyst for the degradation of phenol was assessed when subjected to visible light. A comprehensive study was conducted exploring the effects of pH, catalyst dosage, and initial phenol concentration on effectiveness of degradation. The optimal conditions for the Fe-beads catalyst were achieved at pH 5, with a dosage of 6.0 g L−1 and an initial phenol concentration of 20 mg L−1, resulting in a phenol photodegradation efficiency of 87.29%. These magnetic bead catalyst implementations for wastewater recovery were cost-effective, quick to implement, eco-friendly, and regenerable. In short, synthesising magnetic bead catalyst might pose an innovative approach towards challenges with wastewater treatment