The benefits of optical fiber sensors have been fully reflected by their widespread use in industrial production and environmental sensing. Several types of sensors with various structural variations have arisen in order to satisfy the demands of various applications and enhance the performance of optical fiber sensors. Consequently, the development of optical fiber sensors with different coating materials has become the primary focus of numerous researchers. In this study, the development of coating materials of optical fiber sensors for different applications in last 10 years has been depicted.

The convergence of nanotechnology and biology has given rise to nano-biosensors, integrating biological sensing components with diverse nanomaterials and holding vast potential in biomedicine. Materials such as nanotubes, graphene, and CNT-based sensors enable precise detection through intricate biochemical reactions. This synergy has led to wearable biomarkers, flexible sensors, and micro-biosensors bridging the macro and nano realms, promising revolutionary advancements in health monitoring, diagnostics, and medical implants. Moreover, electrochemical organic conducting salts and derivatives exhibit promise in analyte detection due to their unique electrochemical characteristics, while graphene's remarkable electronic properties make it versatile in various fields. Enzymatic and non-enzymatic biosensors using graphene detect chemicals such as glucose and heavy metal ions. Reduced graphene oxide enhances detection, particularly in ion-sensitive transistors. Biocompatible polymers and nanomaterials offer selectivity for biomolecules in medical and environmental monitoring. Bioresorbable sensors offer a solution for accurate pressure monitoring without surgical removal. The evolution of biosensors based on field-effect transistors and the potential of plasmonic materials, specifically surface plasmon resonances, further elevate biosensor capabilities.

Sensor technologies have had a significant impact on the development of intelligent manufacturing and industry 4.0. In the internet of things era, many sensor technologies are crucial for data collection and efficiently utilizing the manufacturing processes. Moreover, sensor technologies have enhanced humankind's quality of life because of their widespread applications in almost all fields. Sensors track changes in the environment or source and collect signals that serve as the basis for the reaction. Innovative sensor technologies are used in a variety of fields, including lifestyle, food safety standards, defense, security, healthcare, fitness, manufacturing, environmental contaminants, medicine, and daily living. Ultrasound, radar, noncontact optoelectronic solutions, laser technology other industrial advances are now driving sensor innovation. Therefore, scientific advances in sensors are important for understanding technological and societal change. This review provides a broad overview of new developments in different types of sensors, identifies and discusses significant applications of sensors, and creates an agenda for future research that encompasses various capabilities of sensor technologies associated with the industry fourth revolution. Moreover, the most recent innovations in the world of sensing materials and future trend is to make sensor devices more affordable has also been discussed. High energy consumption, cost reduction, various process stages, and incorrect model inputs because of sensor flaws are some of the biggest hurdles in sensor development. Some novel sensor technologies are required to be capable of providing functionalities and implementing new ecologies such as the Internet of Things, Precise Agriculture, and Smart Grids. Modern methods, such as flexible or elastic electronics, are required for applications in industries like augmented reality and rehabilitation. Additionally, numerous other anticipated uses have increased the demand for sensors as an extension of perceptive functions in recent decades and boosting interest in sensors.

Municipal solid waste management (MSWM) poses a considerable challenge to developing countries like Bangladesh because of the rising waste generation rates and lack of effective management practices such as illegal open dumping and informal waste collection. One of the crucial factors in the successful management of MSW is to select the appropriate technology which is a complex multi-criteria and laborious process. Despite the global emphasis on the importance of MSWM in the literature, there is a lack of studies conducted in developing countries that effectively identify and analyze the critical performance criteria for appropriate technology selection. This research aims to address this shortcoming by identifying, and prioritizing the selection criteria and finally investigating the inter-relationship between them and the degree to which they affect or are affected by one another. First, a thorough literature review and expert consultation were employed to determine a set of 21 key criteria using the Fuzzy Delphi method (FDM). Later, taking into account the imprecise and subjective nature of the DEMATEL method on human judgements, the Fuzzy DEMATEL technique was employed to investigate the cause-effect relationships among the identified criteria. The findings of the study demonstrated that 14 criteria were categorized as causal elements that have the most significant influence on the MSWM technology selection process and 7 criteria were categorized as effect. The selection of MSWM technology demands greater consideration of the top three ranked criteria, namely T4- Access to Technology (AT), T8- Feasibility (F), and the Ec6-Infrastructure requirements (IR). By identifying the pertinent criteria, structures and interrelationships, the outcome of the study can facilitate a better understanding of causal relationships among the criteria that require specific consideration from the decision-makers and allow them to select appropriate MSW management technology.

Heat-treated steel is widely used in industrial applications due to its high strength and other desirable mechanical qualities. Grinding, which requires a lot of power and is expensive, is typically used to harden machining. In recent times, hard machining has emerged as a viable alternative to grind in select applications. In this investigation, turning operations with a carbide insert (CNMA 120408-KR3215) were carried out on SKD 11 (53 HRC) hardened steel. A total of nine machining tests were completed using the L9 orthogonal array. The response variables considered in this study were surface roughness (Ra) and material removal rate (MRR). The analysis of the signal to noise ratio reveals that the optimal combination of cutting process parameters for achieving a desired surface roughness consists of a cutting speed of 119 m/min, a feed rate of 0.11 mm/rev, and a depth of cut of 0.2 mm. The contribution of each process parameter to the machining performance of the carbide tool-work piece combination is determined through the use of ANOVA. Depth of cut has the greatest impact (57.33%) to MRR, while feed rate has the highest contribution (82.15%) to Ra. Moreover, desirability function analysis (DFA) was conducted to optimize the multiple responses. DFA suggested that, to attain a satisfactory response to the output parameters, higher range of cutting speed, depth of cut, and lower range of feed rate are appreciable; therefore, the analytical findings suggest that a cutting speed of 189 m/min, feed rate of 0.11 mm/rev, and a depth of cut of 0.5 mm can induce a favorable Ra of 0.971 μm and MRR of 10.248 cm3/min. In hard machining, cutting speed has a bigger influence on surface finish than feed rate.

The optimum utilisation of CuO-nanofluid in flat plate solar collector has been investigated under Malaysian climatic condition. To determine the optimum nanoparticle concentration required in the base fluid, a simulation was carried out using MATLAB program. From the simulation, it was found that, 0.5 vol.% of CuO nanoparticles in the base fluid yielded maximum collector efficiency. The test was conducted over six months following the ASHRAE standard with nanofluid in the flat plate collector to ascertain its efficiency. The maximum average solar radiation incident on the collector, collector outlet and ambient temperatures were observed about 1000 W/m2, 50 ºC and 38 ºC respectively. From the efficiency curve, the absorbed and removed energy parameters were found to be 0.501 and 24.23 respectively. At a mass flow rate of one litre per minute, the maximum average instantaneous efficiency was 51%. The result of experimental efficiency was compared with the result of simulation and the efficiency values were within 4% of each other. CuO nanofluid base collector increases the efficiency compared to water as the collector fluid. The experimental results revealed that the efficiency of FPSC with CuO nanofluid was 4.78% higher than water base collector at the same mass flow rate of 1 L/min. The uncertainty analysis of result has shown that instantaneous efficiency uncertainty was about 3.3%. The simulation result has indeed minimised number of experiments required to determine the optimum concentration of nanofluid for maximum efficiency.

Currently, the industry generally uses electrical discharge machining (EDM) with kerosene facing problems in terms of processing efficiency, perilous environment, and low quality of the machined surface. In this paper, water-in-oil (W/O) emulsion dielectric is introduced as an alternative for this drawback. Kerosene has low properties especially thermal conductivity, viscosity and, higher heat capacity. Vegetable oil such as canola oil can be selected as an alternative dielectric fluid. This work has measured the properties of canola oil including thermal conductivity, heat capacity and viscosity for possible use as a dielectric fluid. The result shows that the emulsion of canola oil has the best combination at 35wt% of Tween20 with heat applied.

The quality enhancement during massive production of the traditional machining products is a risky challenge when the cost and environmental impact must be considered. The tool life, material recycling, energy consumption, space, and environmental pollution are the direct and indirect factors to increase the cost during different machining processes. Treatment of cooling liquids to be eco-friendly and cheaper, and machining tools to enhance their surface morphology and increase their lives are the keys of the sustainable machining. This paper reviews the sustainability evaluation and the performance of different types of cooling fluids and lubricants, and surface texture modification of tool surfaces and their effects on the machining outputs and environment as well.

In this work, locally sourced non-hazardous materials were used to produce brake pad using grey relational analysis (GRA) and experimental design via central composite design. Raw materials selected for production include coconut shell, epoxy resin (binder), graphite (friction modifier) and aluminum oxide (abrasive). Twenty-seven samples were produced separately using coconut shell as reinforcement material by varying process parameters. Formulation of the brake pads samples was done using rule of mixture and a weight percent of 52% reinforcement material, 35% binder, 8% abrasive and 5% friction modifier were used for the production. Grey relational analysis (GRA) shows that optimal process performance can be obtained using molding pressure, molding temperature, curing time and heat treatment time of 14 MPa, 140 °C, 8 min and 5 h, respectively. Optimized sample was produced using the optimal set of process parameters obtained from GRA and compared with commercially available sample produced by Ibeto Group. The experimental results showed that the performance of the optimized coconut shell-reinforced brake pad compared satisfactorily with commercially available samples and capable of producing less brake noise and vibration during application. Analysis of variance shows that curing time with a contribution of 30.38% and 31.40% have the most significant effect on the hardness and ultimate tensile strength of the coconut shell-reinforced friction material, respectively, while heat treatment time with a contribution of 46.3% and 24.23% have the most significant effect on the wear rate and friction coefficient of coconut shell-reinforced brake pad, respectively. The effects of all the factors on the properties of the friction materials are significant since their p values are greater than 0.010 (1%).

Product quality is one of the important aspects in deep drawing practice and the variation in process temperature was claimed to improve the quality. Therefore, in this research, the effect of the heating temperature on the drawability of a circular metal cup has been investigated. Firstly, circular metal cups of aluminium, mild steel and stainless steel were drawn from the blank diameters of 60 mm, 65 mm, and 70 mm. The experiment was conducted at room temperature followed by at 100 °C, 150 °C and 200 °C. The Taguchi method was selected as the design of experiment approach, and L9 (34) array design methodology was adopted in this experimental research. The drawability was measured based on the punching force needed to deform the sheet metal blanks. The deep drawing process was conducted at room, and elevated temperature conditions and the response factor was analysed and compared through the analysis of variance (ANOVA) statistical approach. The results obtained from ANOVA indicate that the blank material has a significant influence on the deep drawing process followed by the blank size, heating temperature and heating technique. The optimal parameter combinations are blank diameter of 60 mm, heating temperature of 200 °C and the die and punch heating technique. Out of the three materials investigated, aluminium has a better drawability compared to mild steel and stainless steel.

The use of vegetable oil as a replacement for conventional mineral-based lubricant has gained many interests in recent years from the machining industries. This is due to the problematic issues with the use of conventional mineral-based lubricant that can cause negative effects on the manufacturing cost, operators' health and the environmental. As vegetable oil is renewable, biodegradable, and non-toxic and has remarkable tribological characteristic from its triglycerides structure, it has been identified as the best replacement for mineral-based cutting lubricant. However, formulating vegetable oil into machining lubricant has its challenges where it must overcome its nature of poor low-temperature properties and low oxidative stability. Therefore, this paper will elaborate the present issues and challenges in formulating green machining lubricant using vegetable oil and its stand under sustainable machining. This includes the method and technique of formulating vegetable-based lubricant and the output performance obtained from vegetable-based lubricant under machining in comparison to the conventional mineral-based lubricant. The result shows that utilizing the vegetable-based lubricant at minimum quantity has comparable or better performance to conventional mineral-based lubricant in terms of surface finish. Therefore, the use of vegetable oil has its challenges and issues as machining lubricant, but it is one of the current best viable alternatives to the mineral-based lubricant in promoting sustainable machining.

Numerous types of hybridizations between type 2 fuzzy logic system (T2FLS) and sliding mode control (SMC) have been proposed to construct an intelligent and robust controller that departs from the drawbacks of SMC and T2FLS. Recently, these hybridizations have been extended to the hybrid structures that are composed of type 2 fuzzy neural network (T2FNN) and SMC in order to produce adaptive, intelligent and robust controllers. Moreover, optimization algorithms are integrated with these controllers in order to tune/optimize their parameters for a superior control performance. In this paper, a survey of the advances on the hybridization of T2FLS, T2FNN, SMC and computational intelligence algorithms is presented. It has been observed that all the works involving T2FLS employed interval type 2 fuzzy logic systems. Despite the advantages of general type 2 fuzzy logic systems (GT2FLS), no record of applying GT2FLSs has been encountered in this domain. The trend of publications, the limitations associated with previous works and future research directions are outlined in the paper. Expert researchers can use this survey as a benchmark for proposing novel approaches while novice researchers (especially graduate students) can use this survey as a starting point.