Search results

The combined heat and power dispatch (CHPD) aims to optimize the outputs of online units in a power plant consisting thermal generators, co-generators and heat-only units. Identifying the operating point of a co-generator within its feasible operating region (FOR) is difficult. This paper aims to solve the CHPD problem in static and dynamic environments.

The CHPD plant operation is formulated as an optimization problem under static and dynamic load conditions with the objectives of minimizations of cost and emissions subject to various system and operational constraints. A novel bio-inspired search technique, grey wolf optimization (GWO) algorithm is used as an optimization tool.

The GWO-based algorithm has been developed to determine the preeminent power and heat dispatch of operating units within the FOR region. The proposed methodology provides fuel cost savings and lesser pollutant emissions than those in earlier reports. Particularly, the GWO always keeps the co-generator’s operating point within the FOR, whereas most of the existing methods fail.

The GWO is applied for the first time to solve the CHPD problems. New dispatch schedules are reported for 7-unit system with the objectives of total fuel cost and emission minimizations, 24-unit system for economic operation and 11-unit system in dynamic environment. The simulation experiments reveal that GWO converges quickly, consistent and the statistical performance clears its applicability to CHPD problems.

Generator maintenance scheduling (GMS) is an essential task for electric power utilities as the periodical maintenance activity enhances the lifetime and also ensures the reliable and continuous operation of generating units. Though numerous meta-heuristic algorithms have been reported for the GMS solution, enhancing the existing techniques or developing new optimization procedure is still an interesting research task. The meta-heuristic algorithms are population based and the selection of their algorithmic parameters influences the quality of the solution. This paper aims to propose statistical tests guided meta-heuristic algorithm for solving the GMS problems.

The intricacy characteristics of the GMS problem in power systems necessitate an efficient and robust optimization tool. Though several meta-heuristic algorithms have been applied to solve the chosen power system operational problem, tuning of their control parameters is a protracting process. To prevail over the previously mentioned drawback, the modern meta-heuristic algorithm, namely, ant lion optimizer (ALO), is chosen as the optimization tool for solving the GMS problem.

The meta-heuristic algorithms are population based and require proper selection of algorithmic parameters. In this work, the ANOVA (analysis of variance) tool is proposed for selecting the most feasible decisive parameters in algorithm domain, and the statistical tests-based validation of solution quality is described. The parametric and non-parametric statistical tests are also performed to validate the selection of ALO against the various competing algorithms. The numerical and statistical results confirm that ALO is a promising tool for solving the GMS problems.

As a first attempt, ALO is applied to solve the GMS problem. Moreover, the ANOVA-based parameter selection is proposed and the statistical tests such as Wilcoxon signed rank and one-way ANOVA are conducted to validate the applicability of the intended optimization tool. The contribution of the paper can be summarized in two folds: the ANOVA-based ALO for GMS applications and statistical tests-based performance evaluation of intended algorithm.

The purpose of this paper is to review Lean Six Sigma (LSS) literature and report different definitions, demographics, methodologies and industries.

This paper highlights various definitions by different researchers and practitioners. A total of 235 research papers has been reviewed for the LSS theme, research methodology adopted, type of industry, author profile, country of research and year of publication.

From the review, four significant LSS classifications were identified that deal with the spread of LSS in different industries followed by observation for classification.

LSS is a strategy for success, but it did not examine its presence in various Industries. From this paper, readers can understand the quantum of its spread before implementing LSS. For academicians, it will be a comprehensive list of papers for research.

This paper reviews 235 research papers for their year, author profile, research methodology and type of industry. Various characteristics of LSS definitions and their theme are also reviewed.

The demand for aluminium alloys has been increasing in almost all the fields. In this study, the friction stir welding (FSW) of similar aluminium alloy AA 8011-h14 has been presented using three levels of tool rotational speed (n), tool tilt angle (ϴ) and tool feed (f). The purpose of this paper is to study the effect of welding parameters on various properties and time-temperature plots.

FSW was carried out using the L-9 orthogonal array of welding parameters generated using the Taguchi approach. Visual inspection and radiography testing were conducted to detect the surface and volume defects, respectively. Taguchi analysis was carried out to get optimised welding parameters for tensile testing. The microstructural analysis was carried out for the specimen possessing maximum tensile strength and the obtained grain structures were compared with the microstructure results of the base material. The peak process temperatures were noted and time-temperature plots were analysed for the varying parameters. The maximum value of hardness was recorded and analysed.

Visual inspection and radiography testing confirmed defect-free joints. The maximum tensile strength achieved was 84.44 MPa with 64.95 per cent efficiency. The optimised parameters obtained using Taguchi analysis for tensile testing were 1,500 rpm, 1° and 50 mm/min. Microstructure analysis for the specimen possessing maximum tensile strength revealed fine and equiaxed grains in the nugget zone. Time-temperature plots suggested the maximum temperature of 389 °C on the advancing side. A maximum hardness value of 36.4 HV was obtained in the nugget zone.

As per the knowledge of the authors, this study is the first attempt for the detailed experimental analysis on the FSW of this particular aluminium alloy AA 8011-h14.

The purpose of this study is to understand the behavior of hybrid bio-composites under varied applications.

Fabrication methods and material characterization of various hybrid bio-composites are analyzed by studying the tensile, impact, flexural and hardness of the same. The natural fiber is a manufactured group of assembly of big or short bundles of fiber to produce one or more layers of flat sheets. The natural fiber-reinforced composite materials offer a wide range of properties that are suitable for many engineering-related fields like aerospace, automotive areas. The main characteristics of natural fiber composites are durability, low cost, low weight, high specific strength and equally good mechanical properties.

The tensile properties like tensile strength and tensile modulus of flax/hemp/sisal/Coir/Palmyra fiber-reinforced composites are majorly dependent on the chemical treatment and catalyst usage with fiber. The flexural properties of flax/hemp/sisal/coir/Palmyra are greatly dependent on fiber orientation and fiber length. Impact properties of flax/hemp/sisal/coir/Palmyra are depended on the fiber content, composition and orientation of various fibers.

This study is a review of various research work done on the natural fiber bio-composites exhibiting the factors to be considered for specific load conditions.

The main purpose of the present work is to study the multi response optimization of dissimilar friction stir welding (FSW) process parameters using Taguchi-based grey relational analysis and desirability function approach (DFA).

The welded sheets were fabricated as per Taguchi orthogonal array design. The effects of tool rotational speed, transverse speed and tool tilt angle process parameters on ultimate tensile strength and hardness were analyzed using grey relational analysis, and DFA and optimum parameters combination was determined.

The tensile strength and hardness values were evaluated from the welded joints. The optimum values of process parameters were estimated through grey relational analysis and DFA methods. Similar kind of optimum levels of process parameters were obtained through two optimization approaches as tool rotational speed of 1150 rpm, transverse speed of 24 mm/min and tool tilt angle of 2° are the best process parameters combination for maximizing both the tensile strength and hardness. Through these studies, it was confirmed that grey relational analysis and DFA methods can be used to find the multi response optimum values of FSW process parameters.

In the present study, the FSW is performed with L9 orthogonal array design with three process parameters such as tool rotational speed, transverse speed and tilt angle and three levels.

Aluminium alloys are widely using in automotive and aerospace industries due to holding a high strength to weight property.

Very limited work had been carried out on multi objective optimization techniques such as grey relational analysis and DFA on friction stir welded joints made with dissimilar aluminium alloys sheets.

Composite materials are replacing the traditional materials because of their remarkable properties and the addition of nanoparticles making a new trend in material world. The nano addition effect on tribological properties is essential to be used in automotive and industrial applications. The current work investigates the sliding wear behavior of an aluminum alloy (AA) 6061-based hybrid metal matrix composites (HMMCs) reinforced with SiC and B₄C ceramic nanoparticles.

The hybrid composites are fabricated using stir casting process. Two different compositions were fabricated by varying the weight percentage of the ceramic reinforcements. An attempt has been made to study the wear and friction behavior of the composites using pin-on-disc tribometer to consider the effects of sliding speed, sliding distance and the normal load applied.

The tribological tests are carried out and the performances were compared. Increase in sliding speed to 500 rpm resulted in the rise of temperature of the contacting tribo-surface which intensified the wear rate at 30N load for the HMMC. The presence of the ceramic particles further reduced the contact region of the mating surface thus reducing the coefficient of friction at higher sliding speeds. Oxidation, adhesion, and abrasion were identified to be the main wear mechanisms which were further confirmed using energy dispersive spectroscopy and field emission scanning electron microscopy (FESEM) of the worn out samples.

The enhancement of wear properties is achieved because of the addition of the SiC and B₄C ceramic nanoparticles, in which these composites can be applied to automobile, aerospace and industrial products where the mating parts with less weight is required.

The influence of nanoparticles on the tribological performance is studied in detail comprising of two different ceramic particles which is almost new research. The sliding effect of hybrid composites with nano materials paves the way for using these materials in engineering and domestic applications.

This research aims to identify lean tools and techniques that are needed to be implemented to improve the performance in the fabrication industry. The objective is to find the wastes in manufacturing processes using value stream mapping (VSM) and prioritize the lean tools suitable to enable the attainment of leanness and streamline the processes.

VSM tool is applied in the industry to construct the current state map, identify improvement proposals and implement in future state. Fuzzy technique for order performance by similarity to ideal solution (TOPSIS), a multi-criteria decision-making technique (MCDM), is used to prioritize the identified improvement proposals. This study observed that mistake-proof processing and layout organization are the two techniques with the top priority that needs further improvement to enhance the leanness of the organization.

Upon successful implementation, the cycle time is reduced by 14.97%, and total inventory is reduced by 45.67% which leads to the improvement of value addition from 5.88 to 9.21%. Although lean has been adopted for many years, implementation of lean in the fabrication industry has been limited.

This study addresses the challenges in terms of implementing lean in fabrication industries and practical implications of lean tools and techniques and the prioritization of lean concepts against various lean criteria to enable leanness.

The deployment of improvement prioritization tool integrated with VSM in the context of a fabrication industry is the original contribution of the authors.

The purpose of this paper is to analyze wind climate parameters and performance functions, on the basis of two years of data, and reliability of Pakistan’s first wind farm located at Jhimpir, Sindh.

The methodology covers assessment of wind climate parameters including wind variation at different hub heights, wind shear and diurnal wind shear. In addition, a performance assessment of a wind farm on the basis of technical and real availability, capacity factor and failure rate of mechanical and electrical components has been conducted. The Weibull method has been used for reliability analysis. The maintenance model is proposed for improving the performance. Last is about annual energy volume lost and of financial constraints’ assessment.

The monthly mean wind variation at heights of 80, 60 and 30 m was found to be 8, 6.9 and 5.9 m/s, respectively. The monthly mean wind shear coefficient was found to be 0.2419. The performance assessment of the wind farm includes technical and real availability, and the capacity factor was found to be 97, 90 and 35.5 per cent, respectively. The failure rate found in the first and second year was 8 and 14 per cent, respectively. Reliability decreased from the first year to the second year, i.e. 0.89 to 0.71 per cent. The components’ failure frequency rose to 57.2 per cent in the second year. The lost energy production due to electrical and mechanical failures was 27.241 GWh in two years that cost Pakistani Rs. 329.8m.

The results of the assessment show that a wind farm needs drastic maintenance strategies to maximize the its performance.

The purpose of this paper is to develop an optimization model allowing the choice of parts feeding policy to assembly lines in order to minimize total cost.

An integer linear programming mathematical model is developed to assign the optimal material feeding policy to each part type. The model allows choice between kitting, line stocking and just in time delivery policies.

The choice of assembly lines feeding policy is not trivial and requires a thorough economic comparison of alternatives. It is found that a proper mix of parts feeding policies may be better that adopting a single material delivery policy for all parts.

The model is aimed at single-model assembly lines operating in a deterministic environment, but can be extended to the multi-model line case. While relevant quantitative cost drivers are included, some context-related qualitative factors are not included yet. The model assumes that information about product structure and part requirements are known and that a preliminary design of the assembly system has been carried out.

Production managers are given a quantitative-decision tool to determine the optimal mix of material supply policies at an early decision stage.

Respect previous simplified literature models, this approach allows to quantify a number of additional factors which are critical for successful implementation of cost-effective parts feeding systems, allowing comparison of alternative policies on a consistent basis.