Energy Science, Engineering and Technology
Performance Analysis of IoT-based Temperature Monitoring Box Type Solar Cooker: A Multi-objective Optimization Approach
The idea behind the Internet of Things is to bring the virtual world into the physical one by connecting commonplace items. With the help of the Internet of Things (IoT) it is possible to remotely sense or control objects through preexisting network infrastructure. This opens up possibilities for computer-based systems to integrate with the physical world which in turn improves efficiency accuracy and economic benefit while reducing the need for human intervention.
The purpose of this patent study is to investigate how a (NSGA-II) multi-objective genetic algorithm might be utilized to optimize the execution of an Internet of Things (IoT) temperature monitoring Box-Type Solar Cooker (BTSC). To determine the best set of output parameters for an IoT temperature monitoring box-type solar cooker (NSGA-II) multi-objective genetic algorithms are used to perform optimizations of the figure of merits (F2) cooking power cooker efficiency and final water temperature.
The present research work involves the development of a Wi-Fi module system integrated with a smart temperature monitoring system for a BTSC. Keeping track of the temperature data from different locations in the BTSC through the IoT system was the primary objective of this project. A waterproof temperature sensor (DS18B20) was used to keep monitoring. After that the data was shown on an LCD stored on a microSD card and made available through a smartphone. The Blynk Applications' IoT was employed. Using existing data regression-based computational models are developed to describe the complex correlations between the decision-processing parameters and the input parameters of an IOT-based solar cooker. These models are applied in the objective functions after determining that a genetic algorithm is more appropriate for the problem. To forecast the optimal values about the figure of merits (F2) cooking power cooker efficiency and final water temperature the Pareto fronts have been developed.
We compare the values of response variables that were gathered experimentally with the values that were predicted by NSGA-II. The predicted values are found to be quite close to experimental values. This indicates that the multi-objective optimization method as used in this study has very good prediction performance. The test results are graphically shown using the error bar. Therefore it is clear that the optimization process used to adjust the parameters of the solar cooker's performance has been quite effective. According to the findings of the experiment the temperature at which a cooking pot remained stagnant on average was 158°C. It was determined that the cooker was of class A based on the values of the first figure of merit (F1) the second figure of merit (F2) and the cooking power (P) which were respectively 0.132 0.359 and 86.108 W. Therefore the thermal efficiency of the IoT-base temperature monitoring box type solar cooker is 39.99%.
The findings of this inquiry furthermore produced the outcome that the model provided can be applied conveniently with a confidence level of 95% to calculate the figure of merits (F2) cooking power cooker efficiency and final water temperature value of an Internet of Things-based temperature monitoring BTSC. The performance of IoT-based BTSC is optimized by providing real-time monitoring and data visualization ultimately improving their efficiency and reliability. This research provides an educational tool to promote awareness and understanding of renewable energy sources and their potential benefits.
Preparation and Characterization of Fe3O4-Modified Graphene Oxide as Heat Transfer Additive for Paraffin Wax Applications
In phase change thermal management systems the development of magnetic phase change materials offers the possibility of effectively integrating passive and active heat control technologies..The low dispersibility of traditional heat transfer additives the high interfacial thermal resistance with phase change matrices and the restricted magnetic response characteristics are some of the current problems that must be resolved.
To overcome these challenges this study employed a co-precipitation method to composite magnetic nanoparticles Fe3O4 with graphene oxide (GO). The active sites on GO were functionalized with alkyl groups to prepare Fe3O4-modified graphene oxide (Fe3O4-MGO)/paraffin magnetic composite phase change materials. The morphology structure chemical composition and thermal properties of the resulting magnetic composite phase change materials were tested and characterized.
The results indicated that Fe3O4-MGO exhibits good dispersibility in paraffin which can enhance the thermal conductivity of the phase change material. The thermal conductivity of the composite phase change material with a Fe3O4-MGO mass fraction of 2.0% was measured to be 0.461 W/m·K representing a 47.3% increase compared to pure paraffin. Additionally Fe3O4-MGO demonstrated a certain phase change capability with a phase change enthalpy reaching 70.35 kJ/kg.
The findings of this study are expected to provide technical support for innovative applications of magnetic-controlled phase change thermal management.
Impact of 3D Printing Settings on Polylactic Acid Filament Mechanical Behaviors Based on the Taguchi Method
3D printing has become an activity changer in some sectors allowing the creation of personalized parts. With its growing popularity in areas needing mechanical capabilities it is essential to grasp how the printing settings impact the mechanical traits of the printed pieces.
This paper presents a novel investigation into the impact of critical 3D printing parameters on the mechanical characteristics of polylactic acid (PLA) a widely used biocompatible and biodegradable polymer. Our experimental approach systematically evaluated the effects of various printing parameters including infill density raster orientation outline overlap and print speed on the printed parts' tensile strength and Young's modulus.
The results consistently showed that increasing the infill density and outline overlap improved tensile strength and Young's modulus. However higher print speeds decreased both underscoring the practical application of our unique findings. This research is a pioneering effort providing engineers and designers with valuable direction for working with 3D-printed PLA parts in aerospace automotive and biomedical applications.
It significantly adds to the expanding corpus of research on the connection between 3D printing process variables and the mechanical characteristics of advanced polymeric materials.
Computational Fluid Dynamics Analysis and Optimization of a Double-suction Turbine Agitator
As one of the essential pieces of chemical equipment a reactor provides the necessary reaction space and conditions for the materials involved in the reaction during the stirring process. However under typical operating conditions issues such as uneven gas distribution suboptimal gas-liquid mixing and low product yield often arise in gas-liquid phase reactors.
To address the issues prevalent in current stirred reactors a new design for a stirred reactor equipped with a double-suction turbine agitator was developed.
In this paper a stirred reactor equipped with a double-suction turbine agitator was designed and its three-dimensional modeling was conducted using SolidWorks. Computational Fluid Dynamics (CFD) simulations based on the Euler-Euler two-phase approach with the RNG k − ε turbulence model were performed to assess variables such as stirring speed installation height blade diameter and agitator inner diameter. The dispersion characteristics and flow field behaviors of the gas-liquid two-phase under varying conditions were comparatively analyzed. Optimizations were conducted across various parameters to enhance the gas mixing efficiency in the liquid phase.
The results show that a diameter of 370mm for the double-suction turbine agitator an installation height of 640mm a blade diameter of 500mm and an inner hole diameter of 200mm yield optimal gas-liquid two-phase mixing performance. This configuration results in a broad and uniform gas distribution within the reactor maintaining a desired high level of gas holdup at specific positions.
The double suction turbine agitator is a type of radial agitator. During operation it induces significant centrifugal forces in the liquid exerts a robust shear effect and enhances the mixing of the gas-liquid phases thereby increasing the production efficiency of the product.
Research Progress on Industrial Robots: A Review
The success of the fourth and upcoming fifth industrial resolution lies majorly in automation and robotics. Industrial robots perform various manufacturing-related tasks due to their autonomy flexibility and autonomous work in a complex environment. Applications including drilling material transfer loading and unloading machines processing assembling and inspection welding spray painting machining and so on are common. The present work comprehensively summarizes all the pertinent work related to the industrial robot such as inverse kinematics problems robot design programming scheduling motion planning and trajectory planning. In addition the present work discusses various optimization algorithms employed in industrial robots. Furthermore several recommendations for future research have been addressed.
RSM Hybrid Modeling of a BSFC for a Single Cylinder Four Stroke CI Engine Fueled with Nano-additives Added to Diesel-biodiesel Fuel Blends
The expanding need for fossil fuels emphasizes the necessity to comprehend renewable energy sources.
This study examined the performance of a single-cylinder diesel engine using Jatropha biodiesel and aluminum dioxide the research aimed to evaluate engine reactivity to compression ratio and load variations. The experiment employed with varitaion compression ratios
This study used the Response Surface Methodology to find the best Brake Specific Fuel Consumption performance indicator location. The researchers used a Central Composite Design setup for analysis. A regression model employing the response surface approach was then created to predict fuel phase-out likelihood
This study examines multiple factors' effect and highlights the potential for patentable innovations in renewable fuel applications. According to studies. Jatropha biodiesel and its blends may improve engine efficiency and lower brake-specific fuel consumption compared to diesel fuel. Minor input parameter modifications are needed to gain these benefits.
Typical Scenario Load Identification Based on Feature Fusion and Transfer Learning
The electricity demand is continuously increasing. However various institutions enterprises and individuals exhibit many irregularities in their electricity usage leading to significant wastage of electricity. To achieve effective energy management researchers are attempting to analyze and regulate users' electricity demands by monitoring their load usage through Non-Intrusive Load Monitoring (NILM) technology. The accuracy of load identification in this technology will greatly impact the results of load monitoring. Although there are currently many articles and patents related to NILM they utilize a large amount of computational resources and require high sampling rates from devices yet the results are still unsatisfactory. Therefore it is necessary to improve the accuracy of load identification in data with relatively low sampling frequencies.
To improve the accuracy of load identification with low sampling frequency data this paper proposes a typical scenario load identification method based on feature fusion and transfer learning.
This method adopts the fusion of current and power factor angles to provide abundant identification information for NILM effectively reducing the situation of single-feature overlap of different loads. By inputting the fused feature data into GoogLeNet and utilizing transfer learning for training not only is the accuracy improved but also the training time and the requirement for the sampling rate of training data are greatly reduced. In addition selecting typical scenario loads can monitor loads in a targeted manner reduce the waste of computing resources caused by irrelevant loads and more effectively guide electricity usage strategies.
The proposed load identification method was tested on the low sampling frequency dataset used in this paper. It achieved an overall load identification accuracy of 94.61% across three scenarios improving accuracy by 3% to 7% compared to other models.
The simulation results indicate that this method achieves high load identification accuracy at low sampling frequencies. It also exhibits good generalization ability. This method not only reduces the performance requirements for monitoring equipment but also enhances monitoring efficiency.
Combinatorial Method for Quality Improvement of the Thrust Plate – A Case Study
This research aims to mitigate defects in the turning operation of thrust plates used in fighter jet fuel tank assemblies thereby reducing the rejection rate and improving overall quality. This aligns with the aerospace industry's reliability goals.
The thrust plate is a critical component in fighter jet fuel tank assembly transmitting engine thrust to the airframe. Quality compromises in this component can impair jet performance. It was observed that the thrust plate had a rejection rate of about 2.9% due to various defects. This real-world scenario underscores the importance of our study on the thrust plate and its potential impact on the aerospace industry. The rejection rate underscores its significance and potential for patent by quality improvement in turning of the thrust plate.
The objective is to mitigate turning operation defects on the thrust plate to reduce rejection rates aligning with aerospace industry reliability goals.
Experimentation encompassed four pivotal factors: turning speed feed rate cutting depth and tool inserts implemented through Taguchi's Orthogonal Array technique. Grey Relational Analysis was utilized to optimize parameters in thrust plate turning. Specifically this paper targeted the enhancement of its diameter surface roughness and tool life.
A single coefficient for the multiple responses i.e. grey relational grade has been determined and optimum levels for the parameters have been identified. Confirmation experiments with the optimal factor level combination were carried out on a sample of thrust plates and no rejections were observed.
An experimental design based on Taguchi’s orthogonal array approach was used to conduct the experiments. The Grey Relational Analysis has been applied to analyze the experimental results and optimize the turning operation process parameters for the responses thrust plate diameter tool life and surface roughness. With this the rejection of the thrust plate has been considerably reduced.
Evaluation of the Critical Success Factors for Household Product Sustainability
Sustainability and sustainable development have received growing attention in both industry and academia due to concerns regarding the rapid decrease in natural resources and increase in carbon emissions.
In this study we focus on the determination evaluation and analysis of the critical success factors in product sustainability by specifically focusing on the household goods industry. In the first phase of the study we determine the critical success factors by referring to the existing literature and opinions of the experts who have experience in the household goods industry. Next we use a trapezoidal type-2 fuzzy AHP algorithm to rank the determined criteria and discuss the main findings from a practical point of view.
Computational results bring several important managerial insights. First we observe that all three aspects of sustainability (economic environmental and social) should be considered to ensure product sustainability. Second the analysis reveals that cost (economic) quality (economic) generated waste and emission during the life cycle (environmental) energy and water consumption during the life cycle (environmental) and occupational health and safety (social) are among the highly ranked criteria.
In order to increase product sustainability the companies should determine ways to decrease water usage energy usage carbon emission and waste without neglecting the cost and quality of the product and without ignoring occupational health and safety.
Computational Modeling and Simulation in Biomedical Research
This reference provides a comprehensive overview of computational modelling and simulation for theoretical and practical biomedical research. The book explains basic concepts of computational biology and data modelling for learners and early career researchers.
Chapters cover these topics:
1. An introduction to computational tools in biomedical research
2. Computational analysis of biological data
3. Algorithm development for computational modelling and simulation
4. The roles and application of protein modelling in biomedical research
5. Dynamics of biomolecular ligand recognition
Key features include a simple easy-to-understand presentation detailed explanation of important concepts in computational modeling and simulations and references.
E-Mobility Revolution: Examining the Types, Evolution, Government Policies and Future Perspective of Electric Vehicles
Electrification is a suitable method for establishing a transportation system that is both clean and energy-efficient addressing environmental concerns. The transportation industry widely recognizes electric vehicles as a highly promising green technology that can reduce carbon emissions and energy consumption. Besides electric vehicles are defined as vehicles that can be externally charged and propelled by an electric motor powered by a battery. Moreover an electric vehicle consists of two distinct types: firstly an all-electric vehicle which relies exclusively on battery power to move an electric motor and secondly plug-in hybrid electric vehicles. This study aims to provide a comprehensive understanding of electric vehicles by covering four key aspects: types of electric vehicles the history of electric vehicles government policies related to electric vehicles and future prospects of electric vehicles. This paper first discusses the basic types of electric vehicles. Through a comprehensive analysis of several categories of electric vehicles their distinct characteristics and their advantages research enables individuals to make well-informed decisions when contemplating sustainable transportation alternatives. After that a brief history of electric vehicles is discussed. Documenting the historical evolution of electric vehicles provides context for understanding the technological advancements challenges and milestones achieved in the development of electric vehicles over time. After that Indian government policies related to electric vehicle promotion are discussed. Consequently this encompasses various incentives subsidies initiatives for infrastructure development and other policy measures with the objective of fostering the use of electric vehicles. Lastly future prospects of electric vehicles are discussed.
An Alternative Concept in Making Hybrid Flow Batteries into Dendrite-Free Full-Flow Batteries
In this study the author proposes an alternative concept of using electrostatic force of cation-exchange resin to attract metal ions and nanoscale conductors onto the polymer matrix to conduct the electrons for the plating/stripping of the metal species. Due to the even distribution of the positively-charged functional groups inside the cation-exchange resin metal formation can also be well distributed and safety issue caused by metal dendrite can be eliminated. By applying this transformative concept various hybrid flow batteries could be “upgraded” to dendrite-free full-flow batteries. Interestingly this new concept could also be generalized for all metal-based aqueous and nonaqueous hybrid systems to upgrade them into next-generation full-flow battery systems. This work offers an alternative concept to deliver unprecedented battery systems and the proof-of-concept would be more easily implemented than anticipated.
A Review of the Applicability of Classical and Extension of Fuzzy Logic Approaches to Project Decision-Making using Real Options
In this study a review of fuzzy implementation to Real Options Approach (ROA) theory where the applicability of classical and extended theories of “fuzziness” studied.
ROA allows taking into account the value of some sources of managerial flexibility and therefore assessing a more accurately project value. The positive value of flexibility results from limiting the impacts of adverse events while taking advantage of positive ones. One of the main lessons is that uncertainty adds value in the presence of flexibility. Ambiguous parameters that have a significant effect on the project value are usually represented as fuzzy sets using Zadeh's classical theory of Fuzzy logic (also termed “type-1”). However there have been so many derivatives and expansions of the fuzzy set theories developed by different researchers. Dealing with uncertainty can be manifested in the different mechanism of fuzziness.
The objective of this review is to identify the research gap as well as provide an elementary guide to the applicability of different varieties of classical and extended applicability of fuzziness to ROA when evaluating project investment.
After a generic review of the progress of ROA theory and fuzzy approaches by researchers This paper reviews the applicability of ROA to fuzzy sets (classical and extended) implementation to decision-making for large projects where project timing and uncertainty are key parameters affecting the project value
After reviewing the applicability of each of the classical and extended theories of fuzzy logic to ROA a tabular format shows the result of this study summarizing the scenario showing the applicability of different techniques.
Most of the reviewed techniques of fuzzy implementation to ROA approach still based on the classical theory of fuzzy logic. Implementation of more extended techniques has a potential of enhancing the outcome of such research.
Security Evaluation of Software by Using Fuzzy-TOPSIS through Quantum Criteria
Quantum computer development attracts security experts in software. Software developers need to pay attention to the development of quantum computers in terms of software security. The security of software is at risk with the computation speed of quantum mechanisms in computing.
Software security evaluation focuses on the fundamental security features of the software as well as the quantum enable security alternatives . The rapid development of a number of qubits in quantum computers makes the present security mechanism of software insecure. The software security evaluation is the most crucial part of surveying controlling and administering security in order to further improve the properties of safety.
It's crucial to understand that performing a security assessment early on in the development process can help you find bugs vulnerabilities faults and attacks. In this quantitative study the definition and use of the quantum computing security approach in software security will be covered. The cryptographic calculations had to secure our institutions based on computers and networks.
The Fuzzy Technique for Order Preference by Similarity to Ideal Situation (Fuzzy-TOPSIS) to quantitatively assess the rank of the quantum enable security alternatives with security factors.
The Quantum Key Distribution [A2] the quantum technique of security approach has got the top priority and quantum key distribution in GHz state [A6] got the least in the estimation of software security during the era of quantum computer by the neural network method of Fuzzy-TOPSIS.
The quantum mechanism of computing makes classical computing insecure. The security estimation of software makes developers focus on the quantum mechanism of security. The quantum mechanism of quantum key distribution is to make software secure.
Determinants of Small and Rural Local Governments’ Renewable Energy Program Adoption in Cascadia
This study aimed to investigate the determinants of renewable energy policy adoption by small and rural local governments in Cascadia.
Small and rural local governments currently face many ongoing and numerous new challenges that complicate their task of sustaining current public services and programs. How government officials adapt to these changes can affect the long-term viability of local governments in both the U.S. and Canadian contexts.
This study has examined the presence or absence of renewable energy programs in small and rural local governments in the “Cascadia” region of Canada and the U.S. (British Columbia Oregon and Washington).
Using surveys and interviews of Cascadia local government leaders during the summer and fall of 2023 correlates of renewable energy policy adoption have been examined including cultural demographic economic and political factors.
Key findings have indicated cities experiencing population growth and those with a progressive political orientation to be more inclined to adopt renewable energy policies. Conversely remote communities have demonstrated a lower propensity for such adoption. Financial constraints evidenced by the impact of inflation and the necessity for service cutbacks have been found to negatively correlate with the consideration of renewable energy policies.
This study has indicated renewable energy projects to be more often found or contemplated in areas being politically liberal densely populated and not predominantly rural. It could be beneficial in shifting the perception of renewable energy from being predominantly an environmental concern to being recognized for its economic benefits.
Ultrasound Technology for Fuel Processing
Ultrasound Technology for Fuel Processing is a comprehensive reference guide that explores the application of sonochemistry and ultrasound waves in the intensified processing of fuels. The book focuses on the cavitation phenomenon which generates extreme conditions such as high temperatures and pressures within the cavitation bubbles leading to significant enhancements in chemical reactions and overall process yields. Key features of the book include comprehensive coverage of ultrasound fuel processing with the inclusion of information about several new processing techniques detailed references and a focus on sustainability enhancing petrochemical technologies. Key Topics: - The basics of ultrasound technology including its history acoustic wave origin and process parameters influencing cavitation thresholds. - Green hydrogen production through sonolysis of water and the influence of various parameters on hydrogen yield. - Pre-treatment methods for biofuel production exploring both conventional and novel green methods. - Ultrasound-based techniques to enhance alternative energy production (biocrude biogas and bioethanol). - Biodiesel synthesis using ultrasound-microwave synergy for enhanced processing rates. - Intensified approaches in sonochemistry including the use of cavitation fundamentals of sonochemical reactors and operational guidelines for maximizing biodiesel yields. - Enhanced oil recovery and crude oil upgradation using ultrasound and cavitation techniques focusing on cracking heavy hydrocarbon molecules. - Ultrasound-assisted chemical and bio-desulfurization processes. Ultrasound Technology for Fuel Processing provides an in-depth understanding of the principles and applications of ultrasound in fuel processing offering valuable insights for researchers faculty and professionals in fuel processing technology and related areas in industrial petroleum and chemical engineering.
Application of Fuzzy Neutrosophic Cone in Decision Making
Aims: This article deals with a new decision-making process under a neutrosophic fuzzy environment. First of all we develop various types of neutrosophic set by means of neutrosophic cones. In fact this set has been developed from the general equation of second degree in the field of classical geometry. Considering the neutrosophic components “true membership” the “falsity membership” and the “indeterminacy” as the three variables of three-dimensional rectangular axes we develop various types of cones like structures of the traditional neutrosophic set and hence a new defuzzification method.
Background: Fuzzy set has some limitations in its domain [01] to describe real-life decision-making problems. The problem of difficulties lies in the variation of lower and upper bound and also the single valued logic (membership function only) systems. In reality three valued logics (membership function non-membership function and indeterminacy) have been established in the name of Neutrosophic logic/sets and two valued logics (membership and non-membership functions) have developed in the name of Intuitionistic fuzzy logic/sets. In three valued logic system the concepts of negation are now a growing subject of any group decision making problems. However to draw a clear estimation of a neutrosophic decision has not yet been studied by modern researchers.
Objective: Various kinds of new establishments of the Neutrosophic set have been studied from the algebraic point of view along with some polynomial structures. We have seen that; no finite geometric structures have been developed yet to qualify the real-world problems.
Methods: We consider the three components of a neutrosophic set as the variables of three-dimensional geometry. Since the decisions are compact and constructive we may consider the convex neutrosophic cone for analyzing single/ multiple group decision making problems.
Results: Various definitions are made over the cone- fundamentals using non-standard neutrosophic set in the domain [−11] x [−11] x [−11]. Then we studied the constructions of several expressions/functions of neutrosophic cones such as reciprocal cone and enveloping cone via a novel thinking process. Then using some examples we have developed a new ranking method along with their geometric structures exclusively.
Conclusion: In this changing world the nature of decision-making behaviors is also changing rapidly. So the need of establishing new concepts is an emerging area of research. However more attention is required in discussing such vital issues in near future. The proposed approach may be applied to the decision-making problems of global issues also.
A Game Theory-based Approach to Fuzzy Linear Transportation Problem
Background: Transport models have wide application areas in the real world and play an important role in reducing transportation costs increasing service quality etc. These models may have uncertain transportation costs and supply or demand capacities of the product. Hence it would be effective to model the vagueness of customer demands economic conditions and technical or non-technical uncertainties because of uncontrollable factors. Therefore we focus on developing a mathematical solution approach to the fuzzy transportation problems.
Objective: In this paper an integrated approach is proposed for the solution of the fuzzy linear transportation problem that has fuzzy cost coefficients in the objective function. Since transportation problem is encountered frequently in the national and international environment it is considered that proposing a new solution method to this problem will be useful.
Methods: Fuzzy cost coefficients are taken as trapezoidal fuzzy numbers due to their widespread use in the literature. Firstly the fuzziness is removed by converting the original single objective fuzzy transportation problem into a crisp Multi-Objective Linear Programming Problem (MOLPP). After the classical payoff matrix is constructed ratio matrices are obtained to scale the objectives. Then an approach based on game theory is implemented to solve the MOLPP which is handled as a zero-sum game.
Results: Creating different ratio matrices in the game theory part of the approach can generate compromise solutions for the decision-makers. To demonstrate the effectiveness of the proposed approach two numerical examples from the literature are solved. While the same solution is obtained in one of the examples a different compromise solution set is generated which could be presented to the decision-maker in the other example.
Conclusion: In this paper we developed a novel game theory-based approach to the fuzzy transportation problem. The proposed approach overcomes the non-linear structure due to the uncertainty in the cost coefficients. The greatest advantage of the proposed approach is that it can generate more than one optimal solution for the decision-maker.
FMEA Method Using Spherical Fuzzy Sets for Risk Analysis of the Tech Startup
Introduction: Tech startups are fast-growing businesses that target the demands of the marketplace by developing innovative products services or platforms. Startups ensure socially economically or environmentally more effective alternatives by using or by creating appropriate technologies. Many factors have become prominent regarding the success and sustainability of the product or service offered by the startup: investment experience and education of the team the leadership of the management creativity innovation technological breakthroughs surrounding community future perspective target marketing strategy location and the analysis of the market etc. But since 80% of startups do not survive after five years defining the important risk factors is crucial to develop the right strategies for successful startups. In this study the risk factors have been defined based on the business model which has an important place in the success of the technology startups which use technology intensively. Comprehensive risk analysis on identified factors is presented to identify effective managerial strategies for technology startups to not fail.
Methods: Spherical Fuzzy Failure Mode and Impact Analysis (SFFMEA) was used within the framework of a business model canvas for risk analysis for the failure of technology startup projects. Due to the lack of recorded data for analysis the opinions of field experts were used. While the business model canvas guided the identification of detailed risk factors FMEA enabled the risk analysis of factors that cause startup projects to fail and considering parameters related to the probability of the relevant risk factors their impact on the failure of the project and the detection level of the risk factor. Spherical Fuzzy on the other hand allowed the quantitative inference of FMEA's comprehensive parameter definitions associated with the risk factors through experts. Thus all risk factors that may cause the failure of tech startups were ranked according to their risk priority numbers (RPNs) with the SFFMEA analysis which offers a comprehensive risk analysis.
Results: The findings show that the most important causes of the tech startup’s failure are “non-compliance with existing restrictions” “inappropriate venture capital strategy” and “lack of clustering support”.
Conclusion: These failure modes can be interpreted according to their frequency of encounter potential effects and detectability and can be considered an important finding in the development of appropriate managerial strategies for the mitigation of the risk factors so the startups can survive in their first five years. Also with the proposed risk analysis methodology a comprehensive analysis of any startup project can be performed according to its conditions and characteristics.
Evaluation of Online Grocery Platform Alternatives Using Fuzzy Z-Numbers
Background: Retail management has evolved into a new business model with the development of online shopping habits. There may be significant differences between onsite service and online service in terms of customer expectations.
Introduction: In this study companies providing online grocery services in Turkey are evaluated by examining the services they provide from the perspective of customers. Fuzzy Z numbers which also add the reliability of linguistic assessments to the analysis are used in order to better describe the uncertainty.
Methods: Fuzzy Z-analytic hierarchy method (FZ-AHP) is used to weight the decision criteria and fuzzy Z-Grey relational analysis (FZ-GRA) method is used to find the best online market company.
Results: As a result of the analysis it is revealed that the most important criteria for online grocery shopping are minimum order amount and brand diversity. The results are also compared with ordinary fuzzy methods.
Conclusion: The comparison of the methods used in the study shows that although the ranks of the criteria and alternatives are the same using fuzzy Z linguistic scale results in a wider interval for the weights and the scores of the alternatives which could change the ordering especially in cases where criterion weights or alternative scores are very close to each other.