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1 – 10 of 154Leiting Zhao, Kan Liu, Donghui Liu and Zheming Jin
This study aims to improve the availability of regenerative braking for urban metro vehicles by introducing a sensorless operational temperature estimation method for the braking…
Abstract
Purpose
This study aims to improve the availability of regenerative braking for urban metro vehicles by introducing a sensorless operational temperature estimation method for the braking resistor (BR) onboard the vehicle, which overcomes the vulnerability of having conventional temperature sensor.
Design/methodology/approach
In this study, the energy model based sensorless estimation method is developed. By analyzing the structure and the convection dissipation process of the BR onboard the vehicle, the energy-based operational temperature model of the BR and its cooling domain is established. By adopting Newton's law of cooling and the law of conservation of energy, the energy and temperature dynamic of the BR can be stated. To minimize the use of all kinds of sensors (including both thermal and electrical), a novel regenerative braking power calculation method is proposed, which involves only the voltage of DC traction network and the duty cycle of the chopping circuit; both of them are available for the traction control unit (TCU) of the vehicle. By utilizing a real-time iterative calculation and updating the parameter of the energy model, the operational temperature of the BR can be obtained and monitored in a sensorless manner.
Findings
In this study, a sensorless estimation/monitoring method of the operational temperature of BR is proposed. The results show that it is possible to utilize the existing electrical sensors that is mandatory for the traction unit’s operation to estimate the operational temperature of BR, instead of adding dedicated thermal sensors. The results also validate the effectiveness of the proposal is acceptable for the engineering practical.
Originality/value
The proposal of this study provides novel concepts for the sensorless operational temperature monitoring of BR onboard rolling stocks. The proposed method only involves quasi-global electrical variable and the internal control signal within the TCU.
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Kessara Kanchanapoom and Jongsawas Chongwatpol
Customer lifetime value (CLV) is one of the key indicators to measure the success or health of an organization. How can an organization assess the organization's customers'…
Abstract
Purpose
Customer lifetime value (CLV) is one of the key indicators to measure the success or health of an organization. How can an organization assess the organization's customers' lifetime value (LTV) and offer relevant strategies to retain prospective and profitable customers? This study offers an integrated view of different methods for calculating CLVs for both loyalty members and non-membership customers.
Design/methodology/approach
This study outlines eleven methods for calculating CLV considering (1) the deterministic aspect of NPV (Net present value) models in both finite and infinite timespans, (2) the geometric pattern and (3) the probabilistic aspect of parameter estimates through simulation modeling along with (4) the migration models for including “the probability that customers will return in the future” as a key input for CLV calculation.
Findings
The CLV models are validated in the context of complementary and alternative medicine (CAM)in the healthcare industry. The results show that understanding CLV can help the organization develop strategies to retain valuable customers while maintaining profit margins.
Originality/value
The integrated CLV models provide an overview of the mathematical estimation of LTVs depending on the nature of the customers and the business circumstances and can be applied to other business settings.
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Lalit Narendra Patil, Hrishikesh P. Khairnar and S.G. Bhirud
Electric vehicles are well known for a silent and smooth drive; however, their presence on the road is difficult to identify for road users who may be subjected to certain…
Abstract
Purpose
Electric vehicles are well known for a silent and smooth drive; however, their presence on the road is difficult to identify for road users who may be subjected to certain incidences. Although electric vehicles are free from exhaust emission gases, the wear particles coming out from disc brakes are still unresolved issues. Therefore, the purpose of the present paper is to introduce a smart eco-friendly braking system that uses signal processing and integrated technologies to eventually build a comprehensive driver assistance system.
Design/methodology/approach
The parameters obstacle identification, driver drowsiness, driver alcohol situation and heart rate were all taken into account. A contactless brake blending system has been designed while upgrading a rapid response. The implemented state flow rule-based decision strategy validated with the outcomes of a novel experimental setup.
Findings
The drowsiness state of drivers was successfully identified for the proposed control map and set up vindicated with the improvement in stopping time, atmospheric environment and increase in vehicle active safety regime.
Originality/value
The present study adopted a unique approach and obtained a brake blending system for improved braking performance as well as overall safety enhancement with rapid control of the vehicle.
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Anwar Zorig, Ahmed Belkheiri, Bachir Bendjedia, Katia Kouzi and Mohammed Belkheiri
The great value of offline identification of machine parameters is when the machine manufacturer does not provide its parameters. Most machine control strategies require parameter…
Abstract
Purpose
The great value of offline identification of machine parameters is when the machine manufacturer does not provide its parameters. Most machine control strategies require parameter values, and some circumstances in the industrial sector only require offline identification. This paper aims to present a new offline method for estimating induction motor parameters based on least squares and a salp swarm algorithm (SSA).
Design/methodology/approach
The central concept is to use the classic least squares (LS) method to acquire the majority of induction machine (IM) constant parameters, followed by the SSA method to obtain all parameters and minimize errors.
Findings
The obtained results showed that the LS method gives good results in simulation based on the assumption that the measurements are noise-free. However, unlike in simulations, the LS method is unable to accurately identify the machine’s parameters during the experimental test. On the contrary, the SSA method proves higher efficiency and more precision for IM parameter estimation in both simulations and experimental tests.
Originality/value
After performing a primary identification using the technique of least squares, the initial intention of this study was to apply the SSA for the purpose of identifying all of the machine’s parameters and minimizing errors. These two approaches use the same measurement from a simple running test of an IM, and they offer a quick processing time. Therefore, this combined offline strategy provides a reliable model based on the identified parameters.
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The standard method to estimate a stochastic frontier (SF) model is the maximum likelihood (ML) approach with the distribution assumptions of a symmetric two-sided stochastic…
Abstract
The standard method to estimate a stochastic frontier (SF) model is the maximum likelihood (ML) approach with the distribution assumptions of a symmetric two-sided stochastic error v and a one-sided inefficiency random component u. When v or u has a nonstandard distribution, such as v follows a generalized t distribution or u has a
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Although numerous studies have been conducted to explore the impact of various factors on employees' turnover intention and intention to remain with the organization, the…
Abstract
Purpose
Although numerous studies have been conducted to explore the impact of various factors on employees' turnover intention and intention to remain with the organization, the relationship between these two constructs remains largely unexplored. Considering the significance of these constructs, particularly in the context of the COVID-19 pandemic, the authors aimed to investigate their association within an academic environment using a dynamic modeling approach.
Design/methodology/approach
This study follows a quantitative approach and utilizes a longitudinal survey design. The authors utilized a cross-lagged panel model (CLPM) and employed the parametric efficient partial least squares (PLSe2) methodology to estimate the dynamic model using data gathered from lecturers associated with both public and private universities in Malaysia. In order to offer methodological insights to applied higher education researchers, the authors also compared the results with maximum likelihood (ML) estimation.
Findings
The findings of the authors' study indicate a reciprocal relationship between turnover intention and intention to remain with the organization, with intention to remain with the organization being a stronger predictor. Moreover, situational factors were found to have a greater influence on eliciting turnover intention within academic settings. As anticipated, the use of the PLSe2 methodology resulted in higher R2 values compared to ML estimation, thereby reinforcing the effectiveness of PLS-based methods in explanatory-predictive modeling in applied studies.
Practical implications
The authors' findings suggest prioritizing policies that enhance training and consultation sessions to foster positive attitudes among lecturers. Positive attitudes significantly impact judgment-driven behaviors like turnover intention and intention to remain with the organization. Additionally, improving working environments, which indirectly influence judgment-driven behaviors through factors like affective work events, affect and attitudes, should also be considered.
Originality/value
This study pioneers the examination of the causal relationship between turnover intention and intention to remain with the organization, their stability over time and the association of changes in these variables using a dynamic CLPM in higher education. It introduces the novel application of the cutting-edge PLSe2 methodology in estimating a CLPM, providing valuable insights for researchers in explanatory-predictive modeling.
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Florian Cramer and Christian Fikar
Short food supply chains have the potential to facilitate the transition to more sustainable food systems. Related distribution processes, however, can be challenging for…
Abstract
Purpose
Short food supply chains have the potential to facilitate the transition to more sustainable food systems. Related distribution processes, however, can be challenging for smallholder and family farmers. To extend the market reach of farmers without the need for extensive investments, crowd logistics (CL) can be used. The purpose of this paper is to explore the benefits and trade-offs of implementing CL platforms in short food supply chains (SFSCs).
Design/methodology/approach
A decision support system (DSS) based on agent-based and discrete event simulation (DES) modelling is developed, which closely approximates the behaviour of customers and distribution processes at outlets. Different scenarios are explored to evaluate the potential of CL in rural and urban settings using the example of regions from Bavaria, Germany.
Findings
Results show that CL can be used to increase the reach of farmers in SFSCs at the cost of minor food quality losses. Moreover, a difference between urban and rural settings is noted: An urban scenario requires less investment in the driver base, whereas the rural scenario shows a higher potential to increase market reach.
Originality/value
Platform-based food delivery services are still mostly unexplored in the context of SFSCs. This research shows that platform services such as CL can be used to support local agriculture and facilitate the distribution of perishable food items, introducing a simulation-based DSS and providing detailed results on various application settings; this research serves as a steppingstone to facilitate successful real-world implementations and encourage further research.
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Suzan Alaswad and Sinan Salman
While steady-state analysis is useful, it does not consider the inherent transient characteristics of repairable systems' behavior, especially in systems that have relatively…
Abstract
Purpose
While steady-state analysis is useful, it does not consider the inherent transient characteristics of repairable systems' behavior, especially in systems that have relatively short life spans, or when their transient behavior is of special concern such as the motivating example used in this paper, military systems. Therefore, a maintenance policy that considers both transient and steady-state availability and aims to achieve the best trade-off between high steady-state availability and rapid stabilization is essential.
Design/methodology/approach
This paper studies the transient behavior of system availability under the Kijima Type II virtual age model. While such systems achieve steady-state availability, and it has been proved that deploying preventive maintenance (PM) can significantly improve its steady-state availability, this improvement often comes at the price of longer and increased fluctuating transient behavior, which affects overall system performance. The authors present a methodology that identifies the optimal PM policy that achieves the best trade-off between high steady-state availability and rapid stabilization based on cost-availability analysis.
Findings
When the proposed simulation-based optimization and cost analysis methodology is applied to the motivating example, it produces an optimal PM policy that achieves an availability–variability balance between transient and steady-state system behaviors. The optimal PM policy produces a notably lower availability coefficient of variation (by 11.5%), while at the same time suffering a negligible limiting availability loss of only 0.3%. The new optimal PM policy also provides cost savings of about 5% in total maintenance cost. The performed sensitivity analysis shows that the system's optimal maintenance cost is sensitive to the repair time, the shape parameter of the Weibull distribution and the downtime cost, but is robust with respect to changes in the remaining parameters.
Originality/value
Most of the current maintenance models emphasize the steady-state behavior of availability and neglect its transient behavior. For some systems, using steady-state availability as the sole metric for performance is not adequate, especially in systems that have relatively short life spans or when their transient behavior affects the overall performance. However, little work has been done on the transient analysis of such systems. In this paper, the authors aim to fill this gap by emphasizing such systems and applications where transient behavior is of critical importance to efficiently optimize system performance. The authors use military systems as a motivating example.
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Tri Bien Minh, Hien Vo and Luan Thanh Hua
The main purpose of the study was mechanical designing, simulation and manufacturing process for a new model of octocopter V-frame and to achieve simple manufacturing with 3D…
Abstract
Purpose
The main purpose of the study was mechanical designing, simulation and manufacturing process for a new model of octocopter V-frame and to achieve simple manufacturing with 3D printing technology. Moreover, the octocopter PID controller was simulated on the Simulink environment to get performance on the roll and pitch angle control.
Design/methodology/approach
Octocopter is one kind of multirotor vehicle (a rotorcraft with more than two rotors), that has lately gained a lot of attention for both the scientific and commercial spheres. With a greater number of rotors, the multirotor is very maneuverable and robust. Multi-copter makes an important contribution to the technological revolution in the military, industry, transportation, mapping and especially agriculture. Nowadays, we are heading to the four-industrial revolutions as well as the new technological application in the agricultural field such as precision agriculture, mapping and surveillance. Due to recently advanced technology about sensors, electronics, 3D printing, battery with high performance, multi-copter can be manufactured at low cost.
Findings
The V-frame octocopter was chosen to design in this paper; it had better performance scores including high redundancy rotors, high payload capability and affordable cost than another multi-copter family. The V-frame octocopter increasing freedom field of view of the camera was considered to place the camera position in the front of the drone.
Research limitations/implications
For the future aspects, the mechanical structure of the octocopter could be improved by using more advanced metal 3D printing to produce the aluminum or titan alloy materials for lighter and more rigid compared with ABS material, and finally the assembly to the real test.
Originality/value
The study shows the new platform of the V-frame octocopter kinematics analysis, designed on the CAD software, with some important mechanical parts using FEM analysis to find the highest stress and displacement under high load applied, the result of all connecting the joints 3D printing part is completely safe. Mechanical parts were manufactured by using 3D printing technology and CNC milling. Moreover, the study has shown V-frame octocopter simulation based on Simulink using the second method Ziegler- Nichols to find suitable parameters of the PID controller for roll and pitch angle. Using the block simulation is good for implementing and fast checking the new algorithm when building the new platform of the robot.
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Pratik Maheshwari, Sachin Kamble, Satish Kumar, Amine Belhadi and Shivam Gupta
The digital warehouse management system is an emergence that forms a critical part of the transformation of economic structure in Industry 4.0. In the present business scenario…
Abstract
Purpose
The digital warehouse management system is an emergence that forms a critical part of the transformation of economic structure in Industry 4.0. In the present business scenario, the warehouse management system encounters a messy layout, poor damage control, unsatisfactory order management, lack of visibility and lack of technological interventions. Digital twin (DT) based warehouse system shows the ontology and knowledge graphs for competitive advantage by consolidating and transferring goods directly from an inbound supplier to an outbound customer on short notice and with no or limited storage. There remains a lack of clarity on how the DT can be implemented successfully in warehouse management.
Design/methodology/approach
The current literature remains largely unstructured and scattered due to a lack of a systematic approach to integrating the research implications and analysis. This paper probes the conceptualization of the DT with the help of theoretical analysis using the systematic literature analysis method.
Findings
The study explores essential concepts such as interoperability and integrability in implementing DT. Further, it analyzes the role of a supply chain control tower (SCCT) in modern supply chain management. A research framework is proposed for practitioners and academicians by incorporating the opportunities and challenges associated with DT implementation. The research findings are mainly threefold: Conceptualization of DT, Featuring SCCT and Exploration of cross-computer platform interfaces, scalability and maintenance strategies.
Originality/value
This study is among the first to analyze and review DT applications in warehouse management. Moreover, the study proposes a theoretical toolbox for the practitioners to successfully implement the DT in warehouse DT-based warehouse management system: A theoretical toolbox for future research and applications.
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