Search results

The present investigation is concerned with the utilisation of the finite element technique for predicting the natural frequencies and the modal damping factor (also called the loss factor) of anisotropic fibre‐reinforced composite laminated plates. The simple definition of the modal damping factor is defined as the ratio of the strain energy dissipated per radian of vibration, in the mode of interest, to the total strain energy of the entire laminate at maximum displacement during the same cycle. Results for the vibration and damping analysis of multi‐layered plates obtained by the present methods are compared with the results obtained by other authors and with the results of experiments.

Gives a bibliographical review of the finite element methods (FEMs) applied for the linear and nonlinear, static and dynamic analyses of basic structural elements from the theoretical as well as practical points of view. The range of applications of FEMs in this area is wide and cannot be presented in a single paper; therefore aims to give the reader an encyclopaedic view on the subject. The bibliography at the end of the paper contains 2,025 references to papers, conference proceedings and theses/dissertations dealing with the analysis of beams, columns, rods, bars, cables, discs, blades, shafts, membranes, plates and shells that were published in 1992‐1995.

A literature review revealed that government of various developing economies have put an effort on health-care supply chain through the executing critical factors (CFs) directly. Although they have attained some significant benefits in this tactic, but it was not up to satisfactory level. One of the reasons can be attributed to the fact that government/policy makers are not quantifying the impact of CFs on health-care supply chain. This paper aims to propose a methodology to quantify and estimate the impact of CFs on government-supported health-care supply chain (GHSC).

The Graph Theoretic Approach is proposed for estimating the impact and utility of CFs on an Indian GHSC. This study is also extended to scenario analysis for comparing results with different performance situation.

The results obtained from this study show that performance of Indian GHSC is satisfactory, but performance gaps exist which need to be reduced. In this research work, 12 CFs are identified under two significant categories (SCs), i.e. enablers and barriers and the intensity of enablers and barriers have been calculated to show the impact or influence of CFs on GHSC. The value of intensity shows that the role or impact of enabler category (i.e. performance measurement, employee recognition and reward, technology adoption, training cell, inbuilt analytical tool for IT system) is higher on Indian GHSC in comparison to barriers category to enhance the performance of GHSC.

The obtained numerical results are completely in specific to the Indian perspective only; hence, they cannot be generalized for other countries. Simultaneously, this study is related to government supported health-care system; hence, the selection of expert panel was crucial due to the unavailability of doctors and other stakeholders of government system.

The proposed approach is aimed at providing a procedure for evaluating the impact of CFs on HSC in general and GHSC in specific. This study is an attempt to assist government and top management of GHSC to assess the impact of CFs on GHSC and accordingly define its course of actions.

Although various issues related to the CFs have been broadly identified and analyzed, no dedicated study has been reported in the field for quantification of impacts of CFs. Furthermore, this proposed model has an ability to recognize the specific contribution of each CF and overall contribution.

Gives a bibliographical review of the finite element analyses of sandwich structures from the theoretical as well as practical points of view. Both isotropic and composite materials are considered. Topics include: material and mechanical properties of sandwich structures; vibration, dynamic response and impact problems; heat transfer and thermomechanical responses; contact problems; fracture mechanics, fatigue and damage; stability problems; special finite elements developed for the analysis of sandwich structures; analysis of sandwich beams, plates, panels and shells; specific applications in various fields of engineering; other topics. The analysis of cellular solids is also included. The bibliography at the end of this paper contains 655 references to papers, conference proceedings and theses/dissertations dealing with presented subjects that were published between 1980 and 2001.

The heterogeneous character of Industry 4.0 opens opportunities for studies to understand the difficulties and challenges found in the transformation process of manufacturers. This article aims to present a critical analysis of the modernization process of an Industry 3.0 automated cell into a fully autonomous cell of Industry 4.0. The objective is to elucidate the difficulties found in this transition process and the possible ways to overcome the challenges, focusing on the management perspective.

For this, the needed steps for the technology transition were defined and the main I4.0 enabling technologies were applied, such as the application of machine learning algorithms to control quality parameters in milling.

The main challenges found were related to the obsolescence of the equipment present in the cell, challenges in data integration and communication protocols, in addition to the training of people who work actively in the project team. The difficulties faced were discussed based on similar studies in the literature and possible solutions for each challenge.

This understanding of possible barriers in the modernization process, and the step-by-step defined for this transition, can be important references for professionals working in manufacturing industries and researchers who aim to deepen their studies in this important and disruptive stage of world industrialization.

The purpose of this paper is to identify the crack in beam-like structures before the complete failure or damage occurs to the structure. The beam-like structure plays an important role in modern architecture; hence, the safety of this structure is much dependent on the safety of the beam. Hence, predicting the cracks is much more important for the safety of the overall structure.

In the present work, the regression analysis has been carried out through LASSO and Ridge regression models. Both the statistical models have been well implemented in the detection of crack depth and crack location. A cantilever beam-like structure has been taken for the analysis in which the first three natural frequencies have been considered as the independent variable and crack location and depth is used as the dependent variable. The first three natural frequencies, f₁, f₂ and f₃ are used as an independent variable. The crack location and crack depth are estimated though the regressor models and the accuracy are compared, to verify the correctness of the estimation.

As stated in the purpose of work, the main aim of the present work is to identify the crack parameters using an inverse technique, which will be more effective and will provide the results with less time. The data used for regression analysis are obtained from theoretical analysis and later the theoretical results are also verified through experimental analysis. The regression model developed is tested for its Bias Variance Trade-off (“Bias” – Overfitting, “variance” – generalization). The regression results have been compared with the theoretical results to check the robustness in the subsequent result section.

The idea is an amalgamation of existing and well-established technologies, that is aimed to achieve better performance for the given task. A regressor is trained from the data obtained through numerical simulation. The model is developed taking bias variance trade-off into consideration. This generalized model gives us very much acceptable performance.

In reinforced concrete (RC) structures, an evidence of damage is the presence of cracking. In order to evaluate the effect of damage on cracking pattern and natural frequency in RC slabs, two of such structures with different dimensions and reinforcement ratios were tested, in which cracks were induced through application of static load, followed by modal tests using impact excitation. The paper aims to discuss this issue.

The gradient of the fundamental natural frequency along the decay, the crack opening rate and also a global damage index based on changes of the fundamental natural frequency were evaluated.

The behaviour of the aforementioned gradient was distinct for both slabs, increasing monotonically with the cracking level for the slab with lowest reinforcement ratio, and increasing until 33 per cent of the collapse load and then decreasing afterwards for the slab with the highest ratio. Changes of the gradient were consistent with changes of the crack opening rate. Both results of gradient changes and cracking pattern brought evidence that the balance between open (old) and breathing (new) cracks differed between the slabs, and may be responsible for such differences.

Damage assessment in RC structures using vibration tests is mostly concentrated on beams. In this work, an advance is made by investigating slabs. The lack of a unique pattern of changes of the gradient implies that its absolute value is not generally suitable for the association with the damage level. However, the impact tests can be effectively used to detect early damage on slabs using this proposed parameter.

This study aims to examine factors that determine the adoption of additive manufacturing by small- and medium-sized industries. It provides insights with regard to benefits, challenges and business factors that influence small- and medium-sized industries when adopting this technology. The study also aims to expand the domain of additive manufacturing by including a broader range of challenges and benefits of additive manufacturing in literature.

Using data collected from 175 small- and medium-sized industries, the study has examined through Mann–Whitney test to understand the difference between owners and design engineers on additive manufacturing technology adoption in small- and medium-sized companies.

This study suggests contribution to academic discussion by providing associated factors that have significant impact on the adoption of additive manufacturing technology. Related advantages of additive manufacturing are reduction in inventory cost, lowering the wastage in production and customization of products. The study also indicates that factors such as cost of machinery, higher level of cost in integrating metal components have a negative impact on the adoption of this technology in small- and medium-sized industries.

Because of the chosen research approach, the research results may lack generalizability. Therefore, researchers are encouraged to test the proposed propositions further in the field of challenges and growth in other areas of application of additive manufacturing, for instance, medical sciences, fabric and aerospace.

The study provides important implications that are of interest for both research and practitioners, related to technology management in small- and medium-sized industries, e.g. foundry and machining industries.

This work/study fulfills an identified need of the small- and medium-sized companies in adopting new technologies and contribute to their growth by understanding the need to accept and implement technology.

This paper fulfills an identified need to study how small- and medium-scale companies accept new technologies and factors associated with implementation in the manufacturing process of the organization.

Many engineering applications in this era require new age materials; however, some classic alloys like spring steel are still used in critical applications such as aerospace, defense and automobile. To machine spring steel material, there exist various difficulties such as rapid tool wear rate, the rough surface formation of a workpiece and higher power consumption. The purpose of this paper is to address these issues, various approaches in addition to electrical discharge machines (EDM) are used such as dry EDM (DEDM) and near dry EDM (NDEDM).

This study focuses on these two approaches and their comparative analysis with respect to tool wear during machining of spring steel material. For this study, current, gap voltage, cycle time and dielectric medium pressure are considered input variables. This study shows that the near dry EDM approach yields better results. Hence, the thermo-electrical model for this approach is developed using ANSYS workbench, which is further validated by comparing with experimental results. This thermo-electrical model covers spark radius variation and formation of temperature profile due to electric discharge. Transient thermal analysis is used to simulate the electric discharge machining.

It is observed from this study that discharge environment parameters such as debris concentration and fluid viscosity largely influences the dielectric fluid pressure value. Experimental results revealed that NDEDM yields better results in comparison with DEDM as it shows a 25% lesser tool wear rate in NDEDM.

The range of predicted results and the experimental results are in close agreement, authenticating the model.

The rapid evacuation of personnel in emergency situations is of great significance to the safety of pedestrians. In order to further improve the evacuation efficiency in emergency situations, this paper proposes a pedestrian evacuation model based on improved cellular automata based on microscopic features.

First, the space is divided into finer grids, so that a single pedestrian occupies multiple grids to show the microscopic behavior between pedestrians. Second, to simulate the velocity of pedestrian movement under different personnel density, a dynamic grid velocity model is designed to establish a linear correspondence relationship with the density of people in the surrounding environment. Finally, the pedestrian dynamic exit selection mechanism is established to simulate the pedestrian dynamic exit selection process.

The proposed method is applied to single-exit space evacuation, multi-exit space evacuation, and space evacuation with obstacles, respectively. Average speed and personnel evacuation decisions are analyzed in specific applications. The method proposed in this paper can provide the optimal evacuation plan for pedestrians in multiple exit and obstacle environments.

In fire and emergency situations, the method proposed in this paper can provide a more effective evacuation strategy for pedestrians. The method proposed in this paper can quickly get pedestrians out of the dangerous area and provide a certain reference value for the stable development of society.

This paper proposes a cellular automata pedestrian evacuation method based on a fine grid velocity model. This method can more realistically simulate the microscopic behavior of pedestrians. The proposed model increases the speed of pedestrian movement, allowing pedestrians to dynamically adjust the speed according to the specific situation.