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The work presented in this paper is concerned with mathematical modeling and experimental validation of mono-tube shock absorber. This paper aims to create damper model to predict accurately damping force, and experimental analysis is done by varying the various parameters, such as flow area in bleed(Ab), mass (M) and operating frequency(?).

Here, input is given in the form of sinusoidal excitation, and the output is received as a numerical data of the displacement transmissibility. These data are then processed to get the values of transmissibility and magnification factor for various frequency ratios. They are then plotted to have transmissibility and frequency response curves, as it is a generally accepted measure of how well the system is isolated from its surroundings.

It is better to have low transmissibility (larger bleed area), for lower suspension velocity, as it will reduce maximum acceleration transmitted to the sprung mass. However, for higher suspension velocity, bleed area should be low (higher transmissibility) to reduce displacement of tyre from road.

The development of faster vehicles and also the requirements of smoother and more comfortable rides have led to the fitment of dampers on almost on all present day vehicles. Shock absorbers have a significant influence on handling performance and riding comfort. Shock absorber plays an important role not only for comfort of the riders of the vehicle but also in the performance and life of the vehicle. However, no further reduction of vehicle vibration can be expected for using the optimum values of damping coefficient and spring stiffness for the shock absorber. Thus, it is necessary to make modification to improve the functions of shock absorber.

Knowledge management (KM) involves strategies and processes of identifying, capturing, and leveraging knowledge to enhance competitiveness. The new world of knowledge‐based organizations is distinguished from the organizations of the last millennium by its emphasis on monitoring and controlling the organization by shared knowledge derived from internal and external data sources. It believes in continual transformation of the knowledge‐base according to changing business strategy. The objective of this paper is to understand the KM practices in Indian manufacturing organisations, which are going through a major transition in this area.

This paper reports the findings of a postal survey carried out to access the impact of KM practices in Indian manufacturing industries. Data were collected and analysed for 71 industries under this category.

The results indicate that the main reasons why these organisations are focusing on KM are gaining completive advantage and creating new knowledge. However, culture and financial constraints are amongst the highest ranked barrier for KM implementation.

There have been major changes in the Indian engineering industry in terms of better awareness and adoption of KM practices. The paper addresses many related issues in this direction.

In today's knowledge economy, a major challenge for the managers is to effectively link the knowledge management (KM) initiatives with the ever‐changing organizational needs. The problem arises due to disjoint strategic alignment between these two, which is mainly due to inappropriate KM framework and adoption of some quick‐fix solutions to achieve business results. Hence, for effective management and utilization of knowledge assets, KM initiative should be dovetailed to link with key organizational goals like new product development (NPD), customer satisfaction and manufacturing excellence. The purpose of this paper is to propose a suitable KM system.

This paper proposes an approach for KM system development to ensure a fit between the organizational needs during NPD and KM initiatives. Soft system methodology (SSM) has been adopted to design this framework.

This research identified a list of knowledge‐sharing methods, which help in intra‐level or inter‐level knowledge flow. The proposed framework highlights the hierarchal nature and bi‐directional flow of knowledge. Further, this work observed that there are two additional key enablers to effective knowledge management system – competency and infrastructure.

This work focuses on an auto‐component supplier in India. Therefore, this work is limited by the organizational culture, location, business model and the sector in which this research was done.

This paper suggests that a technical knowledge driven process like NPD has three strategic enablers – technology, people and process. The sustenance of the NPD process is affected by the balance among these enablers. Fundamentally, a comprehensive and integrative framework not only ensures a structured framework but also helps in better adoption due to stakeholders' buy‐in of the process.

The purpose of this paper is to propose an interpretive structural modeling (ISM) model which highlights the relationships between the identified just-in-time (JIT) elements useful for the implementation of JIT in maintenance and understand mutual influences of these identified JIT elements on JIT implementation in maintenance. Further, this paper seeks to identify dependence power and driving power of identified JIT elements using an ISM and Matrice d’Impacts Croisés Multiplication Appliquée á un Classement (MICMAC) analysis.

The methodology used in the paper is ISM with a view to evolving mutual relationships among JIT elements. The identified JIT elements have been further classified, based on their dependence power and driving power using MICMAC analysis.

This paper has developed the relationships among 16 identified JIT elements using the ISM methodology. Further, this paper analyses the driving power and dependence power of identified JIT elements with the help of MICMAC analysis. The incorporated approach is developed here, as the ISM provides only binary correlation among identified JIT elements. The MICMAC analysis is adopted here as it is useful in specific examination related to driving and the dependence power of identified JIT elements. The ISM developed model and MICMAC analysis finding are validated with the help of industrial experts.

The weightage and validation for the ISM and MICMAC analysis are obtained throughout the opinion of academics and industry experts. Further hypothesis may be conducted to examine the validity of the planned model, and structural model may also be validated statistically with the help of structural equation modeling.

The ISM model development and MICMAC analysis of identified JIT elements provide academics and maintenance managers a macro picture of the profits gained by the organizations by the implementation of JIT in maintenance of an organization.

The results will be useful for maintenance managers to understand the process of implementation of JIT in maintenance and to gain benefits after the implementation of JIT in maintenance of an organization.

The main purpose of this paper is to identify and rank various barriers to pharmacovigilance (PV) in context of emerging economies and examine their interrelationships using the interpretive structural modeling (ISM) approach. The result is a model that offers insights about how to achieve rational and safe use of medicines and ensure patient safety as realized through robust national PV systems.

The paper develops a model to analyze the interactions among PV barriers using the ISM approach. Based on input from clinical and medical product development experts, PV barriers in emerging economies were identified and reviewed. The hierarchical interrelationships among these PV barriers were analyzed in context of their driving/dependence powers.

Findings of the study identify key PV barriers—lack of resources/infrastructure, weak legislation, unfair burden of disease, lack of PV capacity, training, and enforcement authority—that drive, or strongly influence, other barriers and thwart implementation of robust national PV systems in emerging economies. Pharmaceutical industry factors were PV barriers that were identified as autonomous, implying their relative disconnection from other barriers, and patient PV practices barrier was strongly dependent on other barriers.

The paper offers policy- and decision-makers alike with a framework to support further research into interdependencies among key PV barriers in emerging economies. It can serve as an impetus for further research with potential to broadening the understanding of how and why PV systems may be rendered ineffective. Future studies can be planned to apply the ISM approach to study PV barriers in the context of developed economies and draw lessons and implications for policy- and decision-makers by contrasting results from these studies.

This paper contributes to the understanding of the multifaceted nature of PV and its barriers. The proposed approach gives public health decision-makers a better comprehension of driver PV barriers that have most influence on others versus dependent PV barriers, which are most influenced by others. Also, knowledge, attitude and practices of patients and caregivers can also be critical PV barriers in emerging economies. This information can be instrumental for public health policymakers, government entities, and health/PV practitioners to identify the PV barriers that they should prioritize for improvement and how to manage trade-offs between these barriers.

PV barriers in emerging economies, as compared to developed economies, are inherently different and need to be examined in their specific context. The hierarchical ISM model suggests that resources and regulation initiatives by governments in emerging economies lead to through informed/enabled pharmaceutical supply chain players and eventually drive PV-specific knowledge, attitude, and practice outcomes improvements across their populace.

This paper highlights the deployment of ISM approach as a health policy decision support tool in the identifying and ranking barriers to effective PV systems in emerging economies, in terms of their contextual relationships, to achieve a better understanding as to how these interrelationships can affect national PV system outcomes.

The surface roughness of additively manufactured parts is usually found to be high. This limits their use in industrial and biomedical applications. Therefore, these parts required post-processing to improve their surface quality. The purpose of this study is to finish three-dimensional (3D) printed acrylonitrile butadiene styrene (ABS) and polylactic acid (PLA) parts using abrasive flow machining (AFM).

A hydrogel-based abrasive media has been developed to finish 3D printed parts. The developed abrasive media has been characterized for its rheology and thermal stability using sweep tests, thermogravimetric analysis (TGA) and differential thermal analysis (DTA). The ABS and PLA cylindrical parts have been prepared using fused deposition modeling (FDM) and finished using AFM. The experiments were designed using Taguchi (L9 OA) method. The effect of process parameters such as extrusion pressure (EP), layer thickness (LT) and abrasive concentration (AC) was investigated on the amount of material removed (MR) and percentage improvement in surface roughness (%ΔR_a).

The developed abrasive media was found to be effective for finishing FDM printed parts using AFM. The microscope images of unfinished and finished showed a significant improvement in surface topography of additively manufactures parts after AFM. The results reveal that AC is the most significant parameter during the finishing of ABS parts. However, EP and AC are the most significant parameters for MR and %ΔR_a, respectively, during the finishing of PLA parts.

The FDM technology has applications in the biomedical, electronics, aeronautics and defense sectors. PLA has good biodegradable and biocompatible properties, so widely used in biomedical applications. The ventilator splitters fabricated using FDM have a profile similar to the shape used in the present study.

The present study is focused on finishing FDM printed cylindrical parts using AFM. Future research may be done on the AFM of complex shapes and freeform surfaces printed using different additive manufacturing (AM) techniques.

An abrasive media consists of xanthan gum, locust bean gum and fumed silica has been developed and characterized. An experimental study has been performed by combining printing parameters of FDM and finishing parameters of AFM. A comparative analysis in MR and %ΔR_a has been reported between 3D printed ABS and PLA parts.

The reduction of food wastage at every stage of a fresh produce supply chain helps in achieving balance among all three dimensions (social, ecological and economic) of the sustainability and helps in stimulating the growth and development in the agricultural domain. The purpose of this paper is to address the causal factors of post-harvesting losses (PHLs) occurring in the transportation phase.

Through exhaustive literature survey and expert opinions, 12 crucial barriers to sustainable transportation of fruits and vegetables (F&V) are identified. The interpretive structural modeling (ISM) methodology, a multi-criteria decision-making (MCDM) approach, is employed for developing a structural model of the identified barriers.

The results of the analysis highlighted that two factors, namely, the non-availability of refrigerated vehicles, and excessive loading on the vehicles, are the most significant barriers to sustainable transportation which are found to have the highest driving power.

The results of the present research are applicable to the F&V supply chains only. The established interrelation among the identified factors depends on the judgments given by the experts which could be biased. The developed ISM model is intended to guide the policy and decision makers for formulating the policies for the performance improvement of the fresh produce value chain.

It is the first research of its kind focusing on the model development of critical factors causing PHLs in the transportation phase of the agricultural fresh produce supply chain using MCDM process.

The purpose of this paper is to understand possible linkage between variables that constitute a lean manufacturing enterprise. In the study the authors have tried to decode the complex relationship among variables which is missing in extant literature.

In the study the authors have used systematic literature review (SLR) approach to identify the variables from extant literature and used interpretive structural modelling (ISM) and Fuzzy MICMAC analysis to understand complex equation among variables from Indian manufacturing firm perspective.

The findings using ISM modeling indicate top management support is the bottom level and business performance is the top level. In order to further resolve conflicts the authors have further analyzed variables using Fuzzy MICMAC analysis which has further divided variables into four clusters. The Fuzzy MICMAC output suggests that top management support, real time production information, training and team work are the driving variables and business performance, total quality management and lean behavior are the dependence variables.

Like any study, the study have its own limitations. In the study the authors have developed the model based on expert opinion. The number may be not enough to validate this model statistically. However, it can be regarded as a platform for further investigation using structural equation modeling.

The present study using ISM model has proposed a model based upon experts, identified from Indian major manufacturing firms. This model can further provide empirical platform for further investigation which can resolve lean manufacturing issues.

The purpose of this paper is to identify and rank the various barriers of the CSR implementation in Indian manufacturing companies. Further, this paper also studies interaction of different barriers.

The study was carried out using an interpretive structural modeling (ISM) approach to analyze the interaction among different barriers for corporate social responsibility (CSR) implementation in manufacturing companies in the Indian context.

In the present study, ten CSR implementation barriers were identified through an extensive literature review followed by the expert’s opinion. The present study outlines that lack of money and consumer’s passive attitude towards CSR are the major barriers in CSR implementation in Indian manufacturing companies. On the other hand, top management commitment, lack of knowledge about CSR and lack of skills for CSR implementation are barriers which occur due to the investment required in term of time and consumer’s passive attitude.

The present study is helpful to both academicians and practitioners by providing a model of CSR barriers. This study is important in the context of India which is a developing economy and this development is exerting pressure on the corporations to adopt CSR in their practices. This ISM-based model of barriers of CSR implementation in the manufacturing sector will help practitioners and managers to have enhanced knowledge about these barriers and to concentrate on important barriers to implement CSR activities in their organizations in an efficient manner.

Textile and Apparel (T&A) sector significantly influences socio-economic and environmental dimensions of the sustainability. The purpose of this paper is proposed to establish the interrelationship among the critical barriers to the sustainable development of T&A supply chains by using a multi-criteria decision-making approach and to obtain a ranking of the barriers.

In the present investigation through literature review and from expert opinions, 14 significant challenges to the sustainable growth of T&A sector have identified. For establishing the interrelationship and for developing a structural model of the identified challenges, interpretive structural modelling (ISM) methodology is employed.

The results of the investigation revealed that lack of effective governmental policies (B8), poor infrastructure (B4), lack of effective level of integration (B6), low foreign investment (B13) and demonetization (B12) are the top most significant challenges.

The model development based on the expert inputs from the industry and academia, these inputs could be biased influencing the accuracy of the model. Also, inclusion more factors for the analysis will improve the reliability of the model.

This research is intended to guide the policy and decision makers for improving overall the growth of the T&A supply chain.