No abstract

PurposeThe study aims to analyze the barriers in the adoption of Industry 4.0 (I4.0) practices in terms of prioritization, cluster formation and clustering of empirical responses, and then narrowing them with identification of the most influential barriers for further managerial implications in the adoption of I4.0 practices by developing an enhanced understanding of I4.0.Design/methodology/approachFor the survey-based empirical research, barriers to I.40 are synthesized from the review of relevant literature and further discussions with academician and industry persons. Three widely acclaimed statistical techniques, viz. principal component analysis (PCA), fuzzy analytical hierarchical process (fuzzy AHP) and K-means clustering are applied.FindingsThe novel integrated approach shows that lack of transparent cost-benefit analysis with clear comprehension about benefits is the major barrier for the adoption of I4.0, followed by “IT infrastructure,” “Missing standards,” “Lack of properly skilled manpower,” “Fitness of present machines/equipment in the new regime” and “Concern to data security” which are other prominent barriers in adoption of I4.0 practices. The availability of funds, transparent cost-benefit analysis and clear comprehension about benefits will motivate the business owners to adopt it, overcoming the other barriers.Research limitations/implicationsThe present study brings out the new fundamental insights from the barriers to I4.0. The new insights developed here will be helpful for managers and policymakers to understand the concept and barriers hindering its smooth implementation. The factors identified are the major thrust areas for a manager to focus on for the smooth implementation of I4.0 practices. The removal of these barriers will act as a booster in the way of implementing I4.0. Real-world testing of findings is not available yet, and this will be the new direction for further research.Practical implicationsThe new production paradigm is highly complex and evolving. The study will act as a handy tool for the implementing manager for what to push first and what to push later while implementing the I4.0 practices. It will also empower a manager to assess the implementation capabilities of the industry in advance.Originality/valuePCA, fuzzy AHP and K means are deployed for identifying the significant barriers to I4.0 first time. The paper is the result of the original conceptual work of integrating the three techniques in the domain of prioritizing and narrowing the barriers from 16 to 6.

No abstract

No abstract

Global competition, advancements in technology and ever changing customers' demand have made the manufacturing companies to realize the importance of flexible manufacturing systems (FMS). These organizations are looking at FMS as a viable alternative to enhance their competitive edge. But, implementation of this universally accepted and challenging technology is not an easy task. A large number of articles have been reviewed and it is found that the existing literature lacks in providing a clear picture about the implementation of FMS. In this paper, work of various researchers has been studied and it is found that it is really a very difficult task for any organization to transform into FMS on the basis of existing research results. A wide gap exists between the proposed approaches/algorithms for the design of different components of FMS and the real-life complexities. Besides describing the gap in various issues related to FMS, some barriers, which inhibit the adaptation and implementation of

No abstract

PurposeToday's volatile condition of the market is forcing the manufacturing organizations to adapt the flexible manufacturing systems (FMS) to meet the challenges imposed by international competition, ever‐changing customer demands, rapid delivery to market, and advancement in technology. There are certain enablers, which help in the implementation of FMS or in the transition process from traditional manufacturing system to FMS. The utmost need is to analyze the behavior of these enablers for their effective utilization in the implementation of FMS. This paper aims to address these issues.Design/methodology/approachThis paper presents a methodology based on graph theoretical approach for finding the feasibility of transition to FMS for any industry. A universal feasibility index of transition (FIT) is proposed that evaluates and ranks different organizations according to their capability to be converted into FMS. This FIT value is obtained from a permanent feasibility function obtained from an enablers' digraph of FMS.FindingsThe major finding of this paper is that one can judge whether a particular industry is fit for FMS or not by calculating its FIT value. This FIT value can also be utilized in ranking different industries for their possible transition to FMS.Practical implicationsThe FIT obtained from a permanent function indicates the strength of enablers and their inter‐relations. More is the value of this index; more will be suitability of that organization for FMS adoption. In this way, managers can judge that a particular organization is suitable or fit for FMS implementation or not, without making the huge investments for such a complex production system and thus, minimize their risks.Originality/valueIdentification, classification of enablers into some important categories, and their analysis is a unique and innovative effort in the area of FMS.

Conventional energy resources are depleting very fast and to meet the global energy demand, the scarcity of these resources is the most crucial factor in the present era. One of the major contributors to carbon emissions is transportation sector which survives mostly on conventional energy resources. In the Indian context, the transportation sector contributes about 18% of CO 2 emissions of total emissions. To decarbonize this sector, the vehicles utilizing renewable resources such as solar PV technology would be a sustainable step. Solar energy which is abundant in nature and present everywhere can prove to be a great alternative to conventional resources. In the present study, solar PV technology is integrated with electric and hybrid vehicles. Additional literature review of solar electric vehicles including three-wheeled as well as four-wheeled is carried out. Autonomous vehicles and robots utilizing PV technology are also studied and presented. Finally, the foremost barriers and challenges to adopting PV technology in electric and autonomous vehicles are identified and presented.