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.
Abstract:The flow-shop scheduling problem (FSP) has been widely studied in the literature and having a very active research area. Over the last few decades, a number of heuristic/meta-heuristic solution techniques have been developed. Some of these techniques offer excellent effectiveness and efficiency at the expense of substantial implementation efforts and being extremely complicated. This paper brings out the application of a Multi-Criteria Decision Making (MCDM) method known as techniques for order preference by similarity to an ideal solution (TOPSIS) using different weighting schemes in flow-shop environment. The objective function is identification of a job sequence which in turn would have minimum makespan (total job completion time). The application of the proposed method to flow shop scheduling is presented and explained with a numerical example. The results of the proposed TOPSIS based technique of FSP are also compared on the basis of some benchmark problems and found compatible with the results obtained from other standard procedures.
Low cost manufacturing of quality products remains an essential part of present economy and technological advances made it possible. Advances and amalgamation of information technology bring the production systems at newer level. Industry 4.0, factory for future, smart factory, digital manufacturing, and industrial automation are the new buzz words of industry stalwarts and academicians. These new technological revolutions bound to change not only the complete manufacturing scenarios but many other sectors of the society. In this paper an attempt has been made to capture the essence of Industry 4.0 by redefining it in simple words, further its complex, disruptive nature and inevitability along with technologies backing it has been discussed. Its enabling role in manufacturing philosophies like Lean Manufacturing, and Flexible Manufacturing are also reported. At last the challenges its adoption and future research areas are proposed.
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