Abstract:This research is focusing on analyzing readiness of automotive manufacturing firm on Industry 4.0 towards quality performance. In the era of globalization, most manufacturing firms all over the world are constantly looking for ways to increase productivity. The manufacturing industry is mainly faced with the problem of Industry 4.0’s awareness and implementation. Top and middle management of DRB-HICOM Automotive manufacturing firm from all departments have been selected as a sample study. The questionnaire has… Show more
“…Tasmin et al. (2020) utilized quantitative methodology to assess I4.0 readiness of automotive organization.…”
Section: Literature Reviewmentioning
confidence: 99%
“…Also, the studies mainly considered technological aspect for I4.0 assessment (Samaranayake et al, 2017). Few studies adopted survey methodology to understand the status of I4.0 in automotive component manufacturing firms (Bassi, 2017;Tasmin et al, 2020;Dudukalov et al, 2021). India's readiness towards I4.0 in automotive component industries was seen as preferred investment destination by major automotive organizations (Khanna et al, 2020).…”
mentioning
confidence: 99%
“…The findings showed that big data maturity and I4.0 infrastructure were the key dimensions enabling readiness of I4.0 in European manufacturing firms. Tasmin et al (2020) utilized quantitative methodology to assess I4.0 readiness of automotive organization. The authors distributed 96 questionnaires to automotive organizations and identified the relationship between I4.0 and quality performance using statistical package.…”
PurposeThe purpose is to assess Industry 4.0 (I4.0) readiness index using fuzzy logic and multi-grade fuzzy approaches in an automotive component manufacturing organization.Design/methodology/approachI4.0 implies fourth industrial revolution that necessitates vital challenges to be dealt with. In this viewpoint, this article presents the evaluation of I4.0 Readiness Index. The evaluation includes two levels with appropriate criteria and factors. Fuzzy logic approach is used for assessment. Furthermore, the results obtained from fuzzy logic have been benchmarked with multi-grade fuzzy approach.FindingsThe proposed assessment model has successfully utilized fuzzy logic approach for assessment of I4.0 readiness index of automotive component manufacturing organization. Based on fuzzy logic approach, readiness index of I4.0 has been found to be (4.74, 6.26, 7.80) which is further benchmarked using multi-grade fuzzy approach. Industry 4.0 readiness index obtained from multi-grade fuzzy approach is 6.258 and thus, validated. Furthermore, 20 weaker areas have been identified and improvement suggestions are provided.Research limitations/implicationsThe assessment module include two levels (Six Criteria and 50 Factors). The assessment model could be expanded based on advancements in industrial developments. Therefore, future researchers could utilize findings of the readiness model to further develop multi-level assessment module for Industry 4.0 readiness in organization. The developed readiness model helped researchers in understanding the methodology to assess I4.0 readiness of organization.Practical implicationsThe model has been tested with reference to automotive component manufacturing organization and hence the inferences derived have practical relevance. Furthermore, the benchmarking strategy adopted in the present study is simple to understand that makes the model unique and could be applied to other organizations. The results obtained from the study reveal that fuzzy logic-based readiness model is efficient to assess I4.0 readiness of industry.Originality/valueThe development of model for I4.0 readiness assessment and further analysis is the original contribution of the authors. The developed fuzzy logic based I4.0 readiness model indicated the readiness level of an organization using I4RI. Also, the model provided weaker areas based on FPII values which is essential to improve the readiness of organization that already began with the adoption of I4.0 concepts. Further modification in the readiness model would help in enhancing I4.0 readiness of organization. Moreover, the benchmarking strategy adopted in the study i.e. MGF would help to validate the computed I4.0 readiness.
“…Tasmin et al. (2020) utilized quantitative methodology to assess I4.0 readiness of automotive organization.…”
Section: Literature Reviewmentioning
confidence: 99%
“…Also, the studies mainly considered technological aspect for I4.0 assessment (Samaranayake et al, 2017). Few studies adopted survey methodology to understand the status of I4.0 in automotive component manufacturing firms (Bassi, 2017;Tasmin et al, 2020;Dudukalov et al, 2021). India's readiness towards I4.0 in automotive component industries was seen as preferred investment destination by major automotive organizations (Khanna et al, 2020).…”
mentioning
confidence: 99%
“…The findings showed that big data maturity and I4.0 infrastructure were the key dimensions enabling readiness of I4.0 in European manufacturing firms. Tasmin et al (2020) utilized quantitative methodology to assess I4.0 readiness of automotive organization. The authors distributed 96 questionnaires to automotive organizations and identified the relationship between I4.0 and quality performance using statistical package.…”
PurposeThe purpose is to assess Industry 4.0 (I4.0) readiness index using fuzzy logic and multi-grade fuzzy approaches in an automotive component manufacturing organization.Design/methodology/approachI4.0 implies fourth industrial revolution that necessitates vital challenges to be dealt with. In this viewpoint, this article presents the evaluation of I4.0 Readiness Index. The evaluation includes two levels with appropriate criteria and factors. Fuzzy logic approach is used for assessment. Furthermore, the results obtained from fuzzy logic have been benchmarked with multi-grade fuzzy approach.FindingsThe proposed assessment model has successfully utilized fuzzy logic approach for assessment of I4.0 readiness index of automotive component manufacturing organization. Based on fuzzy logic approach, readiness index of I4.0 has been found to be (4.74, 6.26, 7.80) which is further benchmarked using multi-grade fuzzy approach. Industry 4.0 readiness index obtained from multi-grade fuzzy approach is 6.258 and thus, validated. Furthermore, 20 weaker areas have been identified and improvement suggestions are provided.Research limitations/implicationsThe assessment module include two levels (Six Criteria and 50 Factors). The assessment model could be expanded based on advancements in industrial developments. Therefore, future researchers could utilize findings of the readiness model to further develop multi-level assessment module for Industry 4.0 readiness in organization. The developed readiness model helped researchers in understanding the methodology to assess I4.0 readiness of organization.Practical implicationsThe model has been tested with reference to automotive component manufacturing organization and hence the inferences derived have practical relevance. Furthermore, the benchmarking strategy adopted in the present study is simple to understand that makes the model unique and could be applied to other organizations. The results obtained from the study reveal that fuzzy logic-based readiness model is efficient to assess I4.0 readiness of industry.Originality/valueThe development of model for I4.0 readiness assessment and further analysis is the original contribution of the authors. The developed fuzzy logic based I4.0 readiness model indicated the readiness level of an organization using I4RI. Also, the model provided weaker areas based on FPII values which is essential to improve the readiness of organization that already began with the adoption of I4.0 concepts. Further modification in the readiness model would help in enhancing I4.0 readiness of organization. Moreover, the benchmarking strategy adopted in the study i.e. MGF would help to validate the computed I4.0 readiness.
“…Inside this context, the Industry 4.0 (I4.0) represents a new technological era that comprises the use of Internet-based technologies, focused on intelligent systems that continuously acquire and process data exchanging information between machines and systems [ 3 , 4 ]. It is also described as the Industry Internet of things (IoT), which connects smart devices to monitor the manufacturing processes [ 5 , 6 ]. These networked interconnections of devices allow the communication among individuals and technologies in cyber-physical systems (CPS) [ 7 ].…”
The present paper provides an overview of the state-of-the-art research, outlining the applications of the Industry 4.0 (I4.0) technologies on the aircraft manufacturing sector and their maturity state based on the technology readiness level (TRL) scale. A literature review has been conducted for the identification, selection, and evaluation of the published research. A total of 57 papers extracted from the two most relevant scientific databases for the area (Web of Science and Scopus), from 2010 to March 2021, were analysed and summarized. The research, analysis, and evaluation of these papers has provided an outlook of how the aircraft manufacturing industry is inserted into the I4.0 context, based on a classification of the I4.0 technologies maturity for this industrial branch. Then, a survey was performed with 12 specialists from 5 different aircraft manufacturing companies aiming to report the practical point-of-view in this area. Thus, this paper highlights and discusses the gaps found in the literature related to the I4.0 technologies applied to aircraft manufacturing and their main useful implications not only from the academic point-of-view but also from competitive business aspects, providing recommendations for industrial managers, engineers, and stakeholders. Finally, this paper proposes new opportunities and challenges for future research.
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