IOT: Key Automation Solution to Efficate the Lean System in Manufacturing Industry
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Abstract
The research paper is based on the secondary data of the published literature review. The paper is informative to the current and future techno-functional trends and transformations required in the industry for its growth. The research study is to make aware of the use of automation technologies like the Internet of Things (IoT) as an efficient and effective solution to lean implementation in the manufacturing and engineering industry. The research study is done to understand the strategic techniques and their applications of lean manufacturing systems. And add to it the use of technologies like Industrial IoT (IIoT), which will help the manufacturing industry to smoothly implement lean system. The study uses secondary data only and is kept for future research on quality and quantitative survey aspects to study the impact and effectiveness on financial performance and human resource productivity using automation for lean manufacturing systems.
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J, V., & O, J. (2023). IOT: Key Automation Solution to Efficate the Lean System in Manufacturing Industry. SAMRIDDHI : A Journal of Physical Sciences, Engineering and Technology, 15(02), 197-205. https://doi.org/10.18090/samriddhi.v15i02.03
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Research Article
References
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[5] Yang, X. Cao, X. Li, Q. Zhang, L. Qian, Mobile-edge-computingbased hierarchical machine learning tasks distribution for IIoT, IEEE Internet of Things Journal 7 (3) (2019) 2169–2180. https:// www.semanticscholar.org/paper/Mobile-Edge-Computing-
Based-Hierarchical-Machine-Yang-Cao/7e75dc30180ef24876 53fa8afc76cfd1bd955cdf
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researchgate.net/publication/316602629_An_empirical_
review_of_lean_manufacturing_and_their_strategies
[7] Mourtzis, E. Vlachou, N.J.P.C. Milas, Industrial big data as a result of IoT adoption in manufacturing, Procedia cirp 55 (2016) 290–295. https://scholar.archive.org/work/ drrhmjwxdvgv7d7zpkaaupcjoi
[8] Singh, G. Tripathi and A. J. Jara, “A Survey of Internet-of-Things: Future Vision, Architecture, Challenges and Services”, Proc. IEEE World Forum on Internet of Things, Seoul, vol.1,pp. 287–292, Mar. 2014. https://sci-hub.se/10.1109/WF-IoT.2014.6803174 [9] Miorandi, S. Sicari, F. De Pellegrini, et al. “Internet of things: Vision, applications and research challenges,” Ad Hoc Networks, 2012, 10(7): 1497-1516. https://www.academia.edu/10395304/Internet_ of_things_Vision_applications_and_research_challenges
[10] Fraile, T. Tagawa, R. Poler, A. Ortiz, Trustworthy industrial IoT gateways for interoperability platforms and ecosystems, IEEE Internet of Things Journal 5 (6) (2018) 4506–4514. https:// www.semanticscholar.org/paper/Trustworthy-Industrial-IoTGatewaysfor-Platforms-Fraile-Tagawa/67b05b46e26dd1ae34
9ee6729764cc473d9e4c94
[11] Forza, C. (1996). Work organization in lean production and traditional plants: what are the differences? International Journal of Operations & Production Management, 16(2), 42-62.
https://www.econbiz.de/Record/work-organization-in-leanproductionand-traditional-plants-what-are-the-differencesforza-
cipriano/10006855601
[12] Gupta, S., & Jain, S. K. (2013). A literature review of lean manufacturing. International Journal of Management Science and Engineering Management, 8(4), 241–249. https://www.
researchgate.net/publication/263555724_A_literature_review_ of_lean_manufacturing
[13] Kagermann, J. Helbig, A. Hellinger, et al. “Recommendations for Implementing the Strategic Initiative INDUSTRIE 4.0: Securing the Future of German Manufacturing Industry; Final Report of the Industrie 4.0 Working Group”, Forschungsunion, 2013. https://www.scirp.org/reference/referencespapers.
aspx?referenceid=2966479
[14] J. Pizo_n, G. Kłosowski, J. Lipski, Key role and potential of Industrial Internet of Things (IIoT) in modern production monitoring applications, in: MATEC Web of Conferences, 252, EDP Sciences, 2019, 09003. https://www.researchgate.
net/publication/330362411_Key_role_and_potential_of_
Industrial_Internet_of_Things_IIoT_in_modern_production_ monitoring_applications
[15] J. Sasiain, A. Sanz, J. Astorga, E. Jacob, Towards flexible integration of 5G and IIoT technologies in industry 4.0: a practical use case, Appl. Sci. 10 (21) (2020) 7670. https:// www.researchgate.net/publication/346017492_Towards_
Flexible_Integration_of_5G_and_IIoT_Technologies_in_
Industry_40_A_Practical_Use_Case
[16] J. Leng, G. Ruan, P. Jiang, K. Xu, Q. Liu, X. Zhou, C. Liu, Blockchainempowered sustainable manufacturing and product lifecycle
management in industry 4.0: a survey, Renew. Sustain. Energy Rev. 132 (2020), 110112. https://www.researchgate.net/ publication/343276482_Blockchain-empowered_sustainable_ manufacturing_and_product_lifecycle_management_in_
industry_40_A_survey
[17] J. Lee, B. Bagheri, H. A. Kao, “A cyber-physical systems architecture for industry 4.0-based manufacturing systems,” Manufacturing Letters, 2015, 3: 18-23. https://www.researchgate.
net/publication/269709304_A_Cyber-Physical_Systems_
architecture_for_Industry_40-based_manufacturing_systems [18] K. Wallis, M. Hüffmeyer, A.S. Koca, C. Reich, Access Rules enhanced by dynamic IIoT context. IoTBDS, 2018, pp. 204–211.
https://scholar.archive.org/work/x3qcx66fkzaijnadxo5wny2ite [19] K.T. Park, Y.T. Kang, S.G. Yang, W.B. Zhao, Y.S. Kang, S.J. Im, S. Do Noh, Cyber physical energy system for saving energy of the dyeing process with industrial Internet of Things and manufacturing big data, International Journal of Precision Engineering and Manufacturing-Green Technology 7 (1) (2020) 219–238. https://www.scirp.org/(S(czeh2tfqyw2orz553k1w0r45))/ reference/referencespapers.aspx?referenceid=2317730
[20] L. Atzori, A. Iera, G. Morabito, “The internet of things: A survey,” Computer networks, 2010, 54(15): 2787-2805. http://www.
sciepub.com/reference/146418
[21] Poksinska, B. (2010). The current state of Lean implementation in health care: literature review. Quality Management in Health Care, 19(4), 319–329. https://www.researchgate.
net/publication/47349706_The_Current_State_of_Lean_
Implementation_in_Health_Care
[22] Pekuri, A., Herrala, M., Aapaoja, A., & Haapasalo, H.
(2012). Applying Lean in Construction – Cornerstones for Implementation. Proceedings for the 20th Annual Conference of the International Group for Lean Construction. https://www.
researchgate.net/publication/265175980_Applying_lean_in_ construction_-_Cornerstones_for_implementation
[23] P. Wright, “Cyber- physical pro duct manufacturing,” Manufacturing Letters, 2014, 2(2): 49-53. https://www.
researchgate.net/publication/306426761_Cyber-physical_ systems_in_manufacturing
[24] P. Zhan, S. Wang, J. Wang, L. Qu, K. Wang, Y. Hu, X. Li, Temporal anomaly detection on IIoT-enabled manufacturing, J. Intell.
Manuf. (2021) 1–10. https://link.springer.com/article/10.1007/ s10845-021-01768-1
[25] Venkata Krishna Bharadwaj Parasaram. (2022). Converging Intelligence: A Comprehensive Review of AI and Machine Learning Integration Across Cloud-Native Architectures.
International Journal of Research & Technology, 10(2), 29–34.
Retrieved from https://ijrt.org/j/article/view/749
[26] R. Contreras-Masse, A. Ochoa-Zezzatti, V. García, L. P_erezDominguez, M. Elizondo-Cort_es, implementing a novel use of multicriteria decision analysis to select IIoT platforms for smart manufacturing, Symmetry 12 (3) (2020) 368. https://researchr.
org/publication/Contreras-Masse20
[27] Rose, A. N. M., Md. Deros, B., & Ab. Rahman, M. N. (2013). A study on lean manufacturing implementation in Malaysian automotive component industry. International Journal of Automotive. http://dx.doi.org/10.15282/ijame.8.2013.33.0121 [28] Sreenivasulu, R., & Rao, C. (2019). Applicability of Industrial Internet of Things (IIoT) in Lean Manufacturing: A brief Study.
AKGEC INTERNATIONAL JOURNAL OF TECHNOLOGY, Vol. 10,
No. 2. https://www.researchgate.net/publication/337286599_ Applicability_of_Industrial_Internet_of_Things_IIoT_in_Lean_ Manufacturing_A_brief_Study
[29] Singh, B., Garg, S. K., & Sharma, S. K. (2010). Development of index for measuring leanness: study of an Indian auto component industry. Measuring Business Excellence, 14(2), 46–53. http://dx.doi.org/10.1108/13683041011047858
[30] Singh, B., Garg, S. K., Sharma, S. K., & Grewal, C. (2010). Lean implementation and its benefits to production industry International Journal of Lean Six Sigma, 1(2), 157–168. https:// doi.org/10.1108/20401461011049520
Satish Kumar Nalluri, Venkata Krishna Bharadwaj Parasaram, Varun Teja Bathini. (2020). Secure Automation Frameworks for Smart Manufacturing Using Blockchain-Assisted Traceability.
International Journal of Research & Technology, 8(2), 47–53.
Retrieved from https://ijrt.org/j/article/view/879
[31] Soriano-Meier, H., & Forrester, P. L. (2002). A model for evaluating the degree of leanness of manufacturing firms.
Integrated Manufacturing Systems, 13(2), 104–109. https://doi.
org/10.1108/09576060210415437
[32] V.A. Yerra, S. Pilla, IIoT-enabled production system for composite intensive vehicle manufacturing, SAE International Journal of Engines 10 (2) (2017) 209–214. https://doi.org/10.4271/201701-0290
[33] Z. Bi, L. D. Xu, C Wang, “Internet of Things for enterprise systems of modern manufacturing,” Industrial Informatics, IEEE Transactions on, 2014, 10(2): 1537-1546. http://dx.doi.
org/10.1109/TII.2014.2300338
[2] A.S. Lalos, A.P. Kalogeras, C. Koulamas, C. Tselios, C. Alexakos, D.
Serpanos, Secure and safe iiot systems via machine and deep learning approaches, Security and Quality in Cyber-Physical Systems Engineering (2019) 443–470. https://researchr.org/ publication/LalosKKTAS19
[3] A. Jayaram, lean six sigma approach for global supply chain management using industry 4.0 and IIoT, in: 2016 2nd international conference on contemporary computing and informatics, IEEE, 2016, December, pp. 89–94. IC3I. https://www.
researchgate.net/publication/314114889_Lean_Six_Sigma_ Approach_for_Global_Supply_Chain_Management_using_
Industry_40_and_IIoT
[4] A. Castiglione, M. Nappi, S. Ricciardi, Trustworthy method for Person identification in IIoT environments by means of facial Dynamics, IEEE Transactions on Industrial Informatics 17 (2) (2020) 766–774. https://scholar.archive.org/work/ omjn6i6hrvddfnuiqtzickcfyi
[5] Yang, X. Cao, X. Li, Q. Zhang, L. Qian, Mobile-edge-computingbased hierarchical machine learning tasks distribution for IIoT, IEEE Internet of Things Journal 7 (3) (2019) 2169–2180. https:// www.semanticscholar.org/paper/Mobile-Edge-Computing-
Based-Hierarchical-Machine-Yang-Cao/7e75dc30180ef24876 53fa8afc76cfd1bd955cdf
[6] Chahala, V., & Narwalb, M. S. (2017). An empirical review of lean manufacturing and their strategies. Growing Science Ltd. https://doi.org/10.5267/j.msl.2017.4.004 https://www.
researchgate.net/publication/316602629_An_empirical_
review_of_lean_manufacturing_and_their_strategies
[7] Mourtzis, E. Vlachou, N.J.P.C. Milas, Industrial big data as a result of IoT adoption in manufacturing, Procedia cirp 55 (2016) 290–295. https://scholar.archive.org/work/ drrhmjwxdvgv7d7zpkaaupcjoi
[8] Singh, G. Tripathi and A. J. Jara, “A Survey of Internet-of-Things: Future Vision, Architecture, Challenges and Services”, Proc. IEEE World Forum on Internet of Things, Seoul, vol.1,pp. 287–292, Mar. 2014. https://sci-hub.se/10.1109/WF-IoT.2014.6803174 [9] Miorandi, S. Sicari, F. De Pellegrini, et al. “Internet of things: Vision, applications and research challenges,” Ad Hoc Networks, 2012, 10(7): 1497-1516. https://www.academia.edu/10395304/Internet_ of_things_Vision_applications_and_research_challenges
[10] Fraile, T. Tagawa, R. Poler, A. Ortiz, Trustworthy industrial IoT gateways for interoperability platforms and ecosystems, IEEE Internet of Things Journal 5 (6) (2018) 4506–4514. https:// www.semanticscholar.org/paper/Trustworthy-Industrial-IoTGatewaysfor-Platforms-Fraile-Tagawa/67b05b46e26dd1ae34
9ee6729764cc473d9e4c94
[11] Forza, C. (1996). Work organization in lean production and traditional plants: what are the differences? International Journal of Operations & Production Management, 16(2), 42-62.
https://www.econbiz.de/Record/work-organization-in-leanproductionand-traditional-plants-what-are-the-differencesforza-
cipriano/10006855601
[12] Gupta, S., & Jain, S. K. (2013). A literature review of lean manufacturing. International Journal of Management Science and Engineering Management, 8(4), 241–249. https://www.
researchgate.net/publication/263555724_A_literature_review_ of_lean_manufacturing
[13] Kagermann, J. Helbig, A. Hellinger, et al. “Recommendations for Implementing the Strategic Initiative INDUSTRIE 4.0: Securing the Future of German Manufacturing Industry; Final Report of the Industrie 4.0 Working Group”, Forschungsunion, 2013. https://www.scirp.org/reference/referencespapers.
aspx?referenceid=2966479
[14] J. Pizo_n, G. Kłosowski, J. Lipski, Key role and potential of Industrial Internet of Things (IIoT) in modern production monitoring applications, in: MATEC Web of Conferences, 252, EDP Sciences, 2019, 09003. https://www.researchgate.
net/publication/330362411_Key_role_and_potential_of_
Industrial_Internet_of_Things_IIoT_in_modern_production_ monitoring_applications
[15] J. Sasiain, A. Sanz, J. Astorga, E. Jacob, Towards flexible integration of 5G and IIoT technologies in industry 4.0: a practical use case, Appl. Sci. 10 (21) (2020) 7670. https:// www.researchgate.net/publication/346017492_Towards_
Flexible_Integration_of_5G_and_IIoT_Technologies_in_
Industry_40_A_Practical_Use_Case
[16] J. Leng, G. Ruan, P. Jiang, K. Xu, Q. Liu, X. Zhou, C. Liu, Blockchainempowered sustainable manufacturing and product lifecycle
management in industry 4.0: a survey, Renew. Sustain. Energy Rev. 132 (2020), 110112. https://www.researchgate.net/ publication/343276482_Blockchain-empowered_sustainable_ manufacturing_and_product_lifecycle_management_in_
industry_40_A_survey
[17] J. Lee, B. Bagheri, H. A. Kao, “A cyber-physical systems architecture for industry 4.0-based manufacturing systems,” Manufacturing Letters, 2015, 3: 18-23. https://www.researchgate.
net/publication/269709304_A_Cyber-Physical_Systems_
architecture_for_Industry_40-based_manufacturing_systems [18] K. Wallis, M. Hüffmeyer, A.S. Koca, C. Reich, Access Rules enhanced by dynamic IIoT context. IoTBDS, 2018, pp. 204–211.
https://scholar.archive.org/work/x3qcx66fkzaijnadxo5wny2ite [19] K.T. Park, Y.T. Kang, S.G. Yang, W.B. Zhao, Y.S. Kang, S.J. Im, S. Do Noh, Cyber physical energy system for saving energy of the dyeing process with industrial Internet of Things and manufacturing big data, International Journal of Precision Engineering and Manufacturing-Green Technology 7 (1) (2020) 219–238. https://www.scirp.org/(S(czeh2tfqyw2orz553k1w0r45))/ reference/referencespapers.aspx?referenceid=2317730
[20] L. Atzori, A. Iera, G. Morabito, “The internet of things: A survey,” Computer networks, 2010, 54(15): 2787-2805. http://www.
sciepub.com/reference/146418
[21] Poksinska, B. (2010). The current state of Lean implementation in health care: literature review. Quality Management in Health Care, 19(4), 319–329. https://www.researchgate.
net/publication/47349706_The_Current_State_of_Lean_
Implementation_in_Health_Care
[22] Pekuri, A., Herrala, M., Aapaoja, A., & Haapasalo, H.
(2012). Applying Lean in Construction – Cornerstones for Implementation. Proceedings for the 20th Annual Conference of the International Group for Lean Construction. https://www.
researchgate.net/publication/265175980_Applying_lean_in_ construction_-_Cornerstones_for_implementation
[23] P. Wright, “Cyber- physical pro duct manufacturing,” Manufacturing Letters, 2014, 2(2): 49-53. https://www.
researchgate.net/publication/306426761_Cyber-physical_ systems_in_manufacturing
[24] P. Zhan, S. Wang, J. Wang, L. Qu, K. Wang, Y. Hu, X. Li, Temporal anomaly detection on IIoT-enabled manufacturing, J. Intell.
Manuf. (2021) 1–10. https://link.springer.com/article/10.1007/ s10845-021-01768-1
[25] Venkata Krishna Bharadwaj Parasaram. (2022). Converging Intelligence: A Comprehensive Review of AI and Machine Learning Integration Across Cloud-Native Architectures.
International Journal of Research & Technology, 10(2), 29–34.
Retrieved from https://ijrt.org/j/article/view/749
[26] R. Contreras-Masse, A. Ochoa-Zezzatti, V. García, L. P_erezDominguez, M. Elizondo-Cort_es, implementing a novel use of multicriteria decision analysis to select IIoT platforms for smart manufacturing, Symmetry 12 (3) (2020) 368. https://researchr.
org/publication/Contreras-Masse20
[27] Rose, A. N. M., Md. Deros, B., & Ab. Rahman, M. N. (2013). A study on lean manufacturing implementation in Malaysian automotive component industry. International Journal of Automotive. http://dx.doi.org/10.15282/ijame.8.2013.33.0121 [28] Sreenivasulu, R., & Rao, C. (2019). Applicability of Industrial Internet of Things (IIoT) in Lean Manufacturing: A brief Study.
AKGEC INTERNATIONAL JOURNAL OF TECHNOLOGY, Vol. 10,
No. 2. https://www.researchgate.net/publication/337286599_ Applicability_of_Industrial_Internet_of_Things_IIoT_in_Lean_ Manufacturing_A_brief_Study
[29] Singh, B., Garg, S. K., & Sharma, S. K. (2010). Development of index for measuring leanness: study of an Indian auto component industry. Measuring Business Excellence, 14(2), 46–53. http://dx.doi.org/10.1108/13683041011047858
[30] Singh, B., Garg, S. K., Sharma, S. K., & Grewal, C. (2010). Lean implementation and its benefits to production industry International Journal of Lean Six Sigma, 1(2), 157–168. https:// doi.org/10.1108/20401461011049520
Satish Kumar Nalluri, Venkata Krishna Bharadwaj Parasaram, Varun Teja Bathini. (2020). Secure Automation Frameworks for Smart Manufacturing Using Blockchain-Assisted Traceability.
International Journal of Research & Technology, 8(2), 47–53.
Retrieved from https://ijrt.org/j/article/view/879
[31] Soriano-Meier, H., & Forrester, P. L. (2002). A model for evaluating the degree of leanness of manufacturing firms.
Integrated Manufacturing Systems, 13(2), 104–109. https://doi.
org/10.1108/09576060210415437
[32] V.A. Yerra, S. Pilla, IIoT-enabled production system for composite intensive vehicle manufacturing, SAE International Journal of Engines 10 (2) (2017) 209–214. https://doi.org/10.4271/201701-0290
[33] Z. Bi, L. D. Xu, C Wang, “Internet of Things for enterprise systems of modern manufacturing,” Industrial Informatics, IEEE Transactions on, 2014, 10(2): 1537-1546. http://dx.doi.
org/10.1109/TII.2014.2300338