Preferencje help
Widoczny [Schowaj] Abstrakt
Liczba wyników
2019 | 10 | nr 3 | 3--13
Tytuł artykułu

Industry 4.0: Tools And Implementation

Treść / Zawartość
Warianty tytułu
Języki publikacji
With the increasing demand of customisation and high-quality products, it is necessary for the industries to digitize the processes. Introduction of computers and Internet of things (IoT) devices, the processes are getting evolved and real time monitoring is got easier. With better monitoring of the processes, accurate results are being produced and accurate losses are being identified which in turn helps increasing the productivity. This introduction of computers and interaction as machines and computers is the latest industrial revolution known as Industry 4.0, where the organisation has the total control over the entire value chain of the life cycle of products. But it still remains a mere idea but an achievable one where IoT, big data, smart manufacturing and cloud-based manufacturing plays an important role. The difference between 3rd industrial revolution and 4th industrial revolution is that, Industry 4.0 also integrates human in the manufacturing process. The paper discusses about the different ways to implement the concept and the tools to be used to do the same. (original abstract)
Opis fizyczny
  • Vellore Institute of Technology, India
  • Vellore Institute of Technology, India
  • Vellore Institute of Technology, India
  • Hamzeh R., Zhong R., Xu X.W., A Survey Study on Industry 4.0 for New Zealand Manufacturing, 46th SME North American Manufacturing Research Conference, NAMRC 46, Texas, USA, Procedia Manufacturing, 26, 49-57, 2018.
  • Sarvari P.A., Ustundag A., Cevikcan E., Kaya I., Cebi S., Technology roadmap for industry 4.0, Industry 4.0: Managing the Digital Transformation, Springer, pp. 95-103, 2018.
  • Santos C., Mehrsai A., Barros A.C., Ara´ujo M., Ares E., Towards Industry 4.0: an overview of European strategic roadmaps, Manufacturing Engineering Society International Conference, MESIC 2017, 28-30 June 2017, Vigo Pontevedra, Spain.
  • Vaidhya S., Ambad P., Bhosle S., Industry 4.0 - A Glimpse, Procedia Manufacturing, 20, 233-238, 2018.
  • Tae Kyung Sung, Industry 4.0: A Korea perspective, Technological Forecasting and Social Change, 132, 40-45, 2018.
  • Ibarra D., Ganzarain J., Igartua J.I., Business model innovation through Industry 4.0: A review, 11th International Conference Interdisciplinarity in Engineering, INTER-ENG 2017, 5-6 October 2017, Tirgu-Mures, Romania.
  • Telukdarie A., Buhulaiga E., Bag S., Gupta S., Luo Z., Industry 4.0 implementation for multinationals, Process Safety and Environmental Protection, 118, 316-329, 2018.
  • Szalavetz A., Industry 4.0 and capability development in manufacturing subsidiaries, Technological Forecasting and Social Change, 145(C), 384-395, 2019.
  • Dinardo G., Fabbiano L., Vacca G., A smart and intuitive machine condition monitoring in the Industry 4.0 scenario, Measurement, 126, 1-12, 2018.
  • Qin J., Liu Y., Grosvenor R., A Categorical Framework of Manufacturing for Industry 4.0 and Beyond, Changeable, Agile, Reconfigurable & Virtual Production, Procedia CIRP, 52, 173-178, 2016.
  • Bassi L., Industry 4.0: hope, hype or revolution?, IEEE 3rd International Forum on Research and Technologies for Society and Industry, 2017.
  • Rymaszewska A., Helo P., Gunasekaran A., IoT powered servitization of manufacturing - an exploratory case study, International Journal of Production Economics, 192, 92-105, 2017.
  • Pedone G., Mezg´ar I., Model similarity evidence and interoperability affinity in cloud-ready Industry 4.0. technologies, Computers in Industry, 100, 278-286, 2018.
  • Brettel M., Friederichsen N., Keller M., Rosenberg M., How Virtualization, Decentralization and Network Building Change the Manufacturing Landscape: An Industry 4.0 Perspective, World Academy of Science, Engineering and Technology International Journal of Information and Communication Engineering, 8, 1, 2014.
  • Zhong R.Y., Xu X., Wang L., IoT-enabled Smart Factory Visibility and Traceability using Laser scanners, 45th SME North American Manufacturing Research Conference, NAMRC 45, LA, USA, Procedia Manufacturing, 10, 1-14, 2017.
  • Menezes S., Creado S., Zhong R.Y., Smart Manufacturing Execution Systems for Small and Mediumsized Enterprises, The 51st CIRP Conference on Manufacturing Systems, Procedia CIRP, 72, 1009-1014, 2018.
  • Mayr A., Weigelt M., K¨uhl A., Grimm S., Erll A., Potzel M., Franke J., Lean 4.0 - A conceptual conjunction of lean management and Industry 4.0, Procedia CIRP, 72, 622-628, 2018.
  • Almada-Lobo F., The Industry 4.0 revolution and the future of Manufacturing Execution Systems (MES), Journal of Innovation Management JIM, 3, 4, 16-21, 2015.
  • Mehami J., Nawi M., Zhong R.Y., Smart automated guided vehicles for manufacturing in the context of Industry 4.0, Procedia Manufacturing, 26, 1077-1086, 2018.
  • Lu S., Xu C., Zhong R.Y.,Wang L., A passive RFID tag-based locating and navigating approach for automated guided vehicle, Computers & Industrial Engineering, 125, 628-636, 2018.
  • Lee J., Davari H., Singh J., Pandhare V., Industrial Artificial Intelligence for industry 4.0-based manufacturing systems, Manufacturing Letters, 18, 20-23, 2018.
  • Lee K., Artificial intelligence, automation, and the economy, The White. House Blog, 2016.
  • Lee J., Bagheri B., Kao H.A., A cyber-physical systems architecture for industry 4.0-based manufacturing systems, Manuf. Lett., pp. 18-23, 2015.
  • Zhong R.Y., Xu X., Klotz E., Newman S.T., Intelligent Manufacturing in the Context of Industry 4.0: A Review, Engineering, 3, 616-630, 2017.
  • Zhong R.Y., Hunag G.Q., Lan S.L., Dai Q.Y., Zhang T., Xu C., A two-level advanced production planning and scheduling model for RFID-enabled ubiquitous manufacturing, Advanced Engineering Informatics, 2015.
  • Suárez F.-M., Marcos M., Peralta M.E., Aguayo F., the challenge of integrating Industry 4.0 in the degree of Mechanical Engineering, Manufacturing Engineering Society International Conference, 2017.
  • Bogetoft P., Performance Benchmarking: Measuring and managing performance, Springer, New York, USA, 2012.
  • Davies R., Industry 4.0: Digitalisation for productivity and growth, European Parliamentary Research Service, Briefing September, 2015.
  • Jihong Yan, Yue Meng, Lei Lu, Lin Li, Industrial Big Data in an Industry 4.0 Environment: Challenges, Schemes, and Applications for Predictive Maintenance, 5, 23484-23491, 2017.
  • Wang S., Wan J., Zhang D., Li D., Zhang C., Towards smart factory for industry 4.0: a selforganized multi-agent system with big-data based feedback and coordination, Computer Networks, 101, 158-168, 2016.
  • Bourne V., The state of big data infrastructure: Benchmarking global big data users to drive future performance, April 2015.
  • Santos M.Y., e Sá J.O., Andrade C., Lima F.V., Costa E., Costa C., Martinho B., Galvão J., A Big Data system supporting Bosch Braga Industry 4.0 strategy, International Journal of Information Management, 37, 6, 750-760, 2017.
  • Miragliotta G., Sianesi A., Convertini E., Distante R., Data driven management in Industry 4.0: a method to measure Data Productivity, IFAC PapersOnLine, 51-11, 19-24, 2018.
  • Cheng Ch.-Y., A novel approach of information visualization for machine operation states in industrial 4.0, Computers & Industrial Engineering, 125, 563-573, 2018.
  • Gamberini R., Galloni L., Lolli F., Rimini B., On the Analysis of Effectiveness in a Manufacturing Cell: A Critical Implementation of Existing Approaches, 27th International Conference on Flexible Automation and Intelligent Manufacturing, FAIM2017, 27-30 June 2017, Modena, Italy, Procedia Manufacturing, 11, 1882-1891, 2017.
  • Peters G., Weber R., dynXcube - Categorizing Dynamic Data Analysis, Information Sciences, 463-464, 21-32, October 2018.
  • Chen F., Deng P., Wan J., Zhang D., Vasilakos A., Rong X., Data mining for the internet of things: literaturę review and challenges, International Journal of Distributed Sensor Networks, 2015.
  • Vallhagen J., Almgren T., Th¨ornblad K., Advanced use of data as an enabler for adaptive production control using mathematical optimization - an application of Industry 4.0 principles, 27th International Conference on Flexible Automation and Intelligent Manufacturing, Procedia Manufacturing, 11, 663-670, 2017.
  • Vallhagen J., Almgren T., Strategies for Value Stream Mapping and Production Planning - Experiences from Low Volume Production in the Aerospace Industry, Proceedings of the 6th Swedish Production Symposium, SPS14, Gothenburg, Sweden, 2014.
  • Foehr M., Towards Industrial Exploitation of Innovative and Harmonized Production Systems, The 42nd Annual Conference of IEEE Industrial Electronics Society, 2016.
  • Leitão P., Instantiating the PERFoRM System Architecture for Industrial Case Studies, 6th Workshop on Service Orientation in Holonic and Multi-Agent Manufacturing, 2016.
  • Liebrecht C., Jacob A., Kuhnle A., Lanza G., Multi-Criteria Evaluation of Manufacturing Systems 4.0 under Uncertainty, The 50th CIRP Conference on Manufacturing Systems, Procedia CIRP, 63, 224-229, 2017.
  • Zhong R.Y., Xu C., Chen C., Huang G.Q., Big data analytics for physical internet based intelligent manufacturing shop floors, Int. J. Prod., pp. 2610-2621, 2017.
  • Liu C., Vengayil H., Zhong R.Y., Xu X., A systematic development method for cyber-physical machine tools, Journal of Manufacturing Systems, 48, 13-24, 2018.
  • Zamfirescu C.-B., Pîrvu B.-C., Loskyll M., Zühlke D., Do Not Cancel My Race with Cyber-Physical Systems, IFAC: Promoting automatic control for the benefit of humankind. Cape Town, South Africa, 2014.
  • Behrendt A., M¨uller N., Odenwälder P., Schmitz C., Industry 4.0 Demystified - Lean's Next Level, McKinsey & Company, 2017.
  • Salkin C., Oner M., Ustundag A., Cevikcan E., A conceptual framework for industry 4.0, in: Industry 4.0: Managing the Digital Transformation, Springer, pp. 3-23, 2018.
  • Baldwin C.Y., Clark K.B., Design Rules: The Power of Modularity, Mit Press, pp. 471, 2000.
  • Weyer S., Schmitt M., Ohmer M., Gorecky D., Towards Industry 4.0 - Standardization as the crucial challenge for highly modular, multi-vendor production systems, IFAC-Papers On-Line, 48-3, 579-584, 2015.
  • Trstenjaka M., Cosic P., Process planning in Industry 4.0 environment, 27th International Conference on Flexible Automation and Intelligent Manufacturing, FAIM2017, 2017.
  • Ahuett-Garza H., Kurfess T., A brief discussion on the trends of habilitating technologies for Industry 4.0 and Smart manufacturing, Manufacturing Letters, 15, 60-63, 2018.
  • Börkircher M., Frank H., Gärtner R., Wüseke F., Digitalisierung & Industrie 4.0, Düsseldorf.
  • Ante G., Facchini F., Mossa G., Digiesi S., Developing a key performance indicators tree for lean and smart production systems, IFAC PapersOnLine, 51-11, 13-18, 2018.
  • Rosimah S., Sudirman I., Siswanto J., Sunaryo I., An Autonomous Maintenance Team in ICT Network System of Indonesia Telecom Company, 2nd International Material, Industrial, and Manufacturing Engineering Conference, 2015.
  • Marvuglia A., Messineo A., Monitoring of wind farms' power curves using machine learning techniques, Appl. Energy, 98, 574-583, 2012.
  • Hedman R., Subramaniyan M., Almström P., Analysis of Critical Factors for Automatic Measurement of OEE, 49th CIRP Conference on Manufacturing Systems, 2016.
  • Whitepaper I., Implementing OEE Systems: Delivering on the Promise: Best Practices for Continuous Improvement, Copyright Idhammar Systems ltd., 2010.
  • Barreto L., Amarala A., Pereira T., Industry 4.0 implications in logistics: an overview, Manufacturing Engineering Society International Conference, MESIC 2017, 2017.
  • Uckelmann D., Definition Approach to Smart Logistics, Wireless Advanced Networking, 2008.
  • KPMG, The Factory of the Future: Industry 4.0 - the challenges of tomorrow, 2016.
  • Schrauf S., Berttram P., Industry 4.0: How digitization makes the supply chain more efficient, agile, and customer-focused, PWC Report, March 2017.
  • Qin E., Long Y., Zhang C., Huang L., Cloud Computing and the Internet of Things: Technology Innovation in Automobile Service, International Conference on Human Interface and the Management of Information. Information and Interaction for Health, Safety, Mobility and Complex Environments, pp. 173-180, 2013.
  • Lezzi M., Lazoi M., Corallo A., Cybersecurity for Industry 4.0 in the current literature: a reference framework, Computers in Industry, 103, 97-110, 2018.
  • Roy R., Stark R., Tracht K., Takata S., Mori M., Continuous maintenance and the future - foundations and technological challenges, CIRP Ann. Manuf. Technol., 65 (2), 667-688, 2016.
  • Kobara K., Cyber physical security for industrial control systems and IoT, IEICE Trans. Inf. Syst., E99D (4), 787-795, 2016.
  • Kagermann H., Wahlster W., Helbig J., Recommendations for implementing the strategic initiative INDUSTRIE 4.0., Final report of the Industrie 4.0 Working Group. Acatech, Frankfurt am Main, Germany, 2013.
  • Müller J.M., Buliga O., Voigt K.-I., Fortune favours the prepared: How SMEs approach business model innovations in Industry 4.0, Technological Forecasting & Social Change, 132, 2-17, 2018.
  • Cusumano M.A., Kahl S.J., Suarez F.F., Services, industry evolution, and the competitive strategies of product firms, Strateg. Manag. J., 36 (4), 559-575, 2015.
  • Angappa Gunasekaran, Nachiappan Subramanian, Sustainable operations modelling and data analytics, Computers and Operations Research, 89, 163-167, 2018.
  • Tranfield D., Denyer D., Smart P., Towards a methodology for developing evidence-informed management knowledge by means of systematic review, Br. J. Manag., 14, 207-222, 2003.
  • Paravizo E., Chaim O.C., Braatz D., Muschard B., Rozenfeld H., Exploring gamification to suport manufacturing education on industry 4.0 as an enabler for innovation and sustainability, Procedia Manufacturing, 21, 438-445, 2018.
  • Sunil Luthra, Sachin Kumar Mangla, Evaluating challenges to Industry 4.0 initiatives for supply chain sustainability in emerging economies, Process Safety and Environmental Protection, 117, 168-179, 2018.
  • Tupa J., Simota J., Steiner F., Aspects of risk management implementation for Industry 4.0, 27th International Conference on Flexible Automation and Intelligent Manufacturing, FAIM2017, June 2017.
  • Faheem M., Shah S.B.H., Butt R.A., Raza B., Anwar M., Ashraf M.W., Ngadi Md.A., Gungor V.C., Smart grid communication and information technologies in the perspective of Industry 4.0: Opportunities and challenges, Computer Science Review, 30, 1-30, 2018.
  • Sachin S. Kamble, Angappa Gunasekaran, Rohit Sharma, Analysis of the driving and dependence power of barriers to adopt industry 4.0 in Indian manufacturing industry, Computers in Industry, 101, 107-119, 2018.
  • Khan M., Wu X., Xu X., Dou W., Big data challenges and opportunities in the hype of Industry 4.0, IEEE International Conference on Communications (ICC), pp. 1-6, 2017.
  • Li L., China's manufacturing locus in 2025: With a comparison of "Made-in-China 2025" and "Industry 4.0", Technological Forecasting & Social Change, 135(C), 66-74, 2018.
  • Md. Abdul Moktadir, Syed Mithun Ali, Simonov Kusi-Sarpong, Md. Aftab Ali Shaikh, Assessing challenges for implementing Industry 4.0: Implications for process safety and environmental protection, Process Safety and Environmental Protection, 117, 730-741, 2018.
  • Hofmann E., Rüsch M., Industry 4.0 and the current status as well as future prospects on logistics, Computer Ind., 89, 23-34, 2017.
  • Angappa Gunasekaran, Nachiappan Subramanian, Eric Ngai, Quality Management in the 21st Century Enterprises: Research pathway towards Industry 4.0, International Journal of Production Economics, 207, 125-129, 2019.
  • Santos K., Loures E., Piechnicki F., Canciglieri O., Opportunities Assessment of Product Development Process in Industry 4.0, 27th International Conference on Flexible Automation and Intelligent Manufacturing, FAIM2017, 2017.
  • Wagner T., Herrmann C., Thiede S., Identifying target oriented Industrie 4.0 potentials in lean automotive electronics value streams, 51st CIRP Conference on Manufacturing Systems, Procedia CIRP, 72, 1003-1008, 2018.
  • Lorenz R., Lorentzen K., Stricker N., Lanza G., Applying User Stories for a customer-driven Industry 4.0 Transformation, IFAC PapersOnLine, 51-11, 1335-1340, 2018.
Typ dokumentu
Identyfikator YADDA

Zgłoszenie zostało wysłane

Zgłoszenie zostało wysłane

Musisz być zalogowany aby pisać komentarze.
JavaScript jest wyłączony w Twojej przeglądarce internetowej. Włącz go, a następnie odśwież stronę, aby móc w pełni z niej korzystać.