A Conceptual Definition and Future Directions of Urban Smart Factory for Sustainable Manufacturing
Abstract
:1. Introduction
2. Research Background
2.1. Mass Personalization
2.2. Sustainable Manufacturing
2.3. Urban Factory
2.4. Smart Factory
3. Literature Review
3.1. Application of SF Core Technologies and Key Manufacturing Systems in Urban Production
3.2. Case Studies
- Adidas—Knit for you (Germany)Concept: Production of personalized knit at a shopping mall (Berlin)Structure: User-friendly design interfaceTechnology: 3D scanning and real-time simulationBenefits: Affordable personalized product, shortened design and production time, and supply chainPersonalization is one of the most critical aspects of the USF, as presented in the previous section. Adidas’ ‘Knit for you’ pop-up store in Berlin is an appropriate case to highlight this concept. Customers directly designed their sweaters, while a 3D scanner was utilized to find the customer’s exact fit, and then the sweater was made in the store, and customers took the product home on the same day [71,72].
- Close to the customer (CTC) mini-factory (Italy)Concept: Production of personalized, sustainable furniture at a shopping mallStructure: User-friendly configuratorTechnology: IoT, cloud, modular product design, real-time update of production data monitoringBenefits: Customer satisfaction, shorter supply chain, reduced waste, image, and appearance shared have impressed a high number of visitors of the shopping mall.Another USF case study focusing on personalization is the ‘Close to the Customer (CTC) mini-factory’ scenario, in which personalized furniture is produced behind a glass panel in a shopping mall. A user-friendly configurator supports customers to personalize furniture preferences. Predefined parametric portfolios of products and functional constraints of the mini-factory are drivers of furniture design [36,73].
- DigiPlex (Sweden)Concept: Resource efficiency—reusing waste heat for heating residents in Stockholm Benefits: Environmental sustainabilityEnvironmental sustainability is primarily concerned with energy and resource efficiency. In addition to energy monitoring, one significant way of improving energy efficiency is that companies supply electricity and heat to the cities from the waste heat of industrial processes. DigiPlex (data center operator) and Stockholm Exergi (heating and cooling supplier) agreed to reuse the waste heat of the data center for heating 10,000 modern apartments in Stockholm, Sweden [43].
- Alpha Biofuel (Singapore)Concept: Material and resource efficiency—reusing waste cooking oil as biofuelsBenefits: Environmental sustainabilityResource efficiency usually improves by minimizing waste through design and process improvement. One innovative way for resource efficiency in urban manufacturing is to use available waste materials as resources. Alpha Biofuel Pte Ltd.(Singapore 637601, Singapore) produces and sells small-scale refineries to convert cooking oil into biodiesel. The National University of Singapore has practiced recycling used cooking oil from different faculties into biodiesel to fuel university cars [38].
- Wittenstein bastian—Future Urban Production (Germany)Concept: Environmental, Social, and Economic Sustainable Production in FellbachTechnology: Smart Sensors, IoT, CPSBenefits: Improving workplace well-being, low noise and emission, and sharing of residual heat with surrounding urban areasWittenstein bastian is a USF located in Fellbach near Stuttgart. People, machines, and products communicate through an intelligent CPS. Wittenstein considers employees fundamental to all production processes. To increase employees’ productivity and flexibility, tailored information is provided to them at the right time. Low noise and emissions, and energy efficiency for residential neighborhoods that contribute to the local community by using residual heat during production as district heating are other company attributes [46,74].
- Factory-as-a-Service (South Korea)Concept: Multiple connected micro-factories for resilient personalized productionStructure: Factory-as-a-Service (FaaS) cloud platform, FaaS manufacturing operation platform, FaaS monitoring and control platformTechnology: DT and CPS, 3D printingBenefits: Real-time monitoring of the present, tracking of past information, and operational decision-making to support the future reduction of cost and production inefficienciesDistributed and modular manufacturing systems contribute to the first pillar of USF, personalization, and bring solutions for major issues such as spatial limits and logistics. FaaS, an open manufacturing service, consists of a multiple connected micro smart factory (CMSF) developed with DT application to achieve logistical advantages and ensure the efficiency of manufacturing through real-time monitoring, tracking the past, and decision-making support by predicting the future [75,76]. To achieve resilient production control, there are core functional requirements: action selection, KPI measurement, adjustment through modular production systems, DT applications, and reinforcement learning [76,77].
- Nobilia—Manufacturing by Wire (Germany)Concept: Production of personalized kitchensStructure: Nobilia Kitchen ConfiguratorTechnology: Smart Sensor, IoT, CPS, decentralized decision-makingBenefits: Optimizing the degree of personalization, shortening the manufacturing time, reducing waste materials and energy consumption, and practical production of products in a wide variety and high volume.Nobilia, the German kitchen manufacturer, produces 2,800 personalized kitchens every day, with 14 million possible variations. This is feasible through CPPS. Nobilia introduced a production system called ‘Manufacturing by Wire’ to secure competitiveness through in-house production in Germany. By implementing SF technologies, such as IoT and CPS, mass personalization was achieved. SF attributes, such as decentralized and autonomous decision-making, significantly reduced the production time. Each raw material was attached to a barcode containing the customer’s order. Material-machine and machine-machine connections, through IoT, made it possible to produce different types of furniture in one production line. Through SF realization, quality is maintained, waste materials are minimized, and production costs are significantly reduced [78,79].
- Volkswagen—Transparent Factory (Germany)Concept: Production of personalized autos in a fully transparent production lineBenefits: Optimizing customer experiencesIn addition to personalization, developing a new business model such as servitization is important for USF. In this regard, Volkswagen’s ‘Glass Factory’, opened in December 2001 in Dresden, is a brilliant example. The production facility, equipped with soundproof windows, is grounded on an entirely new approach that blends industrial vehicle production and high-quality workmanship under visible conditions. Purchasing has transformed into a personalized matter in which, customers can not only choose and order the vehicle, but also monitor the manufacturing in real-time. As a result, the emotional ties between customers and the brand are reinforced. The ‘Transparent Factory’ also establishes new norms as a service center where the manufacturing process is displayed as an attraction. The image and appearance of an urban factory are well reflected [80,81].
- Hyundai Motor Group—E-FOREST (HMGICS at Singapore)Concept: Sustainable and resilient production of personalized mobility productsStructure: Customer interface for personalized designTechnology: Smart sensor, IoT, DT and CPSBenefits: Optimizing customer satisfaction, improving workplace well-being, sharing infrastructure for global research and development experts, and collaboration with local communitiesRecently, Hyundai Motor Group announced the E-FOREST as ‘an innovative smart factory of Hyundai/Kia Motors that would connect people, nature, and technology into one.’ The E-forest seeks manufacturing system innovation by naturally connecting everything to create customer value. The E-Forest pilot plant was launched in Ulsan in January 2020. E-Forest strives to achieve three values: auto-flex, intelligence, and humanity. Auto-flex is about the flexibility and responsiveness of the system that comes by introducing a new and advanced automated manufacturing technique. Autonomous systems are realized by using artificial intelligence and big data to achieve self-resilience. In addition to all data from systems within the factory, information from beyond the facility is collected and analyzed to optimize consumer satisfaction. Finally, workplace well-being is of great value and is maximized in the E-Forest. Two examples are of wearable robots that aid employees in the manufacturing line (Vest Exoskeleton) and a knee-supporting robot (chairless exoskeleton) [82]. After the E-Forest pilot plant launched domestically, the Hyundai Motor Group announced the establishment of the Hyundai Mobility Global Innovation Center in Singapore (HMGICS). It was introduced as a manufacturing hub hosting a thriving ecosystem of researchers, technology, training providers, and future factories. HMGICS, as a complete model of E-Forest, is expected to open in the second half of 2022. As a customer-centered smart mobility environment, personalization and mobility services maximize customer well-being. Human-centered digital transformation improves workplace well-being. As an urban factory located in the center of Singapore, it not only cares about environmental sustainability (through renewable energy use and resource efficiency) but also shares infrastructure for global research and development experts while expanding collaboration with local research institutes and universities [83,84].
4. Urban Smart Factory
4.1. Concept
“a factory in which product/service personalization, employee well-being, collaboration with local communities, sustainability, and resilience are the primary objectives to be achieved through the utilization and realization of the SF”.
4.2. USF Structure
- The customer–design interface provides customers with easy and comprehensive virtual design tools and attractive visualization.
- The product lifecycle management interface gathers product data at the usage stage for product performance analysis and future design improvement purposes and facilitates recycling and reusing activities.
- Collaboration with local communities, such as excess energy sharing, education, and open innovation, can be managed by a collaboration interface.
4.3. USF Core Technologies and Key Manufacturing Systems
4.4. Benefits
5. Conclusions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
- Herrmann, C.; Schmidt, C.; Kurle, D.; Blume, S.; Thiede, S. Sustainability in manufacturing and factories of the future. Int. J. Precis. Eng. Manuf.-Green Technol. 2014, 1, 283–292. [Google Scholar] [CrossRef] [Green Version]
- Qin, J.; Liu, Y.; Grosvenor, R. A categorical framework of manufacturing for industry 4.0 and beyond. Procedia CIRP 2016, 52, 173–178. [Google Scholar] [CrossRef] [Green Version]
- Koren, Y. The Global Manufacturing Revolution: Product-Process-Business Integration and Reconfigurable Systems; John Wiley & Sons: Hoboken, NJ, USA, 2010; Volume 80. [Google Scholar]
- Hu, S.J.; Ko, J.; Weyand, L.; ElMaraghy, H.A.; Lien, T.K.; Koren, Y.; Bley, H.; Chryssolouris, G.; Nasr, N.; Shpitalni, M. Assembly system design and operations for product variety. CIRP Ann. 2011, 60, 715–733. [Google Scholar] [CrossRef]
- Xu, L.D.; Xu, E.L.; Li, L. Industry 4.0: State of the art and future trends. Int. J. Prod. Res. 2018, 56, 2941–2962. [Google Scholar] [CrossRef] [Green Version]
- Lu, Y. Industry 4.0: A survey on technologies, applications and open research issues. J. Ind. Inf. Integr. 2017, 6, 1–10. [Google Scholar] [CrossRef]
- Kang, H.S.; Lee, J.Y.; Choi, S.; Kim, H.; Park, J.H.; Son, J.Y.; Kim, B.H.; Noh, S.D. Smart manufacturing: Past research, present findings, and future directions. Int. J. Precis. Eng. Manuf.-Green Technol. 2016, 3, 111–128. [Google Scholar] [CrossRef]
- Westkämper, E. Global “Megatrend’s” grand societal challenges. In Towards the Re-Industrialization of Europe; Springer: Berlin, Germany, 2014; pp. 17–22. [Google Scholar] [CrossRef]
- Retief, F.; Bond, A.; Pope, J.; Morrison-Saunders, A.; King, N. Global megatrends and their implications for environmental assessment practice. Environ. Impact Assess. Rev. 2016, 61, 52–60. [Google Scholar] [CrossRef]
- Burggräf, P.; Dannapfel, M.; Uelpenich, J.; Kasalo, M. Urban factories: Industry insights and empirical evidence within manufacturing companies in German-speaking countries. Procedia Manuf. 2019, 28, 83–89. [Google Scholar] [CrossRef]
- Simons, L.; Stiehm, S.; Richert, A.; Jeschke, S. Reflecting Factors of Urban Production: A Text Mining Approach. In Proceedings of the European Conference on Knowledge Management, Barcelona, Spain, 7–8 September 2017; Academic Conferences International Limited: Kidmore End, UK; pp. 906–912. [Google Scholar]
- Tsui, T.; Peck, D.; Geldermans, B.; van Timmeren, A. The Role of Urban Manufacturing for a Circular Economy in Cities. Sustainability 2021, 13, 23. [Google Scholar] [CrossRef]
- Haselsteiner, E.; Grob, L.M.; Frey, H.; Madner, V.; Laa, B.; Schwaigerlehner, K. The Vertical Urban Factory as a Concept for Mixed Use in Future Cities. In Shaping Urban Change —Livable City Regions for the 21st Century, Proceedings of the REAL CORP 2020—25th International Conference on Urban Development, Regional Planning and Information Society, Aachen, Germany, 15–18 September 2020; CORP: Vienna, Austria, 2020; pp. 873–881. [Google Scholar]
- Matt, D.T.; Orzes, G.; Rauch, E.; Dallasega, P. Urban production—A socially sustainable factory concept to overcome shortcomings of qualified workers in smart SMEs. Comput. Ind. Eng. 2020, 139, 105384. [Google Scholar] [CrossRef]
- Juraschek, M.; Bucherer, M.; Schnabel, F.; Hoffschröer, H.; Vossen, B.; Kreuz, F.; Thiede, S.; Herrmann, C. Urban factories and their potential contribution to the sustainable development of cities. Procedia CIRP 2018, 69, 72–77. [Google Scholar] [CrossRef]
- Aheleroff, S.; Zhong, R.Y.; Xu, X. A Digital Twin Reference for Mass Personalization in Industry 4.0. Procedia CIRP 2020, 93, 228–233. [Google Scholar] [CrossRef]
- Guo, D.; Ling, S.; Li, H.; Ao, D.; Zhang, T.; Rong, Y.; Huang, G.Q. A framework for personalized production based on digital twin, blockchain and additive manufacturing in the context of Industry 4.0. In Proceedings of the 2020 IEEE 16th International Conference on Automation Science and Engineering (CASE), Hong Kong, China, 20–21 August 2020; IEEE: New York, NY, USA, 2020. [Google Scholar] [CrossRef]
- Mourtzis, D.; Doukas, M. Design and planning of manufacturing networks for mass customization and personalization: Challenges and outlook. Procedia CIRP 2014, 19, 1–13. [Google Scholar] [CrossRef] [Green Version]
- Koren, Y.; Hu, S.; Gu, P.; Shpitalni, M. Open-architecture products. CIRP Ann. 2013, 62, 719–729. [Google Scholar] [CrossRef]
- Mourtzis, D.; Doukas, M.; Psarommatis, F.; Giannoulis, C.; Michalos, G. A web-based platform for mass customization and personalization. CIRP J. Manuf. Sci. Technol. 2014, 7, 112–128. [Google Scholar] [CrossRef]
- Kumar, A. From mass customization to mass personalization: A strategic transformation. Int. J. Flex. Manuf. Syst. 2007, 19, 533–547. [Google Scholar] [CrossRef]
- Herrmann, C.; Juraschek, M.; Burggräf, P.; Kara, S. Urban production: State of the art and future trends for urban factories. CIRP Ann. 2020, 69, 764–787. [Google Scholar] [CrossRef]
- Mourtzis, D.; Doukas, M.; Psarommatis, F. Simulation-based design of production networks for manufacturing of personalized products. In Proceedings of the IFIP International Conference on Advances in Production Management Systems, Rhodes, Greece, 24–26 September 2012; Springer: Berlin, Germany, 2012. [Google Scholar] [CrossRef] [Green Version]
- Aheleroff, S.; Philip, R.; Zhong, R.Y.; Xu, X. The degree of mass personalization under Industry 4.0. Procedia CIRP 2019, 81, 1394–1399. [Google Scholar] [CrossRef]
- Dwivedi, A.; Moktadir, M.A.; Jabbour, C.J.C.; de Carvalho, D.E. Integrating the circular economy and industry 4.0 for sustainable development: Implications for responsible footwear production in a big data-driven world. Technol. Forecast. Soc. Chang. 2021, 175, 121335. [Google Scholar] [CrossRef]
- Whicher, A.; Harris, C.; Beverley, K.; Swiatek, P. Design for circular economy: Developing an action plan for Scotland. J. Clean. Prod. 2018, 172, 3237–3248. [Google Scholar] [CrossRef]
- Emas, R. The Concept of Sustainable Development: Definition and Defining Principles; Brief for GSDR 2015; United Nations’ 2015 Global Sustainable Development Report; United Nations: New York, NY, USA, 2015. [Google Scholar]
- Machado, C.G.; Winroth, M.P.; da Silva, E.H.D.R. Sustainable manufacturing in Industry 4.0: An emerging research agenda. Int. J. Prod. Res. 2020, 58, 1462–1484. [Google Scholar] [CrossRef]
- Sharma, R.; Jabbour, C.J.C.; de Sousa Jabbour, A.B.L. Sustainable manufacturing and industry 4.0: What we know and what we don’t. J. Enterp. Inf. Manag. 2020, 34, 230–266. [Google Scholar] [CrossRef]
- Henao-Hernández, I.; Solano-Charris, E.L.; Muñoz-Villamizar, A.; Santos, J.; Henríquez-Machado, R. Control and monitoring for sustainable manufacturing in the Industry 4.0: A literature review. IFAC-PapersOnLine 2019, 52, 195–200. [Google Scholar] [CrossRef]
- Elkington, J. Enter the triple bottom line. In The Triple Bottom Line: Does It All Add Up; Routledge: London, UK, 2013; pp. 23–38. [Google Scholar]
- Kishawy, H.A.; Hegab, H.; Saad, E. Design for sustainable manufacturing: Approach, implementation, and assessment. Sustainability 2018, 10, 3604. [Google Scholar] [CrossRef] [Green Version]
- Rosen, M.A.; Kishawy, H.A. Sustainable manufacturing and design: Concepts. practices and needs. Sustainability 2012, 4, 154–174. [Google Scholar] [CrossRef] [Green Version]
- Purvis, B.; Mao, Y.; Robinson, D. Three pillars of sustainability: In search of conceptual origins. Sustain. Sci. 2019, 14, 681–695. [Google Scholar] [CrossRef] [Green Version]
- Wang, L.; Bi, Z.M. Challenges for better sustainable manufacturing. In Advances in Sustainable and Competitive Manufacturing Systems; Springer: Heidelberg, Germany, 2013. [Google Scholar] [CrossRef]
- Jawahir, I.S. Beyond the 3R’s: 6R concepts for next generation manufacturing: Recent trends and case studies. In Proceedings of the Symposium on Sustainability and Product Development, Chicago, IL, USA, 7–8 August 2008; IIT: Chicago, IL, USA, 2008. [Google Scholar]
- Barni, A.; Carpanzano, E.; Landolfi, G.; Pedrazzoli, P. Urban Manufacturing of Sustainable Customer-Oriented Products. In Proceedings of the International Conference on the Industry 4.0 Model for Advanced Manufacturing, Belgrade, Serbia, 3–6 June 2019; Springer: Cham, Switzerland, 2019. [Google Scholar] [CrossRef]
- Juraschek, M.; Vossen, B.; Hoffschröer, H.; Reicher, C.; Herrmann, C. Urban Factories: Ecotones as Analogy for Sustainable Value Creation in Cities. In Proceedings of the Interdiziplinäre Konferenze zur Zukunft der Wertschöpfung 2016, Hamburg, Germany, 14–15 December 2016; Available online: https://www.researchgate.net/profile/Manuel-Moritz/publication/311776114_Konferenzband_zur_1_interdisziplinaren_Konferenz_zur_Zukunft_der_Wertschopfung/links/585a648408ae64cb3d4a9b06/Konferenzband-zur-1-interdisziplinaeren-Konferenz-zur-Zukunft-der-Wertschoepfung.pdf#page=141 (accessed on 23 December 2021).
- Herrmann, C.; Büth, L.; Juraschek, M.; Abraham, T.; Schäfer, L. Application of biological transformation to foster positive urban production. Procedia CIRP 2020, 90, 2–9. [Google Scholar] [CrossRef]
- Abdoli, S.; Juraschek, M.; Thiede, S.; Kara, S.; Herrmann, C. An Investigation into Holistic Planning of Urban Factories. Procedia CIRP 2019, 80, 649–654. [Google Scholar] [CrossRef]
- Matt, D.T.; Spath, D.; Braun, S.; Schlund, S.; Krause, D. Morgenstadt–urban production in the city of the future. In Enabling Manufacturing Competitiveness and Economic Sustainability; Springer: Cham, Switzerland, 2014; pp. 13–16. [Google Scholar] [CrossRef]
- Spath, D.; Lentes, J. Urban production to advance the competitiveness of industrial enterprises. In Proceedings of the ICPR22—22nd International Conference on Production Research, Iguassu Falls, Brazil, 28 July–1 August 2013. [Google Scholar]
- Allam, Z.; Jones, D.; Thondoo, M. Decarbonization and Urban Sustainability. In Cities and Climate Change; Palgrave Macmillan: Cham, Switzerland, 2020; pp. 33–54. [Google Scholar] [CrossRef]
- Tötzer, T.; Stollnberger, R.; Krebs, R.; Haas, M. How can urban manufacturing contribute to a more sustainable energy system in cities? Int. J. Sustain. Energy Plan. Manag. 2019, 24, 67–74. [Google Scholar] [CrossRef]
- Lentes, J.; Hertwig, M.; Zimmermann, N.; Mahlau, L.M. Development Path for Industrial Enterprises towards Urban Manufacturing. DEStech Trans. Eng. Technol. Res. 2017, 69–74. [Google Scholar] [CrossRef] [Green Version]
- Juraschek, M.; Herrmann, C.; Thiede, S. Utilizing gaming technology for simulation of urban production. Procedia CIRP 2017, 61, 469–474. [Google Scholar] [CrossRef]
- Singh, S.; Hertwig, M.; Lentes, J. Economic Impact of Ultraefficient Urban Manufacturing. In Smart Economy in Smart Cities; Springer: Singapore, 2017; pp. 273–293. [Google Scholar] [CrossRef]
- Juraschek, M.; Kreuz, F.; Bucherer, M.; Spengler, A.; Thiede, S.; Herrmann, C.; Schmidt, A.; Clausen, U. Urban Factories–Identification of Measures for Resource-Efficient Integration of Production Systems in Cities. In Proceedings of the Interdisciplinary Conference on Production, Logistics and Traffic, Dortmund, Germany, 27–28 March 2019; Springer: Cham, Switzerland, 2019; pp. 221–232. [Google Scholar] [CrossRef]
- Abramovici, M.; Göbel, J.C.; Neges, M. Smart engineering as enabler for the 4th industrial revolution. In Integrated Systems: Innovations and Applications; Springer: Cham, Switzerland, 2015; pp. 163–170. [Google Scholar] [CrossRef]
- Zhou, K.; Liu, T.; Zhou, L. Industry 4.0: Towards future industrial opportunities and challenges. In Proceedings of the 2015 12th International Conference on Fuzzy Systems and Knowledge Discovery (FSKD), Zhangjiajie, China, 15–17 August 2015; pp. 2147–2152. [Google Scholar] [CrossRef]
- Hermann, M.; Pentek, T.; Otto, B. Design principles for industrie 4.0 scenarios. In Proceedings of the 2016 49th Hawaii International Conference on System Sciences (HICSS), Kauai, HI, USA, 5–8 January 2016; pp. 3928–3937. [Google Scholar] [CrossRef]
- Lee, E.A. Cyber physical systems: Design challenges. In Proceedings of the 2008 11th IEEE International Symposium on Object and Component-Oriented Real-Time Distributed Computing (ISORC), Orlando, FL, USA, 5–7 May 2008; pp. 363–369. [Google Scholar] [CrossRef] [Green Version]
- Wang, L.; Törngren, M.; Onori, M. Current status and advancement of cyber-physical systems in manufacturing. J. Manuf. Syst. 2015, 37, 517–527. [Google Scholar] [CrossRef]
- Lee, J. Industrial AI: Applications with Sustainable Performance; Springer Nature Pte Ltd.: Singapore, 2020; ISBN 978-981-15-2143-0. [Google Scholar]
- Hozdić, E. Smart factory for industry 4.0: A review. Int. J. Mod. Manuf. Technol. 2015, 7, 28–35. [Google Scholar]
- Pico-Valencia, P.; Holgado-Terriza, J.A.; Quiñónez-Ku, X. A brief survey of the main internet-based approaches. An outlook from the internet of things perspective. In Proceedings of the 2020 3rd International Conference on Information and Computer Technologies (ICICT), San Jose, CA, USA, 9–12 March 2020; pp. 536–542. [Google Scholar] [CrossRef]
- Wang, S.; Wan, J.; Zhang, D.; Li, D.; Zhang, C. Towards smart factory for industry 4.0: A self-organized multi-agent system with big data based feedback and coordination. Comput. Netw. 2016, 101, 158–168. [Google Scholar] [CrossRef] [Green Version]
- Mabkhot, M.M.; Al-Ahmari, A.M.; Salah, B.; Alkhalefah, H. Requirements of the smart factory system: A survey and perspective. Machines 2018, 6, 23. [Google Scholar] [CrossRef] [Green Version]
- Radziwon, A.; Bilberg, A.; Bogers, M.; Madsen, E.S. The smart factory: Exploring adaptive and flexible manufacturing solutions. Procedia Eng. 2014, 69, 1184–1190. [Google Scholar] [CrossRef] [Green Version]
- Chen, B.; Wan, J.; Shu, L.; Li, P.; Mukherjee, M.; Yin, B. Smart factory of industry 4.0: Key technologies, application case, and challenges. IEEE Access 2017, 6, 6505–6519. [Google Scholar] [CrossRef]
- Shrouf, F.; Ordieres, J.; Miragliotta, G. Smart factories in Industry 4.0: A review of the concept and of energy management approached in production based on the Internet of Things paradigm. In Proceedings of the 2014 IEEE International Conference on Industrial Engineering and Engineering Management, Selangor Darul Ehsan, Malaysia, 9–12 December 2014; pp. 697–701. [Google Scholar] [CrossRef]
- Rüßmann, M.; Lorenz, M.; Gerbert, P.; Waldner, M.; Justus, J.; Engel, P.; Harnisch, M. Industry 4.0: The future of productivity and growth in manufacturing industries. Boston Consult. Group 2015, 9, 54–89. [Google Scholar]
- Strozzi, F.; Colicchia, C.; Creazza, A.; Noè, C. Literature review on the ‘Smart Factory’concept using bibliometric tools. Int. J. Prod. Res. 2017, 55, 6572–6591. [Google Scholar] [CrossRef]
- Akpolat, C.; Sahinel, D.; Sivrikaya, F.; Lehmann, G.; Albayrak, S. CHARIOT: An IoT Middleware for the Integration of Heterogeneous Entities in a Smart Urban Factory. In Proceedings of the 2017 Federated Conference on Computer Science and Information Systems—FedCSIS, Prague, Czech Republic, 3–6 September 2017; PTI: Warsaw, Poland, 2017; pp. 135–142. [Google Scholar]
- Pinzone, M.; Albe, F.; Orlandelli, D.; Barletta, I.; Berlin, C.; Johansson, B.; Taisch, M. A framework for operative and social sustainability functionalities in Human-Centric Cyber-Physical Production Systems. Comput. Ind. Eng. 2020, 139, 105132. [Google Scholar] [CrossRef]
- Romero, D.; Stahre, J.; Taisch, M. The Operator 4.0: Towards socially sustainable factories of the future. Comput. Ind. Eng. 2020, 139, 106128. [Google Scholar] [CrossRef]
- Juraschek, M. Analysis and Development of Sustainable Urban Production Systems; Springer: Berlin, Germany, 2021. [Google Scholar]
- Rauch, E.; Dallasega, P.; Matt, D.T. Distributed manufacturing network models of smart and agile mini-factories. Int. J. Agil. Syst. Manag. 2017, 10, 185–205. [Google Scholar] [CrossRef]
- Juraschek, M.; Becker, M.; Thiede, S.; Kara, S.; Herrmann, C. Life Cycle Assessment for the comparison of urban and non-urban produced products. Procedia CIRP 2019, 80, 405–410. [Google Scholar] [CrossRef]
- Birtel, M.; Mohr, F.; Hermann, J.; Bertram, P.; Ruskowski, M. Requirements for a human-centered condition monitoring in modular production environments. IFAC-PapersOnLine 2018, 51, 909–914. [Google Scholar] [CrossRef]
- Pradel, P.; Campbell, R.I.; Bibb, R. When design never ends-a future scenario for product development. In Proceedings of the Design Society: International Conference on Engineering Design, Delft, The Netherlands, 5–8 August 2019; Cambridge University Press: Cambridge, UK, 2019; Volume 1, pp. 829–838. [Google Scholar] [CrossRef] [Green Version]
- Schüler, M.; Fee Maier, M.; Liljedal, K.T. Motives and barriers affecting consumers’ co-creation in the physical store. Int. Rev. Retail. Distrib. Consum. Res. 2020, 30, 289–310. [Google Scholar] [CrossRef] [Green Version]
- Barni, A.; Corti, D.; Pedrazzoli, P.; Rovere, D.; Lucisano, G. Mini-factories for close-to-customer manufacturing of customized furniture: From concept to real demo. Procedia Manuf. 2017, 11, 854–862. [Google Scholar] [CrossRef]
- Geissbauer, R.; Schrauf, S.; Berttram, P.; Cheraghi, F. Digital Factories 2020: Shaping the Future of Manufacturing; PricewaterhouseCoopers: London, UK, 2017; Volume 17, p. 2018. [Google Scholar]
- Kang, H.S.; Do Noh, S.; Son, J.Y.; Kim, H.; Park, J.H.; Lee, J.Y. The FaaS system using additive manufacturing for personalized production. Rapid Prototyp. J. 2018, 24, 1355–2546. [Google Scholar] [CrossRef]
- Park, K.T.; Nam, Y.W.; Lee, H.S.; Im, S.J.; Noh, S.D.; Son, J.Y.; Kim, H. Design and implementation of a digital twin application for a connected micro smart factory. Int. J. Comput. Integr. Manuf. 2019, 32, 596–614. [Google Scholar] [CrossRef]
- Park, K.T.; Son, Y.H.; Ko, S.W.; Noh, S.D. Digital Twin and Reinforcement Learning-Based Resilient Production Control for Micro Smart Factory. Appl. Sci. 2021, 11, 2977. [Google Scholar] [CrossRef]
- Wahlster, W. Semantic technologies for mass customization. In Towards the Internet of Services: The Theseus Research Program; Springer: Cham, Switzerland, 2014; pp. 3–13. [Google Scholar] [CrossRef]
- Jeong, T.S. The suggestion for successful factory converging automation by reviewing smart factories in German. J. Korea Converg. Soc. 2016, 7, 189–196. [Google Scholar] [CrossRef] [Green Version]
- Volkswagen, A.G. Brochure: Historical Notes 7: Volkswagen Chronicle—Becoming a Global Player. 2008. Available online: https://www.volkswagenag.com/presence/medien/HN7e_www2.pdf (accessed on 18 August 2021).
- Comeron, O. Layers of Labor in Cultural Production: Notes on Aesthetics and Commitment from the Transparent Factory. In Commitment and Complicity in Cultural Theory and Practice; Palgrave Macmillan: London, UK, 2009; pp. 167–181. [Google Scholar] [CrossRef]
- E-FOREST, The Future Mobility Smart Factory. 2020. Available online: https://tech.hyundaimotorgroup.com/article/e-forest-the-future-mobility-smart-factory (accessed on 19 August 2021).
- New Hyundai Motor Group Innovation Center in Singapore to Transform Customer Experience through Future Mobility R&D. 2020. Available online: https://news.hyundaimotorgroup.com/MediaCenter/News/Press-Releases/New-Hyundai-Motor-Group-Innovation-Center-in-Singapore-to-Transform-Customer-Experience-through-Future-Mobility-RnD (accessed on 27 September 2021).
- Human-Centered Mobility Vision: Innovation Center In Singapore. 2020. Available online: https://news.hyundaimotorgroup.com/Article/Human-Centered-Mobility-Vision-Innovation-Center-In-Singapore (accessed on 19 August 2021).
- Dameri, R.P. Searching for smart city definition: A comprehensive proposal. Int. J. Comput. Technol. 2013, 11, 2544–2551. [Google Scholar] [CrossRef]
- Lombardi, P.; Giordano, S.; Farouh, H.; Yousef, W. Modelling the smart city performance. Innov. Eur. J. Soc. Sci. Res. 2012, 25, 137–149. [Google Scholar] [CrossRef]
- Storolli, W.G.; Makiya, I.K.; César, F.I.G. Comparative analyzes of technological tools between industry 4.0 and smart cities approaches: The new society ecosystem. Indep. J. Manag. Prod. 2019, 10, 1134–1158. [Google Scholar] [CrossRef]
- Wang, S.; Wan, J.; Li, D.; Zhang, C. Implementing smart factory of industrie 4.0: An outlook. Int. J. Distrib. Sens. Netw. 2016, 12, 3159805. [Google Scholar] [CrossRef] [Green Version]
- Lee, J.; Bagheri, B.; Kao, H.A. A cyber-physical systems architecture for industry 4.0-based manufacturing systems. Manuf. Lett. 2015, 3, 18–23. [Google Scholar] [CrossRef]
- Tao, F.; Qi, Q.; Wang, L.; Nee, A.Y.C. Digital twins and cyber–physical systems toward smart manufacturing and industry 4.0: Correlation and comparison. Engineering 2019, 5, 653–661. [Google Scholar] [CrossRef]
- Qi, Q.; Tao, F. Digital twin and big data towards smart manufacturing and industry 4.0: 360 degree comparison. IEEE Access 2018, 6, 3585–3593. [Google Scholar] [CrossRef]
- Milgram, P.; Kishino, F. A taxonomy of mixed reality visual displays. IEICE Trans. Inf. Syst. 1994, 77, 1321–1329. [Google Scholar]
- Baroroh, D.K.; Chu, C.H.; Wang, L. Systematic literature review on augmented reality in smart manufacturing: Collaboration between human and computational intelligence. J. Manuf. Syst. 2020, 61, 696–711. [Google Scholar] [CrossRef]
Megatrend | Trend | Potentials of Urban Factory |
---|---|---|
Demographic Changes | Urbanization Population growth Population ageing | utilize urban infrastructure |
create local working-class jobs | ||
offer part-time jobs for qualified workers | ||
opportunities for elderly workforces | ||
Sustainability | Climate change Emissions Resource shortage Human well-being Market fluctuating Higher profitability of manufacturing | lessen transportation emissions |
exchange of waste heat, excess energy, and recycled materials | ||
customer experience/satisfaction/well-being | ||
employee well-being | ||
community well-being | ||
cooperation with research institutions and universities | ||
connected-continued innovation | ||
develop new business concepts | ||
Individualization | Product personalization | customer involvement and co-creation |
decentralized production organization | ||
Micro-Fabs/Mini-factories | ||
Human Resource | Talent shortage or War for talents Unemployment | availability of workforce especially highly qualified experts |
collaborative learning/vocational training | ||
higher employer attractiveness |
Case | Type | Sector | Description |
---|---|---|---|
Knit For You | Practical Business | Sportswear (Adidas) | Personalized knit |
CTC | Research Paper | Furniture Manufacturing | Personalized furniture |
DigiPlex | Practical Business | Data Centre | Reuse of waste heat |
Alpha Biofuel | Practical Business | Refinery | Recycling of used cooking oil |
Wittenstein | Practical Business | Engineering (gear systems) | Workplace well-being, energy sharing, Noise and emissions reduction |
FaaS/CMSF | Research Paper | Manufacturing | Personalization, resilience, solution for spatial limits |
Nobilia | Practical Business | Kitchen Manufacturer | Product personalization, Sustainability |
VW T-Factory | Practical Business | Automotive Industry | Service personalization, Sustainability |
E-Forest HMGICS | Practical Business | Automotive Industry | Service and product Personalization, sustainability, resilience |
Characteristic | Category | Description |
---|---|---|
Human-Centric | Customer | Personalization of product/service through co-creation Workplace well-being, lifelong education, etc. Close collaboration, education, open innovation, etc. |
Employee | ||
Communities | ||
Sustainable | Environmental | Minimizing emissions/pollutions, Resource and energy efficiency Customer/employee/citizen well-being Value creation, new business model development |
Social | ||
Economy | ||
Resilient | Internal | Wrong decision-making, equipment failure, strike, etc. Political issues, natural disasters, regulations, etc. |
adversity | ||
External | ||
adversity |
USF Characteristics | Type | Smart Factory Technologies | USF Characteristics |
---|---|---|---|
Human-centric | Customer Employee | IoT, CPS and DT, Big data, AI, 3D Printing, MR, Wearables, on-demand manufacturing, modular, decentralized, and distributed manufacturing | Customer satisfaction Workplace well-being Higher employer attractiveness |
Sustainability | Environmental Social Economy | IoT, Sensor, CPS and DT, Big Data, AI IoT, Sensor, CPS and DT, Big Data, AI, MR, 3D Printing IoT, Sensor, CPS and DT, Big Data, AI, MR, 3D Printing | Minimize emission and pollutants, Energy/Resource efficiency, Design for circular economy Education, Open innovation, Energy/Resource share, Product and Service Innovation Value creation, New business model development |
Resilience | Internal adversity External adversity | IoT, Sensor, CPS and DT, Big Data, AI, MR CPS and DT, Big Data, AI, 3D Printing | Worry-free Production Flexibility, Dynamic scheduling |
Case | Concept (Pillar) | Core Technologies | Benefits |
---|---|---|---|
Knit For You | Personalization | 3D scanning and real-time simulation | Affordable personalized product, shortened design and production time, and supply chain |
CTC | Personalization Sustainability (environmental, economic) | IoT, cloud, modular product design, real-time update of production data monitoring | Customer satisfaction, shorter supply chain, reduced waste, image and appearance shared have impressed a high number of visitors of the shopping mall |
DigiPlex | Sustainability (Environmental, economic) | - | Reuse of waste heat of data center for heating residents |
Alpha Biofuel | Sustainability (Environmental, economic) | - | Material and resource efficiency |
Wittenstein | Sustainability (Environmental, social, economic) | Smart sensors, IoT, CPS | Improving workplace well-being, low noise and emission, sharing of residual heat with surrounding urban areas |
FaaS/CMSF | Personalization Sustainability Resilience | DT and CPS, 3D printing | Real-time monitoring of the present, tracking information from the past, and operational decision-making support for the future, reducing the cost and production inefficiencies |
Nobilia | Personalization Sustainability | Smart sensor, IoT, CPS | Optimizing the degree of personalization, optimizing customer experiences, shortened manufacturing time, reducing waste materials and energy, practical production of products in a wide variety and high volume |
VW T-Factory | Personalization Sustainability | - | Optimizing customer experiences |
E-Forest HMGICS | Personalization Sustainability Resilience | Smart sensor, IoT, CPS, Collaborative robots | Optimizing customer satisfaction, improving workplace well-being, share infrastructure for global research and development experts and collaboration with local communities |
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Sajadieh, S.M.M.; Son, Y.H.; Noh, S.D. A Conceptual Definition and Future Directions of Urban Smart Factory for Sustainable Manufacturing. Sustainability 2022, 14, 1221. https://doi.org/10.3390/su14031221
Sajadieh SMM, Son YH, Noh SD. A Conceptual Definition and Future Directions of Urban Smart Factory for Sustainable Manufacturing. Sustainability. 2022; 14(3):1221. https://doi.org/10.3390/su14031221
Chicago/Turabian StyleSajadieh, Seyed Mohammad Mehdi, Yoo Ho Son, and Sang Do Noh. 2022. "A Conceptual Definition and Future Directions of Urban Smart Factory for Sustainable Manufacturing" Sustainability 14, no. 3: 1221. https://doi.org/10.3390/su14031221
APA StyleSajadieh, S. M. M., Son, Y. H., & Noh, S. D. (2022). A Conceptual Definition and Future Directions of Urban Smart Factory for Sustainable Manufacturing. Sustainability, 14(3), 1221. https://doi.org/10.3390/su14031221