Using the Process Digital Twin as a tool for companies to evaluate the Return on Investment of manufacturing automation
The fourth industrial revolution is gaining momentum, but still lacks full realization. Several studies suggest that many companies around the world have begun the digital transformation undertaking, but most are still far from full adoption and yet fail to see the full economic potential, being stu...
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Published in | Procedia CIRP Vol. 107; pp. 724 - 728 |
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Main Authors | , , , |
Format | Journal Article |
Language | English |
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Elsevier B.V
2022
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Abstract | The fourth industrial revolution is gaining momentum, but still lacks full realization. Several studies suggest that many companies around the world have begun the digital transformation undertaking, but most are still far from full adoption and yet fail to see the full economic potential, being stuck in what has been called "pilot purgatory”. Digitalization is largely recognized as an accelerator and enabler for full automation in manufacturing, but companies are still struggling to assess the return on investment and the impact on operational performance indicators. Therefore, companies, especially SMEs characterized by dynamic, high-value, high-mix, and low-volume contexts, are reluctant to invest further. By incorporating simulation, data analytics and behavioral models, digital twins may also be used to support automation solutions ramp-up, demonstrate their impact evaluation, usage scenarios, eliminating the need for physical prototypes, reducing development time, and improving quality. Few forward-thinking companies are pursuing the digital transformation path, while the majority are clipping the wings of a transformation that is essential for a sustainable manufacturing. This paper describes a theoretical approach to exploit the digital twin technology to gather insights towards a realistic economical assessment of full automation solutions, to back and encourage investments to realize the potential of the digital manufacturing transformation. The approach is being tested under the European Union’s Horizon 2020 research and innovation program under grant agreement No. 958363, which provides an opportunity to assess how the various components of the method are constructed, how complex they are, and what level of effort is required, using a practical example. |
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AbstractList | The fourth industrial revolution is gaining momentum, but still lacks full realization. Several studies suggest that many companies around the world have begun the digital transformation undertaking, but most are still far from full adoption and yet fail to see the full economic potential, being stuck in what has been called "pilot purgatory”. Digitalization is largely recognized as an accelerator and enabler for full automation in manufacturing, but companies are still struggling to assess the return on investment and the impact on operational performance indicators. Therefore, companies, especially SMEs characterized by dynamic, high-value, high-mix, and low-volume contexts, are reluctant to invest further. By incorporating simulation, data analytics and behavioral models, digital twins may also be used to support automation solutions ramp-up, demonstrate their impact evaluation, usage scenarios, eliminating the need for physical prototypes, reducing development time, and improving quality. Few forward-thinking companies are pursuing the digital transformation path, while the majority are clipping the wings of a transformation that is essential for a sustainable manufacturing. This paper describes a theoretical approach to exploit the digital twin technology to gather insights towards a realistic economical assessment of full automation solutions, to back and encourage investments to realize the potential of the digital manufacturing transformation. The approach is being tested under the European Union’s Horizon 2020 research and innovation program under grant agreement No. 958363, which provides an opportunity to assess how the various components of the method are constructed, how complex they are, and what level of effort is required, using a practical example. |
Author | Chiara Magnanini, Maria Eleftheriadis, Ragnhild Pedrazzoli, Paolo Caccamo, Chiara |
Author_xml | – sequence: 1 givenname: Chiara surname: Caccamo fullname: Caccamo, Chiara email: chiara.caccamo@sintef.no organization: SINTEF Manufacturing AS, Digital Production, Norway – sequence: 2 givenname: Paolo surname: Pedrazzoli fullname: Pedrazzoli, Paolo organization: Department of Innovative Technologies, SUPSI, CH-6962, Lugano, Switzerland – sequence: 3 givenname: Ragnhild surname: Eleftheriadis fullname: Eleftheriadis, Ragnhild organization: SINTEF Manufacturing AS, Digital Production, Norway – sequence: 4 givenname: Maria surname: Chiara Magnanini fullname: Chiara Magnanini, Maria organization: Department of Mechanical Engineering, Politecnico di Milano, Italy |
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References | Koulouri, Misailidi, Petride (bib0009) 2021; 126 Hriberni, Cabr, Mandreol, Mentza (bib00010) 2021; 133 Manufacturing Technology Norwegian Catapult Centre Ferrari, Confalonier, Barn, Izz, Landolf, Pedrazzol (bib00011) 2019; 38 Palomino, Quezad, Donos, Gonzale (bib0003) 2019; 39 Albukhita (bib0004) 2020; 170 ElMaragh, Monostor, Schu, ElMaragh (bib0002) 2021; 70 Azzone, Bertele (bib0008) 1989; 27 Matt, Rauch, Dallasega (bib00012) 2014; 17 Caccamo, Eleftheriadis, Magnanini, Powell, Myklebus (bib0001) 2021; 632 Walker, Childe, Wang (bib0006) 2019; 52 accessed on December 3rd at 20:20. Martin (bib0005) 2020; 93 Magnanini, Tolio (bib00015) 2021 Stanko Strmĉnik, Matjaz Miŝiĉ, Janko ĉernetiĉ, Simplified Assesment Of Benefits In Automation And Information Technology Projects, IFAC Proceedings Volumes, Volume 39, Issue 4, 2006, Pages 59-64, ISSN 1474-6670, ISBN 9783902661050 Eger, F., Tempel, P., Magnanini, M.C., Reiff, C., Colledani, M., & Verl, A. (2019, February). Part variation modeling in multi-stage production systems for zero-defect manufacturing. In 2019 IEEE International Conference on Industrial Technology (ICIT) (pp. 1017-1022). IEEE. 10.1016/j.procir.2022.05.052_bib00014 10.1016/j.procir.2022.05.052_bib00013 Palomino (10.1016/j.procir.2022.05.052_bib0003) 2019; 39 Albukhita (10.1016/j.procir.2022.05.052_bib0004) 2020; 170 Hriberni (10.1016/j.procir.2022.05.052_bib00010) 2021; 133 Walker (10.1016/j.procir.2022.05.052_bib0006) 2019; 52 Ferrari (10.1016/j.procir.2022.05.052_bib00011) 2019; 38 Magnanini (10.1016/j.procir.2022.05.052_bib00015) 2021 Matt (10.1016/j.procir.2022.05.052_bib00012) 2014; 17 ElMaragh (10.1016/j.procir.2022.05.052_bib0002) 2021; 70 Koulouri (10.1016/j.procir.2022.05.052_bib0009) 2021; 126 10.1016/j.procir.2022.05.052_bib0007 Caccamo (10.1016/j.procir.2022.05.052_bib0001) 2021; 632 Azzone (10.1016/j.procir.2022.05.052_bib0008) 1989; 27 Martin (10.1016/j.procir.2022.05.052_bib0005) 2020; 93 |
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Artificial Intelligence for Sustainable and Resilient Production Systems. APMS 2021. IFIP Advances in Information and Communication Technology contributor: fullname: Myklebus – volume: 70 start-page: 635 year: 2021 end-page: 658 ident: bib0002 article-title: Evolution and future of manufacturing systems publication-title: CIRP Annals contributor: fullname: ElMaragh – volume: 39 start-page: 565 year: 2019 end-page: 573 ident: bib0003 article-title: A Model of Economic Evaluation for the Acquisition of Flexible Manufacturing Technologies publication-title: Procedia Manufacturing contributor: fullname: Gonzale – volume: 39 start-page: 565 year: 2019 ident: 10.1016/j.procir.2022.05.052_bib0003 article-title: A Model of Economic Evaluation for the Acquisition of Flexible Manufacturing Technologies publication-title: Procedia Manufacturing doi: 10.1016/j.promfg.2020.01.420 contributor: fullname: Palomino – ident: 10.1016/j.procir.2022.05.052_bib0007 doi: 10.3182/20060522-3-FR-2904.00010 – year: 2021 ident: 10.1016/j.procir.2022.05.052_bib00015 article-title: A model-based Digital Twin to support responsive manufacturing systems publication-title: CIRP Annals doi: 10.1016/j.cirp.2021.04.043 contributor: fullname: Magnanini – volume: 38 start-page: 663 year: 2019 ident: 10.1016/j.procir.2022.05.052_bib00011 article-title: A Multipurpose Small-Scale Smart Factory For Educational And Research Activities publication-title: Procedia Manufacturing doi: 10.1016/j.promfg.2020.01.085 contributor: fullname: Ferrari – volume: 133 start-page: 103508 year: 2021 ident: 10.1016/j.procir.2022.05.052_bib00010 article-title: Autonomous, context-aware, adaptive Digital Twins—State of the art and roadmap publication-title: Computers in Industry doi: 10.1016/j.compind.2021.103508 contributor: fullname: Hriberni – volume: 17 start-page: 178 year: 2014 ident: 10.1016/j.procir.2022.05.052_bib00012 article-title: Mini-factory - A Learning Factory Concept for Students and Small and Medium Sized Enterprises publication-title: Procedia CIRP. doi: 10.1016/j.procir.2014.01.057 contributor: fullname: Matt – volume: 170 start-page: 664 year: 2020 ident: 10.1016/j.procir.2022.05.052_bib0004 article-title: Developing Digital Transformation Strategy for Manufacturing publication-title: Procedia Computer Science doi: 10.1016/j.procs.2020.03.173 contributor: fullname: Albukhita – volume: 27 start-page: 735 issue: 5 year: 1989 ident: 10.1016/j.procir.2022.05.052_bib0008 article-title: Measuring the economic effectiveness of flexible automation: a new approach publication-title: International Journal of Production Research doi: 10.1080/00207548908942583 contributor: fullname: Azzone – ident: 10.1016/j.procir.2022.05.052_bib00013 – volume: 93 start-page: 371 year: 2020 ident: 10.1016/j.procir.2022.05.052_bib0005 article-title: Antal Dér, Christoph Herrmann, Sebastian Thiede, Assessment of Smart Manufacturing Solutions Based on Extended Value Stream Mapping publication-title: Procedia CIRP doi: 10.1016/j.procir.2020.04.019 contributor: fullname: Martin – volume: 52 start-page: 2273 issue: 13 year: 2019 ident: 10.1016/j.procir.2022.05.052_bib0006 article-title: Analysing manufacturing enterprises to identify opportunities for automation and guide implementation - a review publication-title: IFAC-PapersOnLine doi: 10.1016/j.ifacol.2019.11.544 contributor: fullname: Walker – ident: 10.1016/j.procir.2022.05.052_bib00014 doi: 10.1109/ICIT.2019.8754964 – volume: 632 year: 2021 ident: 10.1016/j.procir.2022.05.052_bib0001 article-title: A Hybrid Architecture for the Deployment of a Data Quality Management (DQM) System for Zero-Defect Manufacturing in Industry 4.0 contributor: fullname: Caccamo – volume: 70 start-page: 635 issue: 2 year: 2021 ident: 10.1016/j.procir.2022.05.052_bib0002 article-title: Evolution and future of manufacturing systems publication-title: CIRP Annals doi: 10.1016/j.cirp.2021.05.008 contributor: fullname: ElMaragh – volume: 126 start-page: 317 year: 2021 ident: 10.1016/j.procir.2022.05.052_bib0009 article-title: Applications of process and digital twin models for production simulation and scheduling in the manufacturing of food ingredients and products publication-title: Food and Bioproducts Processing doi: 10.1016/j.fbp.2021.01.016 contributor: fullname: Koulouri |
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Title | Using the Process Digital Twin as a tool for companies to evaluate the Return on Investment of manufacturing automation |
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