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A tradespace exploration approach for changeability assessment from a system-of-systems perspective: application from the construction machinery industry

Published online by Cambridge University Press:  16 May 2024

Raj Jiten Machchhar ,
Carl Nils Konrad Toller Melén  and
Alessandro Bertoni
Raj Jiten Machchhar*
Affiliation:
Blekinge Institute of Technology, Sweden
Carl Nils Konrad Toller Melén
Affiliation:
Blekinge Institute of Technology, Sweden
Alessandro Bertoni
Affiliation:
Blekinge Institute of Technology, Sweden
*
raj.jiten.machchhar@bth.se

Abstract

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The rapid development of new technologies such as electrification, autonomy, and other contextual factors pose significant challenges to development teams in balancing competing aspects while developing value-robust solutions. One approach for achieving value robustness is designing for changeability. This paper presents a tradespace exploration from a Systems-of-Systems perspective to facilitate changeability assessment during early design stages. The approach is further demonstrated on a fleet of haulers operating in a mining site.

Keywords

systems engineering (SE)design optimisationdynamic programmingprocess modellingearly design phase
Type
Systems Engineering and Design
Information
Proceedings of the Design Society , Volume 4: DESIGN 2024 , May 2024 , pp. 2655 - 2664
Creative Commons
Creative Common License - CCCreative Common License - BYCreative Common License - NCCreative Common License - ND
This is an Open Access article, distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives licence (http://creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is unaltered and is properly cited. The written permission of Cambridge University Press must be obtained for commercial re-use or in order to create a derivative work.
Copyright
The Author(s), 2024.

References

Avison, D.E., Lau, F., Myers, M.D. and Nielsen, P.A. (1999), “Action research”, Communications of the ACM, Vol. 42 No. 1, pp. 94–97. https://doi.org/10.1145/291469.291479CrossRefGoogle Scholar
Berntorp, K., Olofsson, B., Bernhardsson, B., Lundahl, K. and Nielsen, L. (2013), “Models and methodology for optimal vehicle maneuvers applied to a hairpin turn”, 2013 American Control Conference, presented at the 2013 American Control Conference, pp. 2139–2146. https://doi.org/10.1109/ACC.2013.6580152CrossRefGoogle Scholar
Bertoni, M. and Bertoni, A. (2019), “Iterative value models generation in the engineering design process”, Design Science, Cambridge University Press, Vol. 5, p. e18. https://doi.org/10.1017/dsj.2019.13Google Scholar
Bertsekas, D. (2019), Reinforcement Learning and Optimal Control, Athena Scientific.Google Scholar
Blessing, L.T. and Chakrabarti, A. (2009), DRM: A Design Research Methodology, Springer.CrossRefGoogle Scholar
Brahma, A. and Wynn, D.C. (2023), “Concepts of change propagation analysis in engineering design”, Research in Engineering Design, Vol. 34 No. 1, pp. 117–151. https://doi.org/10.1007/s00163-022-00395-yCrossRefGoogle Scholar
Cardin, M.-A. (2013), “Enabling Flexibility in Engineering Systems: A Taxonomy of Procedures and a Design Framework”, Journal of Mechanical Design, Vol. 136 No. 1. https://doi.org/10.1115/1.4025704Google Scholar
Collopy, P.D. and Hollingsworth, P.M. (2011), “Value-Driven Design”, Journal of Aircraft, American Institute of Aeronautics and Astronautics, Vol. 48 No. 3, pp. 749–759. https://doi.org/10.2514/1.C000311Google Scholar
Dehghanimohammadabadi, M. and Keyser, T.K. (2017), “Intelligent simulation: Integration of SIMIO and MATLAB to deploy decision support systems to simulation environment”, Simulation Modelling Practice and Theory, Vol. 71, pp. 45–60. https://doi.org/10.1016/j.simpat.2016.08.007CrossRefGoogle Scholar
Ertugrul, N., Kani, A.P., Davies, M., Sbarbaro, D. and Morán, L. (2020), “Status of Mine Electrification and Future Potentials”, 2020 International Conference on Smart Grids and Energy Systems (SGES), presented at the 2020 International Conference on Smart Grids and Energy Systems (SGES), pp. 151–156. https://doi.org/10.1109/SGES51519.2020.00034CrossRefGoogle Scholar
Frank, M. (2019), A Step Towards the Design of Collaborative Autonomous Machines: A Study on Construction and Mining Equipment, Licentiate thesis, comprehensive summary, Blekinge Institute of Technology Licentiate Dissertation Series, Blekinge Tekniska Högskola, Karlskrona.Google Scholar
Ghandriz, T., Jacobson, B., Laine, L. and Hellgren, J. (2020), “Impact of automated driving systems on road freight transport and electrified propulsion of heavy vehicles”, Transportation Research Part C: Emerging Technologies, Vol. 115, p. 102610. https://doi.org/10.1016/j.trc.2020.102610CrossRefGoogle Scholar
Guzzella, L. and Sciarretta, A. (2007), Vehicle Propulsion Systems: Introduction to Modeling and Optimization, Springer Science & Business Media.Google Scholar
Heydari, B. and Herder, P. (2020), “Technical and Social Complexity”, in Maier, A., Oehmen, J. and Vermaas, P.E. (Eds.), Handbook of Engineering Systems Design, Springer International Publishing, Cham, pp. 1–30. https://doi.org/10.1007/978-3-030-46054-9_9-1Google Scholar
INCOSE. (2015), INCOSE Systems Engineering Handbook: A Guide for System Life Cycle Processes and Activities, John Wiley & Sons.Google Scholar
Machchhar, R.J., Aeddula, O.K., Bertoni, A., Wall, J. and Larsson, T. (2023), “SUPPORTING CHANGEABILITY QUANTIFICATION IN PRODUCT-SERVICE SYSTEMS VIA CLUSTERING ALGORITHM”, Proceedings of the Design Society, Vol. 3, Cambridge University Press, pp. 3225–3234. https://doi.org/10.1017/pds.2023.323Google Scholar
Machchhar, R.J. and Bertoni, A. (2022), “Supporting the Transition Towards Electromobility in the Construction and Mining Sector: Optimization Framework and Demonstration on an Electrical Hauler”, Proceedings of the Design Society, Vol. 2, pp. 1649–1658. https://doi.org/10.1017/pds.2022.167CrossRefGoogle Scholar
Maier, M.W. (1998), “Architecting principles for systems-of-systems”, Systems Engineering, Vol. 1 No. 4, pp. 267–284. https://doi.org/10.1002/(SICI)1520-6858(1998)1:4<267::AID-SYS3>3.0.CO;2-D3.0.CO;2-D>CrossRefGoogle Scholar
Martins, J.R.R.A. and Ning, A. (2021), Engineering Design Optimization, 1st ed., Cambridge University Press. https://doi.org/10.1017/9781108980647CrossRefGoogle Scholar
McManus, H. and Hastings, D. (2005), “A framework for understanding uncertainty and its mitigation and exploitation in complex systems”, Vol. 15, presented at the INCOSE international symposium, Wiley Online Library, pp. 484–503.CrossRefGoogle Scholar
Papageorgiou, A., Ölvander, J., Amadori, K. and Jouannet, C. (2020), “Multidisciplinary and multifidelity framework for evaluating system-of-systems capabilities of unmanned aircraft”, Journal of Aircraft, Vol. 57 No. 2, pp. 317–332. https://doi.org/10.2514/1.C035640CrossRefGoogle Scholar
Rehn, C.F., Pettersen, S.S., Garcia, J.J., Brett, P.O., Erikstad, S.O., Asbjørnslett, B.E., Ross, A.M., et al. (2019), “Quantification of changeability level for engineering systems”, Systems Engineering, Vol. 22 No. 1, pp. 80–94. https://doi.org/10.1002/sys.21472CrossRefGoogle Scholar
Rondini, A., Tornese, F., Gnoni, M.G., Pezzotta, G. and Pinto, R. (2017), “Hybrid simulation modelling as a supporting tool for sustainable product service systems: a critical analysis”, International Journal of Production Research, Vol. 55 No. 23, pp. 6932–6945. https://doi.org/10.1080/00207543.2017.1330569CrossRefGoogle Scholar
Ross, A., McManus, H., Rhodes, D., Hastings, D. and Long, A. (2009), “Responsive Systems Comparison Method: Dynamic Insights into Designing a Satellite Radar System”, AIAA SPACE 2009 Conference & Exposition, presented at the AIAA SPACE 2009 Conference & Exposition, American Institute of Aeronautics and Astronautics, Pasadena, California. https://doi.org/10.2514/6.2009-6542Google Scholar
Ross, A.M., Rhodes, D.H. and Hastings, D.E. (2008), “Defining changeability: Reconciling flexibility, adaptability, scalability, modifiability, and robustness for maintaining system lifecycle value”, Systems Engineering, John Wiley & Sons, Ltd, Vol. 11 No. 3, pp. 246–262. https://doi.org/10.1002/sys.20098Google Scholar
Sánchez, F. and Hartlieb, P. (2020), “Innovation in the Mining Industry: Technological Trends and a Case Study of the Challenges of Disruptive Innovation”, Mining, Metallurgy & Exploration, Vol. 37 No. 5, pp. 1385–1399. https://doi.org/10.1007/s42461-020-00262-1CrossRefGoogle Scholar
Stringer, E.T. (2013), Action Research, SAGE Publications.Google Scholar