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Developing a selective assembly technique for sheet metal assemblies

Author

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  • Abolfazl Rezaei Aderiani
  • Kristina Wärmefjord
  • Rikard Söderberg
  • Lars Lindkvist

Abstract

Applying the concept of Digital Twin in production processes supports the manufacturing of products of optimal geometry quality. This concept can be further supported by a strategy of finding the optimal combination of individual parts to maximise the geometrical quality of the final product, known as selective assembly technique. However, application of this technique has been limited to assemblies where the final dimensions are just function of the mating parts' dimensions and this is not applicable in sheet metal assemblies. This paper develops a selective assembly technique for sheet metal assemblies and investigates the effect of batch size on the improvements. The presented method utilises a variation simulation tool (Computer-Aided Tolerancing tool) and an optimisation algorithm to find the optimal combination of the mating parts. The approach presented is applied to three industrial cases of sheet metal assemblies. The results show that using this technique leads to a considerable reduction of the final geometrical variation and mean deviation for these kinds of assemblies. Moreover, increasing the batch size reduces the amount of achievable improvement in variation but increases the amount of achievable improvement in the mean deviation.

Suggested Citation

  • Abolfazl Rezaei Aderiani & Kristina Wärmefjord & Rikard Söderberg & Lars Lindkvist, 2019. "Developing a selective assembly technique for sheet metal assemblies," International Journal of Production Research, Taylor & Francis Journals, vol. 57(22), pages 7174-7188, November.
    • Handle: RePEc:taf:tprsxx:v:57:y:2019:i:22:p:7174-7188
    DOI: 10.1080/00207543.2019.1581387
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    Cited by:

    1. Nguyen, Tiep & Duong, Quang Huy & Nguyen, Truong Van & Zhu, You & Zhou, Li, 2022. "Knowledge mapping of digital twin and physical internet in Supply Chain Management: A systematic literature review," International Journal of Production Economics, Elsevier, vol. 244(C).
    2. Kamble, Sachin S & Gunasekaran, Angappa & Parekh, Harsh & Mani, Venkatesh & Belhadi, Amine & Sharma, Rohit, 2022. "Digital twin for sustainable manufacturing supply chains: Current trends, future perspectives, and an implementation framework," Technological Forecasting and Social Change, Elsevier, vol. 176(C).
    3. Mencaroni, Andrea & Claeys, Dieter & De Vuyst, Stijn, 2023. "A novel hybrid assembly method to reduce operational costs of selective assembly," International Journal of Production Economics, Elsevier, vol. 264(C).

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