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A multi-dimensional measure for determining the complexity of manual assembly operations

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Abstract

A key to solving the discrepancies of deterministic and static assembly sequences at manual work places is seen in situation-oriented and cognitive methodologies in assembly. These provide means for efficient and ergonomically feasible worker guidance. An accurate and detailed technique of adjusting the instructional content is seen as a prerequisite. In this context the authors present factors for a multi-dimensional measurement of the degree of detail and complexity of manual assembly tasks. It extends the concept and application of common systems of predetermined times. It includes dimensions of actual human performance and attention allocation, as well as learning effects based on the product and its reference levels. It is assumed that identifying global attributes that contribute to assembly difficulty will provide means for predicting assembly complexity more effectively.

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References

  1. Wiendahl HP, ElMaraghy HA, Nyhuis P, Zäh MF, Wiendahl HH, Duffie N, Brieke M (2007) Changeable manufacturing–classification, design and operation. Ann CIRP 56(2):783–809

    Article  Google Scholar 

  2. Zäh MF, Beetz M, Shea K, Reinhart G, Bender K, Lau C, Ostgathe M, Vogl W, Wiesbeck M, Engelhard M, Ertelt C, Ruehr T, Friedrich M, Herle S (2009) The cognitive factory. In: ElMaraghy HA (ed) Changeable and reconfigurable manufacturing systems. London, Springer

    Google Scholar 

  3. ElMaraghy WH, Urbanic RJ (2004) Assessment of manufacturing operational complexity. Ann CIRP 53(1):401–406

    Article  Google Scholar 

  4. Jensen PL, Alting L (2006) Human factors in the management of production. Ann CIRP 55(1):457–460

    Article  Google Scholar 

  5. Reinhart G, Patron C (2003) Integrating augmented reality in the assembly domain–fundamentals, benefits and applications. Ann CIRP 52(1):5–8

    Article  Google Scholar 

  6. Zaeh M, Prasch M (2007) Systematic workplace and assembly redesign for aging workforces. J Prod Eng 1(1):57–64

    Article  Google Scholar 

  7. Kjellberg A, Abestam L (1997) Human factor framework for analysis of an assembly work. Ann CIRP 46(1):377–380

    Article  Google Scholar 

  8. Zäh M, Wiesbeck M, Wallhoff F, Stork S, Engstler F, Bannat A, Schubö A, Friesdorf F (2007) Kognitive Assistenzsysteme in der manuellen Montage. Wt Werkstattstechnik online, 97(9):644–650

  9. Dopping-Hepenstal LL (1981) Head-up displays: the integrity of flight information. IEE Proc-F Commun Radar Signal Process 128(7):440–442

    Google Scholar 

  10. Yeh M, Wickens CD (2000) Attention and trust biases in the design of augmented reality displays. Technical report. Chicago, Aviation research lab of the University of Illinois

  11. Zaeh MF, Wiesbeck M, Stork S, Schubö A (2009) Factors for a task-induced complexity measure for manual assembly operations. 3rd international conference on changeable, agile, reconfigurable and virtual production (CARV 2009), Munich, Germany, 2009

  12. Picker C (2007) Prospektive Zeitbestimmung für nicht wertschöpfende Montagetätigkeiten, Aachen, Shaker

  13. Hinckley M (1993) A global conformance quality model—a new strategic tool for minimizing defects caused by variation, error and complexity. Stanford University, Stanford

    Google Scholar 

  14. Beiter KA, Cheldelin B, Ishii K (2000) Assembly quality method: a tool in aid of product strategy, design and process improvements.In: ASME design engineering technical conference, Baltimore

  15. Shibata H, Cheldelin B, Ishii K (2003) Assembly quality method: integrating design for assembly cost-effectiveness (DAC) to improve defect prediction. In: ASME design engineering technical conference, Chicago

  16. Kim YH (1999) A system complexity approach for the integration of product development and production system design. Massachusetts Institute of Technology, Cambridge

    Google Scholar 

  17. Kief L (2002) Eine Methode zur Ermittlung statistisch abgesicherter Montagezeiten im Produktentwicklungsprozess. Verlag Praxiswissen, Dortmund

  18. Westkämper E, Sautter K, Meyer R (1998) Eine Empirische Untersuchung zum Methodeneinsatz in Produzierenden Unternehmen. Fachtagung “Mehr Erfolg durch professionellen Methodeneinsatz”. Fraunhofer IRB, Darmstadt

  19. Papenfuß R, Theis K-D (1988) Die WORK-FACTOR-Verfahren. Angewandte Arbeitswissenschaft 117:3–18

    Google Scholar 

  20. Boothroyd G, Alting L (1992) Design for assembly and disassembly. Ann CIRP 41(2):625–636

    Article  Google Scholar 

  21. Miyakawa S, Ohashi T (1986) The Hitachi assembly evaluation method (AEM). In: International conference on product design for assembly, Newport, Rhode Island

  22. Bokranz R, Landau K (2006) Produktivitätsmanagement von Arbeitssystemen. Schäffer-Poeschel, Stuttgart

    Google Scholar 

  23. Wickens CD (2002) Multiple resources and performance prediction. Theor Issues Ergon Sci 32:159–177

    Article  Google Scholar 

  24. Stoessel C, Wiesbeck M, Stork S, Zaeh MF, Schuboe A (2008) Towards optimal worker assistance: investigating cognitive processes in manual assembly. In: Mitsuishi M, Ueda K, Kimura F (Eds.) The 41st CIRP conference on manufacturing systems. Springer, Tokyo, Japan

  25. Stork S, Stobel C, Müller H, Wiesbeck M, Schubö A (2007) A neuroergonomic approach for the investigation of cognitive processes in interactive assembly environments.In: 16th IEEE international symposium on robot and human interactive communication 2007 (IEEE RO-MAN 2007)

  26. Norman DA, Bobrow DG (1975) On data-limited and resource-limited processing. Cogn Psychol 74:4–64

    Google Scholar 

  27. Müller HJ, Krummenacher J (2002) Aufmerksamkeit. In: Müsseler J, Prinz W (eds) Allgemeine Psychologie. Elsevier, Heidelberg

    Google Scholar 

  28. Jayaram S, Connacher H, Lyons K (1997) Virtual assembly using virtual reality techniques. Comput Aided Des 29(88):575–584

    Article  Google Scholar 

  29. Gupta R, Whitney D, Zeltzer D (1997) Prototyping and design for assembly analysis using multimodal virtual environments. Comput Aided Des 29(88):585–597

    Article  Google Scholar 

  30. Carpenter ID, Dewer RG, Richie JM, Simmons JEL (1996) Enhancing a virtual environment for manual assembly. In: 12th international conference on CAD/CAM robotics and factories of the future

  31. Homem de Mello LS, Sanderson AC (1991) Representations of mechanical assembly sequences. IEEE Trans Rob Autom 7(2):211–227

    Article  Google Scholar 

  32. Sanderson AC, Zhang H, Homem de Mello LS (1989) Assembly sequence planning. Manuscript prepared for AI Magazine: special issue on assembly planning, Vol 33

  33. Lee S (1992) Backward assembly planning with assembly cost analysis. In: Proceedings of 1992 IEEE international conference on robotics and automation. Nice

  34. Homem de Mello LS, Sanderson AC (1991) A correct and complete algorithm for the generation of mechanical assembly sequences. IEEE Trans Rob Autom 7(2):228–240

    Article  Google Scholar 

  35. Gu T, Xu Z, Yang Z (2008) Symbolic OBDD representations for mechanical assembly sequences. Comput Aided Des 40(4):411–421

    Article  Google Scholar 

  36. Iyer N, Jayanti S, Lou K, Kalyanaraman Y, Ramani K (2005) Three-dimensional shape searching: state-of-the-art review and future trends. Comput Aided Des 37(5):509–530

    Article  Google Scholar 

  37. Dmitriy B, Cheuk Yiu I, William CR, Joshua S (2005) Benchmarking CAD search techniques. In: Proceedings of the 2005 ACM Symp on solid and physical modeling. Cambridge, Massachusetts

  38. Stork S, Stössel C, Schubö A (2008) The influence of instruction mode on reaching movements during manual assembly. USAB 2008—Usability—HCI for education and work, lecture notes in computer science LNCS, Austria, Graz

  39. Stork S, Stössel C, Schubö A (2008) Optimizing Human–Machine Interaction in Manual Assembly. In: Proceedings of 17th IEEE international conference on robot and human interactive communication (RO-MAN)

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Acknowledgments

The present research is conducted within the Cluster of Excellence CoTeSys—Cognition for Technical Systems in Munich, Germany. It aims for a considerable utilization and establishment of cognitive capabilities in technical systems.

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Correspondence to Mathey Wiesbeck.

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Zaeh, M.F., Wiesbeck, M., Stork, S. et al. A multi-dimensional measure for determining the complexity of manual assembly operations. Prod. Eng. Res. Devel. 3, 489 (2009). https://doi.org/10.1007/s11740-009-0171-3

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