technical-note

Should firms use digital work instructions?—Individual learning in an agile manufacturing setting

Authors:

Peter Letmathe,

Marc RößlerAuthors Info & Claims

Journal of Operations Management, Volume 68, Issue 1

Pages 94 - 109

https://doi.org/10.1002/joom.1159

Published: 07 October 2021 Publication History

Abstract

New technological innovations in robotics, automation, and digitization enable agile manufacturing, smaller lot sizes, and quicker changes to the product and the production process. In such environments, learning is important, since workers must learn new tasks and adapt to frequent changes quickly. In an experimental study, we compare digital work instructions with traditional paper‐based ones, the latter still being common in today's quality management systems. Our analysis is based on subjects working in the demonstration factory of a large German university in a realistic work environment; it, therefore, guarantees high internal and external validity. We show that digitally animated, interactive work instructions are an effective way to foster faster learning and enhanced performance when new manufacturing tasks are being carried out. Our results indicate that a combination of digital and traditional paper‐based instructions does not yield any advantages over a sole reliance on digital learning.

Highlights

•

Digital work instructions lead to superior manufacturing performance compared with paper‐based instructions.

•

A combination of digital and traditional paper‐based work instructions does not yield any advantages over a sole reliance on digital learning.

•

In agile manufacturing settings, companies should invest in digital learning.

References

[1]

Ainsworth, S. (2006). DeFT: A conceptual framework for considering learning with multiple representations. Learning and Instruction, 16(3), 183–198.

[2]

Alavi, S., Abd. Wahab, D., Muhamad, N., & Arbab Shirani, B. (2014). Organic structure and organisational learning as the main antecedents of workforce agility. International Journal of Production Research, 52(21), 6273–6295.

[3]

Baumers, M., & Holweg, M. (2019). On the economics of additive manufacturing: Experimental findings. Journal of Operations Management, 65(8), 794–809.

[4]

Beatty, J. K., Thimling, D., & Walsh, T. (2004, November 16). Electronic work instruction object oriented system and method. Google Patents. https://www.google.com/patents/US6819965.

[5]

Benkard, C. L. (2000). Learning and forgetting: The dynamics of aircraft production. American Economic Review, 90(4), 1034–1054.

[6]

BMBF (Bundesministerium für Bildung und Forschung) (2015). Report on vocational education and training 2015. BMBF. Bonn. https://www.bmbf.de/upload_filestore/pub/Berufsbildungsbericht_2015_eng.pdf

[7]

Clark, J., & Paivio, A. (1991). Dual coding theory and education. Educational Psychology Review, 3(3), 149–210.

[8]

de Treville, S., Antonakis, J., & Edelson, N. M. (2005). Can standard operating procedures be motivating? Reconciling process variability issues and Behavioural outcomes. Total Quality Management, 16(2), 231–241.

[9]

Deater‐Deckard, K., Petrill, S. A., Thompson, L. A., & Dethorne, L. S. (2005). Fast‐track report ‐ a cross‐sectional behavioral genetic analysis of task persistence in the transition to middle childhood. Developmental Science, 3, 21–26.

[10]

Dong‐Sik, J. O., Kim, Y.‐W., Yang, U.‐Y., & Kim, K.‐H. (2012, April 26). Assembly process visualization apparatus and method. Google Patents. https://www.google.com/patents/US20120100520.

[11]

Euler, D. (1994). (Multi) Mediales Lernen‐Theoretische Fundierungen und Forschungsstand. Unterrichtswissenschaft, 22(4), 291–311.

[12]

Eysenck, H. J., & Thompson, W. (1966). The effects of distraction on pursuit rotor learning, performance and reminiscence. British Journal of Psychology, 57(1–2), 99–106.

[13]

Gilbert, A. (2016). Virtual, augmented and mixed reality. In S. Lackey & R. Shumaker (Eds.), Virtual, augmented and mixed reality: 8th international conference, VAMR 2016, held as part of HCI international 2016, Toronto, Canada, July 17–22, 2016 (pp. 375–385). Springer.

[14]

Goodell, K. H., Cao, C. G. L., & Schwaitzberg, S. D. (2006). Effects of cognitive distraction on performance of laparoscopic surgical tasks. Journal of Laparoendoscopic & Advanced Surgical Techniques, 16(2), 94–98.

[15]

Goss, L. (2001, May 22). Manufacturing system and method for assembly of computer systems in a build‐to‐order environment. Google Patents. https://www.google.com/patents/US6236901.

[16]

Grant, A. M. (2008). Does intrinsic motivation fuel the prosocial fire? Motivational synergy in predicting persistence, performance, and productivity. Journal of Applied Psychology, 93(1), 48–58.

[17]

Guan, J., Xiang, P., McBride, R., & Bruene, A. (2006). Achievement goals, social goals, and Students' reported persistence and effort in high school physical education. Journal of Teaching in Physical Education, 25(1), 58–74.

[18]

Holmström, J., Holweg, M., Lawson, B., Pil, F. K., & Wagner, S. M. (2019). The digitalization of operations and supply chain management: Theoretical and methodological implications. Journal of Operations Management, 65(8), 728–734.

[19]

Jain, N. K., & Jain, V. K. (2001). Computer aided process planning for agile manufacturing environment. In A. Gunasekaran (Ed.), Agile manufacturing: The 21st century competitive strategy (pp. 515–534). Elsevier Science Ltd.

[20]

Kablan, Z., & Erden, M. (2008). Instructional efficiency of integrated and separated text with animated presentations in computer‐based science instruction. Computers in Education, 51(2), 660–668.

[21]

Kock, N. (2005). Media richness or media naturalness? The evolution of our biological communication apparatus and its influence on our behavior toward E‐communication tools. IEEE Transactions on Professional Communication, 48(2), 117–130.

[22]

Kock, N. (2009). Information systems theorizing based on evolutionary psychology: An interdisciplinary review and theory integration framework. MIS Quarterly, 33(2), 395–418.

[23]

Krauter, L. G., Eide, D. M., & Kersavage, K. K. (2016, December 6). Apparatus and method for automatic work instruction generation. Google Patents, https://www.google.com/patents/US20100175013.

[24]

Letmathe, P., & Rößler, M. (2016). Spillover effects of learning for production ramp‐ups. In Proceedings of the 3rd international conference on ramp‐up Management in Aachen, Germany (Vol. 51, pp. 111–115). Procedia CIRP.

[25]

Letmathe, P., & Rößler, M. (2019). Tacit knowledge transfer and spillover learning in ramp‐ups. International Journal of Operations & Production Management, 39(9/10), 1099–1121.

[26]

Letmathe, P., & Schinner, M. (2017). Competence management in the age of cyber physical systems. In S. Jeschke, C. Brecher, H. Song, & D. B. Rawat (Eds.), Industrial internet of things (pp. 595–614). Springer.

[27]

Letmathe, P., Schweitzer, M., & Zielinski, M. (2012). How to learn new tasks: Shop floor performance effects of knowledge transfer and performance feedback. Journal of Operations Management, 30(3), 221–236.

[28]

Letmathe, P., & Zielinski, M. (2016). Determinants of feedback effectiveness in production planning. International Journal of Operations & Production Management, 36(7), 825–848.

[29]

Mayer, R. E. (1997). Multimedia learning: Are we asking the right questions? Educational Psychologist, 32(1), 1–19.

[30]

Mayer, R. E. (2001). Multimedia learning. Cambridge University Press.

[31]

Michas, I. C., & Berry, D. C. (2000). Learning a procedural task: Effectiveness of multimedia presentations. Applied Cognitive Psychology, 14(6), 555–575.

[32]

Moreno, R., Mayer, R. E., Spires, H. A., & Lester, J. C. (2001). The case for social Agency in Computer‐Based Teaching: Do students learn more deeply when they interact with animated pedagogical agents? Cognition and Instruction, 19(2), 177–213.

[33]

Nerdel, C. (2002). Die Wirkung von Animation und Simulation auf das Verständnis von stoffwechselphysiologischen Prozessen. (Doctoral Dissertation), Christian‐Albrechts‐Universität zu Kiel.

[34]

Ngu, B. H., Mit, E., Shahbodin, F., & Tuovinen, J. (2009). Chemistry problem solving instruction: A comparison of three computer‐based formats for learning from hierarchical network problem representations. Instructional Science, 37(1), 21–42.

[35]

Nunnally, J. C., Bernstein, I. H., & ten Berge, J. M. T. (1967). Psychometric theory (Vol. 226). McGraw‐Hill.

[36]

Paas, F. (1992). Training strategies for attaining transfer of problem solving skill in statistics: A cognitive‐load approach. Journal of Educational Psychology, 84(4), 429–434.

[37]

Paas, F., Ayres, P., & Pachman, M. (2008). Assessment of cognitive load in multimedia learning. In D. Robinson & G. Schraw (Eds.), Recent innovations in educational technology that facilitate student learning (pp. 11–35). Information Age Publishing Inc.

[38]

Paivio, A. (1990). Mental representations: A dual coding approach. Oxford University Press.

[39]

Park, O.‐C., & Hopkins, R. (1992). Instructional conditions for using dynamic visual displays: A review. Instructional Science, 21(6), 427–449.

[40]

Peterson, R. A. (2001). On the use of college students in social science research: Insights from a second‐order meta‐analysis. Journal of Consumer Research, 28(3), 450–461.

[41]

Salomon, G. (1979). Interaction of media, cognition, and learning: An exploration of how symbolic forms cultivate mental skills and affect knowledge acquisition. Jossey‐Bass Publishers.

[42]

Schnotz, W., Böckheler, J., & Grzondziel, H. (1999). Individual and co‐operative learning with interactive animated pictures. European Journal of Psychology of Education, 14(2), 245–265.

[43]

Schwan, S., & Riempp, R. (2004). The cognitive benefits of interactive videos: Learning to tie nautical knots. Learning and Instruction, 14(3), 293–305.

[44]

Senesac, C. J. (2017, May 3). Method and apparatus for providing visual assistance in aircraft assembly. Google Patents. https://www.google.com/patents/EP2778073A3?cl=en&hl=de.

[45]

Spangenberg, R. W. (1973). The motion variable in procedural learning. Audio‐Visual Communication Review, 21(4), 419–436.

[46]

Sun, Z.‐Y., Xiao, D.‐H., Wang, Y.‐J., & Xiao, Y.‐L. (2010, April 22). System and method for directing display of a standard operation procedure of an item using multimedia devices. Google Patents. https://www.google.com/patents/US20100100609.

[47]

Terwiesch, C., & Bohn, R. E. (2001). Learning and process improvement during production ramp‐up. International Journal of Production Economics, 70(1), 1–19.

[48]

Venkatesan, M. (1967). Laboratory experiments in marketing: The experimenter effect. Journal of Marketing Research, 4(2), 142–146.

[49]

Wright, T. P. (1936). Factors affecting the cost of airplanes. Journal of the Aeronautical Sciences, 3(4), 122–128.

[50]

Yin, Y., Stecke, K. E., Swink, M., & Kaku, I. (2017). Lessons from seru production on manufacturing competitively in a high cost environment. Journal of Operations Management, 49–51, 67–76.

[51]

Yusuf, Y. Y., Sarhadi, M., & Gunasekaran, A. (1999). Agile manufacturing: The drivers, conceps and attributes. International Journal of Production Economics, 62, 33–43.

Cited By

Marino EBarbieri LBruno FMuzzupappa M(2024)Assessing user performance in augmented reality assembly guidance for industry 4.0 operatorsComputers in Industry10.1016/j.compind.2024.104085157:COnline publication date: 1-May-2024
https://dl.acm.org/doi/10.1016/j.compind.2024.104085
Seeliger ACheng LNetland T(2023)Augmented reality for industrial quality inspectionComputers in Industry10.1016/j.compind.2023.103985151:COnline publication date: 1-Oct-2023
https://dl.acm.org/doi/10.1016/j.compind.2023.103985

Recommendations

Information Technology Resources, the Organizational Capability of Lean-Agile Manufacturing, and Business Performance

This article drew on the resource-based view of the firm and assessed how manufacturing firms-particularly in developing countries-can leverage their IT resources in support of lean manufacturing and agile manufacturing. The data collection was ...
Agile Manufacturing Model of Small and Medium-Sized Manufacturing Enterprises
FITME '09: Proceedings of the 2009 Second International Conference on Future Information Technology and Management Engineering

Through the actuality analysis of the medium and small-scale manufacturing industry production mode in our country, in which the agile manufacturing is implemented, the conclusion shows that it is very necessary for the medium and small-sized ...
Modeling of agile intelligent manufacturing-oriented production scheduling system

Agile intelligent manufacturing is one of the new manufacturing paradigms that adapt to the fierce globalizing market competition and meet the survival needs of the enterprises, in which the management and control of the production system have surpassed ...

Comments

Please enable JavaScript to view thecomments powered by Disqus.

Information & Contributors

Information

Published In

cover image Journal of Operations Management

Journal of Operations Management Volume 68, Issue 1

January 2022

129 pages

ISSN:0272-6963

EISSN:1873-1317

DOI:10.1002/joom.v68.1

Issue’s Table of Contents

© 2021 The Authors. Journal of Operations Management published by Wiley Periodicals LLC on behalf of Association for Supply Chain Management, Inc.

This is an open access article under the terms of the Creative Commons Attribution‐NonCommercial License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited and is not used for commercial purposes.

Publisher

John Wiley & Sons, Inc.

United States

Publication History

Published: 07 October 2021

Author Tags

Qualifiers

Technical-note

Contributors

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

2
Total Citations
View Citations
0
Total Downloads

Downloads (Last 12 months)0
Downloads (Last 6 weeks)0

Reflects downloads up to 18 Feb 2025

Other Metrics

View Author Metrics

Citations

Cited By

Marino EBarbieri LBruno FMuzzupappa M(2024)Assessing user performance in augmented reality assembly guidance for industry 4.0 operatorsComputers in Industry10.1016/j.compind.2024.104085157:COnline publication date: 1-May-2024
https://dl.acm.org/doi/10.1016/j.compind.2024.104085
Seeliger ACheng LNetland T(2023)Augmented reality for industrial quality inspectionComputers in Industry10.1016/j.compind.2023.103985151:COnline publication date: 1-Oct-2023
https://dl.acm.org/doi/10.1016/j.compind.2023.103985

View Options

View options

Figures

Tables

Media

View Issue’s Table of Contents