{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,9,13]],"date-time":"2025-09-13T16:00:00Z","timestamp":1757779200628,"version":"3.38.0"},"reference-count":55,"publisher":"SAGE Publications","issue":"2","license":[{"start":{"date-parts":[[2022,10,15]],"date-time":"2022-10-15T00:00:00Z","timestamp":1665792000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/journals.sagepub.com\/page\/policies\/text-and-data-mining-license"}],"content-domain":{"domain":["journals.sagepub.com"],"crossmark-restriction":true},"short-container-title":["Journal of Integrated Design and Process Science: Transactions of the SDPS, Official Journal of the Society for Design and Process Science"],"published-print":{"date-parts":[[2023,2,22]]},"abstract":"<jats:p> The need for flexible production has turned manufacturing\u2019s attention to integrate fast and uncomplicated solutions. Collaborative robots (cobots) have been considered the most impactful technology due to their versatility and human-robot interaction feature. Its implementation requires expertise in both process and cobot programming. Consequently, demand for effective programming training has increased over the past years. This paper, then, aims to design and explore a smart cobot programming system and conduct an empirical study to understand human engagement and programming performance. A repertory grid is employed based on cobot experts to understand different cobot programming approaches. Meaningful insights were considered to design and implement a smart programming system configuration. Then, an empirical programming study was performed considering cobot expertise and human engagement. Results demonstrated similarities and disparities in data collected, which was inferred to indicate differences in cobot programming behavior. Finally, the work identifies and discusses patterns to differentiate programmer expertise levels and behaviors. <\/jats:p>","DOI":"10.3233\/jid-221012","type":"journal-article","created":{"date-parts":[[2022,10,18]],"date-time":"2022-10-18T15:46:36Z","timestamp":1666107996000},"page":"159-181","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":1,"title":["Empirical study for human engagement in collaborative robot programming"],"prefix":"10.1177","volume":"26","author":[{"given":"Joao Paulo","family":"Jacomini Prioli","sequence":"first","affiliation":[{"name":"Department of Industrial and Systems Engineering, Wayne State University, Detroit, MI, USA"}]},{"given":"Shengyu","family":"Liu","sequence":"additional","affiliation":[{"name":"Department of Industrial and Systems Engineering, Wayne State University, Detroit, MI, USA"}]},{"given":"Yinfeng","family":"Shen","sequence":"additional","affiliation":[{"name":"Department of Industrial and Systems Engineering, Wayne State University, Detroit, MI, USA"}]},{"given":"Van Thong","family":"Huynh","sequence":"additional","affiliation":[{"name":"Department of Artificial Intelligence Convergence, Chonnam National University, Gwangju, South Korea"}]},{"given":"Jeremy L.","family":"Rickli","sequence":"additional","affiliation":[{"name":"Department of Industrial and Systems Engineering, Wayne State University, Detroit, MI, USA"}]},{"given":"Hyung-Jeong","family":"Yang","sequence":"additional","affiliation":[{"name":"Department of Electronics and Computer Engineering, Chonnam National University, Gwangju, South Korea"}]},{"given":"Soo-Hyung","family":"Kim","sequence":"additional","affiliation":[{"name":"Department of Artificial Intelligence Convergence, Chonnam National University, Gwangju, South Korea"}]},{"given":"Kyoung-Yun","family":"Kim","sequence":"additional","affiliation":[{"name":"Department of Industrial and Systems Engineering, Wayne State University, Detroit, MI, USA"}]}],"member":"179","published-online":{"date-parts":[[2022,10,15]]},"reference":[{"key":"ref001","doi-asserted-by":"crossref","unstructured":"Alimardani,M, Kemmeren,L, Okumura,K, Hiraki,K. (2020). Robot-Assisted Mindfulness Practice: Analysis of Neurophysiological Responses and Affective State Change, 2022 29th IEEE International Conference on Robot and Human Interactive Communication (RO-MAN), 683\u2013689. https:\/\/doi.org\/10.1109\/RO-MAN47096.2020.9223428","DOI":"10.1109\/RO-MAN47096.2020.9223428"},{"key":"ref002","doi-asserted-by":"publisher","DOI":"10.1007\/s12369-015-0298-7"},{"key":"ref003","first-page":"11","volume":"4","author":"Bajic, B.","journal-title":"Machine Learning Techniques for Smart Manufacturing: Applications and Challenges in Industry."},{"key":"ref004","doi-asserted-by":"crossref","unstructured":"Baltrusaitis,T, Zadeh,A, Lim,Y. C, Morency,L.P. (2018). OpenFace 2.0: Facial Behavior AnalysisToolkit. 2018 13th IEEE International Conference on Automatic Face & Gesture Recognition (FG 2018), 59\u201366. https:\/\/doi.org\/10.1109\/FG.2018.00019","DOI":"10.1109\/FG.2018.00019"},{"key":"ref005","doi-asserted-by":"crossref","unstructured":"Barattini,P, Morand,C, Robertson,N. M. (2012). A proposed gesture set for the control of industrial collaborative robots. 2012 IEEE RO-MAN: The 21st IEEE International Symposium on Robot and Human Interactive Communication, 132-137. https:\/\/doi.org\/10.1109\/ROMAN.2012.6343743","DOI":"10.1109\/ROMAN.2012.6343743"},{"key":"ref006","doi-asserted-by":"crossref","unstructured":"Ben-Youssef,A, Clavel,C, Essid,S, Bilac,M, Chamoux,M, Lim,A. (2017). UE-HRI: A new dataset for the study of user engagement in spontaneous human-robot interactions. 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Detecting Student Emotions in Computer-Enabled Classrooms. 5."},{"key":"ref011","doi-asserted-by":"crossref","unstructured":"Burr,V, King,N, Heckmann,M. (2020). The qualitative analysis of repertory grid data: Interpretive Clustering. Qualitative Research in Psychology, 1-25. https:\/\/doi.org\/10.1080\/14780887.2020.1794088","DOI":"10.1080\/14780887.2020.1794088"},{"key":"ref012","unstructured":"Clustering of constructs and elements. (n.d.). Retrieved December 20, 2021, from http:\/\/docu.openrepgrid.org\/clustering.html"},{"key":"ref013","unstructured":"Coetzer,CF, Rothmann,S (n.d.). Job demands, job resources and work engagement of employees in a manufacturing organisation 16."},{"key":"ref014","doi-asserted-by":"crossref","unstructured":"Cohen,Y, Shoval,S, Faccio,M, Minto,R. (2021). Deploying cobots in collaborative systems: Major considerations and productivity analysis, International Journal of Production Research 1\u201317. https:\/\/doi.org\/10.1080\/00207543.2020.1870758","DOI":"10.1080\/00207543.2020.1870758"},{"key":"ref015","doi-asserted-by":"publisher","DOI":"10.1016\/j.mechmachtheory.2007.03.003"},{"key":"ref016","unstructured":"Definition of teach pendant | PCMag. (n.d.). Retrieved December 20, 2021, from https:\/\/www.pcmag.com\/encyclopedia\/term\/teach-pendant"},{"key":"ref017","doi-asserted-by":"publisher","DOI":"10.1016\/j.infsof.2017.03.004"},{"key":"ref018","doi-asserted-by":"publisher","DOI":"10.4271\/2016-01-0337"},{"key":"ref019","unstructured":"Educational Robot Market Size Global Forecast to 2026 | MarketsandMarketsTM. (n.d.). Retrieved March 10, 2022, from https:\/\/www.marketsandmarkets.com\/Market-Reports\/educational-robot-market-28174634.html"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1080\/23311975.2020.1781995"},{"key":"ref21","first-page":"162","volume":"116","author":"El Zaatari, S","year":"2019","journal-title":"RoboticsandAutonomousSystems"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1007\/s43154-020-00006-5"},{"key":"ref23","unstructured":"Ezell,S (n.d.). IoTandSmartManufacturing. 41."},{"key":"ref24","unstructured":"Hader,B. (2021). Intuitive programming of collaborative human robot processes. 187."},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1016\/j.jprocont.2017.06.012"},{"key":"ref26","doi-asserted-by":"crossref","unstructured":"Hurtienne,M.W,Hurtienne,L.E,Kempen,M. (2021). Employee engagement: Emerging insight of the millennial manufacturing  workforce, Human Resource Development Quarterly. 21453. https:\/\/doi.org\/10.1002\/hrdq.21453","DOI":"10.1002\/hrdq.21453"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1016\/j.procir.2020.05.213"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1016\/j.cie.2019.01.052"},{"key":"ref029","doi-asserted-by":"publisher","DOI":"10.1109\/TCDS.2018.2843122"},{"key":"ref030","doi-asserted-by":"publisher","DOI":"10.1016\/j.jmsy.2019.11.001"},{"key":"ref031","doi-asserted-by":"publisher","DOI":"10.3390\/robotics8040100"},{"key":"ref032","doi-asserted-by":"publisher","DOI":"10.1016\/j.entcom.2021.100440"},{"key":"ref033","doi-asserted-by":"publisher","DOI":"10.3390\/ijerph17072438"},{"key":"ref034","doi-asserted-by":"publisher","DOI":"10.3390\/pr5030039"},{"key":"ref035","doi-asserted-by":"publisher","DOI":"10.1016\/j.procir.2016.02.080"},{"key":"ref036","doi-asserted-by":"publisher","DOI":"10.1115\/1.4048950"},{"key":"ref037","doi-asserted-by":"publisher","DOI":"10.1016\/j.sftr.2020.100023"},{"key":"ref038","doi-asserted-by":"crossref","unstructured":"Pieska,S, Kaarela,J, Makela,J (2018). Simulation and programming experiences of collaborative robots for small-scale manufacturing, 2018 2nd International Symposium on Small-Scale Intelligent Manufacturing Systems (SIMS), 1\u20134. https:\/\/doi.org\/10.1109\/SIMS.2018.8355303","DOI":"10.1109\/SIMS.2018.8355303"},{"key":"ref039","unstructured":"R: The R Project for Statistical Computing. (n.d.). Retrieved December 20, 2021, from https:\/\/www.r-project.org\/"},{"key":"ref040","unstructured":"Repertory Grids. (n.d.). Retrieved December 20, 2021, from https:\/\/kellysociety.org\/repgrids.html"},{"key":"ref041","unstructured":"Robot Simulation and Programming\u2014RoboDK. (n.d.). Retrieved December 20, 2021, from https:\/\/robodk.com\/cn\/simulation"},{"key":"ref042","doi-asserted-by":"publisher","DOI":"10.1016\/j.rcim.2018.03.008"},{"key":"ref043","first-page":"905","volume":"128","author":"Shukla, N","year":"2019","journal-title":"Industrial Engineering"},{"key":"ref044","doi-asserted-by":"publisher","DOI":"10.3389\/frobt.2020.532279"},{"key":"ref045","doi-asserted-by":"crossref","unstructured":"Thong Huynh,V, Kim,S.H, Lee,G.S, Yang,H.J. (2019). Engagement Intensity Prediction withFacial Behavior Features, International Conference on Multimodal Interaction, 567\u2013571. https:\/\/doi.org\/10.1145\/3340555.3355714","DOI":"10.1145\/3340555.3355714"},{"key":"ref046","doi-asserted-by":"publisher","DOI":"10.3390\/s21144626"},{"key":"ref047","doi-asserted-by":"crossref","unstructured":"Toyoda,Y, Lucas,G, Gratch,J. (2021). Predicting Worker Accuracy from Nonverbal Behaviour: Benefits and Potential for Algorithmic Bias, Companion Publication of the International Conference on Multimodal Interaction, 25\u201330. https:\/\/doi.org\/10.1145\/3461615.3485427","DOI":"10.1145\/3461615.3485427"},{"key":"ref048","unstructured":"Universal Robots\u2014Log Viewer V1.2.1.0. (n.d.). Retrieved December 20, 2021, from https:\/\/www.universal-robots.com\/download\/softwaree-series\/support\/ur-log-viewer\/log-viewer-v1210\/"},{"key":"ref049","doi-asserted-by":"crossref","unstructured":"Weintrop,D, Afzal,A, Salac,J, Francis,P, Li,B, Shepherd,D. C, Franklin,D. (2018). Evaluating CoBlox: A Comparative Study of Robotics Programming Environments for Adult Novices, Proceedings of the CHI Conference on Human Factors in Computing Systems, 1\u201312. https:\/\/doi.org\/10.1145\/3173574.3173940","DOI":"10.1145\/3173574.3173940"},{"key":"ref050","unstructured":"What are teach pendants? (2015, July 22). 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