{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,10,18]],"date-time":"2024-10-18T04:29:41Z","timestamp":1729225781239,"version":"3.27.0"},"reference-count":24,"publisher":"Institute of Electronics, Information and Communications Engineers (IEICE)","issue":"4","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEICE Trans. Inf. &amp; Syst."],"published-print":{"date-parts":[[2023,4,1]]},"DOI":"10.1587\/transinf.2022iip0012","type":"journal-article","created":{"date-parts":[[2023,3,31]],"date-time":"2023-03-31T22:28:34Z","timestamp":1680301714000},"page":"469-476","source":"Crossref","is-referenced-by-count":1,"title":["Parts Supply Support Method for Leveling Workload in In-Process Logistics"],"prefix":"10.1587","volume":"E106.D","author":[{"given":"Noriko","family":"YUASA","sequence":"first","affiliation":[{"name":"Computer Science Program Nagoya Institute of Technology"}]},{"given":"Masahiro","family":"YAMAGUCHI","sequence":"additional","affiliation":[{"name":"Benesse Corporation"}]},{"given":"Kosuke","family":"SHIMA","sequence":"additional","affiliation":[{"name":"Department of Computer Science Nagoya Institute of Technology"}]},{"given":"Takanobu","family":"OTSUKA","sequence":"additional","affiliation":[{"name":"Department of Computer Science Nagoya Institute of Technology"}]}],"member":"532","reference":[{"key":"1","doi-asserted-by":"publisher","unstructured":"[1] S.M. Davis, \u201cFrom future perfect: Mass customizing,\u201d Strategy and Leadership, vol.17, no.2, pp.16-21, 1989. 10.1108\/eb054249","DOI":"10.1108\/eb054249"},{"key":"2","doi-asserted-by":"crossref","unstructured":"[2] P. Rewers, M. Bo\u017cek, and W. Kulus, \u201cIncreasing the efficiency of the production process by production levelling,\u201d Manag. Prod. Eng. Rev., vol.10, no.2, 2019. 10.24425\/mper.2019.129572","DOI":"10.24425\/mper.2019.129572"},{"key":"3","doi-asserted-by":"crossref","unstructured":"[3] V.P. Gupta, \u201cSmart sensors and industrial IoT (IIoT): A driver of the growth of industry 4.0,\u201d pp.37-49, Springer International Publishing, Cham, 2021. 10.1007\/978-3-030-52624-5_3","DOI":"10.1007\/978-3-030-52624-5_3"},{"key":"4","doi-asserted-by":"publisher","unstructured":"[4] A. Raj, G. Dwivedi, A. Sharma, A.B. Lopes de Sousa Jabbour, and S. Rajak, \u201cBarriers to the adoption of industry 4.0 technologies in the manufacturing sector: An inter-country comparative perspective,\u201d Int. J. Prod. Econ., vol.224, Article No. 107546, June 2020. 10.1016\/j.ijpe.2019.107546","DOI":"10.1016\/j.ijpe.2019.107546"},{"key":"5","unstructured":"[5] H.D. Nguyen, K.P. Tran, X. Zeng, L. Koehl, P. Castagliola, and P. Bruniaux, \u201cIndustrial Internet of Things, Big Data, and Artificial Intelligence in the Smart Factory: a survey and perspective,\u201d ISSAT Int. Conf. Data Science in Business, Finance and Industry, Da Nang, Vietnam, pp.72-76, July 2019."},{"key":"6","doi-asserted-by":"publisher","unstructured":"[6] L. Custodio and R.L. Machado, \u201cFlexible automated warehouse: a literature review and an innovative framework,\u201d Int. J. Adv. Manuf. Technol., vol.106, pp.1-26, Jan. 2020. 10.1007\/s00170-019-04588-z","DOI":"10.1007\/s00170-019-04588-z"},{"key":"7","doi-asserted-by":"crossref","unstructured":"[7] J. Nelles, S. Kuz, A. Mertens, and C.M. Schlick, \u201cHuman-centered design of assistance systems for production planning and control: The role of the human in industry 4.0,\u201d 2016 IEEE Int. Conf. Industrial Technology (ICIT), pp.2099-2104, March 2016. 10.1109\/ICIT.2016.7475093","DOI":"10.1109\/ICIT.2016.7475093"},{"key":"8","doi-asserted-by":"publisher","unstructured":"[8] J. Fang, G.Q. Huang, and Z. Li, \u201cEvent-driven multi-agent ubiquitous manufacturing execution platform for shop floor work-in-progress management,\u201d Int. J. Production Research, vol.51, no.4, pp.1168-1185, 2013. 10.1080\/00207543.2012.693644","DOI":"10.1080\/00207543.2012.693644"},{"key":"9","doi-asserted-by":"crossref","unstructured":"[9] L. Wanganoo, \u201cStreamlining reverse logistics through iot driven warehouse management system,\u201d 2020 8th Int. Conf. Reliability, Infocom Technologies and Optimization (Trends and Future Directions) (ICRITO), pp.854-858, June 2020. 10.1109\/ICRITO48877.2020.9197929","DOI":"10.1109\/ICRITO48877.2020.9197929"},{"key":"10","doi-asserted-by":"crossref","unstructured":"[10] T.M. Fern\u00e1ndez-Caram\u00e9s, O. Blanco-Novoa, I. Froiz-M\u00edguez, and P. Fraga-Lamas, \u201cTowards an autonomous industry 4.0 warehouse: A uav and blockchain-based system for inventory and traceability applications in big data-driven supply chain management,\u201d Sensors, vol.19, no.10, May 2019. 10.3390\/s19102394","DOI":"10.3390\/s19102394"},{"key":"11","doi-asserted-by":"publisher","unstructured":"[11] P. Tripicchio, S. D&apos;Avella, and M. Unetti, \u201cEfficient localization in warehouse logistics: a comparison of LMS approaches for 3D multilateration of passive UHF RFID tags,\u201d Int. J. Adv. Manuf. Technol., pp.4977-4988, March 2022. 10.1007\/s00170-022-09018-1","DOI":"10.1007\/s00170-022-09018-1"},{"key":"12","doi-asserted-by":"publisher","unstructured":"[12] H. Zadgaonkar and M. Chandak, \u201cLocating objects in warehouses using ble beacons &amp; machine learning,\u201d IEEE Access, vol.9, pp.153116-153125, 2021. 10.1109\/ACCESS.2021.3127908","DOI":"10.1109\/ACCESS.2021.3127908"},{"key":"13","doi-asserted-by":"publisher","unstructured":"[13] R. Ramakrishnan, L. Gaur, and G. Singh, \u201cFeasibility and efficacy of ble beacon iot devices in inventory management at the shop floor,\u201d Int. J. Electr. Comput. Eng., vol.6, no.5, pp.2362-2368, 2016. 10.11591\/ijece.v6i5.pp2362-2368","DOI":"10.11591\/ijece.v6i5.pp2362-2368"},{"key":"14","doi-asserted-by":"publisher","unstructured":"[14] P. Kriz, F. Maly, and T. Kozel, \u201cImproving indoor localization using bluetooth low energy beacons,\u201d Mob. Inf. Syst., vol.2016, pp.1-11, April 2016. 10.1155\/2016\/2083094","DOI":"10.1155\/2016\/2083094"},{"key":"15","doi-asserted-by":"publisher","unstructured":"[15] K.E. Jeon, J. She, P. Soonsawad, and P.C. Ng, \u201cBle beacons for internet of things applications: Survey, challenges, and opportunities,\u201d IEEE Internet Things J., vol.5, no.2, pp.811-828, April 2018. 10.1109\/JIOT.2017.2788449","DOI":"10.1109\/JIOT.2017.2788449"},{"key":"16","doi-asserted-by":"crossref","unstructured":"[16] A.K. Pundir, J.D. Jagannath, and L. Ganapathy, \u201cImproving supply chain visibility using iot-internet of things,\u201d 2019 IEEE 9th Annual Computing and Communication Workshop and Conference (CCWC), pp.0156-0162, Jan. 2019. 10.1109\/CCWC.2019.8666480","DOI":"10.1109\/CCWC.2019.8666480"},{"key":"17","doi-asserted-by":"crossref","unstructured":"[17] P. Octaviani and W. Ce, \u201cInventory placement mapping using bluetooth low energy beacon technology for warehouses,\u201d 2020 Int. Conf. Information Management and Technology (ICIMTech), pp.354-359, 2020. 10.1109\/ICIMTech50083.2020.9211206","DOI":"10.1109\/ICIMTech50083.2020.9211206"},{"key":"18","doi-asserted-by":"publisher","unstructured":"[18] M. Bertolini, G. Esposito, D. Mezzogori, and M. Neroni, \u201cOptimizing retrieving performance of an automated warehouse for unconventional stock keeping units,\u201d Procedia Manufacturing, vol.39, pp.1681-1690, 2019. 25th Int. Conf. Production Research Manufacturing Innovation: Cyber Physical Manufacturing August 9-14, 2019 | Chicago, Illinois (USA). 10.1016\/j.promfg.2020.01.272","DOI":"10.1016\/j.promfg.2020.01.272"},{"key":"19","doi-asserted-by":"publisher","unstructured":"[19] A. Bolu and \u00d6. Kor\u00e7ak, \u201cAdaptive task planning for multi-robot smart warehouse,\u201d IEEE Access, vol.9, pp.27346-27358, 2021. 10.1109\/ACCESS.2021.3058190","DOI":"10.1109\/ACCESS.2021.3058190"},{"key":"20","doi-asserted-by":"publisher","unstructured":"[20] B. Zhang, G. Wang, Y. Yang, and S. Zhang, \u201cSolving the order planning problem at the steelmaking shops by considering logistics balance on the plant-wide process,\u201d IEEE Access, vol.7, pp.139938-139956, 2019. 10.1109\/ACCESS.2019.2937659","DOI":"10.1109\/ACCESS.2019.2937659"},{"key":"21","doi-asserted-by":"publisher","unstructured":"[21] J. Liu, S.Y. Liew, B.Y. Ooi, and D. Qin, \u201cDynamic order-based scheduling algorithms for automated retrieval system in smart warehouses,\u201d IEEE Access, vol.9, pp.158340-158352, 2021. 10.1109\/ACCESS.2021.3129585","DOI":"10.1109\/ACCESS.2021.3129585"},{"key":"22","doi-asserted-by":"publisher","unstructured":"[22] Y. Wang and Q. Shi, \u201cImproved dynamic pso-based algorithm for critical spare parts supply optimization under (t, s) inventory policy,\u201d IEEE Access, vol.7, pp.153694-153709, 2019. 10.1109\/ACCESS.2019.2948859","DOI":"10.1109\/ACCESS.2019.2948859"},{"key":"23","doi-asserted-by":"publisher","unstructured":"[23] A. Ikpehai, B. Adebisi, K.M. Rabie, K. Anoh, R.E. Ande, M. Hammoudeh, H. Gacanin, and U.M. Mbanaso, \u201cLow-power wide area network technologies for internet-of-things: A comparative review,\u201d IEEE Internet Things J., vol.6, no.2, pp.2225-2240, April 2019. 10.1109\/JIOT.2018.2883728","DOI":"10.1109\/JIOT.2018.2883728"},{"key":"24","doi-asserted-by":"crossref","unstructured":"[24] M. Yamaguchi, N. Yuasa, Y. Yoshimura, and T. Otsuka, \u201cIdentifying anomaly work in intralogistics using ble and lpwa,\u201d Advances and Trends in Artificial Intelligence. From Theory to Practice, pp.533-539, 2021. 10.1007\/978-3-030-79463-7_45","DOI":"10.1007\/978-3-030-79463-7_45"}],"container-title":["IEICE Transactions on Information and Systems"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.jstage.jst.go.jp\/article\/transinf\/E106.D\/4\/E106.D_2022IIP0012\/_pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,10,17]],"date-time":"2024-10-17T14:03:11Z","timestamp":1729173791000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.jstage.jst.go.jp\/article\/transinf\/E106.D\/4\/E106.D_2022IIP0012\/_article"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,4,1]]},"references-count":24,"journal-issue":{"issue":"4","published-print":{"date-parts":[[2023]]}},"URL":"https:\/\/doi.org\/10.1587\/transinf.2022iip0012","relation":{},"ISSN":["0916-8532","1745-1361"],"issn-type":[{"type":"print","value":"0916-8532"},{"type":"electronic","value":"1745-1361"}],"subject":[],"published":{"date-parts":[[2023,4,1]]},"article-number":"2022IIP0012"}}