Kolaboratif robot kullanılan sipariş-toplama depo tasarımlarının eniyilenmesi

Yıl 2024, Cilt: 39 Sayı: 1, 203 - 216, 21.08.2023

Mahmut Tutam

https://doi.org/10.17341/gazimmfd.974331

Öz

Dijital teknolojilerin e-ticaret platformlarına hızlı bir şekilde entegrasyonu ile özellikle son yıllarda online satışlarda önemli ölçüde artışlar yaşanmaktadır. Ayrıca, müşterilerin yüzlerce e-ticaret firması arasındaki küresel rekabetin farkında olması, yüksek kalite, düşük fiyat, hızlı ve ücretsiz teslimat gibi müşteri beklentilerini hiç olmadığı kadar artırmaktadır. Buna karşılık, e-ticaret şirketleri artan beklentileri karşılayarak ve operasyonel maliyetleri en aza indirerek böylesine rekabetçi bir iş ortamında ayakta kalabilmek için lojistik sistemlerini yeniden gözden geçirmeye başlamışlardır. Böylece, şirketlerin çoğu yüksek operasyon süreleri ve işçilik maliyetleri ile karakterize edilen sipariş-toplama süreçlerine odaklanmışlardır. Bu yüzden, sipariş-toplama işlemlerini daha verimli ve kârlı hale getirmek için kolaboratif robotlar (kobotlar) birçok depoda kullanılmaya başlanmıştır. Toplama lokasyonları arasındaki uzaklığa bağlı olarak, bir kobot ya sipariş toplayıcı tarafından sürülebilir ya da sipariş toplayıcı yürürken otonom olarak sonraki toplama lokasyonuna hareket edebilir. Bu makale, kolaboratif robotların kullanıldığı depoların optimal tasarımlarını bulmak için iki seviyeli bir programlama modeli önermektedir. Üst-düzey model, sipariş-toplama süresini en aza indiren optimal şekil faktörünü (en-boy-oranı) belirlemek için kullanılırken; alt-düzey model, optimal rota ve iş birliği stratejisini belirlemektedir. Monte Carlo simülasyonu temelinde, toplama listesindeki sipariş sayısı küçükse şekil faktörünün sipariş toplama turunun uzunluğunu önemli ölçüde etkilediği gösterilmiştir. Ayrıca, optimal şekil faktörünün toplama listesi büyüklüğüne bağlı olarak değiştiği sonucuna varılmıştır.

Anahtar Kelimeler

Sipariş-toplama deposu, Optimal şekil faktörü, Optimal rota, Optimal iş birliği, Toplama-listesi büyüklüğü

Destekleyen Kurum

TÜBİTAK

Proje Numarası

1059B191900637

Teşekkür

Bu makalede bulunan çalışmalar TÜBİTAK (Türkiye Bilimsel Teknolojik ve Araştırma Kurumu) 1059B191900637 numaralı proje kapsamında yer almaktadır. Sağlanan destekten dolayı TÜBİTAK’a teşekkür ederiz.

Optimizing order-picking warehouse designs using collaborative robots

Öz

With the rapid integration of digital technologies into e-commerce platforms, online sales have increased dramatically in recent years. Additionally, customers' awareness of the global competition among hundreds of e-commerce companies has increased their expectations such as high quality, low price, fast and free delivery like never before. In response, e-commerce companies have started revisiting their logistics systems to survive in such a business environment by meeting rising expectations and minimizing operational costs. Thus, most companies have been focused on order-picking processes, which are characterized by high operating times and labor costs. Accordingly, collaborative robots (cobots) have been used in many warehouses to make order-picking operations more efficient and profitable. Depending on the distance between pick locations, a cobot can either be ridden by the order picker or autonomously move to the next pick location while the order picker is walking. This paper proposes a bi-level programming model to find the optimal designs of order-picking warehouses employing collaborative robots. The top-level model is used to determine the optimal shape factor (width-to-depth ratio) minimizing the order-picking time; whereas, the bottom-level model determines the optimal route and collaboration strategy. Based on Monte Carlo simulation, it is shown that the shape factor significantly affects the length of an order-picking tour when the pick-list size is small. However, it is concluded that the optimal shape factor varies depending on the pick-list size.

Anahtar Kelimeler

Order-picking warehouse, Optimal shape factor, Optimal route, Optimal collaboration, Pick-list size

Proje Numarası

1059B191900637

Kaynakça

• R. Cop and D. Oyan, “Küçük Yerleşim Yerlerindeki Tüketicilerin, İnternetten Ürün Satın Alma Davranışları Üzerine Bir Uygulama,” Niğde Üniversitesi İktisadi ve İdari Bilim. Fakültesi Derg., vol. 3, no. 1, pp. 98–115, 2010.
• Statista, “E-commerce share of total global retail sales from 2015 to 2024,” 2021. [Online]. Available: https://www.statista.com/statistics/534123/e-commerce-share-of-retail-sales-worldwide/.
• E-ticaret bilgi platformu, “2020 Yılı E-Ticaret Verileri Açıklandı,” 2020. [Online]. Available: https://www.eticaret.gov.tr/haberler/10040/detay.
• K. Gyllengahm, “Making material handling more efficient - Reduction of non-value-adding activities at a wood products company,” Swedish University of Agricultural Sciences, 2020.
• The Establish Davis Database, “Logistics Cost and Service 2015,” 2015. [Online]. Available: https://www.establishinc.com/establish-davis-database.
• Lojistik Sözlük Çalışma Grubu, “Lojistik,” 2021. http://www.lojistiksozluk.com/lojistik.html.
• A. Bild and S. Svensson, “How third-party logistics provider can reduce non-value adding activities and total cost in the material handling process,” Linnaeus University, 2019.
• J. A. Tompkins, J. A. White, Y. A. Bozer, and J. M. A. Tanchoco, Facilities planning, 4th ed. New York, NY: John Wiley & Sons, 2010.
• A. Miller, “Order Picking for the 21st Century Voice vs. Scanning Technology,” 2004. [Online]. Available: https://www.logisticsit.com/absolutenm/articlefiles/688-voice_vs_scanning.pdf.
• J. J. Bartholdi and S. T. Hackman, Warehouse & distribution science: release 0.98.1. Atlanta, GA: Supply Chain and Logistics Institute, 2019.
• Crown Equipment Coorporation, “Crown QuickPickTM Remote: [Order Picking Technology]: Productivity. Motivation. Safety,” Order Picking Technology | QuickPick Remote | Crown Lift Trucks UK, 2013. https://www.crown.com/uk/forklifts/pdfs/brochures/order-picker-quickpick-remote-brochure-GB.pdf.
• I. BigRentz, “How to use pallet jack,” 2019. https://www.bigrentz.com/blog/how-to-use-pallet-jack.
• Associated, “Case Handling,” 2021. https://www.associated-solutions.com/automation/case-handling.
• K. J. Roodbergen and I. F. A. Vis, “A survey of literature on automated storage and retrieval systems,” Eur. J. Oper. Res., vol. 194, no. 2, pp. 343–362, Apr. 2009, doi: 10.1016/j.ejor.2008.01.038.
• K. Azadeh, R. De Koster, and D. Roy, “Robotized and automated warehouse systems: Review and recent developments,” Transp. Sci., vol. 53, no. 4, pp. 917–945, 2019, doi: 10.1287/trsc.2018.0873.
• LogisticsIQ, “Warehouse Automation Market,” 2020. [Online]. Available: https://www.thelogisticsiq.com/research/warehouse-automation-market/.
• R. De Koster, “Cobotic Order Picking Systems,” 2021. https://www.informs.org/Resource-Center/Video-Library/Webinars/Cobotic-Order-Picking-Systems.
• Linde Material Handling, “Saving time and energy in the order picking process,” 2021. [Online]. Available: https://www.linde-mh.com/en/technical/News-Detail_4816317.html.
• Ö. Öztürkoğlu and D. Hoşer, “Yeni bir depo tasarım problemi ve polinomsal zamanlı optimal sipariş toplama algoritması önerisi,” Gazi Üniversitesi Mühendislik Mimar. Fakültesi Derg., vol. 33, no. 4, pp. 1569–1588, 2018.
• F. Caron, G. Marchet, and A. Perego, “Optimal layout in low-level picker-to-part systems,” Int. J. Prod. Res., vol. 38, no. 1, pp. 101–117, Jan. 2000, doi: 10.1080/002075400189608.
• E. H. Grosse, C. H. Glock, and W. P. Neumann, “Human factors in order picking system design: A content analysis,” IFAC-PapersOnLine, vol. 28, no. 3, pp. 320–325, 2015, doi: 10.1016/j.ifacol.2015.06.101.
• T. Van Gils, K. Ramaekers, A. Caris, and R. B. M. de Koster, “Designing efficient order picking systems by combining planning problems: State-of-the-art classification and review,” Eur. J. Oper. Res., vol. 267, no. 1, pp. 1–15, May 2018, doi: 10.1016/j.ejor.2017.09.002.
• M. Masae, C. H. Glock, and E. H. Grosse, “Order picker routing in warehouses: A systematic literature review,” Int. J. Prod. Econ., vol. 224, p. 107564, 2020, doi: 10.1016/j.ijpe.2019.107564.
• R. De Koster, T. Le-Duc, and K. J. Roodbergen, “Design and control of warehouse order picking: A literature review,” Eur. J. Oper. Res., vol. 182, no. 2, pp. 481–501, Oct. 2007, doi: 10.1016/j.ejor.2006.07.009.
• G. Tuna and G. Tunçel, “Depo Yönetiminde Sipariş Toplama Sistemleri: Bir Literatür Araştırması,” Dokuz Eylül Üniversitesi Mühendislik Fakültesi Fen ve Mühendislik Derg., vol. 14, no. 42, pp. 15–31, 2012.
• Ç. Cergibozan and A. S. Tasan, “Order batching operations: an overview of classification, solution techniques, and future research,” J. Intell. Manuf., vol. 30, no. 1, pp. 335–349, Jan. 2019, doi: 10.1007/s10845-016-1248-4.
• F. Yener and H. R. Yazgan, “Optimal warehouse design: Literature review and case study application,” Comput. Ind. Eng., vol. 129, pp. 1–13, Mar. 2019, doi: 10.1016/j.cie.2019.01.006.
• Y. Jaghbeer, R. Hanson, and M. I. Johansson, “Automated order picking systems and the links between design and performance: a systematic literature review,” Int. J. Prod. Res., vol. 58, no. 15, pp. 4489–4505, Aug. 2020, doi: 10.1080/00207543.2020.1788734.
• H. D. Ratliff and A. S. Rosenthal, “Order-Picking in a Rectangular Warehouse: a Solvable Case of the Traveling Salesman Problem.,” Oper. Res., vol. 31, no. 3, pp. 507–521, 1983, doi: 10.1287/opre.31.3.507.
• M. Goetschalckx and H. D. Ratliff, “An efficient algorithm to cluster order picking items in a wide aisle,” Eng. Costs Prod. Econ., vol. 13, no. 4, pp. 263–271, Apr. 1988, doi: 10.1016/0167-188X(88)90012-2.
• M. Goetschalckx and H. D. Ratliff, “Order picking in an aisle,” IIE Trans., vol. 20, no. 1, pp. 53–62, Mar. 1988, doi: 10.1080/07408178808966150.
• R. W. Hall, “Distance approximations for routing manuel pickers in a warehouse,” IIE Trans., vol. 25, no. 4, pp. 76–87, Jul. 1993, doi: 10.1080/07408179308964306.
• F. Caron, G. Marchet, and A. Perego, “Routing policies and COI-based storage policies in picker-to-part systems,” Int. J. Prod. Res., vol. 36, no. 3, pp. 713–732, Mar. 1998, doi: 10.1080/002075498193651.
• R. De Koster and E. Van Der Poort, “Routing orderpickers in a warehouse: A comparison between optimal and heuristic solutions,” IIE Trans. (Institute Ind. Eng., vol. 30, no. 5, pp. 469–480, May 1998, doi: 10.1080/07408179808966487.
• C. G. Petersen, “An evaluation of order picking routeing policies,” Int. J. Oper. Prod. Manag., vol. 17, no. 11, pp. 1098–1111, Nov. 1997, doi: 10.1108/01443579710177860.
• C. G. Petersen, “The impact of routing and storage policies on warehouse efficiency,” Int. J. Oper. Prod. Manag., vol. 19, no. 10, pp. 1053–1064, Oct. 1999, doi: 10.1108/01443579910287073.
• K. J. Roodbergen and R. De Koster, “Routing order pickers in a warehouse with a middle aisle,” Eur. J. Oper. Res., vol. 133, no. 1, pp. 32–43, 2001, doi: 10.1016/S0377-2217(00)00177-6.
• K. J. Roodbergen and R. De Koster, “Routing methods for warehouses with multiple cross aisles,” Int. J. Prod. Res., vol. 39, no. 9, pp. 1865–1883, Jan. 2001, doi: 10.1080/00207540110028128.
• K. R. Gue, R. D. Meller, and J. D. Skufca, “The effects of pick density on order picking areas with narrow aisles,” IIE Trans., vol. 38, no. 10, pp. 859–868, Oct. 2006, doi: 10.1080/07408170600809341.
• L. Hsieh and L. Tsai, “The optimum design of a warehouse system on order picking efficiency,” Int. J. Adv. Manuf. Technol., vol. 28, no. 5–6, pp. 626–637, Mar. 2006, doi: 10.1007/s00170-004-2404-0.
• T. Suray, B. Kutlu, A. Zincidi, and E. Atmaca, “Improvement of order picking process in warehouse system,” J. Fac. Eng. Archit. Gazi Univ., vol. 23, no. 2, pp. 357–364, 2008.
• J. C.-H. Pan and M.-H. Wu, “A study of storage assignment problem for an order picking line in a pick-and-pass warehousing system,” Comput. Ind. Eng., vol. 57, no. 1, pp. 261–268, Aug. 2009, doi: 10.1016/j.cie.2008.11.026.
• J. C.-H. Pan and M.-H. Wu, “Throughput analysis for order picking system with multiple pickers and aisle congestion considerations,” Comput. Oper. Res., vol. 39, no. 7, pp. 1661–1672, Jul. 2012, doi: 10.1016/j.cor.2011.09.022.
• C. H. Glock and E. H. Grosse, “Storage policies and order picking strategies in U-shaped order-picking systems with a movable base,” Int. J. Prod. Res., vol. 50, no. 16, pp. 4344–4357, Aug. 2012, doi: 10.1080/00207543.2011.588621.
• N. Özçakar, A. Görener, and V. Arıkan, “DEPOLAMA SİSTEMLERİNDE SİPARİŞ TOPLAMA İŞLEMLERİNİN GENETİK ALGORİTMALARLA OPTİMİZASYONU,” İstanbul Üniversitesi İşletme Fakültesi İşletme İktisadı Enstitüsü Yönetim Derg., vol. 23, no. 71, pp. 118–144, 2012, [Online]. Available: https://dergipark.org.tr/en/pub/iuiieyd/issue/9203/115552.
• F. Chen, H. Wang, C. Qi, and Y. Xie, “An ant colony optimization routing algorithm for two order pickers with congestion consideration,” Comput. Ind. Eng., vol. 66, no. 1, pp. 77–85, Sep. 2013, doi: 10.1016/j.cie.2013.06.013.
• S. S. Rao and G. K. Adil, “Optimal class boundaries, number of aisles, and pick list size for low-level order picking systems,” IIE Trans., vol. 45, no. 12, pp. 1309–1321, Dec. 2013, doi: 10.1080/0740817X.2013.772691.
• L. M. Thomas and R. D. Meller, “Analytical models for warehouse configuration,” IIE Trans., vol. 46, no. 9, pp. 928–947, Sep. 2014, doi: 10.1080/0740817X.2013.855847.
• M. Çelk and H. Süral, “Order picking under random and turnover-based storage policies in fishbone aisle warehouses,” IIE Trans., vol. 46, no. 3, pp. 283–300, Mar. 2014, doi: 10.1080/0740817X.2013.768871.
• Y. Şahin and A. Eroğlu, “SİPARİŞ TOPLAMA VE KAPASİTE KISITLI ARAÇ ROTALAMA PROBLEMLERİNİN HİYERARŞİK ÇÖZÜMÜ,” Süleyman Demirel Üniversitesi Mühendislik Bilim. ve Tasarım Derg., vol. 3, no. 1, pp. 15–28, 2015.
• M. Çelik and H. Süral, “Order picking in a parallel-aisle warehouse with turn penalties,” Int. J. Prod. Res., vol. 54, no. 14, pp. 4340–4355, 2016, doi: 10.1080/00207543.2016.1154624.
• Ö. Öztürkoğlu and D. Hoşer, “A new warehouse design problem and a proposed polynomial-time optimal order picking algorithm,” J. Fac. Eng. Archit. Gazi Univ., vol. 33, no. 4, pp. 1569–1588, 2018.
• Ş. Kiriş, D. Deliktaş, and Ö. Üstün, “Order Picking Problem in a Warehouse with Bi-Objective Genetic Algorithm Approach: Case Study,” Doğuş Üniversitesi Dergisi, vol. 19, no. 1, pp. 69–77, 2018.
• E. Bottani, R. Montanari, and M. Rinaldi, “Development and testing of software tool for warehouse design and picking optimisation,” Int. J. Manag. Decis. Mak., vol. 18, no. 2, p. 119, 2019, doi: 10.1504/IJMDM.2019.098649.
• O. Ozturkoğlu and D. Hoşer, “An Evaluation of Order-picking Tour Efficiency in Two-block Warehouses,” Oper. Supply Chain Manag. An Int. J., pp. 74–87, May 2019, doi: 10.31387/oscm0370225.
• H. Diefenbach and C. H. Glock, “Ergonomic and economic optimization of layout and item assignment of a U-shaped order picking zone,” Comput. Ind. Eng., vol. 138, p. 106094, Dec. 2019, doi: 10.1016/j.cie.2019.106094.
• İ. Çobanoğlu, İ. Güre, and V. Bayram, “Sipariş toplama sıklığı düşünceleri altında veri güdümlü depolama yeri atama problemi: sezgisel bir yaklaşım,” Pamukkale Univ. J. Eng. Sci., 2021.
• M. Shekari Ashgzari and K. R. Gue, “A puzzle‐based material handling system for order picking,” Int. Trans. Oper. Res., vol. 28, no. 4, pp. 1821–1846, Jul. 2021, doi: 10.1111/itor.12886.
• S. G. Ozden, A. E. Smith, and K. R. Gue, “A computational software system to design order picking warehouses,” Comput. Oper. Res., vol. 132, p. 105311, Aug. 2021, doi: 10.1016/j.cor.2021.105311.
• S. G. Ozden, A. E. Smith, and K. R. Gue, “A novel approach for modeling order picking paths,” Nav. Res. Logist., vol. 68, no. 4, pp. 471–484, Jun. 2021, doi: 10.1002/nav.21966.
• N. Boysen, R. de Koster, and F. Weidinger, “Warehousing in the e-commerce era: A survey,” Eur. J. Oper. Res., vol. 277, no. 2, pp. 396–411, Sep. 2019, doi: 10.1016/j.ejor.2018.08.023.
• N. Boysen, R. de Koster, and D. Füßler, “The forgotten sons: Warehousing systems for brick-and-mortar retail chains,” Eur. J. Oper. Res., vol. 288, no. 2, pp. 361–381, Jan. 2021, doi: 10.1016/j.ejor.2020.04.058.
• Í. R. da Costa Barros and T. P. Nascimento, “Robotic Mobile Fulfillment Systems: A survey on recent developments and research opportunities,” Rob. Auton. Syst., vol. 137, p. 103729, Mar. 2021, doi: 10.1016/j.robot.2021.103729.
• R. Meller, D. Nazzal, and L. M. Thomas, “Collaborative Bots in Distribution Centers,” in 15th IMHRC Proceedings, 2018, vol. 17, [Online]. Available: https://digitalcommons.georgiasouthern.edu/pmhr_2018/17.
• K. Azadeh, D. Roy, and M. B. M. R. de Koster, “Dynamic Human-Robot Collaborative Picking Strategies,” SSRN Electron. J., 2020, doi: 10.2139/ssrn.3585396.
• M. Löffler, N. Boysen, C. Glock, and M. Schneider, “Picker routing in AGV-assisted order picking systems,” Work. Pap. DPO-2018-01 (version 7, 23.10.2020), vol. 01, pp. 1–43, 2018, Accessed: Apr. 12, 2021. [Online]. Available: http://www.dpo.rwth-aachen.de/global/show_document.asp?id=aaaaaaaaababzeb.
• M. Zhang, T. Semar, E. H. Grosse, S. Winkelhaus, and C. H. Glock, “Mensch-Roboter-Kollaboration in der Kommissionierung,” Zeitschrift für wirtschaftlichen Fabrikbetr., vol. 116, no. 6, pp. 372–376, Jun. 2021, doi: 10.1515/zwf-2021-0107.
• A. Pasparakis, J. de Vries, and M. B. M. R. de Koster, “In Control or under Control? Human-Robot Collaboration in Warehouse Order Picking,” SSRN Electron. J., 2021, doi: 10.2139/ssrn.3816533.
• C. E. Miller, A. W. Tucker, and R. A. Zemlin, “Integer Programming Formulation of Traveling Salesman Problems,” J. ACM, vol. 7, no. 4, pp. 326–329, Oct. 1960, doi: 10.1145/321043.321046.