This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.
Bheda R, Narag AS, Singla ML. Apparel manufacturing: A strategy for productivity improvement. Journal of Fashion Marketing and Management. 2003;7(1):12–22. Available from: https://doi.org/10.1108/13612020310464331BhedaRNaragASSinglaMLApparel manufacturing: A strategy for productivity improvementJournal of Fashion Marketing and Management2003711222Available from: https://doi.org/10.1108/13612020310464331Search in Google Scholar
Chen JC, Chen C, Yuan C, et al. Assembly line balancing problem of sewing lines in garment industry. In: International Conference on Industrial Engineering and Operations Management; 2014; Bali, Indonesia. Elsevier; p. 1215–25. Available from: https://doi.org/10.1016/j.eswa.2012.02.055ChenJCChenCYuanCAssembly line balancing problem of sewing lines in garment industryIn:International Conference on Industrial Engineering and Operations Management2014Bali, IndonesiaElsevier121525Available from: https://doi.org/10.1016/j.eswa.2012.02.055Search in Google Scholar
Prakash C. Implementation of lean tools in apparel industry to improve productivity and quality. Current Trends in Fashion Technology & Textile Engineering. 2018;4(1):10–4. Available from: https://doi.org/10.19080/CTFTTE.2018.04.555628PrakashCImplementation of lean tools in apparel industry to improve productivity and qualityCurrent Trends in Fashion Technology & Textile Engineering201841104Available from: https://doi.org/10.19080/CTFTTE.2018.04.555628Search in Google Scholar
Sit, S K H., & Lee, C. (2023, September 1). Design of a Digital Twin in Low-Volume, High-Mix Job Allocation and Scheduling for Achieving Mass Personalization. Multidisciplinary Digital Publishing Institute, 11(9), 454–454. https://doi.org/10.3390/systems11090454SitS K H.LeeC.2023September1Design of a Digital Twin in Low-Volume, High-Mix Job Allocation and Scheduling for Achieving Mass PersonalizationMultidisciplinary Digital Publishing Institute119454454https://doi.org/10.3390/systems11090454Search in Google Scholar
Abdulatif, N., Yasser, S., Fahim, I S., Emad, Y., Saleh, A., & Kassem, S. (2020, November 8). Decision Support Using Simulation to Improve Productivity: A Case Study. , 14, 1120–1127.AbdulatifN.YasserS.FahimI S.EmadY.SalehA.KassemS.2020November8Decision Support Using Simulation to Improve Productivity: A Case Study1411201127Search in Google Scholar
Tsai, W. (2018, August 9). Green Production Planning and Control for the Textile Industry by Using Mathematical Programming and Industry 4.0 Techniques. Multidisciplinary Digital Publishing Institute, 11(8), 2072–2072. https://doi.org/10.3390/en11082072TsaiW2018August9Green Production Planning and Control for the Textile Industry by Using Mathematical Programming and Industry 4.0 TechniquesMultidisciplinary Digital Publishing Institute11820722072https://doi.org/10.3390/en11082072Search in Google Scholar
Santos, P., Campilho, R., & Silva, F. (2020, July 3). A new concept of full-automated equipment for the manufacture of shirt collars and cuffs. Elsevier BV, 67, 102023–102023. https://doi.org/10.1016/j.rcim.2020.102023SantosP.CampilhoR.SilvaF.2020July3A new concept of full-automated equipment for the manufacture of shirt collars and cuffsElsevier BV67102023102023https://doi.org/10.1016/j.rcim.2020.102023Search in Google Scholar
Özcan U, Peker A. Karişik modelli U-tipi montaj hatlarında hat dengeleme ve model sıralama problemleri için yeni bir sezgisel yaklaşım. Gazi Üniversitesi Mühendislik Mimarlık Fakültesi Dergisi. 2007;22(2):277–86.ÖzcanUPekerAKarişik modelli U-tipi montaj hatlarında hat dengeleme ve model sıralama problemleri için yeni bir sezgisel yaklaşımGazi Üniversitesi Mühendislik Mimarlık Fakültesi Dergisi200722227786Search in Google Scholar
Delice Y, Kızılkaya Aydoğan E, Özcan U. Stochastic two-sided U-type assembly line balancing: A genetic algorithm approach. International Journal of Production Research. 2016;54(11):3429–51. Available from: https://doi.org/10.1080/00207543.2016.1140918DeliceYKızılkaya AydoğanEÖzcanUStochastic two-sided U-type assembly line balancing: A genetic algorithm approachInternational Journal of Production Research20165411342951Available from: https://doi.org/10.1080/00207543.2016.1140918Search in Google Scholar
Chen JC, Chen C, Su LH, et al. Assembly line balancing in garment industry. Expert Systems with Applications. 2012;39(11):10073–81. Available from: https://doi.org/10.1016/j.eswa.2012.02.055ChenJCChenCSuLHAssembly line balancing in garment industryExpert Systems with Applications201239111007381Available from: https://doi.org/10.1016/j.eswa.2012.02.055Search in Google Scholar
Khatun MM. Effect of time and motion study on productivity in garment sector. International Journal of Scientific & Engineering Research. 2014;5(5):825–33.KhatunMMEffect of time and motion study on productivity in garment sectorInternational Journal of Scientific & Engineering Research20145582533Search in Google Scholar
Nabi F, Mahmud R, Islam MM. Improving sewing section efficiency through utilization of worker capacity by time study technique. International Journal of Textile Science. 2015;4(1):1–6. Available from: https://doi.org/10.5923/j.textile.20150401.01NabiFMahmudRIslamMMImproving sewing section efficiency through utilization of worker capacity by time study techniqueInternational Journal of Textile Science20154116Available from: https://doi.org/10.5923/j.textile.20150401.01Search in Google Scholar
Mothilal B, Prakash C. Implementation of lean tools in apparel industry to improve productivity and quality. Current Trends in Fashion Technology & Textile Engineering. 2018;4(1):9–14.MothilalBPrakashCImplementation of lean tools in apparel industry to improve productivity and qualityCurrent Trends in Fashion Technology & Textile Engineering201841914Search in Google Scholar
Kays HM, Prodhan S, Karia N, Karim A, Sharif S. Improvement of operational performance through value stream mapping and Yamazumi chart: A case of Bangladeshi RMG industry. International Journal of Recent Technology and Engineering. 2019;8:11977–86. Available from: https://doi.org/10.35940/ijrte.D9926.118419KaysHMProdhanSKariaNKarimASharifSImprovement of operational performance through value stream mapping and Yamazumi chart: A case of Bangladeshi RMG industryInternational Journal of Recent Technology and Engineering201981197786Available from: https://doi.org/10.35940/ijrte.D9926.118419Search in Google Scholar
Correia D, Gouveia R, Pereira T, Pinto FL. Improving manual assembly lines devoted to complex electronic devices by applying Lean tools. Procedia Manufacturing. 2018;17:663–71. Available from: https://doi.org/10.1016/j.promfg.2018.10.115CorreiaDGouveiaRPereiraTPintoFLImproving manual assembly lines devoted to complex electronic devices by applying Lean toolsProcedia Manufacturing20181766371Available from: https://doi.org/10.1016/j.promfg.2018.10.115Search in Google Scholar
Eugenia M, Barrientos S, Hinojosa VA, et al. Line balancing in assembly line: A case study. In: Proceedings of the International Conference on Industrial Engineering and Operations Management; 2018; Paris, France. IEOM Society International; p. 2476–86.EugeniaMBarrientosSHinojosaVALine balancing in assembly line: A case studyIn:Proceedings of the International Conference on Industrial Engineering and Operations Management2018Paris, FranceIEOM Society International247686Search in Google Scholar
Wang CC, Liu CT. An empirical study of the machine assembly efficiency improvement based on Lean Six Sigma technique. TEM Journal. 2019;8(2):471–6. Available from: https://doi.org/10.18421/TEM82-21WangCCLiuCTAn empirical study of the machine assembly efficiency improvement based on Lean Six Sigma techniqueTEM Journal2019824716Available from: https://doi.org/10.18421/TEM82-21Search in Google Scholar
Mridha J, Hasan S, Ahmed F, Shahjalal M. Implementation of Six Sigma to minimize defects in sewing section of apparel industry in Bangladesh. Global Journal of Engineering Science and Researches. 2019;19:11–8.MridhaJHasanSAhmedFShahjalalMImplementation of Six Sigma to minimize defects in sewing section of apparel industry in BangladeshGlobal Journal of Engineering Science and Researches201919118Search in Google Scholar
Zieliński J. Analysis of selected organizational systems of sewing teams. Fibres & Textiles in Eastern Europe. 2008;16(4):90–5.ZielińskiJAnalysis of selected organizational systems of sewing teamsFibres & Textiles in Eastern Europe2008164905Search in Google Scholar
Rahman MM, Nur F, Talapatra S. An integrated framework of applying line balancing in apparel manufacturing organization: a case study. Journal of Mechanical Engineering. 2015;44(2):117–23.RahmanMMNurFTalapatraSAn integrated framework of applying line balancing in apparel manufacturing organization: a case studyJournal of Mechanical Engineering201544211723Search in Google Scholar
Güner MG, Ünal C. Line balancing in the apparel industry using simulation techniques. Fibres & Textiles in Eastern Europe. 2008;16(2):75–8.GünerMGÜnalCLine balancing in the apparel industry using simulation techniquesFibres & Textiles in Eastern Europe2008162758Search in Google Scholar
Kursun S, Kalaoglu F. Simulation of production line balancing in apparel manufacturing. Fibres & Textiles in Eastern Europe. 2009;17(4):68–71.KursunSKalaogluFSimulation of production line balancing in apparel manufacturingFibres & Textiles in Eastern Europe20091746871Search in Google Scholar
Kayar M, Akalin M. Comparing heuristic and simulation methods applied to the apparel assembly line balancing problem. Fibres & Textiles in Eastern Europe. 2016;24(2):131–7.KayarMAkalinMComparing heuristic and simulation methods applied to the apparel assembly line balancing problemFibres & Textiles in Eastern Europe20162421317Search in Google Scholar
Eryuruk SH. Clothing assembly line design using simulation and heuristic line balancing techniques. Journal of Textile & Apparel / Tekstil ve Konfeksiyon. 2012;22(4):360–8.EryurukSHClothing assembly line design using simulation and heuristic line balancing techniquesJournal of Textile & Apparel / Tekstil ve Konfeksiyon20122243608Search in Google Scholar
Tomar A, Manoria A. Increasing line efficiency with COMSOAL, RPW, and LCR methods of assembly line balancing problem. International Journal of Soft and Hard Research Engineering. 2016;4(1):23–7.TomarAManoriaAIncreasing line efficiency with COMSOAL, RPW, and LCR methods of assembly line balancing problemInternational Journal of Soft and Hard Research Engineering201641237Search in Google Scholar
Türkmen A, Yesil Y, Kayar M. Heuristic production line balancing problem solution with MATLAB software programming. International Journal of Clothing Science and Technology. 2016;28:750–79. Available from: https://doi.org/10.1108/IJCST-01-2016-0002TürkmenAYesilYKayarMHeuristic production line balancing problem solution with MATLAB software programmingInternational Journal of Clothing Science and Technology20162875079Available from: https://doi.org/10.1108/IJCST-01-2016-0002Search in Google Scholar
Jha P, Khan MS. An experimental study on the automotive production line using assembly line balancing techniques. International Journal of Mechanical Engineering and Technology. 2017;8:22–33.JhaPKhanMSAn experimental study on the automotive production line using assembly line balancing techniquesInternational Journal of Mechanical Engineering and Technology201782233Search in Google Scholar
Ghutukade ST, Sawant SM. Use of ranked position weighted method for assembly line balancing. International Journal of Advanced Engineering Research Studies. 2013;2(4):1–3.GhutukadeSTSawantSMUse of ranked position weighted method for assembly line balancingInternational Journal of Advanced Engineering Research Studies20132413Search in Google Scholar
Buchari, Tarigan U, Ambarita M. Production layout improvement by using line balancing and systematic layout planning (SLP) at PT. XYZ. IOP Conference Series: Materials Science and Engineering. 2018;309:012116. Available from: https://doi.org/10.1088/1757-899X/309/1/012116BuchariTariganUAmbaritaMProduction layout improvement by using line balancing and systematic layout planning (SLP) at PT. XYZIOP Conference Series: Materials Science and Engineering2018309012116Available from: https://doi.org/10.1088/1757-899X/309/1/012116Search in Google Scholar
Wang S, Wan J, Zhang D, et al. Towards smart factory for Industry 4.0: a self-organized multi-agent system with big data based feedback and coordination. Computer Networks. 2016;101:41–51. Available from: https://doi.org/10.1016/j.comnet.2015.12.017WangSWanJZhangDTowards smart factory for Industry 4.0: a self-organized multi-agent system with big data based feedback and coordinationComputer Networks20161014151Available from: https://doi.org/10.1016/j.comnet.2015.12.017Search in Google Scholar
Fu X, Zou J, Ju CA. Sewing line planning model based on RFID technology. Journal of Electrical Engineering & Technology. 2020;15:1441–52. Available from: https://doi.org/10.1007/s42835-020-00420-xFuXZouJJuCASewing line planning model based on RFID technologyJournal of Electrical Engineering & Technology202015144152Available from: https://doi.org/10.1007/s42835-020-00420-xSearch in Google Scholar
Olanrewaju O, Ojima OA, Bakhtiyar D. Advancing manufacturing efficiency through real-time production monitoring and control systems. Journal of Engineering Research and Reports. 2024;26(4):184–93. Article no. JERR.115010. ISSN: 2582-2926.OlanrewajuOOjimaOABakhtiyarDAdvancing manufacturing efficiency through real-time production monitoring and control systemsJournal of Engineering Research and Reports202426418493Article no. JERR.115010. ISSN: 2582-2926.Search in Google Scholar
Von Haartman R, Bengtsson L, Niss C. Lean practices and the adoption of digital technologies in production. International Journal of Services and Operations Management. 2021;40:286–304. Available from: https://doi.org/10.1504/IJSOM.2021.118260Von HaartmanRBengtssonLNissCLean practices and the adoption of digital technologies in productionInternational Journal of Services and Operations Management202140286304Available from: https://doi.org/10.1504/IJSOM.2021.118260Search in Google Scholar
Koç B. Hazır Giyim Dikim İşletmesinde Yalın Üretim ve Sürdürülebilir Yalın Dijital Model Tasarımı (Unpublished PhD thesis). Istanbul Technical University; Faculty of Textile Engineering; 2025.KoçBHazır Giyim Dikim İşletmesinde Yalın Üretim ve Sürdürülebilir Yalın Dijital Model Tasarımı(Unpublished PhD thesis).Istanbul Technical University; Faculty of Textile Engineering2025Search in Google Scholar
Zhang, Y., & Sun, S. (2013, April 1). Real-time data driven monitoring and optimization method for IoT-based sensible production process. , 22, 486–490. https://doi.org/10.1109/icnsc.2013.6548787ZhangY.SunS.2013April1Real-time data driven monitoring and optimization method for IoT-based sensible production process22486490https://doi.org/10.1109/icnsc.2013.6548787Search in Google Scholar
Mohd J, Abid H, Ravi PS, Rajiv S, Ernesto SG. Understanding the adoption of Industry 4.0 technologies in improving environmental sustainability. Sustainable Operations and Computers. 2022;3:203–17. Available from: https://doi.org/10.1016/j.susoc.2022.01.008MohdJAbidHRaviPSRajivSErnestoSGUnderstanding the adoption of Industry 4.0 technologies in improving environmental sustainabilitySustainable Operations and Computers2022320317Available from: https://doi.org/10.1016/j.susoc.2022.01.008Search in Google Scholar
Khalil M, Din M, Ali A, Tahir M. Enhancing the productivity and assembly line balancing through takt time implementation. Research Square. 2024. Available from: https://doi.org/10.21203/rs.3.rs-4275556/v1KhalilMDinMAliATahirMEnhancing the productivity and assembly line balancing through takt time implementationResearch Square2024Available from: https://doi.org/10.21203/rs.3.rs-4275556/v1Search in Google Scholar
Edokpia R, Owu F. Assembly line re-balancing using ranked positional weight technique and longest operating time technique: a comparative analysis. Advanced Materials Research. 2013;824:568–78. Available from: https://doi.org/10.4028/www.scientific.net/AMR.824.568EdokpiaROwuFAssembly line re-balancing using ranked positional weight technique and longest operating time technique: a comparative analysisAdvanced Materials Research201382456878Available from: https://doi.org/10.4028/www.scientific.net/AMR.824.568Search in Google Scholar
Can E, Öner A. Analysis and balancing of assembly line in a machine molding factory. International Advanced Researches and Engineering Journal. 2021;5(1):87–96.CanEÖnerAAnalysis and balancing of assembly line in a machine molding factoryInternational Advanced Researches and Engineering Journal2021518796Search in Google Scholar
Bongomin O, Mwasiagi J, Oyondi N, et al. Improvement of garment assembly line efficiency using line balancing technique. Engineering Reports. 2020;2:1–22. Available from: https://doi.org/10.1002/eng2.12157BongominOMwasiagiJOyondiNImprovement of garment assembly line efficiency using line balancing techniqueEngineering Reports20202122Available from: https://doi.org/10.1002/eng2.12157Search in Google Scholar
Talapatra S, Al-Mahmud S, Kabir I. Overall Efficiency Improvement of a Production Line by Using Yamazumi Chart: A Case Study. Proceedings of the International Conference on Industrial Engineering and Operations Management; 2019; Paris, France.TalapatraSAl-MahmudSKabirIOverall Efficiency Improvement of a Production Line by Using Yamazumi Chart: A Case StudyProceedings of the International Conference on Industrial Engineering and Operations Management2019Paris, FranceSearch in Google Scholar
Xiao Y. Effect and Influencing Factors of Digital Transformation of Manufacturing Industry. 2022. Available from: https://doi.org/10.2991/aebmr.k.220405.072XiaoYEffect and Influencing Factors of Digital Transformation of Manufacturing Industry2022Available from: https://doi.org/10.2991/aebmr.k.220405.072Search in Google Scholar
Casciani D, Chkanikova O, Pal R. Exploring the nature of digital transformation in the fashion industry: opportunities for supply chains, business models, and sustainability-oriented innovations. Sustainability: Science, Practice and Policy. 2022;18(1):773–795. Available from: https://doi.org/10.1080/15487733.2022.2125640CascianiDChkanikovaOPalRExploring the nature of digital transformation in the fashion industry: opportunities for supply chains, business models, and sustainability-oriented innovationsSustainability: Science, Practice and Policy2022181773795Available from: https://doi.org/10.1080/15487733.2022.2125640Search in Google Scholar
Scherrer M, Deflorin P, Anand G. Manufacturing flexibility through outsourcing: effects of contingencies. International Journal of Operations & Production Management. 2014;34(9):1210–1242. Available from: https://doi.org/10.1108/ijopm-01-2012-0033ScherrerMDeflorinPAnandGManufacturing flexibility through outsourcing: effects of contingenciesInternational Journal of Operations & Production Management201434912101242Available from: https://doi.org/10.1108/ijopm-01-2012-0033Search in Google Scholar
Keough I, Benjamin D. Multi-objective optimization in architectural design. 2010. Available from: https://doi.org/10.1145/1878537.1878736KeoughIBenjaminDMulti-objective optimization in architectural design2010Available from: https://doi.org/10.1145/1878537.1878736Search in Google Scholar
Hasan M, Shanta MR, Shams A, Rahman S, Elahi S, Islam M. Advantages of lean techniques application in apparel industry: case study on knit jacket. Journal of Textile Engineering & Fashion Technology. 2019;5(5). Available from: https://doi.org/10.15406/jteft.2019.05.00210HasanMShantaMRShamsARahmanSElahiSIslamMAdvantages of lean techniques application in apparel industry: case study on knit jacketJournal of Textile Engineering & Fashion Technology201955Available from: https://doi.org/10.15406/jteft.2019.05.00210Search in Google Scholar