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Advances in Production Engineering & Management
Volume 16 | Number 4 | December 2021 | pp 389–518

Contents
A deep learning-based worker assistance system for error prevention: Case study in a real-world manual assembly
Riedel, A.; Gerlach, J.; Dietsch, M.; Herbst, S.; Engelmann, F.; Brehm, N.; Pfeifroth, T.
https://doi.org/10.14743/apem2021.4.408
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Optimal path planning of a disinfection mobile robot against COVID-19 in a ROS-based research platform
Banjanovic-Mehmedovic, L.; Karabegovic, I.; Jahic, J.; Omercic, M.
https://doi.org/10.14743/apem2021.4.409
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Using augmented reality devices for remote support in manufacturing: A case study and analysis
Buń, P.; Grajewski, D.; Górski, F.
https://doi.org/10.14743/apem2021.4.410
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The impact of the collaborative workplace on the production system capacity: Simulation modelling vs. real-world application approach
Ojstersek, R.; Javernik, A.; Buchmeister, B.
https://doi.org/10.14743/apem2021.4.411
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A multi-criteria decision-making in turning process using the MAIRCA, EAMR, MARCOS and TOPSIS methods: A comparative study
Trung, D.D.; Thinh, H.X.
https://doi.org/10.14743/apem2021.4.412
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Molecular-dynamics study of multi-pulsed ultrafast laser interaction with copper
Yin, C.P.; Zhang, S.T.; Dong, Y.W.; Ye, Q.W.; Li, Q.
https://doi.org/10.14743/apem2021.4.413
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A comparative study of different pull control strategies in multi-product manufacturing systems using discrete event simulation
Xanthopoulos, A.S.; Koulouriotis, D.E.
https://doi.org/10.14743/apem2021.4.414
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Latent class analysis for identification of occupational accident casualty profiles in the selected Polish manufacturing sector
Nowakowska, M.; Pajęcki, M.
https://doi.org/10.14743/apem2021.4.415
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Impact of Industry 4.0 on decision-making in an operational context
Rosin, F.; Forget, P.; Lamouri, S.; Pellerin, R.
https://doi.org/10.14743/apem2021.4.416
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Advances in Production Engineering & Management
Volume 16 | Number 3 | September 2021 | pp 265–388

Contents
A new solution to distributed permutation flow shop scheduling problem based on NASH Q-Learning
Ren, J.F.; Ye, C.M.; Li, Y.
https://doi.org/10.14743/apem2021.3.399
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Using the gradient boosting decision tree (GBDT) algorithm for a train delay prediction model considering the delay propagation feature
Zhang, Y.D.; Liao, L.; Yu, Q.; Ma, W.G.; Li, K.H.
https://doi.org/10.14743/apem2021.3.400
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A smart Warehouse 4.0 approach for the pallet management using machine vision and Internet of Things (IoT): A real industrial case study
Vukićević, A.; Mladineo, M.; Banduka, N.; Mačužić, I.
https://doi.org/10.14743/apem2021.3.401
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Increasing Sigma levels in productivity improvement and industrial sustainability with Six Sigma methods in manufacturing industry: A systematic literature review
Purba, H.H.; Nindiani, A.; Trimarjoko, A.; Jaqin, C.; Hasibuan, S.; Tampubolon, S.
https://doi.org/10.14743/apem2021.3.402
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Modeling and optimization of finish diamond turning of spherical surfaces based on response surface methodology and cuckoo search algorithm
Kramar, D.; Cica, Dj.
https://doi.org/10.14743/apem2021.3.403
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Tactical manufacturing capacity planning based on discrete event simulation and throughput accounting: A case study of medium sized production enterprise
Jurczyk-Bunkowska, M.
https://doi.org/10.14743/apem2021.3.404
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Simulation-based optimization of coupled material–energy flow at ironmaking-steelmaking interface using One-Ladle Technique
Hu, Z.C.; Zheng, Z.; He, L.M.; Fan, J.P.; Li, F.
https://doi.org/10.14743/apem2021.3.405
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Recharging and transportation scheduling for electric vehicle battery under the swapping mode
Huang, A.Q.; Zhang, Y.Q.; He, Z.F.; Hua, G.W.; Shi, X.L.
https://doi.org/10.14743/apem2021.3.406
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A multi-objective selective maintenance optimization method for series-parallel systems using NSGA-III and NSGA-II evolutionary algorithms
Xu, E.B.; Yang, M.S.; Li, Y.; Gao, X.Q.; Wang, Z.Y.; Ren, L.J.
https://doi.org/10.14743/apem2021.3.407
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Advances in Production Engineering & Management
Volume 16 | Number 2 | June 2021 | pp 141–264

Contents
Hybrid ANFIS-Rao algorithm for surface roughness modelling and optimization in electrical discharge machining
Agarwal, N.; Shrivastava, N.; Pradhan, M.K.
https://doi.org/10.14743/apem2021.2.390
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A multi-objective optimal decision model for a green closed-loop supply chain under uncertainty: A real industrial case study
Fang, I.W.; Lin, W.-T.
https://doi.org/10.14743/apem2021.2.391
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Improved Genetic Algorithm (VNS-GA) using polar coordinate classification for workload balanced multiple Traveling Salesman Problem (mTSP)
Wang, Y.D.; Lu, X.C.; Shen, J.R.
https://doi.org/10.14743/apem2021.2.392
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Change impact analysis of complex product using an improved three-parameter interval grey relation model
Yang, W.M.; Li, C.D.; Chen, Y.H.; Yu, Y.Y.
https://doi.org/10.14743/apem2021.2.393
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Bone drilling with internal gas cooling: Experimental and statistical investigation of the effect of cooling with CO2 on reduction of temperature rise due to drill bit wear
Shakouri, E.; Haghighi Hassanalideh, H.; Fotuhi, S.
https://doi.org/10.14743/apem2021.2.394
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Joint distribution models in fast-moving consumer goods wholesale enterprise: Comparative analysis and a case study
Wang, L.; Chen, X.Y.; Zhang, H.
https://doi.org/10.14743/apem2021.2.395
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Designing a warehouse internal layout using a parabolic aisles based method
Zhang, Z.Y.; Liang, Y.; Hou, Y.P.; Wang, Q.
https://doi.org/10.14743/apem2021.2.396
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Optimization of disassembly line balancing using an improved multi-objective Genetic Algorithm
Wang, Y.J.; Wang, N.D.; Cheng, S.M.; Zhang, X.C.; Liu, H.Y.; Shi, J.L.; Ma, Q.Y.; Zhou, M.J.
https://doi.org/10.14743/apem2021.2.397
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Modelling and optimization of sulfur addition during 70MnVS4 steelmaking: An industrial case study
Kovačič, M.; Lešer, B.; Brezocnik, M.
https://doi.org/10.14743/apem2021.2.398
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Advances in Production Engineering & Management
Volume 16 | Number 1 | March 2021 | pp 1–140

Contents
Analysis of the impact of COVID-19 on the coupling of the material flow and capital flow in a closed-loop supply chain
Duan, W.; Ma, H.; Xu, D.S.
https://doi.org/10.14743/apem2021.1.381
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A dynamic job-shop scheduling model based on deep learning
Tian, W.; Zhang, H.P.
https://doi.org/10.14743/apem2021.1.382
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Multi-objective automated guided vehicle scheduling based on MapReduce framework
Shi, W.; Tang, D.B.; Zou, P.
https://doi.org/10.14743/apem2021.1.383
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A conceptual model for measuring the competency level of Small and Medium-sized Enterprises (SMEs)
Oztemel, E.; Ozel, S.
https://doi.org/10.14743/apem2021.1.384
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Study of load-bearing timber-wall elements using experimental testing and mathematical modelling
Premrov, M.; Ber, B.; Kozem Šilih, E.
https://doi.org/10.14743/apem2021.1.385
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The implications of product modularisation on the development process, supplier integration and supply chain design in collaborative product development
Koppenhagen, F.; Held, T.
https://doi.org/10.14743/apem2021.1.386
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Exploring the link between project management approach and project success dimensions: A structural model approach
Ciric, D.; Delic, M.; Lalic, B.; Gracanin, D.; Lolic, T.
https://doi.org/10.14743/apem2021.1.387
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Optimization of a multi-objective location model of manufacturing base considering cooperative manufacturing capabilities and service benefits
Sun, J.Z.; Zhang, Q.S.; Yu, Y.Y.
https://doi.org/10.14743/apem2021.1.388
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A new management approach based on Additive Manufacturing technologies and Industry 4.0 requirements
Patalas-Maliszewska, J.; Topczak, M.
https://doi.org/10.14743/apem2021.1.389
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