1. A holistic approach to cooling system selection and injection molding process optimization based on non-dominated sortingJanez Gotlih, Miran Brezočnik, Snehashis Pal, Igor Drstvenšek, Timi Karner, Tomaž Brajlih, 2022, original scientific article Abstract: This study applied a holistic approach to the problem of controlling the temperature of critical areas of tools using conformal cooling. The entire injection molding process is evaluated at the tool design stage using four criteria, one from each stage of the process cycle, to produce a tool with effective cooling that enables short cycle times and ensures good product quality. Tool manufacturing time and cost, as well as tool life, are considered in the optimization by introducing a novel tool-efficiency index. The multi-objective optimization is based on numerical simulations. The simulation results show that conformal cooling effectively cools the critical area of the tool and provides the shortest cycle times and the lowest warpage, but this comes with a trade-off in the tool-efficiency index. By using the tool-efficiency index with non-dominated sorting, the number of relevant simulation cases could be reduced to six, which greatly simplifies the decision regarding the choice of cooling system and process parameters. Based on the study, a tool with conformal cooling channels was made, and a coolant inlet temperature of 20 °C and a flow rate of 5 L/min for conformal and 7.5–9.5 L/min for conventional cooling channels were selected for production. The simulation results were validated by experimental measurements.
Keywords: conformal cooling, injection molding, tooling, additive manufacturing, numerical simulation, non-dominated sorting
Published in DKUM: 05.12.2024; Views: 0; Downloads: 0
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2. Simulation and mechanical properties of fine-grained heat-affected zone microstructure in 18CrNiMo7-6 steelTomaž Vuherer, Fidan Smaili, Edvard Bjelajac, Mirza Manjgo, Gorazd Lojen, 2022, original scientific article Abstract: Heat-affected zones (HAZs) in real welds are usually quite narrow, and consequently most standard mechanical tests are difficult or even impossible. Therefore, simulated microstructures are often used for mechanical tests. However, the most often used weld thermal cycle simulator produces only a few millimeters wide area of simulated microstructure in the middle of specimens. Consequently, these kind of simulated specimen are not suitable for standard tensile tests, and even for Charpy impact tests, the simulated area can be too narrow. Therefore, to investigate the mechanical properties of a fine-grain heat-affected zone in 18CrNiMo7-6 steel, two methods were used for simulation of as-welded microstructures: (a) a weld thermal cycle simulator, and (b) as an alternative, though not yet verified option, austenitizing in a laboratory furnace + water quenching. The microstructures were compared and mechanical properties investigated. The grain sizes of the simulated specimens were 10.9 μm (water-quenched) and 12.6 μm (simulator), whereby the deviations from the real weld were less than 10%. Both types of simulated specimen were used for hardness measurement, Charpy impact tests, and fatigue tests. Water-quenched specimens were large enough to enable standard tensile testing. A hardness of 425 HV, yield strength Rp02 = 1121 MPa, tensile strength Rm = 1475 MPa, impact energy KV = 73.11 J, and crack propagation threshold ΔKthR = 4.33 MPa m0.5 were obtained with the water quenched specimens, and 419 HV, KV = 101.49 J, and ΔKthR = 3.4 MPa m0.5 with the specimens prepared with the simulator. Comparison of the results confirmed that the annealed and quenched specimens were suitable for mechanical tests of FG HAZs, even for standard tensile tests. Due to the use of simulated test specimens, the mechanical properties determined can be linked to the FG HAZ microstructure in 18CrNiMo7-6 steel.
Keywords: weld joint, fine-grained HAZ, simulation of microstructure, hardness, impact toughness, tensile properties, fatigue crack growth, 18CrNiMo7-6 steel
Published in DKUM: 05.12.2024; Views: 0; Downloads: 1
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3. The Economic efficiency of micro biogas plants: ǂa ǂSustainable Energy solution in Slovenia - Case studyPeter Vindiš, Karmen Pažek, Jernej Prišenk, Črtomir Rozman, 2024, original scientific article Abstract: This paper presents a simulation model for determining the most suitable type of microbiogas plant for small local communities on Slovenian farms, focusing on the efficient processing of organic waste. This model uses various input parameters, including different types and quantities of slurry and corn silage. Four different scenarios were developed to represent potential plant sizes, each evaluated using key economic indicators: net present value, breakthrough price, and internal rate of return. A scenario sensitivity analysis was conducted to assess the effects of changes in investment costs, fluctuations in energy prices, and the addition of corn silage to the anaerobic digestion process. The results highlight significant differences in economic viability across the scenarios, with some demonstrating positive financial outcomes and shorter payback periods and others indicating potential financial risks and longer recovery times under certain conditions. The analysis suggests that smaller micro biogas plants may struggle to achieve profitability without optimizing input ratios or reducing costs, whereas larger plants show more favorable economic indicators, provided certain conditions are met. Furthermore, the economic efficiency improves when adding maize silage to the fermentor mixture.
Keywords: micro biogas plant, biogas, economic efficiency, simulation
Published in DKUM: 27.11.2024; Views: 0; Downloads: 3
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4. Ergonomic evaluation of human–robot collaborative order picking : a combined laboratory and simulation studyMinqi Zhang, Jakob Marolt, Primož Bencak, Eric Grosse, Tone Lerher, 2024, published scientific conference contribution Abstract: Thanks to rapid technological developments in robotics, various automation technologies are being applied in warehouses today. Order picking, as a key process in warehouse operations, has drawn attention in academia and practice for decades. In addition to many studies dedicated to manual and fully automated order picking, efforts have also been made to study semi-automated warehouses in which humans and robots collaborate. However, these studies mostly focused on system efficiency and ignored ergonomic aspects. Order picking was confirmed as a labor-intensive process in an environment in which workers are at a high risk of developing health problems. Therefore, this study addresses the investigation of physical human working conditions in both manual and robot-assisted order picking systems via real-life laboratory experiments and simulation modeling. We used a motion capture system to assess human working postures when working with and without robot assistance. In addition, we estimated the daily workload by applying the energy expenditure concept. Using simulation experiments, we were able to extend the results to various practical scenarios with different design variables, for example warehouse layouts, order sizes, and human-robot team configuration. Our preliminary results reveal that human-robot collaboration can reduce human workload. Posture evaluation also shows a slight improvement.
Keywords: order picking, autonomous mobile robot, human factors, ergonomics, assisted order picking, hybrid order picking, simulation, performance evaluation
Published in DKUM: 21.11.2024; Views: 0; Downloads: 2
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5. Development and control of virtual industrial process using Factory IO and MATLABGoran Munđar, Miha Kovačič, Uroš Župerl, 2024, original scientific article Abstract: In today's rapidly evolving business landscape, the strategic adoption of virtual manufacturing methods has emerged as a key driver for companies seeking to streamline
operations and expedite product launches in a cost-effective manner. This progressive approach involves the creation of a synthetic and interconnected environment, empowered
by advanced software tools and systems, including Virtual Reality and Simulation technologies, tailored to optimize industrial processes. Our methodology employs a unique
combination of two simulation software tools: Factory I/O for process development and MATLAB for control program implementation. Furthermore, we explore the use of the
Modbus TCP/IP communication protocol as the framework for seamless interaction between these software tools during simulation. This research presents practical insights into
the transformative potential of virtual manufacturing, showcasing its real-world application in enhancing operational efficiency and agility within industrial settings.
Keywords: Factory I/O, MATLAB, Modbus TCP/IP, simulation technologies, virtual manufacturing
Published in DKUM: 19.09.2024; Views: 0; Downloads: 2
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6. Optimal bus stops' allocation : a school bus routing problem with respect to terrain elevationKlemen Prah, Abolfazl Keshavarzsaleh, Tomaž Kramberger, Borut Jereb, Dejan Dragan, 2018, original scientific article Abstract: The paper addresses the optimal bus stops allocation in the Laško municipality. The goal is to achieve a cost reduction by proper re-designing of a mandatory pupils' transportation to their schools. The proposed heuristic optimization algorithm relies on data clustering and Monte Carlo simulation. The number of bus stops should be minimal possible that still assure a maximal service area, while keeping the minimal walking distances children have to go from their homes to the nearest bus stop. The working mechanism of the proposed algorithm is explained. The latter is driven by three-dimensional GIS data to take into account as much realistic dynamic properties of terrain as possible. The results show that the proposed algorithm achieves an optimal solution with only 37 optimal bus stops covering 94.6 % of all treated pupils despite the diversity and wideness of municipality, as well as the problematic characteristics of terrains' elevation. The calculated bus stops will represent important guidelines to their actual physical implementation.
Keywords: logistics, maximal covering problems, optimization, data clustering, Monte Carlo simulation, geographic information system (GIS), reduction of transportation costs, Laško, Slovenia
Published in DKUM: 22.08.2024; Views: 35; Downloads: 9
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7. Implementation of the digital sales channel in the coatings industryEva Krhač Andrašec, Marjan Senegačnik, Benjamin Urh, Tomaž Kern, 2021, original scientific article Abstract: The development process in the coatings industry can be shortened by digital transformation, and its costs can be reduced using a technical enabler. However, formulators need up-to-date and comprehensive data on existing and potential ingredients to develop the formulation. We were curious about how to supply formulators with data. The idea was that suppliers of ingredients provide data using the “common enabling technology”. We hypothesize that direct data entry compensates suppliers because they can shorten the sales process and increase sales. We used a survey to select key sales channels in the industry. Detailed process models were designed using structured interviews. We analyzed models using structural and operational indicators. Finally, we formed a new digital sales process and verified it. The results show that the digitally formatted sales process can be shortened by up to 32%. Simultaneously, more potential customers can be accessed using the common technology. Existing sales channels would not be closed down. Nevertheless, the digital sales channel is expected to prove its worth over time and gradually increase its share. The suppliers of ingredients can thus avoid a radical process transformation and the immediate integration of additional information technology into the company information system in such an evolutionary way.
Keywords: digital sales channel, process analyses and improvement, digital transformation, technical enabler, coatings industry, process simulation
Published in DKUM: 06.08.2024; Views: 103; Downloads: 10
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8. Road freight transport forecasting : a fuzzy Monte-Carlo simulation-based model selection approachDejan Dragan, Simona Šinko, Abolfazl Keshavarzsaleh, Maja Rosi, 2022, original scientific article Abstract: As important as the classical approaches such as Akaike's AIC information and Bayesian BIC criterion in model-selection mechanism are, they have limitations. As an alternative, a novel modeling design encompasses a two-stage approach that integrates Fuzzy logic and Monte Carlo simulations (MCSs). In the first stage, an entire family of ARIMA model candidates with the corresponding information-based, residual-based, and statistical criteria is identified. In the second stage, the Mamdani fuzzy model (MFM) is used to uncover interrelationships hidden among previously obtained models criteria. To access the best forecasting model, the MCSs are also used for different settings of weights loaded on the fuzzy rules. The obtained model is developed to predict the road freight transport in Slovenia in the context of choosing the most appropriate electronic toll system. Results show that the mechanism works well when searching for the best model that provides a well-fit to the real data.
Keywords: forecasting road transport, electronic toll system, Monte Carlo simulation, ARIMA models, logistics
Published in DKUM: 11.06.2024; Views: 135; Downloads: 11
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