1. 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: 6
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3. The need for simulation in complex industrial systemsKhalid Aboura, Miroljub Kljajić, Ali Eskandarian, 2012, original scientific article Abstract: We discuss the concept of simulation and its application in the resolution of problems in complex industrial systems. Most problems of serious scale, be it an inventory problem, a production and distribution problem, a management of resources or process improvement, all real world problems require a mix of generic, data algorithmic and Ad-hoc solutions making the best of available information. We describe two projects in which analytical solutions were applied or contemplated. The first case study uses linear programming in the optimal allocation of advertising resources by a major internet service provider. The second study, in a series of projects, analyses options for the expansion of the production and distribution network of mining products, as part of a sensitive strategic business review. Using the examples, we make the case for the need of simulation in complex industrial problems where analytical solutions may be attempted but where the size and complexity of the problem forces a Monte Carlo approach.
Keywords: simulation, linear programming, production process
Published in DKUM: 10.07.2015; Views: 1232; Downloads: 399
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4. Segmenting risks in risk managementBorut Jereb, 2009, original scientific article Abstract: The paper describes a segmentation of risks to make each risk segment more manageable. The proposed approach is primarily intended to improve the confidentiality of risk simulations. The description of the approach is based on a logistics business process system which requires that its input is represented as a process graph. Each process is defined in terms of input and output; input comprises general input as well as risks; output comprises general output as well as impacts. The model takes into consideration internalas well as external input and output. Parameters can be used to define individual processes. Processes include functions that calculate new values of parameters and output on the bases of given input. Based on given tolerance levels for risks, impacts and process parameters, the model determines whether these levels are acceptable. The model assumes that parameters and functions are non-deterministic, i.e. parameters and functions may change in time. Although the approach is described on a very general level, each segment can be further subdivided into subsegments in order to include more characteristics of observed risks.
Keywords: risk, impact, segmentation, risk management, process parameters, logistics, model, simulation tools, non-deterministic
Published in DKUM: 05.06.2012; Views: 2069; Downloads: 53
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5. A Multi-criteria decision analysis framework tool for the selection of farm business models on organic mountain farmsKarmen Pažek, Črtomir Rozman, Franc Bavec, Andreja Borec, Martina Bavec, 2010, original scientific article Abstract: Mountain regions are important producers of organic food. For them, reliable decision making regarding business planning necessitates different critical support methods. KARSIM 1.0 (DSM) is a methodology based on an integrated deterministic simulation system application for decision-making support, consisting of 74 deterministic production simulation models. DSM enables different types of cost and financial feasibility calculations for organic production and food processing. KARSIM 1.0 was used to simulate three specific business alternatives for mountain organic farms. (Alternative 1: spelt grain, fruit cider, wine and brandy, plum brandy, calves meat and sheep-soft cheese production, Alternative 2: spelt flour, pear and apple juice, plum brandy, veal and sheep's milk, Alternative 3: spelt grain, dried fruit, calves, soft and hard sheep cheese). Simulation model results were compared using two multi-objective analysis methods: the analytical hierarchical process (Expert Choice Decision Support System software) and DEX-i method. the results showed the bigest multi-objective decision evaluation for alternative 2 (Expert Choice = 0.361 and DEX-i evaluation = excellent). We can conclude that the combination of a deterministic cost simulation model and multi-criteria decision analysis present an acceptable decision support tool for mountain organic farms; however, further research is desirable.
Keywords: simulation modeling, KARSIM 1.0, MCDA, DEXži, analytical hierarchical process, mountain organic farms
Published in DKUM: 05.06.2012; Views: 2345; Downloads: 138
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6. A model of simulation environment for prediction and optimisation of production processesIgor Drstvenšek, Mirko Ficko, Ivo Pahole, Jože Balič, 2004, original scientific article Abstract: Paper describes means and methods for computer based optimisation of production processes using a new approach based on technological database (TDB) with genetic algorithm incorporated into a database management system (DBMS). The TDB serves as a store of tools and machine tools from which they can be assigned to different work operations. Work operations are basic entities of orders placed into queues. The goal of the model is to find available resources from the TDB in order to empty the queue in shortest time with lowest costs. To this purpose the model consist the technological database whose DBMS includes a genetic algorithm based optimiser. It checks the orders queue and searches for appropriate combinations of tools and machine tools from the TDB, which can be combined into needed work operations. It also performs an optimisation of time and costs according to so called static parameters of tools and machine tools.
Keywords: production processes, simulation, process planning, technological databases, genetic algorithms
Published in DKUM: 01.06.2012; Views: 1875; Downloads: 103
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9. Using neural networks in the process of calibrating the microsimulation models in the analysis and design of roundabouts in urban areasIrena Ištoka Otković, 2011, dissertation Abstract: The thesis researches the application of neural networks in computer program calibration of traffic micro-simulation models. The calibration process is designed on the basis of the VISSIM micro-simulation model of local urban roundabouts.
From the five analyzed methods of computer program calibration, Methods I, II and V were selected for a more detailed research. The three chosen calibration methods varied the number of outgoing traffic indicators predicted by neural networks and a number of neural networks in the computer program calibration procedure. Within the calibration program, the task of neural networks was to predict the output of VISSIM simulations for selected functional traffic parameters - traveling time between the measurement points and queue parameters (maximum queue and number of stopping at the roundabout entrance). The Databases for neural network training consisted of 1379 combinations of input parameters whereas the number of output indicators of VISSIM simulations was varied. The neural networks (176 of them) were trained and compared for the calibration process according to training and generalization criteria. The best neural network for each calibration method was chosen by using the two-phase validation of neural networks.
The Method I is the calibration method based on calibration of a traffic indicator -traveling time and it enables validation related to the second observed indicator – queue parameters. Methods II and V connect the previously described calibration and validation procedures in one calibration process which calibrates input parameters according to two traffic indicators.
Validation of the analyzed calibration methods was performed on three new sets of measured data - two sets at the same roundabout and one set on another location. The best results in validation of computer program calibration were achieved by the Method I which is the recommended method for computer program calibration.
The modeling results of selected traffic parameters obtained by calibrated VISSIM traffic model were compared with: values obtained by measurements in the field, the existing analysis methods of operational roundabouts characteristics (Lausanne method, Kimber-Hollis, HCM) and modeling by the uncalibrated VISSIM model. The calibrated model shows good correspondence with measured values in real traffic conditions. The efficiency of the calibration process was confirmed by comparing the measured and modeled values of delays, of an independent traffic indicator that was not used in the process of calibration and validation of traffic micro-simulation models.
There is also an example of using the calibrated model in the impact analysis of pedestrian flows on conflicting input and output flows of vehicles in the roundabout. Different traffic scenarios were analyzed in the real and anticipated traffic conditions.
Keywords: traffic models, traffic micro-simulation, calibration of the VISSIM model, computer program calibration method, neural networks in the calibration process, micro-simulation of roundabouts, traffic modeling parameters, driving time, queue parameters, delay
Published in DKUM: 02.06.2011; Views: 5471; Downloads: 383
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