Material Flow Simulation Research Articles

System efficient integration of standby control and heat pump storage systems in manufacturing processes

Prerequisite for system efficiency towards an industrial energy transition is the reducing of energy demand on the process level. In typical manufacturing systems with machine tools and washing machines, the proper design of intelligent standby control and heat pump storage system (HPS) represent high efficiency. The integration of HPS is complicated due to high non-continuity, especially when implementing a standby control system. Our approach aims at designing one single HPS for multiple heat sources and sinks. Robust design should consider the various influencing material flow system factors. For the generation of stochastic heating and cooling demand sum curves, 512 Design of Experiments-based material flow simulations for each of three standby scenarios have been conducted. These curves serve as input data for HPS sizing and dynamic thermal system simulation. The combined integration of an HPS and a practical standby control system offers the best compromise in terms of system efficiency with significantly lower investment costs and only slightly lower energy savings than ideal standby operation. Compared to the initial state, the electrical energy demand of the machines can be reduced by 27% and both the heating (83%) and cooling (48%) demand can be efficiently covered by HPs.

Simulation and visualization of material flows in sanitation systems for streamlined sustainability assessment.

New and alternative sanitation systems are increasingly discussed and find their way into implementation. However, discussions on sanitation concepts often are held in a rather emotional way. Furthermore, not all the available sanitation concepts might be known to the decision maker. The work presented here attempts to contribute to a good discussion and decision making process by compiling available technologies, by defining easy-to-implement criteria for a sustainability assessment method and by integrating these results into a simulation tool which allows to visualize the related resource fluxes (e.g. those on nutrients, such as N, P and K) and to analyse different sanitation options with regard to their capital and operational costs and with regard to environmental impact criteria such as greenhouse gas emissions. Whilst the calculations are to be considered as being approximate in their nature (due to uncertainties or lack of suitable input data), this tool allows the planners, with sometimes little modelling experience, to consider the characteristics of sanitation systems. Whilst starting from earlier work, such as Eawag's Sanitation Compendium and work on material flow analysis, work described in this contribution merges resource flux modelling, easy-to-use simulation and visualization and methods of life cycle assessment and life cycle costing. The simulation tool is freely available on https://www.ifak.eu/en/products/sampsons.

Simulation Model Creation for Verifying the Production Capacity of a Production Line and Sizing in-Process Inventory

The high complexity of logistical systems in connection with the high competitive pressure makes the implementation of efficient processes in companies and supply chains inevitable. Unlike the optimization in which an attempt is made to model a problem directly, analytically or through modelling using heuristic, the simulation tracks another, i.e. intuitive approach. The development of information technology has created the need to apply a comprehensive system of technical data management in industrial practice. It was necessary to increase the efficiency of information sharing within the value-added chain of the company on specific projects. The aim of this paper is to create a model of production disposition with material flow simulation in TX Plant Simulation software environment for verifying the maximal potential capacity of production.

Investigation of Inventory Record Accuracy in Product-Service System

In this paper we examine Product-Service System (PSS) in manufacturing industries application to inventory control in Malaysian Elaeis Guineensis or known as palm oil industries. We are particularly interested in the record of inventory accuracy for palm oil tree, fresh fruit bunch (FFB) and palm oil. If the inventory is uncontrolled or not accurate, the production will face problems to meet customers demand. We focus not just on inventory activities themselves, but also the key linkages between production, market, supply chain, and oil production. These linkages are examined using generic model using IDEF0 which consists five charts: A0 chart, A1 chart, A2 chart, A3 chart and A4 chart. This paper has provided useful insights into the actual data collection and the preliminary analysis, as well as the contextual and associated information relating to inventory control system. Further research will be to evaluate the generic model development using Technomatix Logistic and Material Flow Simulation Software.

Development of PYMUS+ Code for Quantitative Evaluation of Nuclear Material Accounting (NMA) System

The Nuclear Material Accounting (NMA) system is one of the main safeguards measures to detect the existence of nuclear material diversion. It has become more important for large reprocessing facilities to apply Near Real Time Accountancy (NRTA) system based on NMA and statistical techniques to meet quantitative and timeliness goals. It is also important to quantitatively evaluate the performance of NMA system including NRTA from the standpoints of Safeguards and Security by Design (SSBD) prior to construction of nuclear-material-handling facilities. Such evaluation improves safeguards effectiveness and efficiency. Modeling and Simulation (M&S) work is a good way to evaluate performance for various NMA systems and to determine the optimal one among different options. For these purposes, in the present study, the PYroprocessing Material flow and MUF Uncertainty Simulation+ (PYMUS+) code, which uses evaluation algorithms to calculate many safeguards factors such as MUF uncertainty, detection probability, and others, was developed. According to a previous report, the PYMUS code, the predecessor of PYMUS+, can calculate MUF uncertainties only for a fixed model having 10 tHM/year, whereas the PYMUS+ code can additionally calculate detection probabilities according to diverse nuclear diversion scenarios as well as MUF uncertainties. The most important feature of the PYMUS+ code is its capability to evaluate many process and NMA system model options that a user wants to evaluate. Furthermore, a user can make a static process model having simplicity and a matching NMA model based on the PYMUS+ code regardless of facility throughput and is not even required to have professional programming knowledge. In the present work, some intercomparative studies were conducted to verify the M&S techniques applied in this code. It is expected that this code will be a useful tool for evaluation of NRTA system of pyroprocessing and other reprocessing facilities.

The logistical approach to the analysis, modelling and simulation of material flow

The logistical approach to the analysis, modelling and simulation of material flow

Reconfiguration of production systems using optimization and material flow simulation

Current market developments, such as intensifying volatility and rising demand for individualized products, require highly flexible and adaptable production systems. Reconfigurable production systems enable manufacturing companies to meet these market developments due to the ability of short-term scalability of capacities and order-specific adjustments of production resources for preserving high delivery performance and utilization rate. The vast complexity of such systems raises the demand for decision support systems. Therefore, this paper presents an innovative approach combining optimization and material flow simulation for developing and selecting optimized reconfiguration scenarios. A prototypical application is presented to demonstrate the feasibility of the approach.

A Survey on Automatic Model Generation for Material Flow Simulation in Discrete Manufacturing

Adaptivity of production systems is acknowledged as a key competition factor in the manufacturing industry. In order to decrease reaction time and increase cost efficiency, changes to a production system are often planned and validated using material flow simulation. However, repeated manual synchronization of the simulation model with the real manufacturing environment is time-consuming and error-prone. Automatic simulation model generation (ASMG) could overcome these issues. In contrast to recent surveys on ASMG, we focus on information retrieval. Accordingly, we constitute the state of the art of this problem domain and outline future research directions.

Validation of a physics engine for the simulation of material flows in cyber-physical production systems

In cyber-physical production systems, physical material flows show complexity due to varying physical aspects of transported work pieces and varying routes. As a result, physically induced disturbances that may lead to delays or damages are hard to predict. The usage of a physics engine offers potential to prevent these disturbances by simulating the physical behavior of material flows prior to their execution. Therefore, the ability of a physics engine to simulate the described disturbances is validated in this paper. For this purpose, the simulation results are compared with an analytical model. Additionally, a practical use case is provided that demonstrates the application of the simulation model.

Simulation based production support system in the field of steel construction for large offshore structures

Commonly, the employment of material flow simulation tools in the steelwork industry is limited to the tactical mid-term and strategical long-term planning tasks. This paper describes an approach how the simulations strengths can be adapted to contribute to short-term planning. By executing iterative simulation runs based on real-time production data automatic planning guidance is generated. This procedure lowers the reaction time and improves the overall planning quality because of steadily updated base data generated by a real-time capable interface. It is shown how historical data is utilized to enhance the data input for future planning tasks using machine learning algorithms.

Physical modeling of material flows in cyber-physical production systems

Cyber-physical production systems that produce customized products usually show complex material flows. Furthermore - due to customization - work pieces that are transported within these production systems strongly vary in terms of their physical properties. In combination, this increases the probability of physically induced material flow disturbances, e.g. a work piece falling off a conveyor belt. In case of damaged work pieces or equipment, the occurrence of these events may result in increased delivery times and costs. However, traditional material flow simulations are unable to predict physically induced disturbances, since their discrete-event approach solely focuses on chronological aspects of the material flow. In consequence, this paper presents the development of a computer-based model to simulate physical aspects of material flows by using a physics engine. In the first step, the requirements for this simulation model are determined. This includes the identification and definition of physical phenomena that influence typical material flow processes. Furthermore, a suitable physics engine is selected, that matches the requirements and is able to simulate the relevant physical phenomena. Subsequently, required input data and parameters are defined. After the theoretical framework is developed, the model is implemented using the selected physics engine. Finally, the model is validated by using an exemplary material flow process. The validation determines if the simulation model is capable of simulating physical aspects in material flows with a suitable degree of reality.

Load and energy management for factories through multi-stage production planning and optimization

The production phase has a major influence on the embodied energy of many products and, thus, their overall environmental performance. As a result, manufacturing enterprises are prompted to raise their energy efficiency and flexibility to improve their products’ sustainability. The simultaneous integration of renewable energy sources and decentral storages is a feasible option in this but also require consistent solutions for appropriately planning and controlling the operation of the entire factory system. This paper proposes an iterative multi-stage heuristic optimization for intelligent load and energy management. A load profile of the production plan, based on the minimized overall makespan, is checked against the available energy supply to identify demands and opportunities to shift single jobs based on calculated buffer times. Whenever infeasibility is determined, the process returns to the previous production planning stage for further alterations. This cycle is initiated regularly (e.g. weekly) or following certain events (e.g. long-lasting machine failure) and terminates once all restrictions are observed or if a termination threshold (e.g. calculation time) is reached. The experimental setup used for developing and validating this approach to energy-aware factory operation makes use of a probabilistic material flow simulation model. It provides information on tasks to be scheduled and executes production plans to evaluate the performance of the proposed solution. This new approach to energy-aware factory operation also provides opportunity to integrate additional ecologic criteria to improve the sustainability of manufactured products.

E|Melt: Simulation-Driven Analysis of Energy Efficiency Measures inside Non-Ferrous Melting and Die-Casting Plants

This paper describes the necessary measures to create an adaptable material flow and energy simulation for melting and die-casting plants. Based on two reference plants, the structural and intralogistical differences are emphasized and examined. These differences specify the necessary extensions to a previously created simulation environment in order to be able to analyze variable plant configurations. Special emphasis is put on the creation of a simplified energy model that allows the modeling of melting furnaces based on rudimentary datasets. Using the adaptable material flow and energy simulation two measures and their effects on the in-plant energy efficiency as well as productivity are analyzed. The simulation results suggest energy savings potentials for both plants and measures to increase productivity for one of the analyzed plants.

Material flow design and simulation for a glass panel recycling installation.

The current paper presents the design of a glass panels recycling flow and the method used for establishing the optimal processing installation architecture. In the solution provided in the current research, a novel approach centred on applying digital twinning in the design of the requested processing architecture is presented. It involves designing the virtual prototype of the diffused processing architecture and modelling the glass waste flow as a hybrid material flow. Dedicated analysis and simulation software is then used for establishing installation architecture and the specific parameters for each processing and transport capacity. The assessment of different processing scenarios by virtual modelling and simulations can also be used for exploring options to increase productivity and profit for other different recycling architectures. The main practical value of the study consists of creating the means to improve the waste recycling of automotive windshields, float glass or construction glass panels with metallic meshes, all representing categories of waste insufficiently recycled in Romania. The simulation results of the study were validated by tests made on the glass panel recycling installation. Also, a recovery glass rate of minimum 85% of the amount of waste loaded into the recycling system was achieved, obtaining a waste recycling quantity three times higher than initially anticipated.

Simulation of strain rate, material flow, and nugget shape during dissimilar friction stir welding of AA6061 aluminum alloy and Al-Mg2Si composite

A three-dimensional model was developed based on computational fluid dynamics (CFD) to study the visco-plastic material flow during friction stir welding of AA6061 aluminum alloy and Al-Mg2Si composite dissimilar joint. To model the dissimilar joint, the volume of fluid (VOF) method was used. The volumetric equation was defined for the heat which generated through the viscous dissipation. The model was investigated for three rotational speeds of 720, 920 and 1120 rpm. The nugget shape was in good agreement with the corresponding experimental results. The results showed that maximum velocity and strain rate occurred at the top surface of the workpiece and outer edge of the shoulder. Also, peak temperature was obtained at the advancing side. The strain rate at the advancing side and the retreating side was about 975s−1 and 926s−1, respectively. In a region of the stir zone where material mixing is dominant, the volume fraction of the AA6061 aluminum alloy is 0.4–0.8.

Finite-element simulation and validation of material flow in thermal drilling process

Galvanized steel is broadly employed in metal roofing, air conditioning duct, support beams, construction materials, and domestic appliances, etc. In conventional drilling method has limitations such as asymmetrical holes, as well as formation of crack inside the hole made in sheet metal. This problem was entirely exterminated in thermal drilling (TD) process. In the course of TD process, the high temperature was developed due to rotational and feed rate of thermal drill into the workpiece. Owing to this reason, the thermal drill pierces workpiece effortlessly. However, in this process, workpiece deformation is very high; therefore, finite-element simulation is used to study the material flow which is challenging in experimental method. According to finite-element method (FEM), the finite-element analysis of TD process was conducted by the DEFORM-3D simulation software. The aim of this study is to conduct an experimental investigation of TD process on galvanized steel (GS), and then, it is compared to numerical results obtained from the FEM. Between experimental and FEM simulation of TD process, a good relationship was found.

Modeling and Control of Bulk Material Flow on the Electromagnetic Vibratory Feeder

This paper presents the results of modeling, simulation and experimental research of the bulk material flow on the electromagnetic vibratory feeder (EVF). The model of the EVF was implemented in Simulink/Matlab and verified in the experimental research. It has been experimentally confirmed that the bulk material flow rate has its maximal value as far as excitation frequency is equal to the EVF mechanical resonant frequency. For certain bulk material flow rate, average value of excitation coil current of EVF has minimal value when named frequencies are equal. In addition to modeling of the EVF, the main contribution of this paper is implementation of flow control algorithm of bulk material on EVF, experimental verification of the adopted model and defines parameters that enable the selection of energy-efficient operating point of the EVF.

Simulation of Epoxy/Cloisite-15A Multifunctional Nanocomposites using Twin Screw Extruders

Simulation of material flow through kneading elements with different staggering angles for the processing of polymer nanocomposites is an emerging area of research. This research presents simulation of epoxy/Cloisite-15A nanocomposite processing in intermesh co-rotating twin screw extruder using Solidworks. Staggering angles of 15°, 30°, 45°, 60° and 90° and disc thickness (3 mm and 6 mm) were considered for the configuration of kneading elements for the simulation. Material flow rate of 1 kg/s was maintained constant for all the configurations with 2 % intensity of turbulence. Boundary conditions were applied at the inlet and front and rear sides of the screw. Staggering angle of 60° and disc thickness of 6 mm corresponded to high pressure and velocity. Uniform particle distribution and high shear rate were obtained in case of 60° staggering angle and 3 mm disc thickness.

Combining physical simulation and discrete-event material flow simulation

Manufacturing customized products leads to increased complexity within the material flows of a manufacturing system. Discrete-event material flow simulations are established models that help to cope with this complexity. A promising way to extend these models is their enhancement with the physical behavior of moving objects. Disturbances in the material flow, which were previously not covered by simulations, could be detected by considering physical effects like friction or acceleration. This paper determines the challenges and potentials of combining discrete-event material flow simulation and physical simulation. A conceptual approach is presented, using a material flow simulation based on an event-driven production control.

Automated Generation of Material Flow Network Models with Cluster Structures Using Random Walks

In spite of the increasing digitization in manufacturing systems, the amount of publicly available data is still low. Therefore, synthetic data are frequently used in material flow simulations. In this paper, we present a new approach to generate material flow networks based on random walks. Random walks are well suited to mimic the movement of a job through a manufacturing system. By altering the parameters of a random walk the material flow can be controlled. Our aim is to show how random walks can be used to generate material flow networks with varying cluster structures as one example.