Integrated planning of transportation and recycling for multiple plants based on process simulation

By-products accrue in all stages of industrial production networks. Legal requirements, shortening of primary resources and their increasing prices make their recycling more and more important. For the re-integration into the economic cycle the scope of common supply chain management is enlarged and so-called closed-loop supply chains with adapted and new planning tasks are developed. In process industries this requires a detailed modelling of the recycling processes. This is of special relevance for operational planning tasks in which an optimal usage of a given production system is envisaged. This contribution presents an integrated planning approach for a real-world case study from the zinc industry to achieve such an adequate process modelling. We consider the planning problem of a company that operates four metallurgical recycling plants and has to allocate residues from different sources to these recycling sites. The allocation determines the raw material mix used in the plants. This blending has an effect on the transportation costs and the costs and revenues of the individual technical processes in the recycling plants. Therefore in this problem transportation and recycling planning for multiple sites have to be regarded in an integrated way. The necessary detailed process modelling is achieved by the use of a flowsheet process simulation system to model each recycling plant individually. The models are used to derive linear input–output functions by multiple linear regression analyses. These are used in an integrated planning model to calculate the decision-relevant input and output flows that are dependent upon the allocation of the residues to the recycling sites. The model is embedded in a decision support system for the operational use. An example application and sensitivity analyses demonstrate and validate the approach and its potentials. The approach is transferable to other recycling processes as well as to other processes in process industries.     

On modeling evaporation

We develop a theoretical model for evaporation of a pure liquid drop on a thermally conductive solid substrate. We discuss a variety of effects regarding evaporation regime, the state of the liquid/gas interface and the content of gas phase. Then, we further consider two models: the one resulting from the one-sided non-equilibrium assumption and the other that assumes diffusion-limited regime and equilibrium at the liquid/gas interface. A single governing equation for the evolution of drop thickness is derived for both models. We show that although the model predicts qualitatively different temperature along liquid/gas and liquid/solid interface, the dynamics of the drops is almost the same.      

Minimizing total earliness and tardiness on re-entrant batch processing machine with time windows

The time window (TW) generalizes the concept of due date. The semiconductor wafer fabrication system is currently one of the most complex production processes, which has typical re-entrant batch processing machine (RBPM). RBPM is a bottleneck. This paper addresses a scheduling of RBPM with job-dependent TWs. According to a general modelling, an improved and new job-family-oriented modelling of the decomposition method that is based on the slack mixed integer linear programming is proposed. First, the complicated scheduling problem of RBPM is divided into sub-problems, which are executed circularly. Then, each one consists of updating, sequencing and dispatching. The objective is to minimize the total earliness and tardiness for job-dependent TWs. In order to evaluate the proposed modelling, the experiments are implemented on the real-time scheduling simulation platform and optimization toolkit ILOG CPLEX. The results show that the improved modelling obtains better solutions in less computation time.     

Evaluation of the mathematical and economic basis for conversion processes in the LEAP energy-economy model

An evaluation was made of the mathematical and economic basis for conversion processes in the LEAP energy-economy model. Conversion processes are the main modelling subunit in LEAP used to represent energy conversion industries and are supposedly based on the classical economic theory of the firm. The study arose out of questions about the uniqueness and existence of LEAP solutions and their relation to classical equilibrium economic theory. An analysis of classical theory and LEAP model equations was made to determine their exact relationship. The conclusions drawn from this analysis were that LEAP theory is not consistent with the classical theory of the firm. Specifically, the capacity for factor formalism used by LEAP does not support a classical interpretation in terms of a technological production function for energy conversion processes. The economic implications of this inconsistency are suboptimal process operation and short term negative profits in years where plant operation should be terminated. A new capacity factor formalism, which retains the behavioural features of the original model, is proposed to resolve these discrepancies.     

Implementation of EOQ and Lambert W function in 1-D engine simulation model for optimizing fuel injection in GDI engine

The aim of this study was to implement Economic Order Quantity method (EOQ) together with the Lambert W function in a 1-D engine simulation model in order to develop a fuel control strategy for a Gasoline direct injection (GDI) engine. Previous work of the co-author demonstrated the possibility of optimizing fuel injection quantity in GDI engine using the EOQ that is commonly used in supply chain of perishable products. This work extends the previous work and implements it in a 1-D, crank angle resolved, engine simulation model for the application of model based calibration process. The present work uses a validated engine simulation model, which is based on predictive combustion modelling approach, and couples the 1-D engine simulation model with SIMULINK to add the evaporation, wall- wetting and heat transfer models. It employs FORTRAN subroutines to modify the internal code of the 1-D simulation software in order to add crank angle resolved evaporation model. Finally, EOQ with Lambert W function was added to the model using MATLAB with special attention to the decimal control for the solution. This study demonstrated that EOQ and Lambert W functions together are a suitable method to develop fuel control strategy for a model based calibration procedure when implemented in crank angle resolved 1-D simulation model.     

A non-Gaussian Ornstein–Uhlenbeck model for pricing wind power futures

The recent introduction of wind power futures written on the German wind power production index has brought with it new interesting challenges in terms of modelling and pricing. Some particularities of this product are the strong seasonal component embedded in the underlying, the fact that the wind index is bounded from both above and below and also that the futures are settled against a synthetically generated spot index. Here, we consider the non-Gaussian Ornstein–Uhlenbeck type processes proposed by Barndorff-Nielsen and Shephard in the context of modelling the wind power production index. We discuss the properties of the model and estimation of the model parameters. Further, the model allows for an analytical formula for pricing wind power futures. We provide an empirical study, where the model is calibrated to 37 years of German wind power production index that is synthetically generated assuming a constant level of installed capacity. Also, based on 1 year of observed prices for wind power futures with different delivery periods, we study the market price of risk. Generally, we find a negative risk premium whose magnitude decreases as the length of the delivery period increases. To further demonstrate the benefits of our proposed model, we address the pricing of European options written on wind power futures, which can be achieved through Fourier techniques.     

A novel repair model for imperfect maintenance

^** Email: shaomin.wu{at}reading.ac.uk Commonly used repair rate models for repairable systems in thereliability literature are renewal processes, generalised renewalprocesses or non-homogeneous Poisson processes. In additionto these models, geometric processes (GP) are studied occasionally.The GP, however, can only model systems with monotonously changing(increasing, decreasing or constant) failure intensities. Thispaper deals with the reliability modelling of failure processesfor repairable systems where the failure intensity shows a bathtub-typenon-monotonic behaviour. A new stochastic process, i.e. an extendedPoisson process, is introduced in this paper. Reliability indicesare presented, and the parameters of the new process are estimated.Experimental results on a data set demonstrate the validityof the new process.     

Lattice Boltzmann modeling of wall-bounded ternary fluid flows

Starting from the phase-field perspective, we first formulate a novel wetting boundary condition to describe the interactions among ternary fluids and a solid and then we propose a boundary scheme for its implementation in the framework of the lattice Boltzmann (LB) method. This scheme for three-phase fluids can preserve the reduction consistency property of the diphasic case such that it can give physically relevant results. Combining this wetting boundary scheme and the LB ternary fluid model based on multicomponent phase-field theory, we simulated several ternary fluid flow problems involving a solid substrate, including the spreading of binary drops on a substrate, the spreading of a compound drop on a substrate, the capillary intrusion of ternary fluids, and the shear of a compound liquid drop on a substrate. The numerical results are found to be good agreement with the analytical solutions and some available results. Finally, as an application, we use the LB model coupled with the present wetting boundary scheme to numerically investigate the impact of a compound drop on a solid circular cylinder. It is found that the dynamics of a compound drop can be remarkably influenced by the wettability of the solid surface and the dimensionless Weber number.     

Forecasting S-shaped diffusion processes via response modelling methodology

Diffusion processes abound in various areas of corporate activities, such as the time-dependent behaviour of cumulative demand of a new product, or the adoption rate of a technological innovation. In most cases, the proportion of the population that has adopted the new product by time t behaves like an S-shaped curve, which resembles the sigmoid curve typical to many known statistical distribution functions. This analogy has motivated the common use of the latter for forecasting purposes. Recently, a new methodology for empirical modelling has been developed, termed response modelling methodology (RMM). The error distribution of the RMM model has been shown to model well variously shaped distribution functions, and may therefore be adequate to forecast sigmoid-curve processes. In particular, RMM may be applied to forecast S-shaped diffusion processes. In this paper, forty-seven data sets, assembled from published sources by Meade and Islam, are used to compare the accuracy and the stability of RMM-generated forecasts, relative to current commonly applied models. Results show that in most comparisons RMM forecasts outperform those based on any individually selected distributional model.     

Exploring the model development process in discrete-event simulation: insights from six expert modellers

This paper explores the model development process in discrete-event simulation (DES) by reporting on an empirical study that follows six expert modellers while building simulation models. DES is a widely used modelling approach, however little is known about the modelling processes and methodology adopted by modellers in practice. Verbal Protocol Analysis is used to collect data, where the participants are asked to speak aloud while modelling. The results show that the expert modellers spend a significant amount of time on model coding, verification and validation, and data inputs. The modellers iterate often between modelling activities. Patterns of modelling behaviour are identified, suggesting that the modellers adopt distinct modelling styles. This study is useful in that it provides an empirical view of existing DES modelling practice, which in turn can inform existing research and simulation practice as well as teaching of DES modelling to novices.     

Relevance assumed: a case study of balanced scorecard development using system dynamics

The balanced scorecard (BSC) has become a popular concept for performance measurement. It focuses attention of management on only a few performance measures and bridges different functional areas as it includes both financial and non-financial measures. However, doubts frequently arise regarding the quality of the BSCs developed as well as the quality of the process in which this development takes place. This article describes a case study in which system dynamics (SD) modelling and simulation was used to overcome both kinds of problems. In a two-stage modelling process (qualitative causal loop diagramming followed by quantitative simulation), a BSC was developed for management of one organizational unit of a leading Dutch insurer. This research illustrates how, through their involvement in this development process, management came to understand that seemingly contradictory goals such as customer satisfaction, employee satisfaction and employee productivity were, in fact, better seen as mutually reinforcing. Also, analysis of the SD model showed how, contrary to ex ante management intuition, performance would first have to drop further before significant improvements could be realized. Finally, the quantitative modelling process also helped to evaluate several improvement initiatives that were under consideration at the time, proving some of them to have unclear benefits, others to be very promising indeed.     

On the modelling of nested risk-neutral stochastic processes with applications in insurance

We propose a modelling framework for risk-neutral stochastic processes nested in a real-world stochastic process. The framework is important for insurers that deal with the valuation of embedded options and in particular at future points in time. We make use of the class of State Space Hidden Markov models for modelling the joint behaviour of the parameters of a risk-neutral model and the dynamics of option market instruments. This modelling concept enables us to perform non-linear estimation, forecasting and robust calibration. The proposed method is applied to the Heston model for which we find highly satisfactory results. We use the estimated Heston model to compute the required capital of an insurance company under Solvency II and we find large differences compared to a basic calibration method.     

An embedding method for simulation of immobilized enzyme kinetics and transport in sessile hydrogel drops

A newly-developed embedding method for simulating enzyme kinetics and transport occurring within axisymmetric 3D domains is presented. The physical problem is pertinent to gel-pad microarrays for assessment of enzymatic activity. An enzyme is immobilized uniformly within a hydrogel which is spotted onto a solid surface in the form of a sessile drop, taking on a spherical cap shape. An aqueous solution containing substrate flows slowly past the porous drop. The substrate diffuses into the drop and is converted to product with the help of the enzyme. The product accumulates in and diffuses out of the drop and is taken away by the flow. Spatiotemporal distribution of the product, monitored via fluorescence, can be used to quantify the enzyme kinetics. This process is described by a system of nonlinear reaction-diffusion partial differential equations, modeling the diffusive transport and enzymatic reaction. The computational domain contains both the hydrogel drop and the bulk fluid phases. The embedding method is a computational technique that enables the use of finite differences on a regular Cartesian grid for simulation of multiphase problems with complex interfaces/boundaries. It uses a volume-fraction-based approach, similar to the volume-of-fluid (VOF) method, to implement the boundary conditions that must be applied at the interface between the phases. The main advantage of the embedding method is its simplicity, which results in code generation that can be highly optimized. In the present work, we apply the embedding method to the aforementioned two-phase reaction-diffusion problem and validate the results by comparing to a number of exact solutions available in simpler geometries and to results obtained using a finite-volume method on an unstructured body-fitted mesh. (© 2008 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim)     

An anisotropic enhanced thermal conductivity approach for modelling laser melt pools for Ni-base super alloys

Ni-base super alloys are extensively used in high temperature gas turbine engines and energy industries. Due to the high replacement costs of these components, there are huge economic benefits of repairing these components. Laser direct metal deposition processes (LDMD) based on laser cladding, laser fusion welding, and laser surface melting are some of the processes which are used to repair these high value components. Precise control of these processes is important to achieve the desired microstructure, stress distribution, distortions due to thermal stresses and other important output variables. Modelling of these processes is therefore an extremely important activity for achieving any degree of control/optimisation. However, modelling of these processes is not straight-forward due to melt pool flows dominated by Marangoni and buoyancy driven convection. Detailed CFD models are required for accurate prediction of melt pool geometry. But these models are computationally expensive and require greater expertise. To simplify and speed up the modelling process, many researchers have used the isotropic enhanced thermal conductivity approach to account for melt pool convection. A recent study on mild steel has highlighted that isotropic enhanced thermal conductivity approach is not able to accurately predict the melt pool geometry. Based on these findings a new approach namely anisotropic enhanced thermal conductivity approach has been developed. This paper presents an analysis on the effectiveness of the isotropic and anisotropic enhanced thermal conductivity approaches for laser melting of Inconel 718 using numerical technique. Experimental melt pool geometry has been compared with modelling results. It has been found that the isotropic enhanced thermal conductivity approach is not able to accurately predict the melt pool geometry, whereas anisotropic enhanced thermal conductivity approach gives good agreement with the experimental results.     

Histogram based bounds and approximations for production lines

We present a modelling method for the analysis of production lines with generally distributed processing times and finite buffers. We consider the complete modelling process, from the data collection to the performance evaluation. First, the data about the processing times is supposed to be collected in the form of histograms. Second, tractable discrete phase-type distributions are built. Third, the evolution of the production line is described by a Markov chain, using a state model.     

Development and application of multiscale models of acute viral infections in intervention research

The objective of this study is to advance two frontiers in multiscale modelling of acute viral infections, which are (a) the mathematical technology or technical frontier, where we present a new method for development of multiscale models of acute viral infections using influenza A virus (IAV) as a paradigm in which a new set of metrics to measure both individual level and community level infectiousness are introduced, and (b) the scientific applications frontier, where we demonstrate the implementation of multiscale modelling in evaluating the comparative effectiveness of IAV health interventions from efficacy data. The multiscale model is developed by integrating the within-host scale and the between-host scale. Using the example of IAV as a paradigm, we demonstrate the utility and process by which multiscale modelling can be used to evaluate the comparative effectiveness of health interventions that operate at different scale domains. The multiscale modelling is general enough to be applicable to other acute viral infections.     

Regularized Adaptation of Fuzzy Inference Systems. Modelling the Opinion of a Medical Expert about Physical Fitness: An Application

This study presents a new approach to adaptation of Sugeno type fuzzy inference systems using regularization, since regularization improves the robustness of standard parameter estimation algorithms leading to stable fuzzy approximation. The proposed method can be used for modelling, identification and control of physical processes. A recursive method for on-line identification of fuzzy parameters employing Tikhonov regularization is suggested. The power of approach was shown by applying it to the modelling, identification, and adaptive control problems of dynamic processes. The proposed approach was used for modelling of human-decisions (experience) with a fuzzy inference system and for the fuzzy approximation of physical fitness with real world medical data.     

稠油油藏高温盐析调剖的孔渗表征方法研究

深层高温油藏在开采过程中,由于近井地带压力变化剧烈,地层水蒸发致使结晶盐析出,进而导致储层孔隙度、渗透率降低.为研究稠油油藏高温盐析调剖的孔渗变化规律,根据盐类溶解/沉淀原理及储层孔隙度渗透率关系和填砂管模型高温盐析实验结果,建立了考虑地层水蒸发、水中氯化钠析出和储层孔渗变化的综合盐析模型.研究结果表明:随着堵剂注入量增加,封堵率快速上升并趋于稳定;实验温度在200~500℃之间氯化钠堵剂具有较好的封堵效果;盐析调堵方法可以有效封堵储层气窜通道,改良吸气剖面,提高周期采油量.最后用实验结果对数学模型进行拟合修正,得到稠油油藏高温盐析调剖的孔渗表征方法.     

Application of PID Control Unit for System Stabilization in Process-integrated Powder Coating by Radial Axial Rolling of Rings

The process integrated powder coating by radial axial rolling of rings represents a new hybrid production technique in order to apply the functional layers on ring-shaped work pieces. Since the layer is produced in a powder metallurgical way [1], the ring volume decreases during the compaction of the layer material. In conventional ring rolling processes an isochoric plastic deformation of the ring is exploited in order to control the process. However this is not true any more for a ring exhibiting a compressible layer [2]. Consequently different control mechanisms have to be developed for the new considered process. One major aspect is the stability of the process which is governed by a stable position of the ring as well as the roundness of the ring. Therefore the finite element (FE) model has been coupled with a PID-controller unit and it will be shown that a stable process can be reached in this way. (© 2011 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim)