Design of Controllable Batch Processes in the Presence of Uncertainty

Design of controllable batch processes can be more challenging than continuous processes because of their unsteady nature of operation. The operating strategy of a batch process is characterized by trajectories of manipulated variables. This precludes the use of conventional controllability measures in evaluating the controllability of a given batch process design. Short process development cycles typically accredited to batch processes lead to uncertainty in the model formulation. Integrated approach to batch process design and control addresses the problem of controllability of a batch process during the design phase. This is best achieved by treating the problem as a dynamic optimization problem with time invariant (design) and time variant (operating) variables. The method proposed in this paper uses the decomposition feature of Generalized Benders Decomposition (GBD) to evolve a 2-level nested optimization problem (primal and master), one involving time variant decision (operating) variables and the other involving time invariant decision (design) variables. To enhance the computational efficiency, a relaxed LP formulation of the master problem is proposed. This variant of GBD, termed as ExGBD, is guaranteed to converge to the optimum for convex problems. A simple batch reactor design problem has been chosen to demonstrate ExGBD.     

Simulation of a Hybrid-Forming Process using Temperature- and Rate-Dependent Viscoplastic Material Models

Hybrid-forming processes for graded structures are quite innovative methods for the production of components with tailored properties, particularly tailored material properties and geometrical shape. In this contribution a hybrid-forming process based on the utilization of locally varying thermo-mechanical effects is investigated [1]. For process optimization and improvement of the resulting work piece the simulation of the entire forming process is necessary in modern engineering. The main topics of this contribution are the simulation of the cyclic thermal loaded forming tool and the simulation of the work piece treated at large deformations with phase transformations. For both materials temperature- and rate-dependent viscoplastic material models are applied and parameter identification using cyclic tensile-compression tests for the forming tool material and phase transformation tests for a low-alloy steel similar to the work piece material is presented. For validation of finite-element-calculations for the forming tool thermal shock experiments are performed with optical deformation measurements. For validation of finite-element-calculations for the work piece numerical results of geometry and structure after heating, forming and cooling are compared to experimental micro sections. Results concerning the forming tool will be used for future lifetime prediction and results concerning the work piece will be used for future specific setting of graded material properties. (© 2009 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim)     

Numerical Comparison of Optimization Methods for Process Parameters Identification in Forming Technology

The SAND formulation known from structural and topology optimization is applied to a forming problem arising from certain technological forming processes. The SAND approach is compared to a well known and widely used method on a model problem within the scope of linear elasticity. (© 2014 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim)     

A comparison of a genetic algorithm with an experimental design technique in the optimization of a production process

This paper describes the optimization of a textile process by means of two differing approaches: the use of a genetic algorithm and the use of an experimental design technique. It considers the efficiency of each method in reaching the optimum and the nature of the information obtained regarding the process. Consideration is given to the success of the optimization and the transferability of the approaches to other industrial processes.     

Towards a finite element simulation of coating by means of thermal spraying

Metal sheet forming processes like deep drawing are applied in order to produce carriage parts in mass production. Therefore, forming tools are required that are well protected against wear. For such forming tools, wear resistant surfaces are, e.g., produced by thermal spraying of hard material coatings. The thermal spraying process itself is a highly transient thermo-mechanical process. In order to gain a better understanding of the heat input and transfer during thermal spraying, a simulation framework for thermal spraying processes is presented. (© 2015 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim)     

Performance analysis of distributed solution approaches in simulation-based optimization

Applying computationally expensive simulations in design or process optimization results in long-running solution processes even when using a state-of-the-art distributed algorithm and hardware. Within these simulation-based optimization problems the optimizer has to treat the simulation systems as black-boxes. The distributed solution of this kind of optimization problem demands efficient utilization of resources (i.e. processors) and evaluation of the solution quality. Analyzing the parallel performance is therefore an important task in the development of adequate distributed approaches taking into account the numerical algorithm, its implementation, and the used hardware architecture. In this paper, simulation-based optimization problems are characterized and a distributed solution algorithm is presented. Different performance analysis techniques (e.g. scalability analysis, computational complexity) are discussed and a new approach integrating parallel performance and solution quality is developed. This approach combines a priori and a posteriori techniques and can be applied in early stages of the solution process. The feasibility of the approach is demonstrated by applying it to three different classes of simulation-based optimization problems from groundwater management.     

Stochastic shape sensitivity in powder metallurgy processing

Stochastic shape sensitivity in forming process of powder metallurgy materials is analyzed. For this purpose the rigid-poroplastic material model has been assumed. The theoretical formulation for stochastic shape sensitivity is described which presents probabilistic distributions taking into account random initial and boundary conditions. The control volume approach is discussed. Stochastic finite element equations for rigid – poroplastic materials are solved for the first two probabilistic moments. Numerical simulations were performed to illustrate shape sensitivity problems in the process of compression of rigid-poroplastic cylinder. The differences in deterministic and stochastic sensitivities are presented. The results derived can be used for the subsequent quantitative stochastic shape design as well as stochastic shape optimization.     

Parameters optimization of selected casting processes using teaching–learning-based optimization algorithm

In the present work, mathematical models of three important casting processes are considered namely squeeze casting, continuous casting and die casting for the parameters optimization of respective processes. A recently developed advanced optimization algorithm named as teaching–learning-based optimization (TLBO) is used for the parameters optimization of these casting processes. Each process is described with a suitable example which involves respective process parameters. The mathematical model related to the squeeze casting is a multi-objective problem whereas the model related to the continuous casting is multi-objective multi-constrained problem and the problem related to the die casting is a single objective problem. The mathematical models which are considered in the present work were previously attempted by genetic algorithm and simulated annealing algorithms. However, attempt is made in the present work to minimize the computational efforts using the TLBO algorithm. Considerable improvements in results are obtained in all the cases and it is believed that a global optimum solution is achieved in the case of die casting process.     

Analysis of optimal metal flow in incremental sheet forming

Sheet metal forming processes are manufacturing processes in which a piece of sheet metal is shaped to a specified geometry, e.g. a car door. A promising new forming process is incremental sheet metal forming, in which the deformation is imposed by a progressive, localised plastic deformation induced by a pin-like forming tool that moves under numerical control along a pre-defined trajectory. This process offers the possibility to control the metal flow by adjusting the trajectory of the forming tool. Mathematically, sheet metal forming processes can be considered as a mapping between the initial, undeformed sheet metal and the final, deformed state. In most applications the surface area of the sheet metal is enlarged during the deformation. In this case, an ideal mapping would produce a homogeneous stretching of the sheet metal such that the final sheet thickness is the same everywhere. In this work, we analyze the following question: for each point in the initial configuration, what must be its location on the final geometry such that the thickness is the same everywhere? We construct a special type of surface evolution that combines flow along the surface normal with appropriate tangential velocity corrections, and show that the flow yields a constant sheet thinning on a sheet metal. (© 2013 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim)     

Reduced quasi-Newton method for simultaneous design and optimization

We consider the task of design optimization where the constraint is a state equation that can only be solved by a typically rather slowly converging fixed point solver. This process can be augmented by a corresponding adjoint solver and based on the resulting approximate reduced derivatives also an optimization iteration which actually changes the design. To coordinate the three iterative processes, we use an exact penalty function of doubly augmented Lagrangian type. The main issue here is how to derive a design space preconditioner for the approximated reduced gradient which ensures a consistent reduction of the employed penalty function as well as significant design corrections. Some numerical experiments for an alternating approach where any combination and sequencing of steps are used to improve feasibility and optimality done on a variant of the Bratu problem are presented.     

Deformation induced martensite transformation in a cold-worked forming process of austenitic stainless steel

Within the last years the goal of industrial manufacturing processes – such as tube forming – has shifted towards an optimization of technological as well as mechanical properties of the manufactured structures. For example, during the forming procedure of sheets made of austenitic stainless steel X5CrNi18-10, the content of strain-induced martensite needs to be controlled. In order to achieve optimal structural properties of the manufactured tube with respect to very high-cycle fatigue (VHCF), a martensite ratio of approximately 25% needs to be obtained [1]. On the basis of experimental investigations this contribution deals with the numerical simulation of the tube-forming process with special consideration of the martensite ratio c as a function of temperature and deformation field. For this purpose we extend an existing martensite model on polyaxial states of stress and compare experimental results and numerical simulations for the modified model. (© 2012 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim)     

Meso-Macro Modelling of Coated Forming Tools under Thermal Shock Conditions

In hybrid-forming processes workpieces are heated up before forming in order to reduce the forming forces. They are innovative methods for the production of components with graded properties, particularly with regard to tailored material properties and geometrical shape. During service life the forming tools are subjected to cyclic thermal shock loading conditions which can result into damage and failure. For improvement of the tool durability in the hybrid-forming process coated forming tools with multilayered coating systems are considered to be applied in future. This contribution shows the actual state of work for the development of a twoscale FE model for the simulation of the multilayered coated forming tool. Within this model the three-dimensional model of the forming tool builds the macromodel. On the macrolevel the multilayered coating is discretized with one element over the coating thickness. The mesomodel of the coating considers the actual layer design with metallic and ceramic layers. The macro-meso transition is realized with a Taylor-assumption. As the microscale is not considered in our model, the constitutive equations are formulated on the mesoscale. The meso-macro transition is done using volume averaging procedures. Furthermore, a damage model is included for particular layers. The scalar damage variable is used in a thermo-mechanical coupled model for simulation of a reduced heat transfer through a partially damaged layer. (© 2011 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim)     

Microstructure evolution during rolling and annealing of mild steels

The process chain for components made of sheet metals consists of different forming techniques like hot rolling, cold rolling, and deep drawing as well as heat treatment operations like annealing. For the design and optimization of the whole manufacturing process and the final component behavior, a correct representation of the material behavior and the application of appropriate numerical simulation techniques are required. For our first investigations, a ferritic mild steel DC04, which is a typical steel grade for automotive applications, is analyzed. Therefore, specimens are taken out of a real manufacturing process after hot and cold rolling and after annealing. These specimens are intensively investigated in order to study the texture evolution and the development of other material properties, like yield function during the process chain. In this paper different homogenization methods are used to simulate the texture evolution during cold rolling. The results are compared concerning accuracy and efficiency of the considered models. (© 2010 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim)     

Development of the parametric tolerance modeling and optimization schemes and cost-effective solutions

Most of previous research on tolerance optimization seeks the optimal tolerance allocation with process parameters such as fixed process mean and variance. This research, however, differs from the previous studies in two ways. First, an integrated optimization scheme is proposed to determine both the optimal settings of those process parameters and the optimal tolerance simultaneously which is called a parametric tolerance optimization problem in this paper. Second, most tolerance optimization models require rigorous optimization processes using numerical methods, since closed-form solutions are rarely found. This paper shows how the Lambert W function, which is often used in physics, can be applied efficiently to this parametric tolerance optimization problem. By using the Lambert W function, one can express the optimal solutions to the parametric tolerance optimization problem in a closed-form without resorting to numerical methods. For verification purposes, numerical examples for three cases are conducted and sensitivity analyses are performed.     

Comparing Optimization Algorithms for Shape Optimization of Extrusion Dies

The classical approach to extrusion die design relies heavily on the experience of the die designer; Especially the designer's ability to create an initial die design from a product design, the designer's constructional knowledge and performance during the running-in trials. Furthermore, the relative unpredictability of the running-in trials combined with the additional resource usage introduce uncertainties and delays in the time-to-market of a given product. To lower these delays and resource usage, extrusion die design can benefit greatly from numerical shape optimization. In this application, however, plastics melts pose a difficult obstacle, due to their rather unintuitive and nonlinear behavior. These properties complicate the numerical optimization process, which mimics running-in trials and relies on a minimal number of optimization iterations. As part of the Cluster of Excellence Integrative Production Technologies for High-Wage Countries at the RWTH Aachen University, an effort is made to shorten the manual running-in process by the means of numerical shape optimization. Using an in-house numerical shape optimization framework, a set of optimization algorithms, consisting of global, derivative-free and gradient-based optimizers, are evaluated with respect to the best die quality and a minimal number of optimization iterations. This evaluation is an important step on the way to include more computationally intensive material models into the optimization framework and identify the best possible optimization strategy for the numerical design of extrusion dies. (© 2014 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim)     

Development of an inverse isogeometric methodology and its application in sheet metal forming process

This paper proposes an inverse isogeometric analysis to estimate the blank and predict the strain distribution in sheet metal forming processes. In this study, the same NURBS basis functions are used for drawing a final part and analysis of the forming process. In other words, this approach requires only one modeling and analysis representation, in contrast to inverse FEM. This model deals with minimization of potential energy, deformation theory of plasticity, and infinitesimal deformation relations with considering a new non-uniform friction model. One advantage of the presented methodology is that the governing equations are solved in two-dimensional space without concerning about pre-estimation results. As a result, the convergence is guaranteed and the computation time decreases significantly which is important at the initial stages of design. Furthermore, by employing this model at the forming design stage, the effects of changing the final part geometry and material property can be simultaneously observed on the formability of the part. Moreover, the effects of isogeometric element size can be automatically studied on the solution accuracy. The capability of this method is demonstrated by presenting three examples including blank estimation of cylindrical cup, square box, and weld line movement in forming of tailor welded blanks. The results obtained by the presented model and those obtained by the forward FEM reveal reasonable accuracy with decreased computational costs.     

A novel heuristic approach to determine compromise management for end-of-life electronic products

The European Union directive of Waste Electrical and Electronic Equipment for recycling end-of-life (EOL) products has had a significant impact on global enterprises. Recent studies have shed light on optimization of the EOL process. In addition to identifying the most economical EOL process, identifying the EOL process with the smallest environmental load is equally important, and this is thus a bi-criteria optimization problem. This study attempts to optimize EOL processes for electronic products based on a three-stage heuristic approach, which simultaneously minimizes cost and environmental impact. The proposed heuristic approach then assesses the most common disassembly and recycling processes by using the characteristics of electronic product recycling. Next, the best process for this bi-criteria optimization problem is identified by using the compromise programming method. The empirical analysis is based on data for notebook, and the potential impact on best EOL processes when notebook adopt new product designs is also discussed.     

A study of design velocity field computation for shape optimal design

Design velocity field computation is an important step in computing shape design sensitivity coefficients and updating a finite element mesh in the shape design optimization process. Applying an inappropriate design velocity field for shape design sensitivity analysis and optimization will yield inaccurate sensitivity results or a distorted finite element mesh, and thus fail in achieving an optimal solution. In this paper, theoretical regularity and practical requirements of the design velocity field are discussed. The crucial step of using the design velocity field to update the finite element mesh in the design optimization process is emphasized. Available design velocity field computation methods in the literature are summarized and their applicability for shape design sensitivity analysis and optimization is discussed. Five examples are employed to discuss applicability of these methods. It was found that a combination of isoparametric mapping and boundary displacement methods is ideal for the design velocity field computation.