Microstructure-sensitive notch root analysis for dwell fatigue in Ni-base superalloys

Macroscopic viscoplastic constitutive models for γ–γ′ Ni-base superalloys typically do not contain an explicit dependence on the underlying microstructure. Microstructure-sensitive models are of interest in many applications since microstructure can vary in components, whether intentional or not. In such cases, the use of experiments from one microstructure condition to fit macroscopic models may be too limiting. The principal microstructure attributes that can significantly affect the cyclic stress–strain response of γ–γ′ Ni-base superalloys are the grain size and γ′ precipitate volume fraction and size distributions. An artificial neural network (ANN) is used to correlate the material parameters of a macroscale internal state variable cyclic viscoplasticity model with these microstructure attributes using a combination of limited experiments augmented by polycrystal plasticity calculations performed on other (virtual) microstructures within the range characterized experimentally. The trained model is applied to an example of a component fatigue notch root analysis with dwell periods at peak load to demonstrate the methodology and explore the potential impact of microstructure-sensitive constitutive models on life prediction for notched structures subjected to realistic load histories.     

Mass customization design of engineer-to-order products using Benders’ decomposition and bi-level stochastic programming

Leveraging product differentiation and mass production efficiency in mass customization basically entails a configure-to-order paradigm. In the engineer-to-order (ETO) business, however, companies build unique products in response to ‘foreseeable’ customer specifications. The key challenge of ETO mass customization lies in the complexity of accommodating future design changes when customers are involved in customizing design specifications. This paper proposes a two-stage, bi-level stochastic programming framework to tackle ETO mass customization. At the first stage, product platform configuration is integrated with production reconfiguration, which is formulated as a shortest path problem with resource constraints (SPPRC) to optimize production delays within the capabilities of the process platform. Benders’ decomposition algorithm is applied to solve this optimal configuration problem owing to its high computational efficiency. The second stage scrutinizes the optimal configuration resulting from the first stage for scaling optimization of design parameters (DPs) for each module. All DPs are differentiated by standard or customizable DPs. A bi-level stochastic program is implemented to leverage conflicting goals between the producer (leader) and consumer (follower) surpluses. As a result, ETO customization design is anchored with optimal values of standard DPs and optimal value ranges of customizable DPs. A case study of ship engine and power generator ETO design is presented, demonstrating the feasibility and potential of the ETO mass customization framework.     

Effect of blade-tip shape on the doctoring step in gravure printing processes

A fundamental limit to the gravure printing process is in the doctoring step, in which a residual film defines the lower bound on allowable feature size. The resolution of finer features requires thin residual films, but these thin films increase the likelihood of wearing the doctor blades. A computational model was used to study the effect of blade-tip shape on residual film thickness while also minimizing the likelihood of wear. The blade-tip shape is altered by varying the bevel angles and the predicted film thickness is computed under various wiping speeds, configurations, and applied forces. In all cases studied, a slower wiping speed resulted in a thinner residual film, which is due to the doctoring step being governed by elastohydrodynamic lubrication. In some cases, a reversal of the wiping configuration created a thinner film, but it had no impact on the likelihood of wearing. Higher applied force leads to thinner residual film but the blade shape can have a more significant influence, indicating that lubrication forces dominate at this scale. Lastly, the likelihood of blade wear was predicted to vary within a small range for a fixed blade-tip shape over all conditions studied, which suggests that tip shape is the primary factor to consider when minimizing blade wear.     

An integration of assembly planning by design into supply chain planning

A supply chain needs to consider the quality of a product as well as the quality of manufacturing process to satisfy customer requirements at efficient resources planning in terms of safety stock allocation and vendor–buyer coordination. The objective of this article is to use an axiomatic approach to make assembly planning by designing and integrating assembly into supply chain planning, particularly during supply chain reconfiguration. The effect of fixture layout planning, the accuracy of demand forecast, and the supplier capability of providing the required material quality are studied. An optimum supply chain network is configured by combining the product, assembly, and supply chain planning. Heuristic-based optimization is used to validate the proposed solution. The performance of the system is measured in terms of lead time variability, the number of backorders, and the level of safety stock. The results and analysis indicate that the axiomatic approach is capable of reducing the assembly variation and employing necessary fixture layout planning to deliver product intents. In addition, the reduction of assembly variation also reduces the safety stock, lead time variability, and backorders. Finally, management decision making is discussed among other concluding remarks.     

Viscocapillary model of slide coating: Effect of operating parameters and range of validity

Slide coating is one of the premetered high‐precision coating methods. The layer thickness is set by the flow rate and web speed. The uniformity of the layer, however, can be affected by other operating conditions. Modeling the flow in the coating bead is necessary in developing the range of operability conditions where the layer is adequately uniform. Lubrication and viscocapillary models have been used to describe the flow and some of the operability limits of different coating processes. However, the available models of slide coating were developed with adhoc hypotheses that compromise their accuracy. We present a critical review of the available viscocapillary models and proposed changes to improve its range of applicability. The accuracy of the model is tested by comparing its predictions to the solution of the full two‐dimensional Navier‐Stokes equation. The model is valid at low capillary and Reynolds number regime and at low gap‐to‐wet thickness ratio. © 2009 American Institute of Chemical Engineers AIChE J, 2009     

Operability limits of slide coating

Slide coating is one of the pre-metered methods used for high precision single and multilayer coatings. The thickness of each liquid layers is set by the flow rate and web speed only and it is independent of other process parameters. The uniformity of the deposited layer, however, is affected by the operating conditions. In the design of coating processes, it is crucial to know the set of conditions at which the deposited layer is adequately uniform, i.e. to define the operability window of the process. We developed a theoretical model of slide coating flow by solving the full two-dimensional Navier–Stokes equations and used it to uncover the mechanisms of coating bead breakdown at low vacuum, high vacuum, and low flow limits. With full understanding of the bead breakup processes, we then constructed a theoretical coating window as a function of coating thickness, web speed, and applied vacuum. A simple stability criterion was used to predict the onset of ribbing instability and deployed to add the onset of ribbing limit inside the coating window.     

Mechanics of the low-flow limit in slot-die coating with no vacuum

Slot-die coating is a premetered, film-deposition process compatible with a wide range of materials. Of topical interest to precision electronics applications is the deposition of high-cost nanomaterial dispersions over moderately sized (>10 cm² ) areas with submicron wet film thickness. In this work, a two-dimensional (2D) model has been developed to understand the limits of the process and to predict the thinnest possible film achievable. Coined the low-flow limit, this parametric operating boundary presents the minimum uniform, defect-free film achievable at a given set of liquid properties and die/substrate geometry. We investigate the low-flow limit with a model that allows menisci to locate anywhere on the die lands, faces, and substrates with prescribed contact angles, thereby minimizing the assumptions on the bead configuration. The model is validated via comparison of its low-flow limit predictions to published experimental data. Analysis yields insights into the mechanics of coating bead breakdown at the low-flow limit.     

Cerium chloride-assisted subcritical water carbonization for fabrication of high-performance cathodes for lithium-ion capacitors

Journal of Applied Electrochemistry - Lithium-ion capacitors are considered highly promising as a hybrid-type energy storage system and are suitable for large-scale energy storage applications...     

Logical reconfiguration of reconfigurable manufacturing systems with stream of variations modelling: a stochastic two-stage programming and shortest path model

Designing flexible manufacturing systems in general, and flexible material handling system in particular, is a complex problem, typically approached through several stages. Here the focus is on the conceptual design stage during which valid approximation-based methods are needed. The segmented flow topology (SFT) AGV systems were developed to facilitate control of complex automated material handling systems. This paper introduces a decomposition method, directly derived from timed Petri nets (TPN) theories, to calculate the expected utilization of AGVs (as servers of SFT systems) and to derive simple operational decision rules leading to maximum system productivity at steady state, for a given deterministic routeing of discrete material through the manufacturing system.     

Experimental and computational design tools for industrial drying processes: Challenges in process-limit prediction

The coating and drying of inks and slurries are important steps to manufacture a plethora of products. Drying processes, particularly, comprise energy-intensive steps that affect product cost and quality. Prior work has highlighted failures of various multicomponent diffusivity models to conserve mass in dryer modeling and challenges in predicting process limits given variability in published values of key thermodynamic parameters. Herein, we develop a computational model and benchtop drying experiments to investigate these concerns for drying polymer-laden coatings. Model predictions of process limits in a single-zone drying oven demonstrate that published variability in Flory–Huggins parameter yields large variations in predicted operating temperatures above which blistering occurs. This indicates that caution should be exercised when choosing approaches to obtain or predict the Flory–Huggins parameter, and that both benchtop drying experiments and a set of additional experiments, such as sorption experiments, are needed to fully characterize and optimize a given drying process.