Robust Design Concept Research Articles

Mathematical modeling and design for six sigma

The mathematical modeling (computational fluid dynamics) has been combined with Six Sigma methodology to guide the design of a Range. The concept of Transfer Function development and Robust Design has been explained. A few sample examples including Laser Surface Heating have been included in the context of Transfer Function and Design for Six Sigma. The concept of Lean and its integration with Six Sigma is briefly covered.

6σ robust and optimal design of micro-motion platform based on kriging model

The two performance indexes of output displacement and inherent frequency are closely related to the design variables of the micro-motion platform. To address the problem that the design variables have certain fluctuations and the high nonlinearity between the design variables and the performance of the micro-motion platform, a multi-objective robust optimization method with high computational efficiency and high fitting accuracy is proposed. Based on the kriging agent model, the high-precision approximate functions of the key design variables with the output displacement and the inherent frequency are established by the Latin hypercube experimental design, respectively. With the maximum stress as the constraint, Monte Carlo simulation, 6σ robust design concept, and nondominated sorting genetic algorithm II (NSGA-II) multi-objective genetic algorithm are integrated to optimize the structure of the micro-motorized platform. The results show that compared with the traditional deterministic optimization method, the 6σ robust design considering parameter uncertainty effectively reduces the fluctuation of the performance of the micromotion platform and improves the resistance of the platform performance to disturbance under uncertainty.

Robust design of monopiles for offshore wind turbines considering uncertainties in dynamic loads and soil parameters

Complex marine environment causes significant variations in the dynamic loads and soil parameters that affect the design of a monopile. Despite these uncertainties, a multi-objective optimization technique is developed to produce the optimal designs. This optimization is based on the robust design concept, in which the design robustness, cost, and safety are considered as the optimal objectives. The responses of a monopile to arbitrary dynamic loads are initially determined using a transient finite element technique, which considers unknown soil parameters. These responses include the maximum rotation and displacement at the midline, maximum axial stress, and fatigue damage. Next, the variations (regarding standard deviations) in these responses, which are determined by the Monte–Carlo simulations, are adopted to define the design robustness. Finally, the cost and safety requirements of the monopile are evaluated, and robust design optimization is performed. The aforementioned robust design protocols are demonstrated with a 5 MW offshore wind turbine, which produces the optimal design. Therefore, the optimal designs for the monopile are investigated based on various safety requirements. Moreover, the design parameters that promote the design robustness with optimum efficiency are studied and proposed.

A new tool and workflow for the simulation of the non-image forming effects of light

Other than supporting vision, light plays an important role in regulating human circadian rhythms through its non-image-forming (NIF) effects. Simulating potential NIF stimulation from daylight indoors, however, is a challenging task, requiring the continuous evaluation of luminous exposures at the eye, which are affected by changing sky's spectral power distributions at a location, time of day and year, and estimation of the sky patches’ contributions at a viewing position, which dynamically vary through a space. Existing multi-channel NIF simulations tools use measured or pre-computed spectral sky data. Yet, these are difficult to obtain with flexible spatio-temporal resolution. To address this challenge, and dynamically estimate a range of NIF metrics, we developed a tool and workflow based on 17 original Python-scripted Grasshopper components. This paper illustrates the design and development of the tool and workflow, also presenting an example of practical application to evaluate the yearly variations of potential NIF stimulation from an interior position or under an unobstructed sky. This is the first step to propose more robust building design and modelling concepts, beyond conventional visual comfort issues, and to adequately balance lighting energy use with occupants’ comprehensive needs, while connecting daylighting and electric lighting systems and controls within integrated solutions.

Design of experiments analysis of fundamental frequency of laminated composite hypar shells with cut-out

The effect of lamination angle (A), width-to-thickness ratio (B), cut-out location along x-direction (C) and cut-out location along y direction (D) on fundamental frequency of hypar shells made of laminated composites is considered using Taguchi robust design concept. Finite element analysis is done to obtain fundamental frequency of the structure for different parametric variation. Three levels of each parameter are considered to form L27 orthogonal array in order to maximize fundamental frequency. Main effect plot identifies the significant parameters. Optimal condition for maximum fundamental frequency is obtained as 45° lamination angle, width-to-thickness ratio of 20, cut-out location along x-direction 0.4 and along y-direction 0.3 (A2B1C3D2). Interaction plots locate the interaction effects between selected parameters. Analysis of Variance study evaluates the significant parameters and their contribution on output, i.e., fundamental frequency. Current investigation reveals, width-to-thickness ratio of shell is the most significant factor while lamination angle and cut-out location have little significance. Among the interacting parameters, interaction between lamination angle & cut-out location (A × C) and interaction between width-to-thickness ratio & cut-out location (B × C) have some significance. Width-to-thickness ratio (B) has 96.76% contribution while lamination angle (A) and cutout locations (C & D) and interactions have low contribution. Residual plots for fundamental frequency are considered and confirmation test validates the present analysis. S/N ratio is found to improve by 12.43% compared to the initial condition.

Design of experiment analysis of elevated temperature wear of Mg-WC nano-composites

Current study explores the effect of selected process parameters i.e. wt.% of reinforcement (A), elevated temperature (B) and load (C) on wear characteristics of Mg-WC nanocomposites using Taguchi robust design concept. Ultrasonic treated stir casting is employed to synthesize nanocomposites. Three levels for every factor are taken into consideration and accordingly L27 orthogonal array (OA) is used for minimization of wear rate. Main effect plot is generated to investigate the important parameters and optimality is also predicted from the main effect plot. Optimal condition for minimum wear rate is 2wt.% of WC, 100°C temperature and 20N load (A3B1C1). Interaction plots are generated to scrutinize the interaction outcome between selected parameters. ANOVA study is executed to evaluate significant parameters and their effective handout on output. Current investigation reveals, Wt.% of WC is the most significant factor while temperature and load are moderately significant. Among the interacting parameters, interaction between wt.% of WC & temperature (A×B) has moderate significance. Wt.% of WC (A) has 43.135% contribution while temperature (B), load (C) and interaction between wt.% of WC & temperature (A×B) have 26.623%, 19.037% and 5.639% contribution respectively. Residual plots for wear rate are discussed and confirmation test finally helps to validate present experimental model. S/N ratio is improved by 4.411 dB (48.60%) than the initial condition.

(Invited) Incorporation of Bulk Proton Carriers in Manganese Perovskites Triggered By Charge Disproportionation between Metal and Oxygen Atoms

Protonic ceramic cells (PCCs), including fuel cells and electrolysis cells, are based on protonic conducting Ba(Zr, Ce)O3 electrolytes, and have more advantages at operating temperatures below 600 °C than solid oxide cells (SOCs) based on a oxide ion conducting Y-ZrO2 because the activation energy required for proton conduction (0.3–0.6 eV) is lower than that required for oxide ion conduction (0.8 eV), which is key to lowering fuel cell costs and extending lifetimes. One major issue of protonic cells is a lack of suitable air electrodes that promote the association of protons and oxide ions via oxygen evolution reaction (OER) / oxygen reduction reaction (ORR). Cobaltite-based cathodes, such as (Sm,Sr)CoO3, (Ba, Sr)(Co,Fe)O3, and (La,Sr)(Co,Fe)O3 are typical oxide ion conductors; there is a mismatch of main ionic carriers between the air electrodes and the electrolyte, which limits the efficient area for air electrodes’ reaction to the electrode–electrolyte–gas triple phase boundaries (TPB). Therefore, it is urgent task to develop electrode materials that exhibit H+/e-/O2- triple conduction to extend the efficient reaction zones beyond the TPB and thus reduce the air electrodes’ overpotentials and improve electrochemical performances for PCCs. The transition metal oxides which is capable of hydration at relatively high temperatures must be promising candidate. Nevertheless, robust design concepts for MPECs, namely, transition metal oxides realizing enhanced bulk hydration ability at intermediate temperatures are still missing. Therefore, it is of both fundamental and technological importance to come up with a key ‘descriptor’ to enhance the proton uptakes of electron-conducting metal oxides. Although La1-x Sr x MnO3 (LSM) is a well-known cathode material for SOFCs and recognized as a good oxide ion electron mixed conductor at elevated temperature, it has not been subject to a proton conducting material. Herein, we report pronounced hydration ability of cubic perovskite type La0.7Sr0.3MnO3- δ in air conditions attributed to the association of water and oxygen vacancies mediated by Mn oxidation, and subsequent proton attachment to oxygen neighbors in exchange for oxygen hole carriers [1,2]. Hence La0.7Sr0.3MnO3- δ is capable of up-taking bulk proton carriers in wet air with the proton contents equaling to that of well-known protonic electrolyte material Ba(Zr,Y)O3 at the intermediate temperature (IT) region.

Supramolecular Networks: Helical Networks of π‐Conjugated Rods – A Robust Design Concept for Bicontinuous Cubic Liquid Crystalline Phases with Achiral Ia3¯d and Chiral I23 Lattice (Adv. Funct. Mater. 45/2020)

In article number 2004353, Goran Ungar, Carsten Tschierske, and co-workers present a general design concept of bicontinuous cubic liquid crystals consisting of helical networks that are stable over a broad temperature range. Increasingly bulky substituents cause increasing helical twist between the three-chain 2,2′-bithiophene based molecular rods, resulting in a sequence of three distinct phases: two ranges of achiral double network (Ia 3 ¯ d) separated by a range of spontaneously chiral triple network (I23).

A Robust and Efficient Method of Designing Piles for Landslide Stabilization

ABSTRACT Stabilizing pile is a widely used method to reduce the development of large-scale landslides. Optimizing the pile geometry is a great challenge in the design of stabilizing piles with the purpose of cost-effectiveness, especially for soil strength parameters with large uncertainty. The objective of this study is to propose a robust and efficient method of designing piles for landslide stabilization with the consideration of the safety of slope, uncertainty of soil parameters, and cost of stabilizing piles. A new response surface, which incorporates soil parameters and stabilizing force into a quadratic polynomial function, is first proposed. Unknown coefficients of the quadratic polynomial function are solved with a numerical method at typical sampling points. Based on the solved quadratic polynomial function, the mean and standard deviation of factor of safety (FOS) of the pile-stabilized slope as well as the signal-to-noise factor are then calculated in order to evaluate the design robustness. A framework based on the concept of robust geotechnical design is presented, and its feasibility is illustrated by two cases of soil slopes. The results indicate that the proposed robust geotechnical design method could be used to optimize the design of landslide-stabilizing piles.

Helical Networks of π‐Conjugated Rods – A Robust Design Concept for Bicontinuous Cubic Liquid Crystalline Phases with Achiral Ia3¯d and Chiral I23 Lattice

AbstractBicontinuous cubic liquid crystalline phases of π‐conjugated molecules, representing self‐assembled 3D‐ordered interpenetrating networks with cubic symmetry, are receiving increasing attention due to their capacity for charge transport in all three dimensions and their inherent spontaneous helicity. Herein, a robust general design concept for creating bicontinuous cubic phases is reported. It is based on a nonsymmetric‐substituted π‐conjugated 5,5′‐diphenyl‐2,2′‐bithiophene platform with one end containing three out‐fanning flexible chains and with a range of substituents at the other end (the apex). The cubic phases are stable over broad temperature ranges, often down to ambient temperature, and tolerate a wide range of apex substitution patterns, allowing structural diversity and tailoring of the cubic phase type and application‐relevant properties. With an increasing number and size of apex substituents, a sequence of three different modes of cubic self‐assembly is observed, following an increasing helical twist. Thus, two ranges of the achiral double network Iad phase range can be distinguished, a long pitch and a short pitch, with the chiral triple network I23 cubic phase in the intermediate pitch range. The findings provide a new prospect for the directed design of cubic phase‐forming functional materials based on spontaneously formed helical network liquid crystals with tunable application specific properties.

Use of Taguchi Robust Design to Optimize Rubber Glove Process

In this paper, Taguchi concept of robust process design and the classical statistical experimental design methodology are integrated for improving both the product quality and efficiency. It is a systematic method of optimizing a production process, and is concerned with productivity enhancement and cost effectiveness. The aim of this study is to investigate the effect of the inputs on the outputs in the presence of a noise factor and also to choose the best level settings of the control factors that will maximize the mean and minimize the variation in the glove's quality characteristics at minimal cost. The quality characteristic of the rubber glove that is considered in this study was the tensile strength. Taguchi L16, the orthogonal array is employed to run the experiments. The analysis of variance (ANOVA) and the signal-to-noise (S/N) ratio were performed. The BG interaction was identified as the important mean effect. However, factor (B), the latex temperature was not affected by factor (G), oven temperature after coagulation dip when it was at high but enhanced the strength when both were set at low. Factor (A), curing temperature profile affected both the mean and the process variability. The effect of humidity (H) appeared insignificant using ANOVA, but was significant in S/N ratio for the mean tensile strength. The preferred optimal setting were: A 2 B 1 C 1 D 1 F 2 H 1 G 1.

Optimal design of stone columns reinforced soft clay foundation considering design robustness

Stone columns are widely used to treat soft clay ground. Optimizing the design of stone columns based on cost-effectiveness is always an attractive subject in the practice of ground treatment. In this paper, the design of stone columns is optimized using the concept of robust geotechnical design. Standard deviation of failure probability, which is a system response of concern of the stone column-reinforced foundation, is used as a measure of the design robustness due to the uncertainty in the coefficient of variation (COV) of the noise factors in practice. The failure probability of a stone column-reinforced foundation can be readily determined using Monte Carlo simulation (MCS) based on the settlements of the stone column-reinforced foundation, which are evaluated by a deterministic method. A framework based on the concept of robust geotechnical design is proposed for determining the most preferred design of stone columns considering multiple objectives including safety, cost and design robustness. This framework is illustrated with an example, a stone column-reinforced foundation under embankment loading. Based on the outcome of this study, the most preferred design of stone columns is obtained.

Fatigue life estimation for the robust design of truck radiator

The growing truck industry, results in larger fleet of trucks serving various transportation needs of the society. On the flip side, the increased sale of vehicles causes environmental pollution affecting the fragile ozone layer. Government and regulatory bodies across the globe enforced tough emission measures to curb the menace. The tougher emission norms translate into design challenges for the truck OEM’s to design lightweight and complex radiator to meet higher operating pressure and durability cycle targets within a tight packaging vehicle space. Robust radiator design is the need of the hour to address the design challenge. A robust design approach coupled with traditional nominal analysis is proposed to determine robust radiator design insensitive to variations. Fatigue Assessment also included in the approach. Nominal design analysis shows that nominal deformation and stress response has 49% reliability and 51% unreliability, which indicates that nominal design does not factor in the variations occurring due to assembly, raw material and manufacturing process. The proposed robust approach identifies robust radiator designs less sensitive to uncertainty and shows 95% reliability. Robust design has 5x higher pressure cycle life as compared against the nominal design. The robust design concept having higher reliability and less sensitive to variations are identified. The approach highlights that robust design has higher pressure cycle durability as compared against the nominal radiator design. Better fatigue life estimation is obtained by using pressure cycle test results.

Adopting hybridized multicriteria decision model as a decision tool in engineering design

PurposeThe purpose of this paper is to determine the suitability of adopting hybridized multicriteria decision-making models as a decision tool in engineering design. This decision tool will assist design engineers and manufacturers to determine a robust design concept before simulation and manufacturing while all the design features and sub features would have been identified during the decision-making process.Design/methodology/approachFuzzy analytical hierarchy process (FAHP) and fuzzy technique for order preference by similarity to ideal solution (FTOPSIS) are hybridized and applied to obtain optimal design of a reconfigurable assembly fixture (RAF) from a set of alternative design concepts. Design features and sub features associated with the RAF are identified and compared using fuzzified pairwise comparison matrices to obtain weights of their relative importance in the optimal design. The FAHP obtained the fuzzy synthetic extent (FSE) values of the design features and sub features. The FSE values are used as weights of the design features and sub features in generating the decision matrix. FTOPSIS and FTOPSIS based on left and right scores were adopted to predict effects of the weights. Results were obtained for normalized and unnormalized weights of the design features and its effects on the relative closeness coefficients of the design alternatives.FindingsThe improved performance of the FTOPSIS based on left and right scores is due to the involvement of the left and right scores of weights of the design features in the computation of distances from positive and negative ideal solutions. Embedding the weights of the design features in the normalized decision matrix before estimating the distances of the design concepts from ideal solutions reduces the dependency of the closeness coefficients on the weights of the design features. This also decreases the difference in the final values of the design concepts. In essence, the weights of the design features have an impact in the closeness coefficient. There is reduction in the closeness coefficients of the design concepts due to normalization of the weights of the design features. However, normalizing the weights of the design features did not affect the variations in the final values of the design concept. As the final value of the design concepts can be influenced by the normalized weights of the design features, it can be implied that normalization of weights of the sub features will also affect the decision matrix. The study has been able to proof that hybridizing FAHP and FTOPSIS can produce effective results for decisions on optimal design by the application of FTOPSIS based on left and right scores rather than the general FTOPSIS.Originality/valueThis research develops a hybridized multicriteria decision-making model for decision-making in engineering design. It presents a detailed extension of hybridized FAHP and FTOPSIS based on left and right scores as a useful tool for considering the relative importance of design features and sub features in optimal design selection.

Towards climate robust buildings: An innovative method for designing buildings with robust energy performance under climate change

Neglecting extremes and designing buildings for the past or most likely weather conditions is not the best approach for the future. Robust design techniques can, however, be a viable option for tackling future challenges. The concept of robust design was first introduced by Taguchi in the 1940s. The result of the design process is a product that is insensitive to the effect of given sources of variability, even though the sources themselves are not eliminated. A robust design optimization (RDO) method is for the first time proposed in this paper, for supporting architects and engineers in the design of buildings with robust energy performance under climate change and extreme conditions. The simplicity and the low computational demand of the process underlies the feasibility and applicability of this method, which can be used at any stage of the design process. The results show that the performance of the optimum solution not only has a 81.5% lower variation (less sensitivity to climate uncertainty) but at the same time has a 14.4% lower mean energy use value compared with a solution that is compliant with a recent construction standard (ASHRAE 90.1-2016). Less sensitivity to climate uncertainty means greater robustness to climate change whilst maintaining high performance.

Robust Process Design in Pharmaceutical Manufacturing under Batch-to-Batch Variation

Model-based concepts have been proven to be beneficial in pharmaceutical manufacturing, thus contributing to low costs and high quality standards. However, model parameters are derived from imperfect, noisy measurement data, which result in uncertain parameter estimates and sub-optimal process design concepts. In the last two decades, various methods have been proposed for dealing with parameter uncertainties in model-based process design. Most concepts for robustification, however, ignore the batch-to-batch variations that are common in pharmaceutical manufacturing processes. In this work, a probability-box robust process design concept is proposed. Batch-to-batch variations were considered to be imprecise parameter uncertainties, and modeled as probability-boxes accordingly. The point estimate method was combined with the back-off approach for efficient uncertainty propagation and robust process design. The novel robustification concept was applied to a freeze-drying process. Optimal shelf temperature and chamber pressure profiles are presented for the robust process design under batch-to-batch variation.

Assessing Initial Stiffness Models for Laterally Loaded Piles in Undrained Clay: Robust Design Perspective

The hyperbolic p−y curve method is commonly used to design laterally loaded piles. The initial stiffness (K) and the ultimate resistance per pile length (pu) are the two key parameters that are required to determine the hyperbolic p−y curve. Multiple competing models are available for determining the term K, which makes it difficult for the designer to select a proper initial stiffness model. Six existing initial stiffness models are assessed and compared from the robust design perspective in this paper. Specifically, a framework based on the concept of robust design is proposed for assessing these initial stiffness models considering multiple objectives such as safety, cost, and design robustness. This framework is illustrated with an example, the design of a laterally loaded pile in clay using the p−y curve method. Based on the outcome of this example study, the most preferred initial stiffness model for the laterally loaded pile design is suggested. To enhance applicability, the proposed framework based on the robust design concept is simplified and illustrated with a spreadsheet solution.

Robust design approach for flexible pavements to minimize the influence of material property uncertainty

This paper presents a new pavement design approach based on the concept of robust design. Robust pavement design is capable of minimizing the influence of various uncertainties (such as uncertain material properties) on the designed pavement rutting life and fatigue life through a rational adjustment of the design parameters. In this new approach, the signal-to-noise ratio is used to quantify the design robustness, and a genetic algorithm is employed to determine the Pareto front. Using a marginal utility function, the knee point on the Pareto front is selected and is recommended as the optimal design that simultaneously best meets the requirements of safety, robustness and cost. A case study is performed to illustrate this new design approach.

Robust optimization of the constructional time delay in the design of double-row stabilizing piles

Double-row stabilizing piles are widely used to stabilize large-scale landslides. The construction process of double-row stabilizing piles is often accompanied by constructional time delay (CTD), which is defined as the time interval between the installation of front-row and rear-row stabilizing piles. The CTD is often selected based on the designer’s experience and the construction arrangement due to the lack of design guidelines for double-row stabilizing piles. In this paper, the CTD is considered as a design parameter and optimized based on the robust design concept. The signal-to-noise ratio, which is a function of the mean and standard deviation of factors of safety (FOS) of the stabilizing piles, is used as a measure of the design robustness. The FOS of the double-row stabilizing piles are computed using an analytical model that considers the CTD. A framework based on the concept of robust design is proposed for determining the most preferred CTD considering multiple objectives, including safety, cost, and design robustness. This framework is illustrated with a case study, the Hongyan landslide project, Taizhou, Zhejiang, China. Based on the outcome of this study, the most preferred CTD is obtained.

Sheathing braced design of cold-formed steel structural members subjected to torsional buckling

The objective of this work is to examine the bracing effect of sheathing boards in inhibiting the instability failure modes of cold-formed steel (CFS) studs in the wall panel construction. A development of accurate and robust sheathing braced design concepts for CFS wall panels will eliminate the need for additional lateral steel bracing, thereby leading to efficient use of construction materials. The current design method by the American Iron and Steel Institute lacks in accurately predicting the design strength of the sheathed CFS stud. Therefore, the current investigation endeavors to fill the gap by carrying out experiments that simulate the behavior of the CFS studs subjected to out-of-plane loading. A total of sixty-seven experiments were carried out with seven different sheathing board types and ten different CFS studs to accomplish the objective. The experiments were carried out using a newly devised test set-up that simulates the worst case failure mode of the sheathing board. The experimental results indicate that the strength, stiffness and failure modes of the sheathing boards vary depending on the following; (i) fiber composition and material properties of the sheathing board; (ii) dimensions of the CFS stud. In addition, the test results also indicated that the stiffness of the sheathing board against the pull-through failure was not influenced by the thickness of the sheathing boards. Based on the inferences (trend of sheathing stiffness and failure modes) from the test results, a new expression is formulated to determine the stiffness of the sheathing board on a function of the tensile modulus of the sheathing board (Es) and dimensions of the CFS stud (d/2). The validation study indicates that the new expression is accurate in terms of both statistical and design application.