Robust Concept Exploration of Materials, Products and Associated Manufacturing Processes

2018 ◽  
Author(s):  
Anand Balu Nellippallil ◽  
Pranav Mohan ◽  
Janet K. Allen ◽  
Farrokh Mistree
Keyword(s):  
Robust Design ◽  
Design Method ◽  
Integrated Design ◽  
Manufacturing Processes ◽  
Type I ◽  
Process Chain ◽  
Process Chains ◽  
Concept Exploration ◽  
Decision Based Design ◽  
Noise Factors

In this paper, we present robust concept exploration using a goal-oriented, inverse decision-based design method to carry out the integrated design of material, product and associated manufacturing processes by managing the uncertainty involved. The uncertainty in complex material and product systems is derived from many sources and we classify robust design based on these sources — uncertainty in noise factors (Type I robust design); uncertainty in design variables or control factors (Type II robust design); uncertainty in function relationship between control/noise and response (Type III robust design); and propagation and potential amplification of uncertainty in a process chain (Type I to III robust designs across process chains). In this paper, we introduce a variation to the existing goal-oriented inverse decision-based design method to bring in robustness for multiple conflicting goals from the stand-point of Type I to III robust design across process chains. The variation embodies the introduction of specific robust design goals and constraints anchored in the mathematical constructs of error margin indices and design capability indices to determine “satisficing robust design” specifications for given performance requirement ranges using the goal-oriented, inverse design method. The design of a hot rolling process chain for the production of a rod is used as an example.

An Inverse, Decision-Based Design Method for Integrated Design Exploration of Materials, Products, and Manufacturing Processes

2018 ◽  
Vol 140 (11) ◽  
Author(s):  
Anand Balu Nellippallil ◽  
Vignesh Rangaraj ◽  
B. P. Gautham ◽  
Amarendra Kumar Singh ◽  
Janet K. Allen ◽  
...  
Keyword(s):  
Design Method ◽  
Integrated Design ◽  
Manufacturing Processes ◽  
Process Chain ◽  
Structure Property ◽  
Horizontal Integration ◽  
Design Exploration ◽  
Rod Rolling ◽  
Manufacturing Process Chain ◽  
Decision Based Design

A material's design revolution is underway with a focus to design the material microstructure and processing paths to achieve certain performance requirements of products. A host of manufacturing processes are involved in producing a product. The processing carried out in each process influences its final properties. To couple the material processing-structure-property-performance (PSPP) spaces, models of specific manufacturing processes must be enhanced and integrated using multiscale modeling techniques (vertical integration) and then the input and output of the various manufacturing processes must be integrated to facilitate the flow of information from one process to another (horizontal integration). Together vertical and horizontal integration allows for the decision-based design exploration of the manufacturing process chain in an inverse manner to realize the end product. In this paper, we present an inverse method to achieve the integrated design exploration of materials, products, and manufacturing processes through the vertical and horizontal integration of models. The method is supported by the concept exploration framework (CEF) to systematically explore design alternatives and generate satisficing design solutions. The efficacy of the method is illustrated for a hot rod rolling (HRR) and cooling process chain problem by exploring the processing paths and microstructure in an inverse manner to produce a rod with specific mechanical properties. The proposed method and the exploration framework are generic and support the integrated decision-based design exploration of a process chain to realize an end product by tailoring material microstructures and processing paths.

A Goal-Oriented, Inverse Decision-Based Design Method to Achieve the Vertical and Horizontal Integration of Models in a Hot Rod Rolling Process Chain

2017 ◽  
Author(s):  
Anand Balu Nellippallil ◽  
Vignesh Rangaraj ◽  
B. P. Gautham ◽  
Amarendra Kumar Singh ◽  
Janet K. Allen ◽  
...  
Keyword(s):  
Manufacturing Process ◽  
Design Method ◽  
Manufacturing Processes ◽  
Process Chain ◽  
Structure Property ◽  
Horizontal Integration ◽  
Design Exploration ◽  
Unit Operations ◽  
Manufacturing Process Chain ◽  
Decision Based Design

Reducing the manufacturing and marketing time of products by means of integrated simulation-based design and development of the material, product, and the associated manufacturing processes is the need of the hour for industry. This requires the design of materials to targeted performance goals through bottom-up and top-down modeling and simulation practices that enables handshakes between modelers and designers along the entire product realization process. Manufacturing a product involves a host of unit operations and the final properties of the manufactured product depends on the processing steps carried out at each of these unit operations. In order to effectively couple the material processing-structure-property-performance spaces, there needs to be an interplay of the systems-based design of materials with enhancement of models of various unit operations through multiscale modeling methodologies and integration of these models at different length scales (vertical integration). This ensures the flow of information from one unit operation to another thereby establishing the integration of manufacturing processes (horizontal integration). Together these types of integration will support the decision-based design of the manufacturing process chain so as to realize the end product. In this paper, we present a goal-oriented, inverse decision-based design method to achieve the vertical and horizontal integration of models for the hot rolling and cooling stages of the steel manufacturing process chain for the production of a rod with defined properties. The primary mathematical construct used for the method presented is the compromise Decision Support Problem (cDSP) supported by the proposed Concept Exploration Framework (CEF) to generate satisficing solutions under uncertainty. The efficacy of the method is illustrated by exploring the design space for the microstructure after cooling that satisfies the requirements identified by the end mechanical properties of the product. The design decisions made are then communicated in an inverse manner to carry out the design exploration of the cooling stage to identify the design set points for cooling that satisfies the new target microstructure requirements identified. Specific requirements such as managing the banded microstructure to minimize distortion in forged gear blanks are considered in the problem. The proposed method is generic and we plan to extend the work by carrying out the integrated decision-based design exploration of rolling and reheating stages that precede to realize the end product.

Inverse Thermo-Mechanical Processing (ITMP) Design of a Steel Rod During Hot Rolling Process

2019 ◽  
Author(s):  
Anand Balu Nellippallil ◽  
Pranav Mohan ◽  
Janet K. Allen ◽  
Farrokh Mistree
Keyword(s):  
Hot Rolling ◽  
Design Method ◽  
Integrated Design ◽  
Computational Design ◽  
Rolling Process ◽  
Manufacturing Processes ◽  
Mechanical Processing ◽  
Design Exploration ◽  
And Performance ◽  
Decision Based Design

Abstract The production of steel products involves a series of manufacturing processes. The material Thermo-Mechanical Processing (TMP) history at each process affects the final properties and performances of the product. Experiments and plant trials to predict these properties and performance of steel products are expensive and time consuming. This has resulted in the need for computational design methods and tools that support a human designer in realizing such complex systems involving the material, product and manufacturing processes from a simulation-based design perspective. In this paper, we present a Goal-oriented Inverse Design method to achieve the integrated design exploration of materials, products and manufacturing processes. The key functionality offered is the capability to carry out a microstructure-mediated design satisficing specific processing requirements and performance goals of the product. Given models to establish the information flow chain, a designer can use the method for the decision-based design exploration of material microstructure and processing paths to realize products in a manufacturing process chain. The efficacy of the method is tested using an industry-inspired hot rolling problem to inversely design the thermo-mechanical processing of a steel rod. The focus here is the method and associated design constructs which are generic and support the formulation and decision-based design of similar problems involving materials, products and associated manufacturing processes.

An Inverse, Decision-Based Design Method for Robust Concept Exploration

2020 ◽  
Vol 142 (8) ◽  
Author(s):  
Anand Balu Nellippallil ◽  
Pranav Mohan ◽  
Janet K. Allen ◽  
Farrokh Mistree
Keyword(s):  
Analytical Model ◽  
Robust Design ◽  
Hot Rolling ◽  
Design Method ◽  
Inverse Design ◽  
Cooling Process ◽  
Robust Solution ◽  
Robust Solutions ◽  
Process Chains ◽  
Inverse Design Method

Abstract In this paper, we extend our previous work on a goal-oriented inverse design method to carry out inverse robust design by managing the uncertainty involved. The extension embodies the introduction of specific robust design goals and new robust solution constraints anchored in the mathematical constructs of Error Margin Indices (EMIs) and Design Capability Indices (DCIs) to determine “satisficing” robust design specifications across analytical model-based process chains. Contributions in this paper include the designer’s ability to explore satisficing robust solution regions when multiple conflicting goals and multiple sources of uncertainty are present. Using the goal-oriented inverse design method, robust solutions are propagated in an inverse manner. We demonstrate the efficacy of the method and the associated robust design functionalities using an industry-inspired hot rolling and cooling process chain example problem for the production of a steel rod. In this example, we showcase the formulation of multiple mechanical property goals for the end product using the robustness metrics and the exploration of satisficing robust solutions for material microstructure after the cooling process using the robust solution constraints. The robust solutions thus identified are communicated in an inverse manner using the design method to explore satisficing robust solutions for the microstructure generated after the hot rolling process. Using the example, we demonstrate the robust co-design of material, product, and associated manufacturing processes. The method and the associated design constructs are generic and support the formulation and inverse robust design exploration under uncertainty of similar problems involving a sequential, analytical model-based flow of information across process chains.

A Procedure for Robust Design: Minimizing Variations Caused by Noise Factors and Control Factors

1996 ◽  
Vol 118 (4) ◽  
pp. 478-485 ◽  
Author(s):  
Wei Chen ◽  
J. K. Allen ◽  
Kwok-Leung Tsui ◽  
F. Mistree
Keyword(s):  
Robust Design ◽  
Irrigation System ◽  
Small Variation ◽  
Type I ◽  
Closed Form Solutions ◽  
Control Factors ◽  
Design Variables ◽  
Solar Powered ◽  
And Control ◽  
Noise Factors

In this paper, we introduce a small variation to current approaches broadly called Taguchi Robust Design Methods. In these methods, there are two broad categories of problems associated with simultaneously minimizing performance variations and bringing the mean on target, namely, Type I—minimizing variations in performance caused by variations in noise factors (uncontrollable parameters). Type II—minimizing variations in performance caused by variations in control factors (design variables). In this paper, we introduce a variation to the existing approaches to solve both types of problems. This variation embodies the integration of the Response Surface Methodology (RSM) with the compromise Decision Support Problem (DSP). Our approach is especially useful for design problems where there are no closed-form solutions and system performance is computationally expensive to evaluate. The design of a solar powered irrigation system is used as an example.

scholarly journals Robust Design of 3D-Printed 6–18 GHz Double-Ridged TEM Horn Antenna

2018 ◽  
Vol 8 (9) ◽  
pp. 1582 ◽  
Author(s):  
Sungwoo Lee ◽  
Youngoo Yang ◽  
Kang-Yoon Lee ◽  
Kyung-Young Jung ◽  
Keum Hwang
Keyword(s):  
Reflection Coefficient ◽  
Robust Design ◽  
Design Method ◽  
Horn Antenna ◽  
Initial Design ◽  
3D Printed ◽  
Tem Horn ◽  
Robust Design Method ◽  
Noise Factors ◽  
Ridged Waveguide

A robust design of a 3D-printed 6–18 GHz double-ridged TEM horn antenna is proposed in this paper. The designed TEM horn antenna has two parts: an adaptor and a horn aperture. The adaptor is realized using a double-ridged waveguide to extend the operating bandwidth of the dominant mode (TE10 mode). Meanwhile, the horn aperture section is implemented in an exponentially tapered configuration to match the impedance of the double-ridged waveguide with the intrinsic impedance. The performance of the initially designed antenna shows that the reflection coefficient and gain levels are less than −13 dB and greater than 5.5 dBi within the 6–18 GHz band, respectively. The initial design was well done, but the noise factors that may occur during the manufacturing process were not taken into account. To design an antenna considering these noise factors, the parameters of the initial design are optimized by a novel robust design method also proposed in this paper. The robustness of the antenna optimized by the proposed method is approximately 12.4% higher than that of the initial antenna. The validity of the proposed method was tested by fabricating the antenna. A prototype of the optimized antenna with the proposed robust design method is fabricated using a 3D printer with a stereolithographic apparatus attached, and the surface of the frame is covered by a nano-silver plating. The measured results of the fabricated antenna are in good agreement with the simulation results over the operating band. The measured −10 dB reflection coefficient bandwidth of the antenna can cover 6–18 GHz. In addition, the measured gain ranges from 4.42 to 10.75 dBi within the 6–18 GHz band.

scholarly journals Robust Product Design: A Modern View of Quality Engineering in Manufacturing Systems

2019 ◽  
Author(s):  
Amir Parnianifard ◽  
SITI AZFANIZAM AHMAD ◽  
M.K.A. Ariffin ◽  
M.I.S. Ismai
Keyword(s):  
Robust Design ◽  
Manufacturing Systems ◽  
Design Method ◽  
Computational Cost ◽  
Optimization Methods ◽  
Manufacturing Processes ◽  
Quality Loss Function ◽  
High Quality ◽  
Different Types ◽  
Robust Design Method

One of the main technological and economic challenges for an engineer is designing high-quality products in manufacturing processes. Most of these processes involve a large number of variables included the setting of controllable (design) and uncontrollable (noise) variables. Robust Design (RD) method uses a collection of mathematical and statistical tools to study a large number of variables in the process with a minimum value of computational cost. Robust design method tries to make high-quality products according to customers’ viewpoints with an acceptable profit margin. This paper aims to provide a brief up-to-date review of the latest development of RD method particularly applied in manufacturing systems. The basic concepts of the quality loss function, orthogonal array, and crossed array design are explained. According to robust design approach, two classifications are presented, first for different types of factors, and second for different types of data. This classification plays an important role in determining the number of necessity replications for experiments and choose the best method for analyzing data. In addition, the combination of RD method with some other optimization methods applied in designing and optimizing of processes are discussed.

scholarly journals Robust Product Design: A Modern View of Quality Engineering in Manufacturing Systems

2018 ◽  
Author(s):  
Amir Parnianifard ◽  
A.S. Azfanizama ◽  
M.K.A. Ariffin ◽  
M.I.S. Ismai
Keyword(s):  
Robust Design ◽  
Manufacturing Systems ◽  
Design Method ◽  
Computational Cost ◽  
Optimization Methods ◽  
Manufacturing Processes ◽  
Quality Loss Function ◽  
High Quality ◽  
Different Types ◽  
Robust Design Method

One of the main technological and economic challenges for an engineer is designing high-quality products in manufacturing processes. Most of these processes involve a large number of variables included the setting of controllable (design) and uncontrollable (noise) variables. Robust Design (RD) method uses a collection of mathematical and statistical tools to study a large number of variables in the process with a minimum value of computational cost. Robust design method tries to make high-quality products according to customers’ viewpoints with an acceptable profit margin. This paper aims to provide a brief up-to-date review of the latest development of RD method particularly applied in manufacturing systems. The basic concepts of the quality loss function, orthogonal array, and crossed array design are explained. According to robust design approach, two classifications are presented, first for different types of factors, and second for different types of data. This classification plays an important role in determining the number of necessity replications for experiments and choose the best method for analyzing data. In addition, the combination of RD method with some other optimization methods applied in designing and optimizing of processes are discussed.

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