scholarly journals Development of a Multi-Criteria Design Optimization Methodology for Automotive Plastics Parts

Polymers ◽  
2021 ◽  
Vol 14 (1) ◽  
pp. 156
Author(s):  
Victor J. Romero ◽  
Alberto Sanchez-Lite ◽  
Gerard Liraut
Keyword(s):  
Design Optimization ◽  
Business Strategy ◽  
Plastic Material ◽  
Evaluation Criteria ◽  
Material Design ◽  
Interaction Matrix ◽  
Future Application ◽  
Concept Design ◽  
Simultaneous Application ◽  
Production Stages

The plastic industry is undergoing drastic changes, due to the customer sustainability perception of plastics, and the eruption of new processes (such 3D printing) and materials (such as renewably sourced resins). To enable a fast transition to high-quality, sustainable plastic applications, a specific methodology could be a key competitive advantage. This novel methodology is focused on improving the objectivity and efficiency of plastic production and the design review process. It is applicable to discrete optimization events in any product lifecycle milestone, from concept design to serial production stages. The methodology includes a natural way to capture plastic-related knowledge and trends, oriented towards building a dynamic “interaction matrix”, with a list of potential optimizations and their positive or negative impacts in a comprehensive set of multi-criteria evaluations. With an innovative approach, the matrix allows the possibility to incorporate a business strategy, which could be different at every lifecycle stage. The business strategy is translated from the common “verbal” definition into a quantitative set of “Target and Restrictions”, making it possible to detect and prioritize the best potential design optimization changes according to the strategy. This methodology helps to model and compare design alternatives, verify impacts in every evaluation criteria, and make robust and objective information-based decisions. The application of the methodology in real cases of plastic material design optimization in the automotive industry has provided remarkable results, accelerating the detection of improvement methods aligned with the strategy and maximizing the improvement in product competitiveness and sustainability. In comparison with the simultaneous application of existing mono-criteria optimization methodologies (such as “Design to Cost” or “Eco Design”) and subjective expert-based reviews, the novel methodology has a reduced workload and risks, confirming its potential for future application and further development in other polymer-based products, such as consumer goods or packaging.

Linear and nonlinear buckling analysis for the material design optimization of wind turbine blades

2019 ◽  
Vol 10 (6) ◽  
pp. 749-765
Author(s):  
Efstathios E. Theotokoglou ◽  
Georgios Balokas ◽  
Evgenia K. Savvaki
Keyword(s):  
Wind Turbine ◽  
Design Optimization ◽  
Turbine Blades ◽  
Material Design ◽  
Fiber Reinforced Polymers ◽  
Fiber Reinforced ◽  
Reinforced Polymers ◽  
Content Type ◽  
Buckling Behavior ◽  
Load Carrying

Purpose The purpose of this paper is to investigate the buckling behavior of the load-carrying support structure of a wind turbine blade. Design/methodology/approach Experimental experience has shown that local buckling is a major failure mode that dominantly influences the total collapse of the blade. Findings The results from parametric analyses offer a clear perspective about the buckling capacity but also about the post-buckling behavior and strength of the models. Research limitations/implications This makes possible to compare the response of the different fiber-reinforced polymers used in the computational model. Originality/value Furthermore, this investigation leads to useful conclusions for the material design optimization of the load-carrying box girder, as significant advantages derive not only from the combination of different fiber-reinforced polymers in hybrid material structures, but also from Kevlar-fiber blades.

scholarly journals Efficient wave-based acoustic material design optimization

2016 ◽  
Vol 78 ◽  
pp. 83-92 ◽  
Author(s):  
Nicolas Morales ◽  
Dinesh Manocha
Keyword(s):  
Design Optimization ◽  
Material Design

scholarly journals The Isotropic Material Design of In-Plane Loaded Elasto-Plastic Plates

Materials ◽  
2021 ◽  
Vol 14 (23) ◽  
pp. 7430
Author(s):  
Sławomir Czarnecki ◽  
Tomasz Lewiński
Keyword(s):  
Optimum Design ◽  
Isotropic Material ◽  
Plastic Material ◽  
Design Method ◽  
Unit Cost ◽  
Yield Condition ◽  
Material Design ◽  
Approximate Solutions ◽  
Constrained Problems ◽  
Design Variables

This paper puts forward a new version of the Isotropic Material Design method for the optimum design of structures made of an elasto-plastic material within the Hencky-Nadai-Ilyushin theory. This method provides the optimal layouts of the moduli of isotropy to make the overall compliance minimal. Thus, the bulk and shear moduli are the only design variables, both assumed as non-negative fields. The trace of the Hooke tensor represents the unit cost of the design. The yield condition is assumed to be independent of the design variables, to make the design process as simple as possible. By eliminating the design variables, the optimum design problem is reduced to the pair of the two mutually dual Linear Constrained Problems (LCP). The solution to the LCP stress-based problem directly determines the layout of the optimal moduli. A numerical method has been developed to construct approximate solutions, which paves the way for constructing the final layouts of the elastic moduli. Selected illustrative solutions are reported, corresponding to various data concerning the yield limit and the cost of the design. The yield condition introduced in this paper results in bounding the values of the optimal moduli in the places of possible stress concentration, such as reentrant corners.

Supply chain redesign for lead-time reduction through Kraljic purchasing portfolio and AHP integration

2019 ◽  
Vol 26 (4) ◽  
pp. 1194-1209 ◽  
Author(s):  
Augusto Bianchini ◽  
Andrea Benci ◽  
Marco Pellegrini ◽  
Jessica Rossi
Keyword(s):  
Supply Chain ◽  
Business Strategy ◽  
Lead Time ◽  
Small And Medium Enterprises ◽  
Evaluation Criteria ◽  
Portfolio Analysis ◽  
Lead Times ◽  
Content Type ◽  
Lead Time Reduction ◽  
Time Reduction

Purpose The purpose of this paper is to provide a flexible and extensible model for the classification of suppliers, within the purchasing guidelines and market trends of an Italian small company, leader in the production of street lamps. The model is applied to identify critical supply chains with the final objective of lead-time reduction. Design/methodology/approach The model is obtained by the application of the purchasing portfolio analysis through the construction of Kraljic matrix. Profit impact and supply risk criteria are selected according to the main company requirements, and then prioritized by the analytical hierarchy process (AHP). Finally, supply chain lead-times are analyzed with Gantt diagrams. Findings The application of the model allows the determination of company criticalities in terms of high lead-times and of the involved suppliers. The analysis of critical suppliers positioning in the Kraljic matrix allows the definition of some possible strategies to implement for lead-time reduction. Research limitations/implications Purchasing portfolio analysis and Kraljic matrix are practical instruments to quickly frame company purchasing situation, but their application is not simple due to the numerous and different factors involved, especially in small and medium enterprises (SMEs), where resource are scarce and several constraints limit operations. The objective of the research is the development of a practical tool for strategic purchasing, simple and robust to be implemented in SMEs, with limited resources and access to quantitative supplier data. Originality/value Evaluation criteria definition is one of the most difficult phases, such as their univocal and quantitative comparison. The problem of selecting and prioritizing both quantitative and qualitative criteria for suppliers classification is overcome with the combined application of Kraljic matrix and AHP. The newly integration of the two methodologies allows the realization of a reliable and robust model for suppliers classification, which can be easily adapted to company business strategy changes.

Parameterized Design Optimization of a Magnetohydrodynamic Liquid Metal Active Cooling Concept

2016 ◽  
Vol 138 (3) ◽  
Author(s):  
Darren J. Hartl ◽  
Edgar Galvan ◽  
Richard J. Malak ◽  
Jeffrey W. Baur
Keyword(s):  
Liquid Metal ◽  
Design Optimization ◽  
Optimization Problems ◽  
Material Design ◽  
Element Model ◽  
Algebraic Model ◽  
Engineering Problem ◽  
Computationally Efficient ◽  
Design Selection ◽  
Computationally Intensive

The success of model-based multifunctional material design efforts relies on the proper development of multiphysical models and advanced optimization algorithms. This paper addresses both in the context of a structure that includes a liquid metal (LM) circuit for integrated cooling. We demonstrate for the first time on a complex engineering problem the use of a parameterized approach to design optimization that solves a family of optimization problems as a function of parameters exogenous to the subsystem of interest. This results in general knowledge about the capabilities of the subsystem rather than a restrictive point solution. We solve this specialized problem using the predictive parameterized Pareto genetic algorithm (P3GA) and show that it efficiently produces results that are accurate and useful for design exploration and reasoning. A “population seeding” approach allows an efficient multifidelity approach that combines a computationally efficient reduced-fidelity algebraic model with a computationally intensive finite-element model. Using data output from P3GA, we explore different design scenarios for the LM thermal management concept and demonstrate how engineers can make a final design selection once the exogenous parameters are resolved.

Dimension Reduction and Decomposition Using Causal Graph and Qualitative Analysis for Aircraft Concept Design Optimization

2017 ◽  
Author(s):  
Di Wu ◽  
Eric Coatanea ◽  
G. Gary Wang
Keyword(s):  
Qualitative Analysis ◽  
Dimension Reduction ◽  
Design Optimization ◽  
Design Problem ◽  
Concept Design ◽  
Causal Graph ◽  
Design Structure ◽  
Decomposition Strategies ◽  
The One ◽  
Optimization Efficiency

With the increasing design dimensionality, it is more difficult to solve Multidisciplinary design optimization (MDO) problems. To reduce the dimensionality of MDO problems, many MDO decomposition strategies have been developed. However, those strategies consider the design problem as a black-box function. In practice, the designers usually have certain knowledge of their problem. In this paper, a method leveraging causal graph and qualitative analysis is developed to reduce the dimensionality of the MDO problem by systematically modeling and incorporating knowledge of the design problem. Causal graph is employed to show the input-output relationships between variables. Qualitative analysis using design structure matrix (DSM) is carried out to automatically find the variables that can be determined without optimization. According to the weight of variables, the MDO problem is divided into two sub-problems, the optimization problem with respect to important variables, and the one with less important variables. The novel method is performed to solve an aircraft concept design problem and the results show that the new dimension reduction and decomposition method can significantly improve optimization efficiency.

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