Cost-efficient digital twins for design space exploration: A modular platform approach

The industrial need to predict the behaviour of radically new products brings renewed interest in how to set up and make use of physical prototypes and testing. However, conducting physical testing of a large number of radical concepts is still a costly approach. This paper proposes an approach to actively use digital twins in the early phases where the design can be largely changed. The approach is based on creating a set of digital twin modules that can be reused and recomposed to create digital twin variants. However, this paper considers that developing a digital twin can be very costly. Therefore, the approach focuses on supporting the decisions about the optimal mix of modules, and about whether a new digital twin module should be developed. The approach is applied to an industrial case derived from the collaboration with two space manufacturers. The results highlight how the design of the modular platform has an impact on the cost of the digital twin, if commonality and reusability aspects are considered. These results point at the cost-efficiency of applying a modular approach to digital twin creation, as a means to reuse the results from physical testing to validate new designs and their ranges of validit

Metaheuristic Approaches to Solve a Complex Aircraft Performance Optimization Problem

The increasing demands for travelling comfort and reduction of carbon dioxide emissions have been considered substantially in the stage of conceptual aircraft design. However, the design of a modern aircraft is a multidisciplinary process, which requires the coordination of information from several specific disciplines, such as structures, aerodynamics, control, etc. To address this problem with adequate accuracy, the multidisciplinary analysis and optimization (MAO) method is usually applied as a systematic and robust approach to solve such complex design issues arising from industries. Since MAO method is tedious and computationally expensive, genetic programming (GP)-based metamodeling techniques incorporating MAO are proposed as an effective approach to minimize the wing stiffness of a large aircraft subject to aerodynamic, aeroelastic and stability constraints in the conceptual design phase. Based on the linear small-disturbance theory, the state-space equation is employed for stability analysis. In the process of multidisciplinary analysis, aeroelastic response simulations are performed using Nastran. To construct metamodels representing the responses of the interests with high accuracy as well as less computational burden, optimal Latin hypercube design of experiments (DoE) is applied to determine the optimized distribution of sampling points. Following that, parametric optimization is carried out on metamodels to obtain the optimal wing geometry shape, elastic axis positions and stiffness distribution, and then the solution is verified by finite element simulations. Finally, the superiority of the GP-based metamodel technique over genetic algorithm is demonstrated by multidisciplinary design optimization of a representative beam-frame wing structure in terms of accuracy and efficiency. The results also show that GP metamodel-based strategy for solving MAO problems can provide valuable insights to tailoring parameters for the effective design of a large aircraft in the conceptual phase

Cost-efficient digital twins for design space exploration: A modular platform approach

The industrial need to predict the behaviour of radically new products brings renewed interest in how to set up and make use of physical prototypes and testing. However, conducting physical testing of a large number of radical concepts is still a costly approach. This paper proposes an approach to actively use digital twins in the early phases where the design can be largely changed. The approach is based on creating a set of digital twin modules that can be reused and recomposed to create digital twin variants. However, this paper considers that developing a digital twin can be very costly. Therefore, the approach focuses on supporting the decisions about the optimal mix of modules, and about whether a new digital twin module should be developed. The approach is applied to an industrial case derived from the collaboration with two space manufacturers. The results highlight how the design of the modular platform has an impact on the cost of the digital twin, if commonality and reusability aspects are considered. These results point at the cost-efficiency of applying a modular approach to digital twin creation, as a means to reuse the results from physical testing to validate new designs and their ranges of validit

Exploring the relationship between manufacturing practices, agile capabilities and organisational performance: a case of the Thai automotive parts industry

Contemporary manufacturers have to endure the challenges of a constantly changing economic environment that is increasingly competitive. Today’s business world has witnessed increasingly intense foreign competition, rapid technological change, shorter product life-cycles and customers frequently demanding new products. To deal with this dynamic and uncertain marketplace, firms are required to become more nimble, flexible and quickly responsive to competitive and pressure situations. Recognising this trend, the manufacturing sector has focused on becoming more agile. In business situations characterised by high uncertainty, agility is not just desirable but is quickly becoming a requirement for organisations’ success. Despite number of theories being developed on agility by many academics and practitioners, few businesses have implemented agility to its full potential. Most studies on the experiences in the manufacturing sector have documented events and processes in developed economies. To respond to these issues, this study explores the development of agility in the context of a developing economy, Thailand, and specifically, its automotive parts industry. This study develops and empirically tests a research model to capture the key enablers of agility and the impact of agile capabilities on organisational performance. The conceptual foundation of the research is grounded in the Resource-based View (RBV) and the Dynamic Capability View (DCV), and in a review of the operations strategy literature. The framework establishes the cause-and-effect relationships between manufacturing practices and agile capability and organisational performance outcomes. To do this, seven hypotheses are developed and tested. The research pursues a positivist paradigm by using Structural Equation Modelling (SEM) analysis. The psychometric properties of the research instrument are generated through a rigorous procedure of content validity. This is followed by a large-scale questionnaire survey involving the Industrial Estates Authority of Thailand, focusing on tier-1 automotive parts producers. The response rate in this study is 43% (n=297). The findings confirm that the manufacturing practices in which organisational resources are integrated and reintegrated to generate new capability positively influence the development of agility. The results confirm the positive impact of agile capabilities on a business organisation’s success, particularly with reference to operational performance.The research makes an original contribution to the operations strategy and agility literature by developing and validating the research model and the accompanying measurement instrument. In particular, the conception, measurement, hypotheses and empirical findings of the manufacturing practices and the agility construct represent a significant contribution in advancing the theoretical foundation and the empirical basis of agility in the context of developing economies. Finally, the research makes a practical contribution by offering a tool for a business organisation to assess and measure its agility initiative and progress, and to identify those areas where improvement is needed