Quantifying the impact of product changes on manufacturing performance

Every adjustment to a physical product disrupts the manufacturing organization, requiring adaptation in tools and processes. The resulting disruption to manufacturing performance is poorly understood. We use design structure matrices and a complexity metric to quantify the complexity and change of product architecture in an explorative, small scale experiment. Based on the results we develop two propositions to guide further research into the factors that affect the shape of consecutive learning curves upon product changes. The first proposition is that after product change, the complexity of the novel part of product architecture is responsible for the initial decrease in manufacturing performance. Second, we propose that the asymptote of a learning curve and the complexity of a product’s architecture are inversely related.Every adjustment to a physical product disrupts the manufacturing organization, requiring adaptation in tools and processes. The resulting disruption to manufacturing performance is poorly understood. We use design structure matrices and a complexity metric to quantify the complexity and change of product architecture in an explorative, small-scale experiment. Based on the results we develop two propositions to guide further research into the factors that affect the shape of consecutive learning curves upon product changes. The first proposition is that after product change, the complexity of the novel part of product architecture is responsible for the initial decrease in manufacturing performance. Second, we propose that the asymptote of a learning curve and the complexity of a product’s architecture are inversely related.</p

On the Design of Functionally Integrated Aero-engine Structures: Modeling and Evaluation Methods for Architecture and Complexity

The drive for airplanes with radically reduced fuel consumption and emissions motivates engine manufacturers to explore innovative engine designs. The novelty of such engines results in changed operating conditions, such as newly introduced constraints, increased loads or rearranged interfaces. To be competitive, component developers and manufacturers must understand and predict the consequences of such changes on their sub-systems. Presently, such assessments are based on detailed geometrical models (CAD or finite element) and consume significant amounts of time. The preparation of such models is resource intensive unless parametrization is employed. Even with parametrization, alternative geometrical layouts for designs are difficult to achieve. In contrast to geometrical model-based estimations, a component architecture representation and evaluation scheme can quickly identify the functional implications for a system-level change and likely consequences on the component. The schemes can, in turn, point to the type and location of needed evaluations with detailed geometry. This will benefit the development of new engine designs and facilitate improvements upon existing designs. The availability of architecture representation schemes for functionally integrated (all functions being satisfied by one monolithic structure) aero-engine structural components is limited. The research in this thesis focuses on supporting the design of aero-engine structural components by representing their architecture as well as by developing means for the quantitative evaluation and comparison of different component designs. The research has been conducted in collaboration with GKN Aerospace Sweden AB, and the components are aero-engine structures developed and manufactured at GKN. Architectural information is generated and described based on concepts from set theory, graph theory and enhanced function–means trees. In addition, the complexities of the components are evaluated using a new complexity metric. Specifically, the developed modeling and evaluation methods facilitate the following activities: \ub7\ua0\ua0\ua0\ua0\ua0\ua0\ua0\ua0 identification and representation of function–means information for the component\ub7\ua0\ua0\ua0\ua0\ua0\ua0\ua0\ua0 representation and evaluation of component architecture\ub7\ua0\ua0\ua0\ua0\ua0\ua0\ua0\ua0 product complexity evaluation\ub7\ua0\ua0\ua0\ua0\ua0\ua0\ua0\ua0 early selection of load path architecture\ub7\ua0\ua0\ua0\ua0\ua0\ua0\ua0\ua0 impact assessment for the component’s functioning in the systemBy means of the methods developed in this thesis, the design rationale for a component is made explicit, and the storing, communicating and retrieving of information about the component in the future is enabled. Through their application to real-life engine structures, the usability of the methods in identifying early load carrying configurations and selecting a manufacturing segmenting option is demonstrated. Together, the methods provide development engineers the ability to compare alternative architectures. Further research could focus on exploring the system (engine) effects of changes in component architecture and improvements to the complexity metric by incorporating manufacturing information

On the Mitigation of Late Stage Redesign in Mechatronics Using Integrated Approaches

RÉSUMÉ Les systèmes mécatronique combinent des éléments issus du génie mécanique, électrique, contrôle et logiciel. Due à la nature multi-domaine de ces systèmes, il est nécessaire de s’assurer d’un processus de conception optimal afin de réduire le temps et le cout de développement. De ce fait, cette thèse s’intéresse aux boucles de re-conception tard durant le processus de développement. Ces boucles peuvent être causé entre autres par des interactions négatives qui affectent la performance et l’intégration des composantes et sous-systèmes et l’incertitude dans les paramètres du système. Premièrement, cette thèse propose une nouvelle méthode de modélisation qui permet d’identifier et d’évaluer les dépendances durant les phases initiales de conception. Cette méthode est ensuite utilisée dans la création d’un index qui permet de représenter le niveau total de dépendances négative du système. L’index est ensuite utilisé dans l’évaluation multicritère, ce qui permet de choisir des systèmes étant plus faciles à concevoir. Finalement, une méthode de modélisation qui permet de considérer de façon concurrente les dépendance positive et négative est présenté. Par la suite, cette thèse propose d’utiliser les nombres flous afin de traiter l’incertitude des paramètres. En premier lieu, la thèse montre que les nombres flous peuvent être utilisé afin de simuler le comportement d’un système mécatronique sujet à de l’incertitude. De plus, une méthode de conception utilisant la simulation floue est proposée afin de concevoir les systèmes mécatronique de façon robuste. De plus, les nombres floues permettent de déterminer la stabilité du système, ce qui permet le développement d’une méthodologie de conception robuste totalement intégré, qui considère à la fois l’aspect physique et contrôle du système.----------ABSTRACT Mechatronic systems are highly integrated devices, with elements from mechanical, electrical, software and control engineering. It is thus necessary to ensure a streamlined design process to reduce development time and cost. Consequently, this thesis researches on the issue of late stages redesigns in mechatronics. The late stages redesigns may occur due to problems while integrating the different components and subsystems. Two causes of these redesigns are unpredicted negative interactions between the elements of the system, and inadequate performance due to uncertainties. To deal with the issue of negative interactions, this thesis first suggests a modeling method that enables to identify and assess negative dependencies early during the design process. It is shown that the modeling method can be efficiently used to detect dependencies that would be detrimental to the system’s performance and which may require more design effort. Then, based on this modeling method, an index representing the total level of negative dependencies present within the system is proposed. The index is shown to be able to predict decrease of performance due to the negative dependencies and can thus be used as a valuable criterion during decision making. Finally, a modeling method to handle concurrently positive and negative dependencies is suggested. This modeling method is shown to have an impact on the currently existing complexity metrics and should thus allow to better represent the reality of the design. Furthermore, to deal with the issue of uncertainties affecting the performance of the system, this thesis proposes a design methodology using fuzzy numbers. First, it is shown that fuzzy numbers can be used to model and simulate the uncertain behavior of mechatronic systems while being computationally efficient. Then a robust design methodology is presented and shown to be effective in optimizing a mechatronic system while reducing the uncertainties in the performance. Furthermore, based on the use of fuzzy numbers in the modeling of the mechatronic system, it is shown that it is possible to determine the stability of the device under uncertainties. Finally, a fully integrated robust design methodology is presented, which consider both control and design parameters selection, and which can be used to mitigate late stages redesigns due to improper performance. In sum, this thesis investigates and suggests multiple integrated design solutions to mitigate late stages redesigns in the mechatronic design process