Platform development: implications for portfolio management

Hsuan, Juliana; Hansen, Poul Henrik Kyvsgaard

doi:10.1590/s0104-530x2007000300003

Cited by 11 publications

(4 citation statements)

References 11 publications

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“…La reutilización podría tener lugar dentro de un lapso de varios años. En la lógica de la reutilización el tiempo es crucial, se pueden adherir componentes rehusados en lugar de desarrollarlos por completo (Hsuan y Hansen, 2007). Esto permite que si a futuro se desea agregar otra empresa al análisis se puede implementar reutilizando lo que ya se tiene, para ello la metodología de desarrollo debe pensarse de esa manera.…”

Section: Estrategia De Aprendizajeunclassified

Proyecto De Un Laboratorio De Riesgos Laborales Para La Institución Universitaria Politécnico Grancolombiano

Trujillo-Flórez

Velandia-Vargas

2019

Poli

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El presente documento plasma el proceso del desarrollo del simulador denominado Laboratorio de Riesgos Laborales para el programa de Gestión de la Seguridad y Salud Laboral el cual se ocupa de los riesgos Biológico, Ergonómico, Físico, Químico, Natural y Seguridad para cinco tipos de empresas diferentes (laboratorio, manufactura, oficina, pozo petrolero y empresa de servicios generales). Se tratará cómo se planeó la estrategia pedagógica y cómo se realizó el diseño instruccional para la creación de la herramienta de software a través de una planeación que va desde la descomposición de la competencia, pasando por un diagrama de tareas y finalizando en la elaboración del guion, para de allí pasar a diseño gráfico, diagramación y programación. El proyecto finaliza con la publicación de la herramienta en las aulas virtuales para los estudiantes del programa en dicha modalidad.

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Section: Estrategia De Aprendizajeunclassified

Proyecto De Un Laboratorio De Riesgos Laborales Para La Institución Universitaria Politécnico Grancolombiano

Trujillo-Flórez

Velandia-Vargas

2019

Poli

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“…The interface compatibility between the modules of a product was reported by Hsuan & Hansen (2007) as the core of the organization of a modular platform because it enables the substitution of modules in certain product architecture, Standardized interfaces determine when the outsourcing is a viable strategy. Figure 1 showed an example in which three modules (M1, M2 and M3) are totally compatible among themselves and a forth module (M4) is compatible with just module M3, i.e.…”

Section: Design Modularity Elementsmentioning

confidence: 99%

Adoção da modularidade em produto e em produção na indústria automotiva: uma análise comparativa em projetos de veículos com participação da engenharia brasileira

Henriques

Miguel

2017

Gest. Prod.

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Resumo: A modularidade é uma estratégia adotada por diversos setores industriais, seja no desenvolvimento de Palavras-chave: Modularidade; Modularidade de projeto; Modularidade de produção; Indústria automotiva.Abstract: Modularity is a strategy adopted by many industrial sectors, either in product development or in industrial production configuration. In this sense, this paper investigates the key elements of modularity in design and production, seeking to formulate a proposal aimed to assess and compare the degree of modularity specifically in the context of the Brazilian automotive industry. The comparison was done considering vehicles developed with the participation of Brazilian engineering centre. Five key conceptual elements of modularity in design and four other elements of modular production were extracted from the literature and applied in the selected units of analysis. As a main result, we developed a categorization matrix for analyzing the modular degree of six vehicles. Fiat Palio's design was considered as the highest degree of modularity in design and the GM plant at Gravataí (Celta) as the more typical modular organization within the studies vehicles and respective assemblers, based on the applied methodology.

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“…Product platforms with a high focus on shared units might restrict potential product variability [239]. Variable costs might increase due to the availability dependency over multiple products [240].…”

Section: State Of the Art Discussionmentioning

confidence: 99%

Automated joining element design for high product variety in the manufacturing industry

Eggink

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Product variety and the manufacturing complexity that it induces are continuously increasing. This poses a challenge in the product development process and, consequently, the design of joints. Joining elements define the manner in which a permanent joint is created between parts. Joining element design is an ambiguous manual task with limited automation solutions. Thus, it can lead to long, iterative, error-prone development trajectories that may result in costly rework. Hence, automation solutions for joining element design must be intelligent. However, simply ensuring the intelligent automation of joining element design is insufficient. Modular design, through the approaches of modularization and commonalization, enables manufacturers to cope with the complexity induced by product variety. Unfortunately, modular design approaches have not yet considered joining elements. Hence, this dissertation study sought to answer the following research question: "How can joining element design be automated for high-variety products?"This dissertation presents a framework for automating joining element design. The framework is structured into smaller design problems, which will guide designers through the process of designing joining elements. This structuring will also enable designers to evaluate and assess artificial intelligence (AI) for each design problem. Moreover, the design problems will enable designers to identify unused AI techniques, such as machine learning.These techniques were conceptualized and several were implemented for validation in this study. A market-validated database with automotive Body-in-White structures was used. The validation included the use of decision trees to predict joining technologies and the number of joining elements. Both prediction tasks seem promising to implement in early design phases due to their simplicity.Next, this study validated two approaches for predicting joining locations. The first was a straight-forward evolutionary algorithm for distributing spot welds over contact regions. However, this algorithm's performance fell off quickly for nontrivial design problems with high solution spaces.The second approach was to use convolutional neural networks to predict spot weld locations, which provided robust and promising results. This study first explored a voxel-based regression and classification task by drawing locations in a grid-like structure. Classification with a segmentation approach produced more robust results due to the spatial dependencies of classes. Supervised machine learning enabled the consideration of knowledge of successful designs in new design problems. This concept was subsequently enriched with nongeometric data using a branding approach. However, these multimodal machine learning models did not improve the joining locations. Furthermore, the models could not extract the i ii

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Platform development: implications for portfolio management

Cited by 11 publications

References 11 publications

Proyecto De Un Laboratorio De Riesgos Laborales Para La Institución Universitaria Politécnico Grancolombiano

Proyecto De Un Laboratorio De Riesgos Laborales Para La Institución Universitaria Politécnico Grancolombiano

Adoção da modularidade em produto e em produção na indústria automotiva: uma análise comparativa em projetos de veículos com participação da engenharia brasileira

Automated joining element design for high product variety in the manufacturing industry

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