Optimization of production parameters based on a two-stage information content approach—a case study
详细信息 查看全文
- 作者：Luis Alberto Rodríguez-Picón
- 关键词：Information ; Uncertainty ; Normal distribution ; Probability ; Functional requirements ; Design of parameters
- 刊名：The International Journal of Advanced Manufacturing Technology
- 出版年：2017
- 出版时间：February 2017
- 年：2017
- 卷：88
- 期：5-8
- 页码：2019-2027
- 全文大小：
- 刊物类别：Engineering
- 刊物主题：Industrial and Production Engineering; Media Management; Mechanical Engineering; Computer-Aided Engineering (CAD, CAE) and Design;
- 出版者：Springer London
- ISSN：1433-3015
- 卷排序：88
文摘
Any organization can be defined as a system whose control is governed by the flow of information across all systems to which it belongs. Information is defined as an infinite-dimensional entity that is constantly moving and being assessed through mechanisms and control systems in order to achieve a goal. This article presents an approach for design of parameters based on information content. The development of a product is evaluated from the initial concept to the optimal design of its production parameters. In this approach, the values of a set of design parameters related to functional requirements are considered. The behavior of these functional requirements is modeled by a Gaussian distribution, which represents the design distribution. Once the product is produced in mass, a Gaussian distribution also models the behavior of the functional requirements and represents the process distribution. The intersection between distributions can be seen as a common range that describes the compliance with the functional requirements. As the process distribution approaches the most to the design distribution, the best functional requirements are met. Best levels of the parameters of the case study were defined based on this approach, which enables to reduce the variation on the response variable.