A configuration design based method for platform commonization for product families

2004 ◽  
Vol 18 (1) ◽  
pp. 21-39 ◽  
Author(s):  
BRIAN CORBETT ◽  
DAVID W. ROSEN
Keyword(s):  
Design Space ◽  
Product Family ◽  
Combinatorial Design ◽  
Product Configuration ◽  
Configuration Design ◽  
Design Problems ◽  
Product Families ◽  
Assembly Design ◽  
Assembly Sequences ◽  
Design Requirements

Product families help companies reach customers in several different markets, lessen the time needed to develop new products, and reduce costs by sharing common components among many products. The product platform can be considered as a set of technologies, components, or functions, and their arrangements, that are utilized for more than one product. Configuration design focuses on the components in a product and their connections and relationships. Discrete, combinatorial design spaces are used to model design requirements regarding physical connections, module partitions, and assembly sequences for the product family. To ensure that products satisfy all design requirements, it is necessary to combine these design spaces into a common configuration space into which all requirements can be mapped. This paper presents computational methods for modeling and combining design spaces so those configurations can be identified that satisfy all constraints. A new representation of assembly sequences facilitates the development of an assembly design space, elements of which can be enumerated readily. Because the size of the combinatorial design spaces can become quite large, computational efficiency is an important consideration. A new designer guided method, called the partitioning method, is presented for decomposing configuration design problems in a hierarchical manner that enables significant reductions in design space sizes. An example of a family of automotive underbodies illustrates the application of the discrete design space approach to develop a common platform.

On combinatorial design spaces for the configuration design of product families

2001 ◽  
Vol 15 (2) ◽  
pp. 91-108 ◽  
Author(s):  
ZAHED SIDDIQUE ◽  
DAVID W. ROSEN
Keyword(s):  
Engineering Design ◽  
Design Space ◽  
Optimization Problems ◽  
Product Family ◽  
Product Variety ◽  
Combinatorial Design ◽  
Configuration Design ◽  
Design Problems ◽  
Engineering Design Problems ◽  
Space Modeling

For typical optimization problems, the design space of interest is well defined: It is a subset of Rn, where n is the number of (continuous) variables. Constraints are often introduced to eliminate infeasible regions of this space from consideration. Many engineering design problems can be formulated as search in such a design space. For configuration design problems, however, the design space is much more difficult to define precisely, particularly when constraints are present. Configuration design spaces are discrete and combinatorial in nature, but not necessarily purely combinatorial, as certain combinations represent infeasible designs. One of our primary design objectives is to drastically reduce the effort to explore large combinatorial design spaces. We believe it is imperative to develop methods for mathematically defining design spaces for configuration design. The purpose of this paper is to outline our approach to defining configuration design spaces for engineering design, with an emphasis on the mathematics of the spaces and their combinations into larger spaces that more completely capture design requirements. Specifically, we introduce design spaces that model physical connectivity, functionality, and assemblability considerations for a representative product family, a class of coffeemakers. Then, we show how these spaces can be combined into a “common” product variety design space. We demonstrate how constraints can be defined and applied to these spaces so that feasible design regions can be directly modeled. Additionally, we explore the topological and combinatorial properties of these spaces. The application of this design space modeling methodology is illustrated using the coffeemaker product family.

Platform Commonization With Discrete Design Spaces: Introduction of the Flow Design Space

2003 ◽  
Author(s):  
Brian P. Corbett ◽  
David W. Rosen
Keyword(s):  
Design Space ◽  
Product Family ◽  
Configuration Design ◽  
Function Form ◽  
Product Families ◽  
Core Function ◽  
Design Requirements ◽  
The Common ◽  
Space Approach ◽  
Common Platform

Many companies have adopted the usage of common platforms to support the development of product families. The problem addressed in this paper deals with the development of a common platform for an existing set of products that may or may not already form a product family. The common platform embodies the core function, form, and technology base shared across the product family. In this work, we focus on configuration aspects of the platform commonization problem to determine which components are in the platform and the relationships among these components. Configuration design spaces are discrete and combinatorial in nature, but not necessarily purely combinatorial, as certain combinations represent infeasible designs. By carefully forming discrete design spaces and applying constraints to them, feasible design regions can be found and their sizes predicted. The purpose of this paper is to outline our approach to defining configuration design spaces for engineering design, with an emphasis on the mathematics of the spaces and their combinations into larger spaces that more completely capture design requirements. A new design space that models flows among components is introduced. Other design spaces that model physical connectivity, functionality, and assembly considerations are summarized. An example of a family of rechargeable flashlights illustrates the application of the discrete design space approach to develop a common platform.

Product Family Configuration Reasoning Using Discrete Design Spaces

2000 ◽  
Author(s):  
Zahed Siddique ◽  
David W. Rosen
Keyword(s):  
Design Space ◽  
Design Method ◽  
Product Family ◽  
Configuration Design ◽  
Continuous Variables ◽  
Market Place ◽  
Product Families ◽  
Multiple Viewpoints ◽  
Design Reasoning ◽  
Common Platform

Abstract In the current market place companies need to deliver more variety with reduced time to market, lower prices and higher quality. These challenges have introduced the concept of developing a set of similar products using a common platform. Development of common platforms to support a family of products requires configuration reasoning. Configuration design spaces can be defined to facilitate platform and product family reasoning. For configuration design problems, the design space is much more difficult to define precisely (than the typical design space which is a subset of Rn, where n is the number of continuous variables), particularly when constraints are present. The purpose of this paper is to present a configuration design method that can be applied to two related problems: develop a common platform that satisfies requirements from multiple viewpoints, and generate members of a product family that also satisfy these requirements. To accomplish this objective, first design spaces are developed to model connectivity, functionality and assemblability considerations, then a common design space is developed to consider constraints from multiple viewpoints simultaneously. These design spaces are developed for both platforms and for product families. The application of this configuration design reasoning methodology is illustrated using a coffee maker product family.

Parallel Processing of Product Configuration for Cloud-Based Mass Customization Service Platform

2012 ◽  
Vol 532-533 ◽  
pp. 1196-1200
Author(s):  
Jun Hua Che ◽  
Bin Ma ◽  
Qian Zeng
Keyword(s):  
Parallel Processing ◽  
Mass Customization ◽  
Product Family ◽  
Product Configuration ◽  
Configuration Design ◽  
Service Platform ◽  
Abc Analysis ◽  
Massive Parallel Processing

The greatest feature of cloud-based mass customization service platform is massive parallel processing of information. So the good or bad of the parallel processing determines the precision and efficiency of cloud-based mass customization service platform. This paper brings up the method of parallel processing of configuration design for the cloud-based mass customization service platform. The parallel processing of product configuration is performed by ABC analysis, parallel BOM and product family. Finally this research has been applied for customization product: Gearbox, and has improved the efficiency of parallel processing for the cloud-based mass customization service platform.

scholarly journals Decomposition-Based Assembly Synthesis for In-Process Dimensional Adjustability

2002 ◽  
Author(s):  
Byungwoo Lee ◽  
Kazuhiro Saitou
Keyword(s):  
Design Process ◽  
Early Stage ◽  
Product Configuration ◽  
Two Dimensional ◽  
Design Phase ◽  
Assembly Design ◽  
Component Design ◽  
Assembly Sequences ◽  
Simple Rules ◽  
Final Design

This paper presents a method of assembly synthesis focused on the in-process adjustability, where assembly synthesis is defined as the decomposition of the end product design prior to the detailed component design phase. Focusing on the effect of joint configurations on dimensional integrity of complex assemblies, the method recursively decomposes a product configuration and assigns joint configurations according to simple rules, in order to achieve a designed dimensional adjustability and non-forced fit. The rules employed during the decomposition process are drawn from the previous works of assembly design. An augmented AND/OR graph is utilized to represent a process of assembly synthesis with the corresponding assembly sequences, and the algorithm for generating the AND/OR graph is discussed. The method is applied to two dimensional skeletons of product designs at very early stage of the design process. The relation of the assembly synthesis to Datum Flow Chain (Mantripragada and Whitney, 1998) is discussed. It is also shown that each final design from the assembly synthesis defines its own Datum Flow Chain.

scholarly journals Decomposition-Based Assembly Synthesis for In-Process Dimensional Adjustability

2003 ◽  
Vol 125 (3) ◽  
pp. 464-473 ◽  
Author(s):  
Byungwoo Lee ◽  
Kazuhiro Saitou
Keyword(s):  
Design Process ◽  
Early Stage ◽  
Product Configuration ◽  
Two Dimensional ◽  
Design Phase ◽  
Assembly Design ◽  
Component Design ◽  
Assembly Sequences ◽  
Simple Rules ◽  
Final Design

This paper presents a method of assembly synthesis focused on the in-process adjustability, where assembly synthesis is defined as the decomposition of the end product design prior to the detailed component design phase. Focusing on the effect of joint configurations on dimensional integrity of complex assemblies, the method recursively decomposes a product configuration and assigns joint configurations according to simple rules, in order to achieve a designed dimensional adjustability and non-forced fit. The rules employed during the decomposition process are drawn from the previous works of assembly design. An augmented AND/OR graph is utilized to represent a process of assembly synthesis with the corresponding assembly sequences, and the algorithm for generating the AND/OR graph is discussed. The method is applied to two dimensional skeletons of products without moving parts at very early stage of the design process. The relation of the assembly synthesis to Datum Flow Chain [1] is discussed. It is also shown that each final design from the assembly synthesis defines its own Datum Flow Chain.

Case Study: User Adoption of a Product Configuration Management System at a Modular Playground Equipment Producer

2006 ◽  
Author(s):  
Bethany M. Byron ◽  
Steven B. Shooter
Keyword(s):  
Management System ◽  
Product Family ◽  
Information Management System ◽  
Product Configuration ◽  
Training Methods ◽  
Product Families ◽  
Product Configuration Management ◽  
Storage And Retrieval ◽  
User Adoption

Product platform and product family strategies place tremendous demands on the efficient capture, storage, and retrieval of information in the form of product data. The user’s adoption of an information management system for product families and mass customization is critical for allowing the system to perform as it ought. The following is a case study at a major modular playground equipment producer undergoing the implementation of a new graphical-based configurator for managing its mass customized products. The case study examines the proliferation of software packages to perform configuration and the flow of information in the configuration process. Next, the new configurator is evaluated on its new features to capture, store, and reuse configurations and its visual appeal. Last, the paper addresses the personal behaviors and training methods used for increasing adoption and their success.

Product Configuration Design Based on Extensible Product Family for Mass Customization

2005 ◽  
Author(s):  
Shuyou Zhang ◽  
Harry H. Cheng
Keyword(s):  
Mass Customization ◽  
Machine Tools ◽  
Nearest Neighbor ◽  
Design Method ◽  
Product Family ◽  
New Product ◽  
Product Configuration ◽  
Basic Unit ◽  
Configuration Design ◽  
Nearest Neighbor Matching

A new product configuration design method based on extensible product family is presented in this paper. The extensible product family is a multi-layered model with extensible function, extensible principle, and extensible structure. Treating extensible element as a basic unit, the model can be used to associate extensible parts with reusable factors in the range from 0 to 1. The principle of configuration method has been implemented in software. Complicated rule editing and modification are handled by Ch, an embeddable C/C++ interpreter. Designers can establish and edit the configuration rules including formulas dynamically. According to the client requirements and nearest-neighbor matching, the results of the designed configuration can be obtained automatically. Furthermore, the multi-dimensional information about parameters and reusable factors can be displayed and analyzed graphically. If the client requirements or configuration rules are changed, the system can be easily re-configured to obtain designed results based on the new configuration quickly. The system has been successfully deployed and used to design complicated products with a large number of configurations and different specifications such as elevators, machine tools and smut-collectors.

Product Architectures Generation Under Uncertainty: Comparison Between Two Methods

2012 ◽  
Author(s):  
Marie-Lise Moullec ◽  
Marija Jankovic ◽  
Marc Bouissou ◽  
Jean-Claude Bocquet
Keyword(s):  
Design Space ◽  
Constraint Satisfaction Problem ◽  
Combinatorial Design ◽  
Computational Method ◽  
Preliminary Design ◽  
Design Problems ◽  
Complex Product ◽  
Advantages And Disadvantages ◽  
Modeling Process ◽  
Architecture Generation

Complex product architecture definition involves technological and architectural choices in order to reach defined system performances. These choices form a wide combinatorial design space whose complete exploration requires a computational method. The latter is made difficult because of the lack and the fuzziness of data and knowledge in preliminary design. To introduce this type of uncertainty, we have proposed an approach based on Bayesian nets: a Bayesian net architecture generation and clustering method is proposed. However, in recent research, lots of conceptual design problems were addressed with Constraint Satisfaction Problem (CSP). The purpose of this paper is to compare these two methods and advantages and challenges in view to design situations under uncertainty. The comparison consists in modeling a sample problem with both methods. The modeling process of each method is described, providing preliminary highlights on advantages and disadvantages of both methods. Then, the methods are evaluated in terms of modeling capabilities and easiness. The number of generated architectures and the execution time of each simulation are also analyzed with regard to the influence of uncertainty introduction in the models. The final objective is to determine which method seems to be the more appropriate to help designers in finding new innovative designs.

RESEARCH ON DESIGN METHOD OF DEMAND-DRIVEN PRODUCT CONFIGURATION FOR MASS CUSTOMIZATION

2011 ◽  
Vol 10 (01) ◽  
pp. 117-125 ◽  
Author(s):  
YAPING WANG ◽  
GUIHUA HAN ◽  
JIANGHUA GE ◽  
JINGRUI QI ◽  
JIANYUAN XU
Keyword(s):  
Mass Customization ◽  
Design Method ◽  
Product Family ◽  
Product Configuration ◽  
Configuration Design ◽  
Customer Demand ◽  
Dynamic Demand ◽  
Ontology Model ◽  
Family Model ◽  
Relationship Of

This paper proposed demand-driven personalized product configuration design method. A variety of customer orders were clustered and fuzzy transformed; using ontology's feature to establish customer demand ontology model; in order to enable the product family to meet the dynamic demand of customers, established mapping relationship of customer demands and product family; using ontology to express product family model, achieved mapping of customer needs ontology and product family ontology, and improved efficiency of product configuration. Finally, we take planetary reducer as an example to demonstrate the feasibility of the method.

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