Incorporating Security Considerations Into Optimal Product Architecture and Component Sharing Decision in Product Family Design

2010 ◽  
Author(s):  
Alvaro J. Rojas Arciniegas ◽  
Harrison M. Kim
Keyword(s):  
A Priori ◽  
Product Family ◽  
Third Party ◽  
Product Architecture ◽  
Decision Making Process ◽  
Sensitive Information ◽  
Product Family Design ◽  
Multiple Factors ◽  
Common Structure ◽  
The Family

Multiple factors affect the decisions of selecting the appropriate components to share in product family design. Some of the challenges that the designers face are maintaining uniqueness and the desired performance in each variant while taking advantage of a common structure. In this paper, the sharing decision making process is analyzed for the case when a firm knows a priori that some of the components contain sensitive information that could be exposed to the user, third-party manufacturers, or undesired agents; thence, it is important to enclose it and protect it. Two important aspects to consider are defining the architecture of the product while protecting the sensitive information. This paper proposes tools to help the designers to identify components that are candidates for sharing among the family and finds the most desirable component arrangement that facilitates sharing while protecting the sensitive information that has been previously identified. The proposed framework is applied to three printers in which the architecture used for the ink cartridges and printheads are significantly different. Third-party manufacturers and remanufacturers offer their own alternatives for these subsystems (ink cartridges and printheads) since the customer for printer supplies is always looking for a cheaper alternative; meanwhile, the OEMs attempt to secure their products and retain their customers with original supplies. Having identified the sensitive components for each printer, the optimal clustering strategy is found, as well as the set of components that are candidates for sharing, according to their connectivity and the security considerations.

Production Cost Modeling to Support Product Family Design Optimization

2003 ◽  
Author(s):  
Jaeil Park ◽  
Timothy W. Simpson
Keyword(s):  
Production Cost ◽  
Cost Model ◽  
Product Family ◽  
Optimization Methods ◽  
Production Costs ◽  
Product Platform ◽  
Product Family Design ◽  
The Family ◽  
The Individual ◽  
Decision Based Design

Product family design involves carefully balancing the commonality of the product platform with the distinctiveness of the individual products in the family. While a variety of optimization methods have been developed to help designers determine the best design variable settings for the product platform and individual products within the family, production costs are thought to be an important criterion to choose the best platform among candidate platform designs. Thus, it is prerequisite to have an appropriate production cost model to be able to estimate the production costs incurred by having common and variant components within a product family. In this paper, we propose a production cost model based on a production cost framework associated with the manufacturing activities. The production cost model can be easily integrated within optimization frameworks to support a Decision-Based Design approach for product family design. As an example, the production cost model is utilized to estimate the production costs of a family of cordless power screwdrivers.

Identification of Product Family Platforms Using Pattern Recognition

2011 ◽  
Author(s):  
Dane Freeman ◽  
Dongwook Lim ◽  
Elena Garcia ◽  
Dimitri Mavris
Keyword(s):  
Pattern Recognition ◽  
A Priori ◽  
Product Family ◽  
Combinatorial Problem ◽  
Equivalence Relations ◽  
Product Family Design ◽  
Product Families ◽  
Cluster Membership ◽  
End Products ◽  
Fuzzy C Means Clustering

In product family design the goal is to generate a set of lowest cost products that target specific market niches. Sharing components, called platforms, between different products can minimize duplication of effort, thereby lowering family costs. However, if the products’ requirements are too dissimilar, sharing components may compromise the end product; such variance will lead to lower end products being overdesigned and/or higher end products being underdesigned. It is important to identify which components are similar enough, so that sharing does not compromise the individual products’ performances. Most existing product family design methods make decisions a priori about platforms; constraining platforms to be used by every product in the family, or not at all. Methods that simultaneously optimize component sharing and design variable settings have the potential to find better families because product subsets may be more similar to each other than to other subsets of products. Allowing components to be shared between any subset of family members leads to a very large combinatorial problem, and considering large product families can be computationally prohibitive. This paper proposes a method to identify possible sets of product family platforms by using the pattern recognition technique of fuzzy c-means clustering on component subspaces. Component subspaces are taken from a database of generated design points for the whole family. If components from different products are similar enough to be grouped into the same cluster, then those components could possibly become the same platform. Fuzzy equivalence relations can be extracted from the cluster membership functions that show the binary relationship from one products’ component to a different products’ component. Ultimately, this method can be used as a platform identification heuristic in a larger product family design methodology. This method is demonstrated by applying it to find possible common components in a family of universal electric motors.

Decision Support for Strategic Redesign

2008 ◽  
Author(s):  
Matthew K. Chamberlain ◽  
Janet K. Allen ◽  
Farrokh Mistree
Keyword(s):  
Decision Support ◽  
Design Research ◽  
Product Family ◽  
Constructal Theory ◽  
Engineering Systems ◽  
Product Family Design ◽  
Original Design ◽  
Performance Levels ◽  
The Family ◽  
A Company

Researchers have paid relatively little attention to the fact that most of what is considered design is more like redesign than original design. Redesign activities are characterized by an attempt to leverage experience, knowledge, and the capital that a company has already invested into existing engineering systems. In this paper, a method for undertaking strategic redesign is proposed and explained. This method includes support for designers making decisions in redesign problems when there exist systems to be leveraged and multiple new systems to be created. In addition, strategy is introduced to the problem through the consideration that new systems may not be offered all at once, as is often assumed in product family design research. In this paper, the aim of the designer is assumed to be a creation, through redesign, of a series of new systems with desirable and distinct performance levels. In addition, a plan is required to involve as little redesign effort throughout the life of the family of systems as possible. The proposed approach is based upon the concepts of Constructal Theory and previous work to create methods for the design of mass customized families of systems. In addition, two metrics are developed to represent considerations unique to redesign as opposed to original design. These metrics for redesign effort and commonality value are utilized in the overall objective formulation for the proposed approach to redesign. Through a simple redesign scenario involving a family of universal motors, it is shown that the overall approach proposed can lead the designer towards promising redesign plans involving leveraging of existing systems, but that the constructal-inspired approach in and of itself has certain limitations when applied to redesign.

Development of a Production Cost Estimation Framework for Product Family Design

2004 ◽  
Author(s):  
Jaeil Park ◽  
Timothy W. Simpson
Keyword(s):  
Cost Estimation ◽  
Production Cost ◽  
Economies Of Scale ◽  
Product Family ◽  
Production Costs ◽  
Main Task ◽  
Primary Concern ◽  
Product Family Design ◽  
Design Variables ◽  
The Family

The main task of a product family designer is to decide the right components/design variables to share among products to maintain economies of scale with minimum sacrifice in the performance of each product in the family. The decisions are usually based on several criteria, but production cost is of primary concern. Estimating the production cost of a family of products involves estimating the production cost of each product in the family including the cost effects of common and variant components/design variables in the family. In this paper, we introduce a production cost estimation framework for product family design based on Activity-Based Costing (ABC), which is composed of three stages: (1) allocation, (2) estimation, and (3) analysis. In the allocation stage, the production activities that are necessary to produce all of the products in the family are identified and modeled with an activity table, a resource table, and an activity flow. To allocate the activities to products, a product family structure is represented by a hierarchical classification of the items that form the product family. In the estimation stage, production costs are estimated by converting the production activities to costs using key cost drivers that consume main resources. In the analysis stage, components/design variables for product family design are investigated with resource sharing methods through activity analysis. As an example, the proposed framework is applied to estimate the production cost of a family of cordless power screwdrivers.

Modular Platform-Based Product Family Design

2000 ◽  
Author(s):  
Javier P. Gonzalez-Zugasti ◽  
Kevin N. Otto
Keyword(s):  
Product Family ◽  
Product Platform ◽  
Product Family Design ◽  
Optimum Degree ◽  
Multiple Products ◽  
The Family ◽  
Subsystem Design ◽  
The Common ◽  
Modular Platform ◽  
The Individual

Abstract In this paper we present a method for designing families of products built onto modular platforms. A product platform is the set of components and subsystems shared across multiple products offered by a firm. A modular platform is one that allows for swapping of modules to configure multiple products in a family. The problem of designing a family of products based on such a platform is formulated as an optimization exercise, from which an implementation is derived. The method allows for the design of the modules that are shared across multiple members of the family, or the platform, as well as the portions of the products that are individually designed, or the variants. The result is a candidate design for the product family: both the combination of which modules should be shared and across which of the products, and the desired settings for the shared modules and the individual portions of each variant. The procedure is illustrated by an example of the telecommunications subsystem design for a set of spacecraft. The optimum degree of commonality for the set of products is found, as well as optimum settings for the common modules.

Merge-Based Design: A New Method for Managing Variety and Improving Customization

2007 ◽  
Author(s):  
Fabrice Alizon ◽  
Callida Williams ◽  
Steven B. Shooter ◽  
Timothy W. Simpson
Keyword(s):  
Product Family ◽  
Product Variety ◽  
Original Method ◽  
New Method ◽  
Common Structure ◽  
Internal Structures ◽  
The Family ◽  
Final Design ◽  
Single Use

With markets becoming more and more fragmented, the management of product variety becomes even more critical. Variety management needs to be continuously improved, especially for highly customized products. Although new techniques are constantly being developed, variety is still an issue, and there is room for complementary assistance to manage variety in the final design. In this context, we propose an original method — merge-based design — to manage variety in a product family better. The proposed method targets the already-tailored (unique) components to reduce the number of variant components in the family. Merge-based design also facilitates customization by enabling designers to reduce non-beneficial variety within a family. The proposed method is described and then illustrated via a case study involving two existing internal structures from single-use cameras. Finally, to highlight for improving customization, a proposed new camera is created using the resulting common structure with a different exterior casing. This new method can be applied during detailed studies as well as in the early stages of the design process.

scholarly journals Further steps on the reconstruction of convex polyominoes from orthogonal projections

2021 ◽  
Author(s):  
Paolo Dulio ◽  
Andrea Frosini ◽  
Simone Rinaldi ◽  
Lama Tarsissi ◽  
Laurent Vuillon
Keyword(s):  
Discrete Geometry ◽  
Convex Subset ◽  
Convex Sets ◽  
A Priori ◽  
Orthogonal Projections ◽  
Reconstruction Process ◽  
Combinatorial Properties ◽  
The Family ◽  
Discrete Counterpart ◽  
Interior Part

AbstractA remarkable family of discrete sets which has recently attracted the attention of the discrete geometry community is the family of convex polyominoes, that are the discrete counterpart of Euclidean convex sets, and combine the constraints of convexity and connectedness. In this paper we study the problem of their reconstruction from orthogonal projections, relying on the approach defined by Barcucci et al. (Theor Comput Sci 155(2):321–347, 1996). In particular, during the reconstruction process it may be necessary to expand a convex subset of the interior part of the polyomino, say the polyomino kernel, by adding points at specific positions of its contour, without losing its convexity. To reach this goal we consider convexity in terms of certain combinatorial properties of the boundary word encoding the polyomino. So, we first show some conditions that allow us to extend the kernel maintaining the convexity. Then, we provide examples where the addition of one or two points causes a loss of convexity, which can be restored by adding other points, whose number and positions cannot be determined a priori.

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