Optimal product family design with platform modularity and component sharing under uncertain environment

2021 ◽  
pp. 1-17
Author(s):  
Qinyu Song ◽  
Yaodong Ni ◽  
Dan Ralescu
Keyword(s):  
Theoretical Model ◽  
Economies Of Scale ◽  
Product Family ◽  
New Product ◽  
Optimal Solutions ◽  
Product Family Design ◽  
Maximum Profit ◽  
Sharing Strategy ◽  
End Products ◽  
Low Costs

The customer demands of various products bring a challenge for manufacturers. They have to design customized products while maintaining economies of scale and low costs. In this paper, to address this challenge, four approaches are argued to help companies find out the optimal solutions of products’ performance and the maximum profit: (i) only platform modularity without component sharing (ii) only component sharing without platform modularity, (iii) using both platform modularity and component sharing to develop products, or iv) the products are developed individually from a given unshared components set. A theoretical model is proposed and the most profitable approach is found to develop a whole new product family when uncertainty exists in the customer demand and economies of scale with pre-defined parameters. We find that, when consumers’ valuation is considered, the manufacturer may prefer to adopt platform or component sharing individually rather than combining them because the performance of high-end products using platform and component sharing strategies is worse than that using two strategies separately. If platform and component sharing are adopted, the high-end product is under designed, but the manufacturer can benefit from economies of scale. When economies of scale of the platform are greater than or equal to that of component sharing, the optimal performance level of low-end products under platform strategy is lower than that under component sharing strategy. Finally, the detailed numerical analysis provides support for the feasibility and effectiveness of the model.

Self-configuring components approach to product variant development

2004 ◽  
Vol 18 (1) ◽  
pp. 41-54 ◽  
Author(s):  
MICHELE GERMANI ◽  
FERRUCCIO MANDORLI
Keyword(s):  
Mass Customization ◽  
Economies Of Scale ◽  
Low Cost ◽  
Product Family ◽  
Theoretical Aspect ◽  
New Product ◽  
Consumer Electronics ◽  
Product Platform ◽  
Functional Requirements ◽  
Definition Of

The use of modularity in the design of a new product or the adoption of a product platform, as the base to define new solutions within a product family, offers the company a chance to meet diverse customer needs at low cost because of economies of scale in all phases of the product's life cycle. At present, the concept of modularity in product design is becoming widely used in many industries such as automobiles and consumer electronics. However, if modularity and mass customization have attracted the interest of industries and researchers, the greatest efforts have been focused on the theoretical aspect whereas the related design support technologies have been only partially implemented. In this context, our intent is to develop highly reusable models, which are able to reconfigure themselves on the basis of new functional requirements. The proposed approach is based on the definition of what we callself-configuring componentsandmultiple-level functions. To describe the approach, a practical example related to the design of modules for woodworking machines is reported.

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.

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.

Attribute Attribute-Based Clustering for Product Family Design

2007 ◽  
Author(s):  
Xiaoli Ye ◽  
John K. Gershenson
Keyword(s):  
Product Family ◽  
New Product ◽  
Design Tool ◽  
Product Family Design ◽  
Product Attributes ◽  
Product Families ◽  
Qualitative Design ◽  
Product Platforms ◽  
Target Values ◽  
The Ideal

As manufacturers are forced by today’s marketplace to provide nearly customized products to satisfy individual customer requirements and simultaneously achieve economies of scale during production, product family design and platform-based product development have garnered their attention. Determining which elements (attributes, functions, components, etc.) should be made common, variable, or unique, across a product family is the critical step in the successful implementation of product families and product platforms. Therefore, the inherent challenge in product family design is to balance the tradeoff between product commonality (how well the components and functions can be reused across a product family) and variety (the range of different products in a product family). There are opportunities to develop tools to directly aid in addressing the commonality/variety tradeoff at the product family planning stage in a way that supports the engineering design process. In this paper, we develop a matrix-based, qualitative design tool – the Attribute-Based Clustering Methodology (ABCM) that enables the design of product families to better satisfy the ideal commonality/variety tradeoff as determined by a company’s competitive focus. The ABCM is used to identify component commonality opportunities in product families without sacrificing product variety by analyzing product attributes across the product family. This paper focuses on the ABCM as used in new product family design and how the ABCM can be used to cluster product attributes into potential modules and product platforms. It is intended as a starting place, an opening set of questions, and as a framework for the general solution to the problem of a qualitative design tool for product family design that directly address the commonality/variety tradeoff. Development of the ABCM starts with the classification of existing product attributes into three categories: common, unique, and variable. The attributes are then clustered into platforms and differentiating modules based on their occurrences, target value ranges (partitioning the target values for each product attribute into achievable ranges), and the manner in which the range changes across the entire target market segments. The ABCM can be used as a qualitative guideline in product family design. In new product family design, it can be used to identify which elements (functions and components) should be clustered into a common platform and which should be clustered into differentiating modules based on an analysis of the product attributes, their occurrences, and their target values across the product family. In product family redesign, the ABCM can be used to identify any elements that are inappropriately included in a platform or inappropriately clustered into differentiating modules by comparing the ideal clustering with the actual clustering.

scholarly journals Diversity minimization through part combination – a Portuguese railway infrastructure case study

2020 ◽  
Vol 7 (1) ◽  
pp. 86-94
Author(s):  
Diogo Rechena ◽  
Luís Sousa ◽  
Virgínia Infante ◽  
Elsa Henriques
Keyword(s):  
Economies Of Scale ◽  
Product Family ◽  
Cost Effective ◽  
Added Value ◽  
Small Scale ◽  
Railway Infrastructure ◽  
Sustainable Services ◽  
Market Needs ◽  
Design Diversity ◽  
Requirement Changes

Abstract With increasing market needs for product and service variety, companies struggle to provide diversity in cost-effective ways. Through standardization of components with a low perceived added value, companies can take advantage of economies of scale while maintaining product diversity. Railway infrastructure managers face similar challenges of providing economically sustainable services while dealing with the costs of maintaining the system diversity. Typically, unintended design diversity stems from design practices in which existing solutions are not reused for new problems and new solutions are rarely planned considering the dynamics of requirement changes. In this paper we provide a methodology to assess how to standardize different designs to minimize design diversity and to assess design divergence in a product family. The developed methodology is able to take into account any set of standardization compatibility constraints that the user can define. The methodology was applied in the context of a small-scale railway infrastructure manager using a dataset of 223 unique designs of functionally similar components from its electrification system. Depending on the activated compatibility constraints, results indicate that over 60% of components can be reduced to a set of 86 unique designs.

A Market-Based Design Strategy for a Universal Product Family

2012 ◽  
Vol 134 (11) ◽  
Author(s):  
Seung Ki Moon ◽  
Daniel A. McAdams
Keyword(s):  
Mass Customization ◽  
Universal Design ◽  
Product Family ◽  
Cost Effective ◽  
Differentiated Products ◽  
Product Family Design ◽  
Design Strategies ◽  
Market Segments ◽  
Light Duty

Companies that generate a variety of products and services are creating, and increasing research on, mass-customized products in order to satisfy customers’ specific needs. Currently, the majority of effort is focused on consumers who are without disabilities. The research presented here is motivated by the need to provide a basis of product design methods for users with some disability—often called universal design (UD). Product family design is a way to achieve cost-effective mass customization by allowing highly differentiated products serving distinct market segments to be developed from a common platform. By extending concepts from product family design and mass customization to universal design, we propose a method for developing and evaluating a universal product family within uncertain market environments. We will model design strategies for a universal product family as a market economy where product family platform configurations are generated through market segments based on a product platform and customers’ preferences. A coalitional game is employed to evaluate which design strategies provide more benefit when included in the platform based on the marginal profit contribution of each strategy. To demonstrate an implementation of the proposed method, we use a case study involving a family of light-duty trucks.

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