Multi-Level Value-Driven Design Approaches for Product Family Design

2017 ◽  
Author(s):  
Sangjin Jung ◽  
Timothy W. Simpson ◽  
Christina Bloebaum
Keyword(s):  
Product Family ◽  
Optimization Methods ◽  
Value Functions ◽  
Product Family Design ◽  
Design Problems ◽  
Cost Performance ◽  
Best Value ◽  
Multi Level ◽  
Future Work ◽  
The Value Function

Companies usually launch families of products into the market to provide value to different segments based on different customer needs; however, most of the research on Value-Driven Design (VDD) in the literature has focused on modeling value functions and optimizing the design of single products, not families of products. In order to increase profit and minimize total cost for product design and manufacturing, VDD should be applicable to product family design. In this work, we propose a multi-level VDD approach for product family design by extending multidisciplinary design optimization methods. The multi-level VDD is applied to a family of front-loading washing machines to validate the effectiveness of the proposed approach. With this example, we demonstrate that design problems that optimize traditional objective functions (e.g., cost, performance) at each level do not necessarily maximize value when compared to an appropriate VDD formulation. On the other hand, when the value function is set as an objective function throughout the organization (company, product family, and product level), we find that the VDD formulation provides the best value. Future work based on these promising findings is also discussed.

Genetic Algorithms for Optimization of Building Envelopes and the Design and Control of HVAC Systems

2003 ◽  
Vol 125 (3) ◽  
pp. 343-351 ◽  
Author(s):  
L. G. Caldas ◽  
L. K. Norford
Keyword(s):  
Genetic Algorithms ◽  
Optimization Problems ◽  
Optimization Methods ◽  
Optimization Method ◽  
Hvac Systems ◽  
Design Problems ◽  
Building Walls ◽  
Building Form ◽  
And Control ◽  
Future Work

Many design problems related to buildings involve minimizing capital and operating costs while providing acceptable service. Genetic algorithms (GAs) are an optimization method that has been applied to these problems. GAs are easily configured, an advantage that often compensates for a sacrifice in performance relative to optimization methods selected specifically for a given problem, and have been shown to give solutions where other methods cannot. This paper reviews the basics of GAs, emphasizing multi-objective optimization problems. It then presents several applications, including determining the size and placement of windows and the composition of building walls, the generation of building form, and the design and operation of HVAC systems. Future work is identified, notably interfaces between a GA and both simulation and CAD programs.

Value-Driven Design Using Discipline-Based Decomposition for a Family of Front-Loading Washing Machines

2017 ◽  
Author(s):  
Sangjin Jung ◽  
Timothy W. Simpson ◽  
Christina Bloebaum
Keyword(s):  
Design Research ◽  
Value Function ◽  
Product Line ◽  
Target Market ◽  
Washing Machines ◽  
Multi Level ◽  
Line Level ◽  
Future Work ◽  
The Value Function ◽  
Corporate Level

In order to determine target market and price, and design products/components for a family of front-loading washing machines, the coordination for decision-making from the corporate level down to the product and ultimately component levels is required. However, existing design research for many products focuses on analyzing single or multiple disciplines, even though optimizing local performance does not guarantee minimizing total cost at the product line level or maximizing value at the company level. In this work, we apply a multi-level value-driven design (VDD) approach to optimize a family of front-loading washing machines using a discipline-based decomposition. The VDD solutions obtained using discipline-based decomposition (DD) are compared with those obtained using product-based decomposition (PD). Consequently, the multi-level VDD approach based on DD for the washer family provides better performance for attributes than PD, but we observed that DD for the washer family does not guarantee maximizing the value function compared to PD because of the larger numbers of subsystems and consistency-related variables. Ongoing and future work to address this problem are discussed.

A Platform Selection Approach Based on Product Family Ontology Modeling

2011 ◽  
Author(s):  
Soon Chong Johnson Lim ◽  
Ying Liu ◽  
Wing Bun Lee
Keyword(s):  
Product Family ◽  
Product Family Design ◽  
Laptop Computer ◽  
Product Representation ◽  
Faceted Search ◽  
Design Concepts ◽  
Selection Approach ◽  
Current Product ◽  
Representation Scheme ◽  
Future Work

Product family design is probably the most widely adopted strategy for product realization in mass customization paradigm. With the ever-increasing product offerings in consumer market, current product representation schemes are restricted by their limited capability in handling multiple conceptual relationships amongst product components and rich semantic annotations associated with different design concepts. Previously, we have studied and proposed an ontology-based information representation scheme for product family design, which offers a promising solution to address the aforementioned challenges. In this study, we suggest a new commonality metric and a faceted platform selection approach, which are both created for ontology-based product family representation models. Utilizing this metric and faceted search, we discuss the advantages of our approach compared to existing modeling possibilities. We also exemplify the applications of our proposal towards an optimal configuration of product variants using a case study of four laptop computer families. Finally, we conclude this paper with some indications for future work.

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.

Product Family and Product Platform Benchmarking With Commonality and Variety Indices

2017 ◽  
Author(s):  
Timothy W. Simpson
Keyword(s):  
Product Family ◽  
Lead Times ◽  
Product Platform ◽  
Effective Strategy ◽  
Product Family Design ◽  
Product Families ◽  
Novel Approach ◽  
Future Work ◽  
Common Platform

As companies are pressured to reduce costs and lead-times while increasing variety, the need to design products based on common platform “elements” is growing. Product family design has become an effective strategy to meet this challenge, but companies still struggle with assessing how “good” their product family is. Companies routinely benchmark their individual products, but they struggle with how to benchmark their platforms and product families against their competitors. A novel approach for product family benchmarking is introduced in this paper integrating commonality and variety indices to compare competing product families and their platform “elements”. An example involving two families of men’s razors is presented to illustrate the approach. Limitations of the approach and future work are also discussed.

Analytical target cascading for multi-level supply chain decisions in cloud perspective

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Yun Huang ◽  
Kaizhou Gao ◽  
Kai Wang ◽  
Haili Lv ◽  
Fan Gao
Keyword(s):  
Supply Chain ◽  
Supplier Selection ◽  
Product Family ◽  
Optimization Method ◽  
Analytical Target Cascading ◽  
Product Family Design ◽  
Decision Rights ◽  
Content Type ◽  
Target Cascading ◽  
Multi Level

PurposeThe purpose of this paper is to adopt a three-stage cloud-based management system for optimizing greenhouse gases (GHG) emission and marketing decisions with supplier selection and product family design in a multi-level supply chain with multiple suppliers, one single manufacturer and multiple retailers.Design/methodology/approachThe manufacturer purchases optional components of a certain functionality from his alternative suppliers and customizes a set of platform products for retailers in different independent market segments. To tackle the studied problem, a hierarchical analytical target cascading (ATC) model is proposed, Jaya algorithm is applied and supplier selection and product family design are implemented in its encoding procedure.FindingsA case study is used to verify the effectiveness of the ATC model in solving the optimization problem and the corresponding algorithm. It has shown that the ATC model can not only obtain close optimization results as a central optimization method but also maintain the autonomous decision rights of different supply chain members.Originality/valueThis paper first develops a three-stage cloud-based management system to optimize GHG emission, marketing decisions, supplier selection and product family design in a multi-level supply chain. Then, the ATC model is proposed to obtain the close optimization results as central optimization method and also maintain the autonomous decision rights of different supply chain members.

scholarly journals Assessing the Performance of Interactive Multiobjective Optimization Methods

2021 ◽  
Vol 54 (4) ◽  
pp. 1-27
Author(s):  
Bekir Afsar ◽  
Kaisa Miettinen ◽  
Francisco Ruiz
Keyword(s):  
Multiobjective Optimization ◽  
Decision Maker ◽  
Optimization Problems ◽  
Optimization Methods ◽  
Interactive Methods ◽  
Value Functions ◽  
Technical Aspects ◽  
Preference Information ◽  
Multiobjective Optimization Problems ◽  
Human Decision

Interactive methods are useful decision-making tools for multiobjective optimization problems, because they allow a decision-maker to provide her/his preference information iteratively in a comfortable way at the same time as (s)he learns about all different aspects of the problem. A wide variety of interactive methods is nowadays available, and they differ from each other in both technical aspects and type of preference information employed. Therefore, assessing the performance of interactive methods can help users to choose the most appropriate one for a given problem. This is a challenging task, which has been tackled from different perspectives in the published literature. We present a bibliographic survey of papers where interactive multiobjective optimization methods have been assessed (either individually or compared to other methods). Besides other features, we collect information about the type of decision-maker involved (utility or value functions, artificial or human decision-maker), the type of preference information provided, and aspects of interactive methods that were somehow measured. Based on the survey and on our own experiences, we identify a series of desirable properties of interactive methods that we believe should be assessed.

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