scholarly journals TWO-LEVEL OPTIMIZATION OF PRODUCT FAMILIES: APPLICATION TO A PRODUCT FAMILY OF WATER HOSE BOXES

2021 ◽  
Vol 1 ◽  
pp. 3259-3268
Author(s):  
Sebastian Rötzer ◽  
Martin Le Bourgeois ◽  
Dominik Thoma ◽  
Markus Zimmermann
Keyword(s):  
Numerical Optimization ◽  
Product Family ◽  
Customer Requirements ◽  
Product Complexity ◽  
Product Families ◽  
Industrial Practice ◽  
Technical Requirements ◽  
Design Variables ◽  
Actual Design ◽  
Assignment Scheme

AbstractIncreasing product complexity and individual customer requirements make the design of optimal product families difficult. Numerical optimization supports optimal design but must deal with the following challenges: many design variables, non-linear or discrete dependencies, and many possibilities of assigning shared components to products. Existing approaches use simplifications to alleviate those challenges. However, for use in industrial practice, they often use irrelevant commonality metrics, do not rely on the actual design variables of the product, or are unable to treat discrete variables. We present a two-level approach: (1) a genetic algorithm (GA) to find the best commonality scheme (i.e., assignment scheme of shared components to products) and (2) a particle swarm optimization (PSO) to optimize the design variables for one specific commonality scheme. It measures total cost, comprising manufacturing costs, economies of scales and complexity costs. The approach was applied to a product family consisting of five water hose boxes, each of them being subject to individual technical requirements. The results are discussed in the context of the product family design process.

A Metric for Evaluating Design Commonality in Product Families

1998 ◽  
Vol 122 (4) ◽  
pp. 403-410 ◽  
Author(s):  
Sridhar Kota ◽  
Kannan Sethuraman ◽  
Raymond Miller
Keyword(s):  
Product Family ◽  
Objective Measure ◽  
Value Added ◽  
New Product ◽  
Product Line ◽  
Product Complexity ◽  
Product Families ◽  
Market Strategy ◽  
Customer Base ◽  
Market Needs

Many companies develop a market strategy built around a family of products. These companies regularly add new product variations to the family in order to meet changing market needs or to attract a broader customer base. Although the core functionality remains essentially unchanged across the products within a family, new functions, feature combinations and technologies are incorporated into each new product. If allowed to grow unchecked, these component variations, commonly referred to as “complexity”, can result in a loss of productivity or quality. The challenge lies in an effective management of product variations in the design studio and on the manufacturing floor. The key is to minimize non-value added variations across models within a product family without limiting customer choices. In this paper we discuss the factors that contribute to product complexity in general, and present an objective measure, called the Product Line Commonality Index, to capture the level of component commonality in a product family. Through our Walkman case study, we present a simple yet powerful method of benchmarking product families1. This method gauges the family’s ability to share parts effectively (modularity) and to reduce the total number of parts (multi-functionality). [S1050-0472(00)02704-5]

Design for Mass Customization by Developing Product Family Architecture

1998 ◽  
Author(s):  
Mitchell M. Tseng ◽  
Jianxin Jiao
Keyword(s):  
Product Development ◽  
Mass Customization ◽  
Product Family ◽  
Customer Requirements ◽  
Market Positioning ◽  
Product Families ◽  
Integration Platform ◽  
Product Family Architecture ◽  
Realization Process ◽  
Product Realization

Abstract Mass customization is becoming an important agenda in industry and academia alike. This paper deals with mass customization from a product development perspective. A framework of design for mass customization (DFMC) by developing product family architecture (PFA) is presented. To deal with tradeoffs between diversity of customer requirements and reusability of design and process capabilities, DFMC advocates shifting product development from designing individual products to designing product families. As the core of DFMC, the concept of PFA is developed to assist different functional departments within a manufacturing enterprise to work together cohesively. A PFA describes variety and product families and performs as a generic product platform for product differentiation in which individual customer requirements can be satisfied through systematic decisions of developing product variants. Based on such a PFA, the DFMC framework provides a unifying integration platform for synchronizing market positioning, soliciting customer requirements, increasing reusability, and enhancing manufacturing scale of economy across the entire product realization process.

Comprehensive Product Platform Planning (CP3) Framework

2011 ◽  
Vol 133 (10) ◽  
Author(s):  
Souma Chowdhury ◽  
Achille Messac ◽  
Ritesh A Khire
Keyword(s):  
Planning Process ◽  
Continuous Optimization ◽  
Product Family ◽  
Mapping Function ◽  
Mixed Integer ◽  
Product Platform ◽  
Production Volume ◽  
Product Families ◽  
Product Platforms ◽  
Design Variables

Development of a family of products that satisfies different market niches introduces significant challenges to today’s manufacturing industries—from development time to aftermarket services. A product family with a common platform paradigm offers a powerful solution to these daunting challenges. This paper presents a new approach, the Comprehensive Product Platform Planning (CP3) framework, to design optimal product platforms. The CP3 framework formulates a generalized mathematical model for the complex platform planning process. This model (i) is independent of the solution strategy, (ii) allows the formation of sub-families of products, (iii) allows the simultaneous identification of platform design variables and the determination of the corresponding variable values, and (iv) seeks to avoid traditional distinctions between modular and scalable product families from the optimization standpoint. The CP3 model yields a mixed integer nonlinear programming problem, which is carefully reformulated to allow for the application of continuous optimization using a novel Platform Segregating Mapping Function (PSMF). The PSMF can be employed using any standard global optimization methodology (hence not restrictive); particle swarm optimization has been used in this paper. A preliminary cost function is developed to represent the cost of a product family as a function of the number of products manufactured and the commonality among these products. The proposed CP3 framework is successfully implemented on a family of universal electric motors. Key observations are made regarding the sensitivity of the optimized product platform to the intended production volume.

Design for Robustness of Modular Product Families for Current and Future Markets

2001 ◽  
Author(s):  
Lan Jiang ◽  
Venkat Allada
Keyword(s):  
Product Family ◽  
Search Space ◽  
Quality Characteristic ◽  
Control Factor ◽  
Customer Requirements ◽  
Product Families ◽  
Modular Product ◽  
Time Period ◽  
The Future ◽  
Noise Factors

Abstract This paper presents a modified Taguchi methodology to improve the robustness of modular product families against changes in customer requirements. The general research questions posed in this paper are: (1) How to effectively design a product family (PF) that is robust enough to accommodate future customer requirements? (2) How far into the future should the designers look to design a robust product family? An example of a simplified vacuum product family is used to illustrate our methodology. In the example, the customer requirements are selected as signal factors; the future changes of customer requirements are selected as noise factors; an index called the quality characteristic (QC) is set to evaluate the product vacuum family; and the module instance matrix (M) is selected as the control factor. Initially a relation between the objective function (QC) and the control factor (M) is established, and then the search space is systemically explored using the simplex method to determine the optimum M and the corresponding QC values. Next, various noise levels at different time points are introduced into the system. For each noise level, the optimal values of M and QC are computed and plotted on a QC-chart. The tunable time period of the control factor (in the example, the module matrix, M) is computed using the QC-chart. The tunable time period represents the maximum time for which a given module matrix can be used to satisfy the current and future customer needs. Finally, a robustness index is used to break up the tunable time period into suitable time periods that the designers should focus on while designing product families.

Products' Shared Visual Features Do Not Cancel in Consumer Decisions

2015 ◽  
Vol 137 (7) ◽  
Author(s):  
Ping Du ◽  
Erin F. MacDonald
Keyword(s):  
Consumer Preferences ◽  
Product Family ◽  
Image Features ◽  
Visual Features ◽  
Cognitive Responses ◽  
Product Family Design ◽  
Product Complexity ◽  
Product Families ◽  
Mass Customisation ◽  
Model C

Consumers' product purchase decisions typically involve comparing competing products' visual features and functional attributes. Companies strive for “product differentiation” (Liu et al., 2013, “Product Family Design Through Ontology-Based Faceted Component Analysis, Selection, and Optimization,” ASME J. Mech. Des., 135(8), p. 081007; Thevenot and Simpson, 2009, “A Product Dissection-Based Methodology to Benchmark Product Family Design Alternatives,” ASME J. Mech. Des., 131(4), p. 041002; Kota et al., 2000, “A Metric for Evaluating Design Commonality in Product Families,” ASME J. Mech. Des., 122(4), pp. 403–410; Orfi et al. 2011, “Harnessing Product Complexity: Step 1—Establishing Product Complexity Dimensions and Indicators,” Eng. Econ., 56(1), pp. 59–79; and Shooter et al. 2005, “Toward a Multi-Agent Information Management Infrastructure for Product Family Planning and Mass Customisation,” Int. J. Mass Customisation, 1(1), pp. 134–155), which makes consumers' product comparisons fruitful but also sometimes challenging. Psychologists who study decision-making have created models of choice such as the cancellation-and-focus (C&F) model. C&F explains and predicts how people decide between choice alternatives with both shared and unique attributes: The shared attributes are “canceled” (ignored) while the unique ones have greater weight in decisions. However, this behavior has only been tested with text descriptions of choice alternatives. To be useful to designers, C&F must be tested with product visuals. This study tests C&F under six conditions defined by: The representation mode (text-only, image-only, and image-with-text) and presentation (sequentially or side-by-side) of choice alternatives. For the products tested, C&F holds for only limited situations. Survey and eye-tracking data suggest different cognitive responses to shared text attributes versus shared image features: In text-only, an attribute's repetition cancels its importance in decisions, while in images, repetition of a feature reinforces its importance. Generally, product differences prove to attract more attention than commonalities, demonstrating product differentiation's importance in forming consumer preferences.

Managing Variety in Product Families Through Design for Commonality

1998 ◽  
Author(s):  
Sridhar Kota ◽  
Kannan Sethuraman
Keyword(s):  
New Technologies ◽  
Product Family ◽  
Objective Measure ◽  
Value Added ◽  
Product Variety ◽  
New Product ◽  
Product Line ◽  
Product Portfolio ◽  
Product Complexity ◽  
Product Families

Abstract Majority of companies develop a family of products and many new product variations are added to the product portfolio regularly to meet changing market needs and/or to attract new customer base. Although, the core functionality remains essentially unchanged across all products within a family, new functions, new feature combinations and new technologies are incorporated into each new product. The component variations, commonly referred to as “complexity”, grow exponentially resulting in loss of productivity and/or quality. The challenge lies in effective management of product variations in the design studies and on the manufacturing floor. The key is to minimize non-value added variations across models within a product family without limiting customer choices. Although the benefits of standardization are widely known and most companies do standardize stock components such as fasteners, they are far from standardizing their product -specific core components and thus fail to reap significant benefits in quality and cost. Through this research, we are developing new methodologies for improved management of product variety to achieve higher productivity. In this paper, we discuss the factors that contribute to product complexity in general, and present an objective measure, called the Product Line Commonality Index, to capture the level of part commonality in a product family. Through our Walkman case study, we illustrate robust design/manufacturing strategies, including modularity and postponement of product differentiation, that help minimize non-value added variation across models within a product family1 without limiting customer choices. Finally, we present a simple and yet a powerful method of benchmarking product families or companies in their ability to share parts effectively (modularity) and reduce the total number of parts (multi-functionality) used in product families.

scholarly journals Design of Personalized Devices—The Tradeoff between Individual Value and Personalization Workload

2020 ◽  
Vol 11 (1) ◽  
pp. 241
Author(s):  
Juliane Kuhl ◽  
Andreas Ding ◽  
Ngoc Tuan Ngo ◽  
Andres Braschkat ◽  
Jens Fiehler ◽  
...  
Keyword(s):  
Customer Value ◽  
Early Stage ◽  
Treatment Success ◽  
Product Family ◽  
Flow Diverter ◽  
New Method ◽  
Product Families ◽  
Wide Range ◽  
The Individual ◽  
Individual Value

Personalized medical devices adapted to the anatomy of the individual promise greater treatment success for patients, thus increasing the individual value of the product. In order to cater to individual adaptations, however, medical device companies need to be able to handle a wide range of internal processes and components. These are here referred to collectively as the personalization workload. Consequently, support is required in order to evaluate how best to target product personalization. Since the approaches presented in the literature are not able to sufficiently meet this demand, this paper introduces a new method that can be used to define an appropriate variety level for a product family taking into account standardized, variant, and personalized attributes. The new method enables the identification and evaluation of personalizable attributes within an existing product family. The method is based on established steps and tools from the field of variant-oriented product design, and is applied using a flow diverter—an implant for the treatment of aneurysm diseases—as an example product. The personalization relevance and adaptation workload for the product characteristics that constitute the differentiating product properties were analyzed and compared in order to determine a tradeoff between customer value and personalization workload. This will consequently help companies to employ targeted, deliberate personalization when designing their product families by enabling them to factor variety-induced complexity and customer value into their thinking at an early stage, thus allowing them to critically evaluate a personalization project.

An Alternative Design Approach for Vehicle Crash Safety Using Crash Pulse Optimization

2000 ◽  
Author(s):  
R. J. Yang ◽  
C. H. Tho ◽  
C. C. Gearhart ◽  
Y. Fu
Keyword(s):  
Time Domain ◽  
Numerical Optimization ◽  
Piecewise Linear ◽  
Linear Representation ◽  
Optimization Techniques ◽  
Safety Requirements ◽  
Crash Safety ◽  
Design Variables ◽  
Piecewise Linear Representation ◽  
Occupant Injury

Abstract This paper presents an approach, based on numerical optimization techniques, to identify an ideal (5 star) crash pulse and generate a band of acceptable crash pulses surrounding that ideal pulse. This band can be used by engineers to quickly determine whether a design will satisfy government and corporate safety requirements, and whether the design will satisfy the requirements for a 5 star crash rating. A piecewise linear representation of the crash pulse with two plateaus is employed for its conceptual simplicity and because such a pulse has been shown to be sufficient for reproducing occupant injury behavior when used as input into MADYMO models. The piecewise linear crash pulse is parameterized with 7 design variables (5 for time domain and 2 for acceleration domain) in the optimization process. A series of sample runs are conducted to validate that pulses falling within the acceptable crash pulse band do in fact satisfy 5 star requirements.

scholarly journals OPTIMUM BUCKLING DESIGN OF CYLINDRICAL STIFFENER SHELL UNDER EXTERNAL HYDROSTATIC PRESSURE

2018 ◽  
Vol 18 (2) ◽  
pp. 239-252 ◽  
Author(s):  
Rawa Hamed M. Al-Kalali
Keyword(s):  
Hydrostatic Pressure ◽  
Numerical Optimization ◽  
Collapse Load ◽  
Ansys Software ◽  
External Hydrostatic Pressure ◽  
Buckling Mode ◽  
Design Elements ◽  
Design Variables ◽  
Thick Cylinder ◽  
Strength Constraints

This paper present an investigation of the collapse load in cylinder shell under uniformexternal hydrostatic pressure with optimum design using finite element method viaANSYS software. Twenty cases are studied inclusive stiffeners in longitudinal and ringstiffeners. Buckling mode shape is evaluated. This paper studied the optimum designgenerated by ANSYS for thick cylinder with external hydrostatic pressure. The primarygoal of this paper was to identify the improvement in the design of cylindrical shell underhydrostatic pressure with and without Stiffeners (longitudinal and ring) with incorporativetechnique of an optimization into ANSYS software. The design elements in this researchwas: critical load, design variable (thickness of shell (TH), stiffener’s width (B) andstiffener’s height (HF). The results obtained illustrated that the objective is minimizedusing technique of numerical optimization in ANSYS with optimum shell thickness andstiffener’s sizes. In all cases the design variables (thickness of shell) was thicker than themonocoque due to a shell’s thicker is essential to achieve the strength constraints. It can beconcluded that cases (17,18,19, and 20) have more than 90% of un-stiffened critical load.The ring stiffeners causes increasing buckling load than un-stiffened and longitudinalstiffened cylinder.

Algorithm-Based Support for the Redesign of Product Variants

2020 ◽  
Author(s):  
Julian Redeker ◽  
Philipp Gebhardt ◽  
Thomas Vietor
Keyword(s):  
Economies Of Scale ◽  
Graph Matching ◽  
Product Family ◽  
Automated Analysis ◽  
Production Volume ◽  
Scale Production ◽  
Product Families ◽  
First Case ◽  
Subtractive Manufacturing ◽  
Definition Of

Abstract Incremental Manufacturing is a novel manufacturing approach where product variants are manufactured based on a finalization of pre-produced parts through additive and subtractive manufacturing processes. This approach allows a multi-scale production with the possibility to scale product variants as well as the production volume. In order to ensure high economic efficiency of the manufacturing concept, there is a need for pre-produced parts that come as close as possible to the final variant geometries to ensure that only variant-specific features need to be added by additive or subtractive manufacturing steps. Furthermore, to ensure high economies of scale, a high degree of commonality should be ensured for the pre-produced parts manufactured in mass production. In this context, a graph-based method is developed that enables an automated analysis of product families, based on physical and functional attributes, for standardization potentials. The method thus provides support for the strategic definition of pre-produced parts and is embedded in an overall approach for the redesign of products for Incremental Manufacturing. For the demonstration of the approach, which is based on 3D Shape and Graph Matching methods, a first case study is carried out using a guiding bush product family as an example.

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