scholarly journals DESIGN FOR FUTURE VARIETY TO ENABLE LONG-TERM BENEFITS OF MODULAR PRODUCT FAMILIES

2021 ◽  
Vol 1 ◽  
pp. 993-1002
Author(s):  
Erik Greve ◽  
Christoph Fuchs ◽  
Bahram Hamraz ◽  
Marc Windheim ◽  
Dieter Krause
Keyword(s):  
Value Chain ◽  
Product Family ◽  
Product Architecture ◽  
Great Effort ◽  
Allocation Model ◽  
Product Families ◽  
Modular Product ◽  
Critical Components ◽  
A Company

AbstractBy developing and using modular product families, large savings can be achieved through reuse and combinability along the entire value chain of a company. Since these potentials often have a very long-term character, the lifetime of a modular product family should be as long as possible. Change drivers, such as changing customer and production requirements, however, result in changes having to be made to the initially developed modular product family, which not only causes a great effort but also prevents the long-term benefits from being fully exploited. With the Change Allocation Model, we introduce a tool that makes it possible to align the essential future changes to the product architecture and to identify and redesign the change-critical components taking into account the existing component variety of the product family. This enables future changes in variety to be considered in the product architecture and a future robust modular product family to be developed. The new visualization is illustrated using the example of a product family of pressure regulating valves and is finally discussed with regard to further potentials and challenges.

scholarly journals Risk Profiles Along the Lifecycle in Dynamic Markets

2015 ◽  
Vol 6 (3) ◽  
pp. 35-46
Author(s):  
Tamas Koplyay ◽  
Brian Mitchell ◽  
Sorin Cohn ◽  
Maria Fekete ◽  
Abdelkader Jazouli
Keyword(s):  
Value Chain ◽  
Critical Role ◽  
Distribution Channel ◽  
Operating Mode ◽  
Life And Death ◽  
Dynamic Markets ◽  
Start Up ◽  
Distribution Channel Management ◽  
A Company

Abstract That supply chain management and logistics are a determining factor for the long term success of a company was well documented by Forrester over a half century ago [1], with the importance of the statement only growing through the intervening years.Whether consciously factored into the operating mode or not, logistics and distribution channel management plays a critical role in the life, and death, of a firm. From the rudimentary beginnings of the start-up company to the hectic world of the growth company and onto the relatively secure existence in mature markets, the value chain consisting of logistics and distribution channel linkages follows the firm, until it solidifies into immutable form of the mature value chain and begins to exert an inexorable pressure on the survival of the entire chain, and conversely the chain imposes its will on the members. The emergence of mature industry value chains is often driven by the need to monopolistically control logistics and distribution channels which provides a competitive advantage but also introduces a serious exposure to pending shock loadings of the chain.

Knowledge Model for Managing Product Variety and Its Reflective Design Process

2006 ◽  
Author(s):  
Yutaka Nomaguchi ◽  
Tomohiro Taguchi ◽  
Kikuo Fujita
Keyword(s):  
Design Process ◽  
Product Family ◽  
Product Variety ◽  
Product Architecture ◽  
Air Conditioner ◽  
Knowledge Model ◽  
Product Families ◽  
Reflective Process ◽  
Reflective Design ◽  
Computer Based

Recent manufacturers have been utilizing product families to diversify and enhance the product performance by simultaneously designing multiple products under commonalization and standardization. Design information of product architecture and family is inevitably more complicated and numerous than that of a single product. Thus, more sophisticated computer-based support system is required for product architecture and family design. This paper proposes a knowledge model for a computer-based system to support reflective process of designing product architecture and product family. This research focuses on three problems which should be overcome when product family are modeled in the computer system; design repository without data redundancy and incorrectness, knowledge acquisition without forcing the additional effort on the designer, and integration of prescriptive models to support early stages of the design process. An ontology that is a foundation of a knowledge model is defined to resolve these problems. An example of designing an air conditioner product family is shown to demonstrate the capability of the system.

Graph Grammar Based Product Variety Modeling

2000 ◽  
Author(s):  
Xuehong Du ◽  
Mitchell M. Tseng ◽  
Jianxin Jiao
Keyword(s):  
Product Family ◽  
Product Variety ◽  
Graph Grammar ◽  
Product Families ◽  
Order Processing ◽  
Product Features ◽  
The Family ◽  
Feature Values ◽  
Data Transferring ◽  
A Company

Abstract This paper discusses the issue of product variety modeling, i.e. the means to organize the data of a family of products according to the underpinning logic among them. The targeted product families are characterized by providing user-selectable product features and feature values and achieving variety by combining parameterized functional or physical modules. A graph grammar based (GGB) model is proposed for the purpose of enhancing the comprehensiveness and manipulability of the data of product families for different functional departments in a company in order to facilitate effective order processing as well as direct customer-manufacturer interaction. To deal with variety effectively, both structural and non-structural family data are represented as family graphs whereas order-specific products are represented as variant graphs derived by applying predefined graph rewrite rules to the family graphs. The most important characteristics of the GGB model are three folds. While emphasizing the distinctiveness of the information that different users are concerned about, it provides cross view data transferring mechanisms. It also supports data manipulation for variety generation. Finally, taking advantage of the graph grammar based language of PROGRES, GGB is a model to be easily implemented as a visualized computer system. The specification of an office chair product family illustrates the principles and construction process of GGB models.

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.

Complex products and systems: Potential from using layout platforms

2004 ◽  
Vol 18 (1) ◽  
pp. 55-69 ◽  
Author(s):  
ADRIAN P. HOFER ◽  
JOHANNES I.M. HALMAN
Keyword(s):  
Market Segmentation ◽  
Product Family ◽  
Product Variety ◽  
Building Blocks ◽  
Product Architecture ◽  
Product Families ◽  
Complex Products ◽  
Dominant Design ◽  
Family Based ◽  
System Layout

In their quest to manage the complexity of offering greater product variety, firms in many industries are considering platform-based development of product families. Key in this approach is the sharing of components, modules, and other assets across a family of products. Current research indicates that companies are often choosing physical elements of the product architecture (i.e., components, modules, building blocks) for building platform-based product families. Other sources for platform potential are widely neglected. We argue that for complex products and systems with hierarchic product architectures and considerable freedom in design, a new platform type, the system layout, offers important commonality potential. This layout platform standardizes the arrangement of subsystems within the product family. This paper is based on three industry case studies, where a product family based on a common layout could be defined. In combination with segment-specific variety restrictions, this results in an effective, efficient, and flexible positioning of a company's products. The employment of layout platforms leads to substantial complexity reduction, and is the basis for competitive advantage, as it imposes a dominant design on a product family, improves its configurability, and supports effective market segmentation.

scholarly journals Knowledge-Based Decision Support for Concept Evaluation Using the Extended Impact Model of Modular Product Families

2022 ◽  
Vol 12 (2) ◽  
pp. 547
Author(s):  
Erik Greve ◽  
Christoph Fuchs ◽  
Bahram Hamraz ◽  
Marc Windheim ◽  
Christoph Rennpferdt ◽  
...  
Keyword(s):  
Decision Support ◽  
Product Architecture ◽  
Impact Model ◽  
Product Families ◽  
Support Tool ◽  
Knowledge Based ◽  
Modular Product ◽  
Concept Evaluation ◽  
The Impact ◽  
Selection Of

The design of modular product families enables a high external variety of products by a low internal variety of components and processes. This variety optimization leads to large economic savings along the entire value chain. However, when designing and selecting suitable modular product architecture concepts, often only direct costs are considered, and indirect costs as well as cross-cost center benefits are neglected. A lack of knowledge about the full savings potential often results in the selection of inferior solutions. Since available approaches do not adequately address this problem, this paper provides a new methodological support tool that ensures consideration of the full savings potentials in the evaluation of modular product architecture concepts. For this purpose, the visual knowledge base of the Impact Model of Modular Product Families (IMF) is used, extended and implemented in a model-based environment using SysML. The newly developed Sys-IMF is then applied to the product family example of electric medium-voltage motors. The support tool is dynamic, expandable and filterable and embedded in a methodical procedure for knowledge-based decision support. Sys-IMF supports decision makers in the early phase of interdisciplinary product development and enables the selection of the most suitable modular solution for the company.

A Systematic Method for Designing Profitable Product Families

2003 ◽  
Author(s):  
Srinivas Nidamarthi ◽  
Gu¨nther Mechler ◽  
Harsh Karandikar
Keyword(s):  
Product Family ◽  
Minimum Cost ◽  
Profit Margin ◽  
Digital Cameras ◽  
Customer Choice ◽  
Systematic Method ◽  
Product Families ◽  
Design Elements ◽  
Wide Range ◽  
A Company

Every company has the business objectives of maximizing customer choice as well as its profitability. Typically, companies address maximum customer choice through a large spectrum of variants in their products to satisfy varying customer needs. For example, a camera manufacturer may wish to offer various choices such as fixed focus, auto-focus, variable zoom, different zoom ranges, SLR, APS, and digital cameras, and in different combinations, to satisfy customers with different demands (including the price that they wish to pay). The business goal, therefore, is to design a product family that meets a wide range of customer choices but at a minimum cost so as to maximize the profit margin. These two objectives, choice and profit margin, are not as contradictory as they seem. In this paper, we show that by using a set of systematic methods a company can identify the essential design elements of a profitable product family. We have successfully applied this method in a number of product families ranging from airhandling fans to robot controllers, and from mass-produced products to project based customized products.

A Graphical Modeling Environment for Configuring Modular Product Families and Platforms

2006 ◽  
Author(s):  
Asli Sahin ◽  
Janis P. Terpenny ◽  
Richard M. Goff
Keyword(s):  
Product Family ◽  
Design Teams ◽  
Multiple Perspectives ◽  
Levels Of Abstraction ◽  
Product Families ◽  
Modular Product ◽  
Modeling Environment ◽  
Relationship Types ◽  
Computer Based ◽  
Technical Functions

A significant amount of research has established that product platform planning is effective for the development of multiple products and management strategy for companies in today’s market. However, there are still significant challenges in planning and the realization of product families and platforms. This is particularly true for determining family and platform architectures—imperative assets in companies in order to pursue competitive advantages. It is a challenging task because individual customization of products generally competes with the goal of maximizing platform commonality. To address this challenge, this paper introduces a graphical computer-based modeling environment to support product design teams in configuring modular product families. In the modeling environment, a product family can be decomposed into its products, modules, and functions. Also, interfaces among the product components can be elaborated by defining the relationship types (fundamental, redundant, and operational). Further elaboration can be achieved by defining an appropriate set of module drivers from four different perspectives: financial, customer, design processes, and organizational culture/IT. These features facilitate modeling of a product family at multiple levels of abstraction as capturing design drivers, reasoning and goals. The application of the modeling environment is illustrated with a family of coffee-makers. It is demonstrated how the proposed modeling method offers a comprehensive representation and understanding of product family planning by integrating multiple perspectives on modular architecting. Moreover, a matrix-based analysis option is provided for design teams to view the relationships between the technical functions and the forms, and the design goals and the customer requirements in a preliminary manner.

Determination of Future Robust Product Features for Modular Product Family Design

2019 ◽  
Author(s):  
Erik Greve ◽  
Christoph Rennpferdt ◽  
Tobias Hartwich ◽  
Dieter Krause
Keyword(s):  
Product Family ◽  
New Product ◽  
Product Architecture ◽  
Modular Product ◽  
Product Features ◽  
Methodical Approach ◽  
Vacuum Cleaning ◽  
Cleaning Robots ◽  
Adaptive Conjoint Analysis

Abstract Modular product architecture design allows product variants to be derived with little effort and cost. An essential part of designing modular product architectures is fulfilling customer-relevant product features, which represent the differentiating aspects for the customer and, thus, stand for the economic success of a product variant. However, product features are not only subject to high fluctuations due to changing environmental influences, but are also of varying relevance to customers over time. Not considering these aspects in the development phase can lead to costly changes in the product architecture later on. To counteract this, these two perspectives are merged and a methodical approach is introduced that identifies new product features and analyses their future development in the context of customer benefit. For this purpose, the current and future relevance to customers as well as uncertainties are calculated using Adaptive Conjoint Analysis and a Monte Carlo simulation. The results are consolidated in a visualization and the product features are classified according to their future implementation in robust product architecture. The procedure is explained using the example of a product family of vacuum cleaning robots.

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