首页 | 本学科首页   官方微博 | 高级检索  
相似文献
 共查询到10条相似文献,搜索用时 108 毫秒
1.
Optimal platform investment for product family design   总被引:2,自引:1,他引:1  
Existing models for developing modular product families based on a common platform are either too engineering oriented or too marketing centric. In this paper, we propose an intermediate modeling ground that bridges this gap by simultaneously considering essential concepts from engineering and marketing to construct an alternative model for platform-based product families. In this model, each variant (in the platform-based product family) contributes a percentage to overall market coverage inside a target market segment. The extent to which a specific variant contributes to market coverage is linked to its degree of distinctiveness. On the other hand the cost of development of all variants (that constitute the product family) is also dependent on the degree of commonality between these variants. The objective of the model is to maximize market coverage subject to an available development budget. Based on a conceptual design of the product family, the proposed model suggests the optimal initial investment in the platform, the commonality level between variants, and the number of variants to be produced in order to maximize market coverage using both analytical and simulation techniques. An application example using an ice scraper product family is included to demonstrate the proposed model.  相似文献   

2.
The realization that designing products in families can and does have significant technological and economic advantages over traditional single product design has motivated increasing interest in recent years in formal design tools and methodologies for product family design. However, currently there is no guidance for designers in the first key strategic decisions of product family design, in particular determining the type of product family to design. Hence, in this paper, first a taxonomy of different types of product families is presented which consists of seven types of product families, categorized based on number of products and time of product introduction. Next a methodology is introduced to support designers in deciding which type of product family is appropriate, based upon early knowledge about the nature of the intended product(s) and their intended market(s). From this information it follows both which manufacturing paradigm and which fundamental design strategies are appropriate for each type of product family. Finally, the proposed methodology is illustrated through a case study examining a family of whitewater kayaks.  相似文献   

3.
Product family design utilizes platform-based modularity to enable product variety and efficient mass-production. While product platform issues have attracted much attention from both academia and industry, traditional product platform design for product families emphasized the platform-based modularity that focuses on product structure dimension (functional or non-functional) to realize cost reductions during the design stage. Both the design architecture and manufacturing process are objectives that define product family modularity (PFM). They should be closely coupled with each other for the planning and configuration of platforms. This paper focuses on the product platform configuration by recognizing and utilizing shared product modules for product families. Instead of clustering product modules only based on their design structure, this approach differentiates each product variant, and considers the inherent relationship between product architecture and processing activities. The advantage is that similar components can be grouped and produced on a shared platform, thus benefitting from lower cost and shorter production time. First, both the architecture and manufacturing information of the product variety are captured in matrix format. Then, hierarchical clustering is applied over the components to generate PFM. Finally, a set of platforms are constructed to efficiently process most components of variants.  相似文献   

4.
The aim of this work is to establish a methodology for an effective working of Reconfigurable Manufacturing Systems (RMSs). These systems are the next step in manufacturing, allowing the production of any quantity of highly customised and complex products together with the benefits of mass production. In RMSs, products are grouped into families, each of which requires a system configuration. The system is configured to produce the first family of products. Once it is finished, the system is reconfigured in order to produce the second family, and so forth. Therefore, the effectiveness of a RMS depends on the formation of the best set of product families. Therefore, a methodology for grouping products into families, which takes into account the requirements of products in RMSs, is an issue of core importance. These requirements are modularity, commonality, compatibility, reusability, and product demand. The methodology starts by calculating, for each product requirement, a matrix that summarises the similarity between pairs of products. Then, through the use of the AHP methodology, a unique matrix that comprises the similarity values between products is obtained. The Average Linkage Clustering algorithm is applied to this matrix in order to obtain a dendogram that shows the diverse sets of product families that may be formed.  相似文献   

5.
Industry 4.0 promotes the utilization of new exponential technologies such as additive manufacturing in responding to different manufacturing challenges. Among these, the integration of additive and subtractive manufacturing technologies can play an important role and be a game changer in manufacturing products. In addition, using product platforms improves the efficiency and responsiveness of manufacturing systems and is considered an enabler of mass customization. In this paper, a model to design multiple platforms that can be customized using additive and subtractive manufacturing to manufacture a product family cost-effectively is proposed. The developed model is used to determine the optimal number of product platforms, each platform design (i.e. its features set), the assignment of each platform to various product variants, and the macro process plans for customizing the platforms while minimizing the overall product family manufacturing cost.The multiple additive/subtractive platforms and their process plans are determined by considering not only the commonality between the product variants but also their various manufacturing cost elements and the customer demand of each variant. The design of multiple product family platforms and their process plans is NP-hard problem. A genetic algorithm-based model is developed to reduce the computational complexity and find optimal or near optimal solution. Two case studies are used to illustrate the developed multiple platform model. The model results were compared with a single platform model in literature and the results demonstrate the multiple platform model superiority in manufacturing product families in lower cost. The use of the developed model enables manufacturing product families cost efficiently and allows manufacturers to manage diversity in products and market demands.  相似文献   

6.
Nowadays, it is quite common for collaborating organizations (or even different areas within a company) to develop and maintain their own product model. This situation leads to information duplication and its associated problems. Besides, traditional product models do not properly handle the high number of variants managed in today competitive markets. In addition, there is a need for an integrated product model to be shared by all the organizations participating in global supply chains (SCs) or all the areas within a company. One way to reach an intelligent integration among product models is by means of an ontology. PRoduct ONTOlogy (PRONTO) is an ontology for the product modeling domain, able to efficiently handle product variants. It defines and integrates two hierarchies to represent product information: the abstraction hierarchy (AH) and the structural one (SH). This contribution presents a ConceptBase formal specification of PRONTO that focuses on the structural hierarchy of products. This hierarchy is a tool to handle product information associated with the multiple available recipes or processes to manufacture a particular product or a set of similar products. The formal specification presented in the paper also includes mechanisms to infer structural information from the explicit knowledge represented at each of the AH levels: Family, VariantSet and Product. This proposal efficiently handles a great number of variants and allows representing product information with distinct granularity degrees, which is a requirement for planning activities taking place at different time horizons. PRONTO easily manages crucial features that should be taken into account in a product representation, such as the efficient handling of product families and variants concepts, composition and decomposition structures and the possibility of specifying constraints. To demonstrate the semantic expressiveness of the proposed ontology a food industry related case-study is addressed and discussed in detail.  相似文献   

7.
Formation of products platforms is carried out during the planning stage and very often separately from the planning of corresponding assembly lines. There is a dearth of literature which considers the different aspects of fully integrating platform design, product family formation, assembly line design, delayed product differentiation, and new concepts of mass customization. A Modular Product Platform Configuration model which uses assembly and disassembly for configuring product variants and Co-Planning of products platforms (MPCC) and their assembly Lines is presented. It is used to co-plan the common platform components and the associated product families simultaneously with the planning of its corresponding mixed-model assembly line. Using both assembly and disassembly to customize the product family platform in order to generate product variants is not commonly discussed in literature. It is defined as the formation of platforms for use to derive multiple products by including many components not shared by every product. The platform is then customized by assembling or disassembling components to form different product variants. The model is formulated using mixed integer mathematical programming to minimize the number of assembly stations and cycle time. Two case studies are used for verification and demonstration. They illustrated the ability of the MPCC model to integrate the planning of product platform, product families and the number of assembly stations required to assemble and disassemble components from mass-assembled product platforms to derive new product variants.  相似文献   

8.
Product family design and product configuration based on data mining technology is identified as an intelligent and automated means to improve the efficiency of product development. However, few of previous literatures have proposed systematic product family design method based on data mining technology. To make up for this deficiency, this research put forward a systematic data-mining-based method for product family design and product configuration. First, the customer requirement information and product engineering information in the historical order are formatted into structural data. Second, principal component analysis is performed on historical orders to extract the customers' differentiated needs. Third, association rule algorithm is introduced to mine the rules between differentiated needs and module instances in the historical orders, thus obtained the configuration knowledge between customer needs and product engineer. Forth, the mined rules are used to construct association rule-based classifier (CBA) that is employed to sort out the best product configuration schemes as popular product variants. Fifth, sequence alignment technique is employed to identify modules for popular product variants, so that the module instances are divided into optional, common and special module, respectively, thereby the product platform is generated based on common modules. Finally, according to new customer needs, the CBA classifier is used to recommend the best configuration schemes, and then popular product variants are configured based on the product platform. The feasibility of the proposed method is demonstrated by the product family design example of desktop computer hosts.  相似文献   

9.
A successful product family design method should achieve an optimal tradeoff among a set of conflicting objectives, which involves maximizing commonality across the family of products with the prerequisite of satisfying customers’ performance requirements. Optimization based methods are experiencing new found use in product family design to resolve the inherent tradeoff between commonality and distinctiveness that exists within a product family. This paper presents and develops a 2-level chromosome structured genetic algorithm (2LCGA) to simultaneously determine the optimal settings for the product platform and corresponding family of products, by automatically varying the amount of platform commonality within the product family during a single optimization process. The single-stage approach can yield improvements in the overall performance of the product family compared with two-stage approaches, in which the first stage involves determining the best settings for the platform variables and values of unique variables are found for each product in the second stage. The augmented scope of 2LCGA allows multiple platforms to be considered during product family optimization, offering opportunities for superior overall design by more efficacious tradeoffs between commonality and performance. The effectiveness of the proposed approach is demonstrated through the design of a family of universal electric motors and comparison against previous work.  相似文献   

10.
COVAMOF is a variability management framework for product families that was developed to reduce the number of iterations required during product derivation and to reduce the dependency on experts. In this paper, we present the results of an experiment with COVAMOF in industry. The results show that with COVAMOF, engineers that are not involved in the product family were now capable of deriving the products in 100% of the cases, compared to 29% of the cases without COVAMOF. For experts, the use of COVAMOF reduced the number of iterations by 42%, and the total derivation time by 38%.  相似文献   

设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号