Optimal platform investment for product family design

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.     

A taxonomy and decision support for the design and manufacture of types of product families

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.     

Product platform configuration for product families: Module clustering based on product architecture and manufacturing process

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.     

A systematic approach for product families formation in Reconfigurable Manufacturing Systems

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.     

Multiple platforms design and product family process planning for combined additive and subtractive manufacturing

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.     

PRONTO: An ontology for comprehensive and consistent representation of product information

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.     

Modular product platform configuration and co-planning of assembly lines using assembly and disassembly

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.     

A systematic data-mining-based methodology for product family design and product configuration

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.     

Multiple-platform based product family design for mass customization using a modified genetic algorithm

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.     

Classifying variability modeling techniques

Variability modeling is important for managing variability in software product families, especially during product derivation. In the past few years, several variability modeling techniques have been developed, each using its own concepts to model the variability provided by a product family. The publications regarding these techniques were written from different viewpoints, use different examples, and rely on a different technical background. This paper sheds light on the similarities and differences between six variability modeling techniques, by exemplifying the techniques with one running example, and classifying them using a framework of key characteristics for variability modeling. It furthermore discusses the relation between differences among those techniques, and the scope, size, and application domain of product families.     

Industrial validation of COVAMOF

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%.     

A procedure for building product models

The application of product modeling in manufacturing companies raises the important question of how to model product knowledge in a comprehensible and efficient way. An important challenge is to qualify engineers to model and specify IT-systems (product models) to support their specification activities. A basic assumption is that engineers have to take the responsibility for building product models to be used in their domain. To do that they must be able to carry out the modeling task on their own without any need for support from computer science experts. This paper presents a set of simple, easily adaptable concepts and methods for modeling product knowledge. The concepts and methods are based on well-defined concepts and methods from data modeling (object oriented analysis) and domain modeling (product modeling). The concepts are general and can be used for modeling all types of specifications in the different phases in the product life cycle. The modeling techniques presented have been tested in different companies and have proved to work.     

Platform-based product design and development: A knowledge-intensive support approach

This paper presents a knowledge-intensive support paradigm for platform-based product family design and development. The fundamental issues underlying the product family design and development, including product platform and product family modeling, product family generation and evolution, and product family evaluation for customization, are discussed. A module-based integrated design scheme is proposed with knowledge support for product family architecture modeling, product platform establishment, product family generation, and product variant assessment. A systematic methodology and the relevant technologies are investigated and developed for knowledge supported product family design process. The developed information and knowledge-modeling framework and prototype system can be used for platform product design knowledge capture, representation and management and offer on-line support for designers in the design process. The issues and requirements related to developing a knowledge-intensive support system for modular platform-based product family design are also addressed.     

基于物料族的可扩展产品配置建模

为快速地进行产品配置设计,针对产品配置模型在建立过程中扩展性弱的问题,提出1种基于物料族的可扩展产品配置建模方法．利用面向对象方法,结合扩展属性类将物料族衍生为不同的零部件族,建立1个扩展性强的产品配置模型．最后通过建立电脑族产品配置模型验证该方法具有扩展性强的特点．     

Present it like it is here: Creating local presence to improve online product experiences

Advanced online product presentation technologies such as virtual mirrors enable consumers to experience products like they are actually present with them in the real world. This study is one of the first to address the mechanism underlying this phenomenon. Inspired by literature on media technology the concept of local presence is put forward and applied to the online consumer behavior domain. A key objective of this paper is to examine whether local presence adds to our understanding of how emerging product presentation formats influence online product experiences. To this end, a laboratory experiment (N = 366) was conducted with product presentation format as a three level (pictures, 360-spin rotation, and virtual mirror) independent variable, allowing for a comparison of the effectiveness of different presentation formats in creating perceptions of local presence. As a second objective, the influence of local presence on perceptions of product tangibility and product likability, two key facets of the online product experience, were assessed. The results, obtained with the use of analysis of variance and partial least squares modeling, show the superiority of the virtual mirror in creating local presence, and demonstrate that local presence is highly predictive of product tangibility and product likability. Theoretical and managerial implications are discussed.     

An efficient decomposed multiobjective genetic algorithm for solving the joint product platform selection and product family design problem with generalized commonality

Product family optimization involves not only specifying the platform from which the individual product variants will be derived, but also optimizing the platform design and the individual variants. Typically these steps are performed separately, but we propose an efficient decomposed multiobjective genetic algorithm to jointly determine optimal (1) platform selection, (2) platform design, and (3) variant design in product family optimization. The approach addresses limitations of prior restrictive component sharing definitions by introducing a generalized two-dimensional commonality chromosome to enable sharing components among subsets of variants. To solve the resulting high dimensional problem in a single stage efficiently, we exploit the problem structure by decomposing it into a two-level genetic algorithm, where the upper level determines the optimal platform configuration while each lower level optimizes one of the individual variants. The decomposed approach improves scalability of the all-in-one problem dramatically, providing a practical tool for optimizing families with more variants. The proposed approach is demonstrated by optimizing a family of electric motors. Results indicate that (1) decomposition results in improved solutions under comparable computational cost and (2) generalized commonality produces families with increased component sharing under the same level of performance. A preliminary version of this paper was presented at the 2007 AIAA Multidisciplinary Design Optimization Specialists Conference.     

A digital twin-enhanced system for engineering product family design and optimization

Engineering product family design and optimization in complex environments has been a major bottleneck in today’s industrial transformation towards smart manufacturing. Digital twin (DT), as a core part of cyber-physical system (CPS), can provide decision support to enhance engineering product lifecycle management workflows via remote monitoring and control, high-fidelity simulation, and solution generation functionalities. Although many studies have proven DT to be highly suited for industry needs, little has been reported on the product family design and optimization capabilities specifically with context awareness, which could be leaving many enterprises ambivalent on its adoption. To fill this gap, a reusable and transparent DT capable of situational recognition and self-correction is essentially required. This paper develops a generic DT architecture reference model to enable the context-aware product family design optimization process in a cost-effective manner. A case study featuring asset re-/configuration within a dynamic environment is further described to demonstrate its in-context decision-aiding capabilities. The authors hope this study can provide valuable insights to both academia and industry in improving their engineering product family management process.     

软件产品线可变性建模技术系统综述

软件产品线是实现大规模的软件复用、保证高质量的新产品开发的最佳实践.软件产品线的关键问题是如何进行可变性管理,并基于可变性管理实现软件核心资产的复用.软件产品线可变性建模是可变性管理的关键技术,实现产品家族成员的共性和可变性的描述.可变性建模涉及软件开发的全生命周期,在领域工程和应用工程中,尤其是在产品构建过程中,起到重要的作用.从众多的建模技术中选择合适的建模技术是十分困难的,在软件产品线领域中开展了可变性建模技术的系统综述,按照系统综述的方法对可变性建模技术进行了系统总结,根据系统综述规则,选取了从1990 年~2011 年发表的论文进行综述.讨论了系统综述的研究成果,从可变性建模方法分类、重要可变性建模技术对比等方面进行深入的探讨,为建模人员和研究人员对可变性建模技术的选择和研究提供支持.最后分析了可变性建模技术的研究趋势,并对可变性建模技术有待深入的研究难点和发展趋势进行了展望.     

SimPL: A product-line modeling methodology for families of integrated control systems

ContextIntegrated control systems (ICSs) are heterogeneous systems where software and hardware components are integrated to control and monitor physical devices and processes. A family of ICSs share the same software code base, which is configured differently for each product to form a unique installation. Due to the complexity of ICSs and inadequate automation support, product configuration in this context is typically error-prone and costly.ObjectiveAs a first step to overcome these challenges, we propose a UML-based product-line modeling methodology that provides a foundation for semi-automated product configuration in the specific context of ICSs.MethodWe performed a comprehensive domain analysis to identify characteristics of ICS families, and their configuration challenges. Based on this, we formulated the characteristics of an adequate configuration solution, and derived from them a set of modeling requirements for a model-based solution to configuration. The SimPL methodology is proposed to fulfill these requirements.ResultsTo evaluate the ability of SimPL to fulfill the modeling requirements, we applied it to a large-scale industrial case study. Our experience with the case study shows that SimPL is adequate to provide a model of the product family that meets the modeling requirements. Further evaluation is still required to assess the applicability and scalability of SimPL in practice. Doing this requires conducting field studies with human subjects and is left for future work.ConclusionWe conclude that configuration in ICSs requires better automation support, and UML-based approaches to product family modeling can be tailored to provide the required foundation.