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.     

A variant approach to product definition by recognizing functional requirement patterns

Product definition has been recognized as one of the deciding factors in designing a product for success in the marketplace. This paper introduces an approach to product definition by evolving from similar existing products. Our methodology is derived from recognizing functional requirement (FR) patterns from past design efforts including FR topology, FR classification, and FR templates. A two-phase methodology of FR pattern recognition and pattern adoption is presented in the paper. The proposed approach not only eases the tedious elaboration process of requirement definition among customers, marketers, and designers, but also reduces the complexities and risks inherent in requirement specification. Furthermore, it opens opportunities for incorporating expert heuristics into FR patterns based on competitive products and technological trends. A case study conducted in power supply design helps to illustrate the feasibility and potential of the proposed approach.     

Measuring consumer perceptions for a better comprehension, specification and assessment of product semantics

Product semantics, the “study of the symbolic qualities of man-made forms in the context of their use, and application of this knowledge to industrial design” is an important challenge in product design. Because of subjectivity, this particular dimension of the user's need is difficult to express, to quantify and to assess. This paper presents a general approach to assess product semantics in a sound way. It is based on usability tests, and involves several classical methods in marketing and decision-making theory, as multidimensional scaling, semantic differential method, factor analysis, pairwise comparison and analytical hierarchy process. As a result, our integrated approach provides designers with a tool which helps understand and specify the semantic part of the need; it rates and ranks the new product prototypes according to their closeness to the specified “ideal product”, and it underlines the particular semantic dimensions that should be improved. To illustrate our approach, we have performed usability tests and applied our methodology to the design of table glasses. For the sake of clarity, each stage of the methodology is presented in detail on this particular example.

Relevance to industry

The integrated framework proposed in this paper can be readily deployed in companies and used at different stages of the design of products. Firstly, our methodology provides a frame for describing how a given products family is perceived by users, and for storing and up-dating these data. Secondly, the data can be used to specify target requirements for a new product by qualitative comparisons to existing products. Finally, emerging product concepts may be directly assessed with regards to the requirements in a simple qualitative and comparative way.     

Data management of green product development with generic modularized product architecture

Many manufacturers are facing a complex situation in the mixed production environment, in which green and non-green products are fabricated simultaneously. They are losing competitiveness as a downstream supplier due to lacking of a cost-effective approach to managing product variations compliant with different green directives. This paper presents a methodology based on generic modularized product architecture that facilitates data management of green product development. The four-level architecture allows one unified representation for multiple product models. An option control mechanism enables a quick generation of their BOMs (bills of material). A procedure consisting of seven steps is proposed to accomplish this. PDM functions are implemented to demonstrate the effectiveness of the methodology using a real LCD TV family as an example. This work complements the past studies on green product development, which mainly tackled the problem from design, process, and supply chain improvement. In contrast, from a management perspective, the proposed methodology provides a simple but useful tool for small-to-medium-sized enterprises (SMEs) to perform green product development in an economical manner.     

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.     

Balancing homogeneity and heterogeneity in design exploration by synthesizing novel design alternatives based on genetic algorithm and strategic styling decision

Designers constantly and consistently draft and develop both general concepts and directions to identify the solution that best fits the styling objectives of the lead designer. Designers often confront design fixations that cognitively clash to explore different design combinations. As design teams explore the range of possible design spaces of a certain design strategy, there is an opportunity for computational approaches to improve the styling process. By implementing product appearance similarity and styling strategy in computational design synthesis, it is possible to discover combinations that would otherwise remain unexplored by human designers. Numerous studies on design synthesis have been conducted. However, there has been no focus on the morphological synthesis of designs with strategic styling decisions. Considering this, the proposed study develops a method to synthesize car styling based on product appearance similarity for effective design exploration in the concept generation phase. The similarities of products across different generations, product portfolios, and competitors’ products are calculated to evaluate the strategic styling decision. The results of the strategic styling decision are used to formulate a fitness function. Car styling is then synthesized with a genetic algorithm based on this fitness function to generate car styling in accordance with the target strategic styling decision. In this respect, designers can computationally synthesize novel design alternatives that consider both homogeneity (family look in design) and heterogeneity (design trend in the market) by pinpointing the desired design exploration area. Ultimately, the style synthesis methodology proposed in this research can help designers to utilize the gradual visualization of styling strategies for more effective and efficient managerial design decisions. To do this, we conduct five major tasks: first, car design data are collected for design synthesis; second, the product appearance similarity is calculated to measure the strategic styling decision; third, synthesis validation is conducted to test whether the proposed methodology can create outside-the-box designs; fourth, a genetic algorithm is used to synthesize car designs in consideration of the strategic styling decision; finally, a series of in-depth interviews with experts and validation experiments are conducted with in-house automobile designers to examine the impact of the proposed methodology. The results showed that designers can quantitatively measure and compare the styling strategies of each car brand, then implement design upgrades, while still maintaining that specific style. Correspondingly, computationally generated design alternatives improve the satisfaction in ease, time, objective reflection and novelty of design outcomes when formulating design strategies in the concept generation phase.     

Product family modeling for mass customization

With growing reliance on modeling in product development, it is imperative to describe product families in a cohesive way. In particular, mass customization calls for a close integration of product life cycle from customer recognition to delivery and services. This paper proposes a triple-view scheme for modeling product families. Technical challenges are discussed by comparing product family modeling with modeling single products. Individual modeling formalisms for different views are discussed. An example of product family modeling in power supply design is presented to illustrate the feasibility and potential of the proposed approach.     

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.     

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.     

Progressive sharing of modules among product variants

Recent market transition from mass production to mass customization forces manufacturers to design products that meet individual requirements. In order to address the high cost of this practice, manufacturers develop product families with a common platform, whose variants are designed to meet different customer demands. Parallel to this transition, the dynamics of the market forces designers to develop products composed of modules that are standardized as much as possible across products, thus can be more resilient than complete designs in a changing world.Starting from an original set of different components, our method designs a modular common platform and additional modules, shared by subsets of the designs, from which variants are composed.We applied the method to the layout design of a set of products. Consequently, the geometric aspect of the product family optimization is emphasized, but functional aspects related to the product features and to customer needs are also addressed due to their manifestation in the layout. The design search space is explored using shape grammar rules that alter component geometry and therefore, functionality. The search for optimal design is performed using simulated annealing. Given different objective formulations or parameter settings, the method can be used to explore the solution space. A simple example problem demonstrates the feasibility of the method.     

Reverse innovative design — an integrated product design methodology

Today’s product designer is being asked to develop high quality, innovative products at an ever increasing pace. To meet this need, an intensive search is underway for advanced design methodologies that facilitate the acquisition of design knowledge and creative ideas for later reuse. Additionally, designers are embracing a wide range of 3D digital design applications, such as 3D digitization, 3D CAD and CAID, reverse engineering (RE), CAE analysis and rapid prototyping (RP). In this paper, we propose a reverse engineering innovative design methodology called Reverse Innovative Design (RID). The RID methodology facilitates design and knowledge reuse by leveraging 3D digital design applications. The core of our RID methodology is the definition and construction of feature-based parametric solid models from scanned data. The solid model is constructed with feature data to allow for design modification and iteration. Such a construction is well suited for downstream analysis and rapid prototyping. In this paper, we will review the commercial availability and technological developments of some relevant 3D digital design applications. We will then introduce three RE modelling strategies: an autosurfacing strategy for organic shapes; a solid modelling strategy with feature recognition and surface fitting for analytical models; and a curve-based modelling strategy for accurate reverse modelling. Freeform shapes are appearing with more frequency in product development. Since their “natural” parameters are hard to define and extract, we propose construction of a feature skeleton based upon industrial or regional standards or by user interaction. Global and local product definition parameters are then linked to the feature skeleton. Design modification is performed by solving a constrained optimization problem. A RID platform has been developed and the main RE strategies and core algorithms have been integrated into SolidWorks as an add-in product called ScanTo3D. We will use this system to demonstrate our RID methodology on a collection of innovative consumer product design examples.     

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 simulation methodology for a system of product life cycle systems

To realize environmental sustainability, the flow of natural resources into industrial systems must be reduced and stabilized at a suitable level. One way to reduce resource flows in society is to establish resource-circulating manufacturing systems. To foster the circulation of resources in industry, life cycle simulation (LCS) technologies, which are based on discrete-event modeling, have been developed to dynamically evaluate the life cycles of products from resource extraction to end of life from both environmental and economic aspects. In reality, various industrial products interact with each other in unanticipated ways, and then these interactions affect the material flows in product life cycles. This type of complex system is called a system of systems (SoS). Focusing on this issue, we expand the evaluation's system boundary to include a system of multiple product life cycle systems. To handle an SoS quantitatively, we introduce typical types of interactions between product life cycle systems. The purpose of this study was to propose a new LCS methodology, called “LCS4SoS,” that focuses on an SoS consisting of different kinds of product life cycle systems. A prototype system of LCS4SoS was implemented based on this proposed methodology. Through a case study, it was found that the proposed methodology is useful for evaluating an SoS consisting of multi-product life cycle systems.     

A quantitative aesthetic measurement method for product appearance design

Product appearance is one of the crucial factors that influence consumers’ purchase decisions. The attractiveness of product appearance is mainly determined by the inherent aesthetics of the design composition related to the arrangement of visual design elements. Hence, it is critical to study and improve the arrangement of visual design elements for product appearance design. Strategies that apply aesthetic design principles to assist designers in effectively arranging visual design elements are widely acknowledged in both academia and industry. However, applying aesthetic design principles relies heavily on the designer’s perception and experience, while it is rather challenging for novice designers. Meanwhile, it is hard to measure and quantify design aesthetics in designing artefacts when designers refer to existing successful designs. In this regard, this study aims to introduce a method that assists designers in applying aesthetic design principles to improve the attractiveness of product appearance. Furthermore, formulas for aesthetic measurement based on aesthetic design principles are also developed, and it makes an early attempt to provide quantified aesthetic measurements of design artefacts. A case study on camera design was conducted to demonstrate the merits of the proposed method where the improved strategies for the camera appearance design offer insights for concept generation in product appearance design based on aesthetic design principles.     

An acceptability estimation and analysis methodology based on Bayesian networks

As companies are forced to conceive innovative products to stay competitive, designers face the challenge of developing products more suited to users' needs and perceptions in order to be accepted, thus reducing project risk failure. Evaluating users' acceptability has become an important research problem. Current approaches leave the acceptance evaluation question to be answered in the last stages of product development process (NPD), when an almost finished prototype is available and when there is no time left for important modifications. Acceptability evaluation methods suitable for use from the early stages of the NPD process are thus needed. This paper proposes a method for acceptability evaluation and analysis that can be used in the early stages of the development cycle. It is based on the evaluation of the solution concept by the users. The relationships among the factors (or criteria) are made explicit, thus helping designers to identify the key factors for acceptance. As the users' tests and the maturity of the concept prototype are limited in this stage, the proposed method exploits the inference properties of Bayesian networks making it possible to make useful estimations and allowing the exploration of actions that could improve the product acceptability level. Two case studies are presented in order to illustrate the method, the first related to a technological product design for a home-health care service provider and the second to a work-related musculoskeletal disorder prevention software design.Relevance to industryThe article describes an acceptability assessment and an analysis approach to be used by industrial engineers, designers and ergonomists in the early phases of design projects. The method can help the design team to identify the levers (key factors) for enhancing product acceptance and to identify different actions (e.g. product modification, deployment strategy, and training).     

A method of constructing an inspiration library driven by user-perceived preference evaluation data for biologically inspired design

Biologically inspired design (BID) is one of the common methods for product design. To solve the problem of inaccurate acquisition of inspirational creatures due to the lack of user perception preference analysis, a data-driven intelligent service model for BID considering user perception needs is proposed based on Kansei engineering. Firstly, by extracting the perceptual features of creatures from the semantic source elements of products through mapping and encodes them, we proposed a data acquisition method based on intuitionistic fuzzy sets considering different customer preference distributions, bridging the gap caused by the asymmetry between designers and users. Secondly, the functional relationship between biometric features and user-perceived attributes is identified and predicted, and a predictive model of biodata considering user preferences is obtained by multiple linear regression analysis. Finally, based on the data clustering and reorganization theory to understand the organization and dynamics of the database, the construction of a BID library was completed, and the design resources in the library were used as analyzed knowledge for designers to plan design activities. Taking the bionic design of a UAV product as an example, a prototype of a computer-aided design service system was developed based on the theory proposed in the article, and the analyzed knowledge was used to improve the efficiency and science of the design, effectively verifying the usefulness of this study for design. To a certain extent, this study addresses the problem of cognitive limitations of designers and cognitive differences between designers and users, promotes the application of bioinspiration in product design, and improves the marketability of design solutions.     

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 methodology for brand feature establishment based on the decomposition and reconstruction of a feature curve

For creative products, maintaining original brand elements and features in a new product is an important issue in the design process as brand features are conceived and generated for longevity. However, current methods rely on designers’ abilities, and the size of forms is easily affected when shape morphing is applied, causing limitations in computer-aided design. In order to focus on design while preserving key features, a systematic method for presenting brand features is proposed in this article. In this method, the feature curves of the brand features of a company are decomposed with defined feature parameters, which were then used to reconstruct the feature curve of the designed product in the design stage by using a residual modified gray prediction model. A classic vehicle configuration design is taken as an example to show the implementation procedure of the proposed method. With residual modification, this method can also assimilate other forms from the original form database, and generate new forms based on gray prediction. The results show that brand features can be retained in the newly designed product based on the proposed method. Though vehicle design is taken as the example, this method can also be used to develop designs for many other the brand features. For classic products with historical value, this method can generate new forms that maintain original brand features, thereby satisfying customers’ needs for brand authenticity.     

A Gestalt–Minimalism-based decision-making model for evaluating product form design

This paper presents a novel methodology for dealing with decision-making problems in product design fields. The purpose of this study is to evaluate product form design in terms of the perspectives of Gestalt psychology and Minimalist principles. Unlike traditional AHP methods, the proposed decision-making model uses distinct mathematical tools to establish priorities for the criteria and synthesize the evaluation results. A case study was conducted to illustrate the practicability of this proposed model. It has shown a credible result. In addition to product form design, this model can be applied to related design fields, such as plane design and other visual design.

Relevance to industry

Product form design is a creative process that involves complex visual perceptions. It is very important to develop an effective decision support system for designers to deal with problems concerning the consumers’ psychological preferences toward product forms. As Gestalt psychology and Minimalist principles provide an important perspective on visual perception, it is appropriate to apply these principles in assessing the quality of product form design.