Product concept generation and selection using sorting technique and fuzzy c-means algorithm

Product conceptualization is regarded as a key activity in new product development (NPD). In this stage, product concept generation and selection plays a crucial role. This paper presents a product concept generation and selection (PCGS) approach, which was proposed to assist product designers in generating and selecting design alternatives during the product conceptualization stage. In the PCGS, general sorting was adapted for initial requirements acquisition and platform definition; while a fuzzy c-means (FCM) algorithm was integrated with a design alternatives generation strategy for clustering design options and selecting preferred product concepts. The PCGS deliberates and embeds a psychology-originated method, i.e., sorting technique, to widen domain coverage and improve the effectiveness in initial platform formation. Furthermore, it successfully improves the FCM algorithm in such a way that more accurate clustering results can be obtained. A case study on a wood golf club design was used for illustrating the proposed approach. The results were promising and revealed the potential of the PCGS method.     

A functional–commercial analysis strategy for product conceptualization

A functional-commercial analysis strategy is proposed to facilitate product conceptualization. General sorting is adopted to elicit initial product platform and generate initial design options. Designers’ importance ratings are gathered and used to deal with cost- and time-related concerns. The restricted coulomb energy neural network is used for classifying and selecting design options. A case study on wood golf club design is conducted to illustrate the proposed approach.     

An in-process customer utility prediction system for product conceptualisation

Customer involvement in new product development, especially in the early stage of product conceptualisation, plays an important role for a successful product. In this study, a customer utility prediction system (CUPS) is proposed. The system comprises two modules, namely design knowledge acquisition module and customer utility evaluation module. In the design knowledge acquisition module, a knowledge acquisition technique called general sorting is utilised to establish a design knowledge hierarchy (DKH), in which design options can be generated. In the same module, customer voices towards diverse design options called customer-sensitive design criteria are solicited from customer requirements. Subsequently, in the customer utility evaluation module, a measurement for customer desirability, i.e. customer utility index (CUI), is formulated using conjoint analysis (CA) technique. Finally, the rated criteria are also used as inputs to a radial basis function (RBF) neural network for in-process customer utility prediction. A case study on cellular phone design is used to illustrate the proposed approach.     

A quality-time-cost-oriented strategy for product conceptualization

In general, product development companies aim to deliver products of optimal quality while incurring minimal cost in the shortest time possible. In this work, a quality-time-cost-oriented strategy (QTCOS) is proposed to facilitate product concept generation and selection. Firstly, general sorting is employed to elicit an initial product platform. The platform, constructed with a design space framework (DSF), serves as a base for generating a preliminary range of design options. Using the repertory grids elicitation method, designers contribute importance ratings with respect to a set of time and cost criteria for the range of design options. To account for trade-offs between cost and time related concerns, these ratings are employed to reduce the number of the derived design options, and thereby used as input features to a restricted coulomb energy (RCE) neural network. The RCE network function is applied to classify the set of design options into different patterns, i.e. cost-time-pairs. The classification results can subsequently serve as bases for the selection of preferred design options. A case study on wood golf club design is conducted to illustrate the proposed QTCOS.     

A stakeholder-oriented innovative product conceptualization strategy based on fuzzy integrals

Knowledge, experiences and skills of corporate members promote new ideas into products, in the context of innovative design. This dynamism is especially important in the critical product conceptualization stage. In customer-oriented design paradigm, most methodologies focus on exploiting end-user requirements, instead of considering project stakeholder requirements in a holistic manner. Previous research in the area of innovative product conceptualization focused on such aspects as functional, cognitive, marketing and commercial perspectives. It involves the participations of customers, designers, engineers, marketers and business managers. Accordingly, a stakeholder-oriented innovative product concept development system (IPCDS) is established to integrate the bespoke four perspectives so as to evaluate product concept innovation comprehensively. To resolve the incomplete, ambiguous, uncertain and subjective nature of innovative design knowledge, the product platform represented in a design knowledge hierarchy (DKH) is generated using general sorting. Subsequently, an innovative design criteria matrix (DCM) constructed using repertory grids technique is rated with regard to specific design option. The ratings are then used as input features to the fuzzy integrals technique, for the purpose of innovative design. A case study on cellular phone design is used for system illustration and the results are discussed on the basis of product concept innovation.     

Green and ecological interior design based on network processor and embedded system

With the growing demand for interior design solutions that are friendly to the green environment, there is a growing awareness of interior designers around the world to the sustainability strategy. Most of the traditional interior design and construction process consumes many natural resources in the manufacturing and installation process. This will harm the environment. Interior designers adopted a sustainable design technology, the opportunity to improve the healthy indoor air quality. To achieve sustainable solutions, materials, construction methods, furniture by selecting the lighting design options. Despite much sustainable design research, discussion of the interior design of sustainability criteria there little. Essential for sustainable standard interior design solutions to support the responsible interior designer. Therefore, this study aims to propose a set of criteria for selecting based on sustainable indoor network processors and embedded system design solutions to ensure a sustainable and consistent product mix of 3DWeb representation of interior design solutions thing. Finally, to enhance its functionality, come to an end because of the importance of effective standards.     

Mapping Product Design Specification for Mass Customization

Mass customization is an emerging field in manufacturing research community where customer satisfaction is achieved by complying with exact customer requirements at mass production efficiencies. Product varieties have mostly failed in the aspect of satisfying customer requirements, since knowing beforehand exactly what customer needs is beyond the scope of any manufacturing or marketing paradigm. So design to order and build to order is widely talked in the industry to capture heterogeneous market segments. In order to achieve the challenging task of customization at mass production efficiencies, a tight integration of the various entities involved is necessary. Gathering customer requirements, finalizing product design and eventual manufacturing need to be seamlessly integrated to achieve mass production efficiencies. Product designs are classified into customizable product platform families, and then searched based on customer requirements to identify the most conformal design family. Finally the design parameter transport is carried out from customer domain to product domain. Eventually a valid and realizable product specification is generated. The paper will address these issues of classification, selection and ultimately the mapping of parameters. A methodology to classify the product design information, which can easily accommodate design variations based on product platform architecture is proposed. Further, adaptive design customization, which relates most design parameters with the scalable platform design parameters using matrix formulation, is discussed. The proposed design parameter classification and adaptive synthesis of design parameters is applied to a spring design example.     

Decision-making support for sustainable product creation

A satisfactory multiobjective design that incorporates physical performance as well as sustainability is necessary from a global environmental protection perspective. For obtaining sustainable lifecycles, decision making in the early phases of the design process, considering multiple sources of uncertainty, is important. Previously, we proposed a preference set-based design (PSD) by Inoue et al. (2010) [16] method, which enables a flexible and robust design under various sources of uncertainty while capturing the designer’s preference based on his/her knowledge or experience. The present study focuses on a decision-making support for sustainable product creation in the early phases of the design process considering the various design uncertainties. We investigate different officially accepted sustainability indicators and identify the ones that are related to the product development process by considering the physical performance and sustainability of the products concurrently. Thereafter, the proposed method is applied to a multiobjective design problem. This paper discusses the applicability of PSD as a decision-making support method for sustainable development using the design of an alternator as an example.     

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.     

Chemical enterprise model and decision-making framework for sustainable chemical product design

The chemical product substitution process is undertaken by chemical industries for complying with regulations, like REACH in Europe. Initially devoted to chemists, chemicals substitution is nowadays a complex process involving corporate, business and engineering stakeholders across the chemical enterprise for orienting the search toward a sustainable solution. We formalize a decision making process framework dedicated to the sustainable chemical product design activity in an industrial context. The framework aims at improving the sharing of information and knowledge and at enabling a collaborative work across the chemical enterprise stakeholders at the strategic, tactical and operational levels. It is supported by information and communication technologies (ICT) and integrates a computer aided molecular design tool. During the initial intelligence phase, a systemic analysis of the needs and usages enables to define the product requirements. In the design phase, they are compiled with the help of a facilitator to generate the input file of a computer aided product design tool. This multiobjective tool is designed to find mixtures with molecular fragments issued from renewable raw materials, and is able to handle environment-health and safety related properties along with process physicochemical properties. The final choice phase discusses the solution relevancy and provides feedback, before launching the product manufacturing. The framework is illustrated by the search of a bio-sourced water–solvent mixture formulation for lithographic blanket wash used in printing industry. The sustainability of the solution is assessed by using the sustainability shades method.     

A collaborative methodology for tacit knowledge management: Application to scientific research

Tacit knowledge, which refers to the know-how, is critical to understand and reuse since it is located in the human heads. It represents the foremost element for human and team evaluation. Seeking for tacit knowledge is achieved only by communicating with the concerned persons, which makes losing it axiomatic if people leave their work without documenting their know-how. Thus, providing a collaborative environment based on a common conceptualization of the domain to formalize the experts’ knowledge and to share their outcomes is required. However, some barriers pertaining to cultural and social factors such as personality traits impede capturing the conceptual model. To cope with these issues, we have proposed a generic two-step methodology that copes with human barriers when capturing the domain experts’ tacit knowledge, their skills, and seeds terms in order to converge to a common knowledge representation. Considering the scientific research management as a use case, we followed the proposed methodology to formalize our scientific research knowledge in the context of network and communication research field. Based on the generated ontology, we have developed a semantic web platform that allows collaboratively annotating experts’ knowledge in a computer interpretable format that can be shared and reused by human and machines. Our evaluation is based on end users’ quality of experience and feedbacks.     

Preliminary design and manufacturing planning integration using web-based intelligent agents

Software agents have been increasingly used in the product and process development in industry over the past years due to the rapid evolvement of the Internet technology. This paper describes agents for the integration of conceptual design and process planning. Agents provide mechanisms to interact with each other. This mechanism is important since both of those processes involve negotiations for optimization. A set of design and planning software agents has been developed. These agents are used in a computer-based collaborative environment, called a multi-agent platform. The main purpose of developing such a platform is to support product preliminary design, optimize product form and structure, and reduce the manufacturing cost in the early design stage. The agents on the platform have access to a knowledge base that contains design and planning rules. These rules are derived from an analysis of design factors that influence process and resource planning, such as product material, form, shape complexity, features, dimension, tolerance, surface condition, production volume, and production rate. These rules are used by process planning agents to provide process planners with information regarding selecting preliminary manufacturing processes, determining manufacturing resources, and constructing feedback information to product designers. Additionally, the agents communicate with WEB servers, and they are accessible by users through Internet browsers. During performing design and planning tasks, agents access the data pertinent to design and manufacturing processes by the programming interfaces of existing computer-aided design (CAD) and manufacturing system. The agents are supported by a developed prototype agent platform. The agents and the platform enable the information exchange among agents, based on a previously developed integrated design and manufacturing process object model.     

支持Top Down整体色彩设计的模型研究*

为了在CAD平台上实现TopDown整体色彩设计,在分析色彩设计领域知识的基础上,结合产品色彩方案库,通过色彩设计树建立了产品几何数据与色彩数据之间的映射,构造了支持TopDown整体色彩设计的模型。同时初步完成了原型系统开发,并与CAXA实体设计2005集成,在机床产品的设计中进行了应用。     

BIM extension for the sustainability appraisal of conceptual steel design

Contemporary advancements in Information Technology and the efforts from various research initiatives in the AEC industry are showing evidence of progress with the emergence of building information modelling (BIM). BIM presents the opportunity of electronically modelling and managing the vast amount of information embedded in a building project, from its conception to end-of-life. Researchers have been looking at extensions to expand its scope. Sustainability is one such modelling extension that is in need of development. This is becoming pertinent for the structural engineer as recent design criteria have put great emphasis on the sustainability credentials in addition to the traditional criteria of structural integrity, constructability and cost. With the complexity of designs, there are now needs to provide decision support tools to aid in the assessment of the sustainability credentials of design solutions. Such tools would be most beneficial at the conceptual design stage so that sustainability is built into the design solution starting from its inception. The sustainability of buildings is related to life cycle and is measured using indicator-terms such as life cycle costing, ecological footprint and carbon footprint. This paper proposes a modelling framework combining these three indicators in providing sustainability assessments of alternative design solutions based on the economic and environmental sustainability pillars. It employs the principles of feature-based modelling to extract construction-specific information from product models for the purposes of sustainability analysis. A prototype system is implemented using .NET and linked to the BIM enabled software, Revit Structures™. The system appraises alternative design solutions using multi-criteria performance analysis. This work demonstrates that current process and data modelling techniques can be employed to model sustainability related information to inform decisions right from the early stages of structural design. It concludes that the utilized information modelling representations – in the form of a process model, implementation algorithms and object-based instantiations – can capture sustainability related information to inform decisions at the early stages of the structural design process.     

Kave: a tool for knowledge acquisition to support artificial ventilation

A decision support system for artificial ventilation is being developed. One of the fundamental goals for this system is the application of the system when a domain expert is not present. Such a system requires a rich knowledge base. The knowledge acquisition process is often considered to be the bottleneck in acquiring such a complete knowledge base. Since no single available method, for example interviewing domain experts, is sufficient for removing this bottleneck, we have chosen a combination of different methods. The different backgrounds of knowledge engineers and domain experts could cause communication restrictions and difficulties between them, e.g. they might not understand each others knowledge domain and this will affect formulation of the knowledge. To solve this problem we needed a tool which supports both the knowledge engineer and the domain expert already from the initial phase of developing the knowledge base. We have developed a knowledge acquisition system called KAVE to elicit knowledge from domain experts and storing it in the knowledge base. KAVE is based on a domain specific conceptual model which is a result of cooperation between knowledge engineers and domain experts during identification, design and structuring of knowledge for this domain. KAVE includes a patient simulator to help validate knowledge in the knowledge base and a knowledge editor to facilitate refinement and maintenance of the knowledge base.     

温室控制专家系统开发平台的设计与实现

本文研制了一个面向领域专家(温室工人)的温室控制专家系统开发平台。其知识编辑器采用图形组态的形式．使不具备专家系统编程方面专门知识的用户也能容易地输入知识经验。平台的知识编辑器与推理机把模糊控制与专家控制理论相结合，提高了系统智能化程度。实例证明了用该平台开发温室控制专家系统的可行性与优点。     

A systematic knowledge-based method for design of transformable product

A transformable product can perform different functions or change functionality by changing its physical structure. It is formed by integration of different components whose states can be transformed each other. However, there is a lack of systematic methods to guide design of the transformable product. In order to improve the design efficiency of transformable products, a large number of products are studied in this research to build a case base of transformation parameters and transformation principles for the design knowledge. A systematic design process is proposed to apply the design knowledge. The transformation design problem is first mapped from the problem domain to the knowledge domain expressed by transformation parameters. A general solution is then obtained in the knowledge domain. A multi-classification support vector machine is used to train a model of the transformation recommendation based on transformation parameters. Finally, the general solution is mapped into the problem domain for the specific solution using the analogy design. The effectiveness of the method is verified in the design of a self-propelled boom sprayer.     

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.     

A study on the collaborative management method of product design cycle knowledge

Because of the ever-increasing market competition and rapidly changing of customers’ requirements, the innovation quality and design efficiency of knowledge-intensive product has become the key factors in business success. The traditional knowledge management method which is based on design reuse and the single categories of design knowledge cannot satisfy these demands any more. Therefore, in order to effectively support the innovative design process of enterprises, a design knowledge collaborative management method based on multi-knowledge migration is proposed. According to the characteristics and functions during the product design process, the design knowledge is divided into three categories, design principle knowledge, design domain knowledge and design object knowledge. By extracting the operation attributes, relation attributes and physical attributes of the design knowledge, a unified knowledge representation model is established for different design participants. The ontology concept and knowledge matrix are used to establish the association between various categories of design knowledge. Multifarious knowledge search methods include keyword, function, principle and natural semantics are proposed for different design participants in different design stages. They can not only realize the knowledge reuse in the same domain but also support the cross-domain knowledge migration among different domain. Finally, based on the system analysis modelling, a design knowledge collaborative platform is established for the design process of mechanical products. A case study is also presented to illustrate the implementation of the platform.