Determination of ranged sets of design specifications by incorporating design-space heterogeneity

Setting design specifications (targets) is a critical task in the early stages of the design process. Flexible targets can accommodate uncertainty and changes in design by postponing design commitments and preserving design freedom. In this article, a new method is developed for obtaining a ranged set of design specifications that meets design criteria whilst incorporating design-space heterogeneity; meaning some areas in the design attribute space are more achievable than the others. The proposed method has two notable features. First, a quantization algorithm based on rough-set theory is used to decompose a design attribute space into sub-regions on the basis of how well they meet design criteria. Second, a new design-flexibility measure is used as a metric to select the most desired ‘target region’ on the bases of both the size of the region and the influence of potential design alternatives on overall achievability. The proposed approach enhances the capacity of a design system to adapt to evolving design knowledge, as well as to unexpected changes. The proposed method is demonstrated by a numerical example and the design of a domestic blender.     

Joint production control and product quality decision making in a failure prone multiple-product manufacturing system

This paper considers joint production control and product quality specifications decision making in unreliable multiple-product manufacturing system. This is with the knowledge that an optimum compromise should guide the decision making process. In fact, tight process specifications will generally lead to products with good quality and higher market values, but at the same time associated with a higher rate of non-conforming parts rejection leading to higher non quality costs and lower plant productivity. Moreover, in unreliable manufacturing context the decision maker should adopt an adequate production policy to hedge against future capacity shortages caused by machine failures in order to meet customer demand. This paper intends to extend previous findings to tackle this problem and study the overall decision making process aiming to guide the production and quality specification decisions in multiple-product context. The overall optimal decision policy is defined here as one that maximises the long term average per unit time profit of a combined measure of quality and quantity dependent sales revenue, minus inventory and backlog costs, in the presence of random plant failures and random repair durations.     

Integrating biopharmaceutics risk assessment and in vivo absorption model in formulation development of BCS class I drug using the QbD approach

Objective: Clinically relevant critical quality attributes (CQA’s) were identified for the development of generic drug products containing fluconazole and potential design spaces relevant to the clinical application of the drug candidate was explored.

Significance: A simplified scoring system for the biopharmaceutics risk assessment roadmap (BioRAM) is proposed to guide product development.

Methods: Factorial design of experiments was employed to study the effect of formulation and process variables on CQA’s. The in vivo model was developed for predicting the fraction of drug absorbed and to identify the effect of formulation components on drug absorption.

Results: BioRAM yielded low scores for fluconazole absorption with respect to severity (risks of sub and supra-bioavailable drug products), probability of incidence of bioinequivalent results and capacity of detection. The results demonstrated that dissolution was highly influenced by the active pharmaceutical ingredient (API) polymorphism and the ratio of diluents. Process variables (mixing time, lubricant concentration, lubrication time and filling speed) did not impact the clinical outcome of the formulation with respect to dissolution and content uniformity.

Conclusions: Understanding the clinical implications of the adopted formulation approach led to the construction of purposeful design space and control strategy.     

A rough set based data mining approach for house of quality analysis

As the first phase of quality function deployment (QFD) and the only interface between the customers and product development team, house of quality (HOQ) plays the most important role in developing quality products that are able to satisfy customer needs. No matter in what shape or form HOQ can be built, the key to this process is to find out the hidden relationship between customers’ requirements and product design specifications. This paper presents a general rough set based data mining approach for HOQ analysis. It utilises the historical information of customer needs and the design specifications of the product that was purchased, employs the basic rough set notions to reveal the interrelationships between customer needs and design specifications automatically. Due to the data reduction nature of the approach, a minimal set of customer needs that are crucial for the decision on the correlated design specifications is derived. The end result of the approach is in the form of a minimal rule set, which not only fulfils the goal of HOQ, but can be used as supporting data for marketing purposes. A case study on the product of electrically powered bicycles is included to illustrate the approach and its efficiency.     

Economic considerations on parameter design

A simultaneous consideration of process mean and variance in product design stages has been considered one of the most significant of Taguchi's contributions. Among his quality improvement methods, parameter design has drawn a great deal of particular attention from researchers. The ultimate objective of Taguchi's parameter design is to find control factor settings to achieve an on‐target process mean with a minimum variance. There is no doubt regarding the virtue of the minimum variance. However, considering a variety of economic aspects related to product specifications as well as a quality loss, the on‐target process mean may not necessarily be economical. This paper investigates the parameter design problem from an economic point of view and proposes an alternative procedure to achieve the most economical process mean as well as the minimum variance by taking product specifications and an asymmetric quality loss into consideration. It is shown through an illustrative example that a significant cost saving can be accrued from the proposed procedure. Copyright © 2000 John Wiley & Sons, Ltd.     

从“7.23”事故谈设计开发应注意的问题

在产品的设计开发过程中要充分考虑硬件、软件的充分性、适宜性和匹配性,要充分考虑自身和外包方的设计能力、使用者或顾客的适应性及其匹配性,保证设计开发到实现的全过程的有效控制,降低新产品设计开发风险,充分体现质量管理体系的原则和要求。     

Capability Indices and Conformance to Specification: The Motivation for Using Cpm

Proposed is a perspective on quality that is different from but consistent with the current Six Sigma thinking. The focus is still squarely on the customer, but the concept of a “defect” is reevaluated. This new perspective can be used to help define key characteristics, process capability, and evaluate overall product quality using a loss function. This article focuses on the concept of process capability using this perspective. Central to the proposed quality perspective is ability to meet the customer's product specifications rather than ability to meet the component feature specifications. Current product and component quality metrics can drive the wrong decisions and wrong behaviors. This can add significant cost to internal processes and suppliers, and inadequately protect the customers from defective products. The new perspective defines component and process quality based on the probability of meeting the product specifications rather than the individual component feature specifications. Cpm is a simple process capability metric that can indicate the probability of meeting the customer's product specification. Cpm can be used to better estimate the cost of poor quality than can be estimated by using Cpk, and thus can be used to better manage product quality to the customer.     

Linking quality citizenship to process design: a quality management perspective

As organisations emphasise their role in society, there is a need to determine the effect of socially responsible practices on organisational processes and firm performance. Although the effect of corporate social responsibility on firm performance has been addressed from different perspectives, little is known about the influence of corporate social responsibility on organisational processes and internal operations of firms. The paper aims to make a link between corporate social responsibility, quality management practices and quality outcomes through emphasising quality citizenship as one of the practices associated with quality management. This paper provides a new perspective on the link between quality citizenship and product/process design within the quality management framework. The stakeholder theory of the firm is used to explain the formation and development of new management practices within a firm. Data were collected from managers in the petroleum industry to examine the role of quality citizenship on design and development of organisational processes. The results show that quality citizenship has a significant effect on employee involvement and an indirect effect on process design. Quality citizenship enables firms to obtain a much broader perspective on product/process design and facilitates design and development of products, services and processes that meet the needs of a broader set of customers – the stakeholders.     

不确定视角下产品结构性能优化设计综述与展望

目的 复杂产品在工程装备、航空航天等我国优先发展的战略领域中扮演着不可替代的重要角色,在其结构设计过程中普遍存在着各种不确定性,导致产品结构性能很难实现最优,甚至出现重大故障。方法 针对复杂产品设计过程中的多粒度模糊不确定、随机不确定、不完备区间不确定和高维混合不确定等特点,将不确定性理论与产品结构设计过程相结合,系统地构建了不确定视角下产品结构性能优化设计理论体系,提出了多粒度模糊不确定下产品质量特性精准提取、随机不确定下产品功能结构模块化求解、不完备区间不确定下产品结构方案多属性决策、高维混合不确定下产品关键结构可靠性优化等关键技术,并指出了产品结构性能优化设计的未来发展方向。结论 此设计理论能够充分适应和利用产品设计过程的多种不确定信息,为在结构设计环节切实提升产品性能提供了有力参考。     

用户感性认知与产品感性设计方法及应用

目的梳理用户感性认知测量及其设计应用,提出人工智能驱动的产品感性设计方法,并以验光仪设计验证其有效性。方法分析国内外文献,归纳总结用户感性认知测量及应用方法,通过验光仪设计验证所提出的产品感性设计方法。结果人工智能驱动的产品感性设计方法能提升设计效率,更好地满足用户感性需求。结论用户感性认知测量能转化为设计规范,并能为产品设计提供有效指导。随着计算机科学的发展,针对传统用户感性认知测量中样本采集量较少、测量不够全面等问题,提出了人工智能驱动的产品感性设计方法,并以验光仪的设计验证了其有效性。研究结果表明,通过文本挖掘提取用户感性认知能引导设计师更加全面地了解用户感性需求,从而使设计出的产品更贴近用户的预期满意度。人工智能与人类智慧相结合的感性设计方法是一种能提高用户对产品的心理接受度,从而提升产品竞争力的设计方法。     

基于知识重用的手机设计需求信息管理方法

 面向大批量定制的产品设计是一个跨领域、跨专业的协同设计过程,设计者不可能掌握所有领域的知识.要加快产品的开发速度,提高产品设计和创新能力,知识的快速获取和运用是关键.针对手机产品的设计特点,提出一种满足客户需求的知识重用设计体系,其包括可重用的设计知识、创新知识、产品建模和物料清单,并应用于集成设计信息CAD系统.为手机产品快速更新换代,功能越来越强大,而开发周期越来越短的矛盾提供了一种有效的解决方案.     

The role of crowdsourcing in product design: The moderating effect of user expertise and network connectivity

To meet the challenges of customization and personalized design in the context of the digital economy, increasing numbers of small and medium-sized enterprises (SMEs) are using crowdsourcing platforms to seek product design innovation. While crowdsourcing has significant potential for eliciting product ideas, it remains unclear whether it can generate high-quality designs for relatively more complex product design tasks. Based on a leading social new product development website Quirky.com, we explore the antecedents of a firm's adoption decision of crowdsourcing, the impact of crowdsourcing on product design quality, and the moderating effect of user expertise and network connectivity by utilizing treatment effect model. The results indicate that: (1) crowdsourcing has a significant positive impact on product design quality; (2) user expertise positively moderates the role of crowdsourcing in product design quality; (3) network connectivity has an inverted U-shaped moderating effect on crowdsourcing and product design quality relationship; (4) the probability of firm's crowdsourcing adoption is negatively correlated with the complexity and reliability of initial product idea but positively correlated with popularity, novelty, and numbers of images. This study not only enriches the crowdsourcing and social network theory; but also provides guidance for crowdsourcing platform firms to better manage the crowdsourcing process and user crowdsourcing communities.     

Knowledge elicitation for risk mapping in concurrent engineering projects

Concurrent Engineering aims to incorporate the overlapping of processes in order to reduce its time-to-market and thereby sustain the existence of organizations in increasingly competitive times. Although faster product design, development, and delivery are the intended outcomes of concurrent engineering, one of the undesirable by-products is an increase in risks as a consequence of uncertainties between interdependent processes. Hence, the risks need to be identified, assessed, and mitigated together with concurrent engineering considerations for the elimination of the ‘domino-effect’ within risk management. This paper concentrates primarily on knowledge elicitation techniques that were used to provide information to the Intelligent Risk Mapping and Assessment System (IRMAS?) to identify, prioritise, analyse, and assist project managers to manage perceived sources of CE risks. Techniques such as expert interviews, brainstorming, the Delphi technique, and the analogy process are discussed in relation to compiling the knowledge used for this expert system. A total of 589 risk items were identified for different project types, and information on 4372 items and 136 lessons learned were collected from experts at HdH. The core of the research is a reasoning methodology used for Knowledge Elicitation of a Risk Mapping and Assessment System which will not only support the decision-making process of the user but also aid the knowledge retrieval, storage, sharing, and updating process of manufacturing organizations. This research provides a systematic engineering approach to risk management of concurrent product and process development.     

A method for imprecision management in complex product development

Managing uncertainty levels is important for organizations carrying out complex product development processes since it fosters design process improvements and optimization. Among the different uncertainties, design imprecision is known to represent uncertainty in decision-making that typically triggers changes to the value assigned to design variables during the early stages of the development process. This paper presents a method aiming to support large organizations understanding, quantifying and communicating this type of uncertainty. The imprecision management method that is proposed relies on five main steps: collection of historical records of change, time evolution reconstruction, statistical characterization of the typical levels of imprecision that should be expected, communication to new projects and continuous knowledge update. In addition, we present results from a case-study performed at Rolls–Royce that tested the method’s applicability in practice. The study shed light to interesting empirical findings about the typical level of imprecision in design variables and its evolution during real product development projects. The results from this initial evaluation suggest that the method provides useful support for design process management and thus has industrial value.     

A Dominance-based Design Metric in Multiattribute Robust Design

This paper outlines the development of an effective and consistent ‘designing-in-quality’ strategy that can be used to deal with concepts of uncertainty, quality and robustness in engineering design. Specifically, this paper presents a decision analysis-based robust design metric that seamlessly integrates objective evaluations on the goodness of a design alternative with the designer’s intent and preferences. This is achieved through the development of a set of performance-reflecting dominance indices for the attributes and their utilization in a preference-influenced multiattribute utility formulation. Such a knowledge feedback-based decision model development will be particularly useful when dealing with complex iteration-based engineering design process where little information on the expected outcomes may be known a priori, or where product performance is computationally expensive to evaluate. Application of this robust design metric in a multi-stage experimentation and modeling design process is presented. The characteristics of the proposed design metric and the effectiveness of the overall design procedure in dealing with constrained engineering design problems are examined with the aid of demonstrative case studies and the results are discussed.     

基于深度学习的产品外观意象情感计算服务平台研究

目的产品外观意象激发用户的情感体验,成为影响消费者购买决策的重要因素。情感的主观性与意象的模糊性,使产品外观意象与用户情感需求的有效映射成为产品设计的难题。产品外观具有多维特征,传统产品意象研究多考虑产品部分特征,需要人工标注产品特征,样本量小,造成设计方案与用户情感需求的偏差。针对这些问题提出解决方案,减少产品情感研究中不确定性因素的干扰,实现产品设计方案与用户意象需求的有效匹配。方法提出构建基于深度学习的产品外观意象情感计算服务平台,研究平台构建方法与关键技术。提出产品外观情感数据库建立方法和产品外观意象情感计算方法。构建产品外观意象情感计算模型,实现更为精确的产品外观意象情感分类与情感特征识别。提出分析不同产品类型的产品外观情感特征权重,研究产品特征对情感意象的贡献程度,挖掘关键情感特征。研究面向用户情感需求的产品外观方案检索方法和技术,以构建产品设计服务平台。结论研究成果将为建立高效、人性化的产品外观意象设计协同服务平台提供参考,从而简化设计师与用户的知识获取过程,促进产品外观设计方案与用户意象需求的有效匹配。     

Improved new product development through enhanced design architecture for engineer-to-order companies

There are many challenges that face companies today in the new product introduction process. These can include reduced design times, fast times to market, improved quality and the need for constant price reductions in order to keep up with the competition. Engineer-to-order firms face even more challenges because of the ‘build to order’ way that they must do business. This study presents new ways for these companies to meet the challenges posed by the market using a business case relating to the product introduction process at a mid-size (～$75 million annual sales) engineer-to-order manufacturer of flexible printed circuits. The company has developed a new product introduction process that seeks to improve quality and delivery times as well as process development for the project at hand. These suggested outcomes of the improved process are generic and widely applicable to contract manufacturers involved in the new product introduction process enabling them to work closely with customers thereby effectively addressing their design concerns. The updated procedures are examined in-depth and the associated forms and record-keeping methods are presented and analysed. The new product introduction process utilises Deming's plan, do, check and act process improvement cycle. Finally, various contributions emanating from the study that enhance our understanding of any engineer-to-order new product development environment are presented.     

An intelligent approach to robust multi-response process design

In order to meet strict customer demands in a global highly-complex industrial sector, it is necessary to design manufacturing processes based on a clear understanding of the customer's requirements and usage of a product, by translating this knowledge into the process parameter design. This paper presents an integrative, general and intelligent approach to the multi-response process design, based on Taguchi's method, multivariate statistical methods and artificial intelligence techniques. The proposed model considers process design in a general case where analytical relations and interdependency in a process are unknown, thus making it applicable to various types of processes, and incorporates customer demands for several (possible correlated) characteristics of a product. The implementation of the suggested approach is presented on a study that discusses the design of a thermosonic copper wire bonding process in the semiconductor industry, for assembly of microelectronic devices used in automotive applications. The results confirm the effectiveness of the approach in the presence of different types of correlated product quality characteristics.     

Better integration of human factors considerations within safety in design

‘Safety in design’ is becoming an increasingly used approach in a variety of domains. Also known as ‘safe design’ or ‘prevention through design’, the general process seeks to eliminate health and safety hazards, or minimise potential risks, by systematically involving end-users and decision makers in the full life cycle of the designed product or system. This article focuses on the need to better integrate human factors considerations within safe design for high-hazard industries. In particular, it describes the benefits of applying a task-based approach to assist design processes. By way of presenting a safe design method for equipment used in mining, it shows the need to obtain end-user input both to better reveal design deficiencies and to identify effective solutions for future equipment. Overall, a multidisciplinary framework is advocated, in particular by blending human factors techniques and structured risk management methods with the existing equipment design processes.