Robot selection using an integrated approach based on quality function deployment and fuzzy regression

The decision-makers have been experiencing difficulties in determining the most suitable robot alternative due to the increase in number of robots and the diversity in their application areas. A robust decision framework for robot selection should consider multiple and conflicting criteria and the dependencies among them. This paper introduces a decision model for robot selection based on quality function deployment (QFD) and fuzzy linear regression. The proposed approach benefits from the fact that QFD focuses on delivering value by taking into account the customer requirements and then by deploying this information throughout the development process, and applies this perspective to robot selection. Fuzzy linear regression is considered as an alternative decision aid for robot selection problems where imprecise relationships among system parameters exist. An example robot selection problem is presented to illustrate the proposed decision-making approach.     

Optimal new product design using quality function deployment with empirical value functions

The house of quality (HOQ) has been widely proposed as a method for capturing the voice of the customer (VOC) when developing requirements for new products. The methodology has lacked a formal mechanism for trading off customer preferences with technical feasibility and economic reality. We propose a non‐linear mathematical program for determining the optimal engineering specifications during new product development as a function of elicited customer value functions, engineering development and production costs and development time constraints. The model is shown to be computationally feasible for realistic‐size problems and to outperform heuristic approaches. Copyright © 1999 John Wiley & Sons, Ltd.     

Normalisation models for prioritising design requirements for quality function deployment processes

The prioritisation of design requirements is critical for determining resource allocation in the new product design stage through the quality function deployment (QFD) planning processes. To prioritise design requirements, normalisation models are usually used to perform aggregation and normalisation functions. Recognising the weakness of the Wasserman normalisation model from both theoretical and practical viewpoints, this paper proposes an improved normalisation model for the aggregation and normalisation functions. It is verified that the proposed model satisfies Lyman’s normalisation requirement and avoids the problem of Wasserman’s normalisation model. In addition, a normalisation model that takes into account the correlation among customer requirements is also developed to complete a generalised normalisation model for QFD planning processes. A product design case is presented to demonstrate the advantages of the proposed normalisation models.     

Prioritizing quality characteristics in dynamic quality function deployment

Due to the combination of rapid influx of new technology, high pressure on time-to-market and increasing globalization, the number of products that have highly uncertain and dynamic specifications or customer requirements might significantly increase. In order to deal with these inherently volatile products or services, we need to adopt a more pro-active approach in order not to produce an unwanted product or service. Thus, based on the idea of the quality loss function and the zero-one goal programming, an intuitively simple mathematical model is developed to prioritize the quality characteristics (QCs) in the dynamic quality function deployment (QFD). It incorporates a pro-active approach towards providing products and services that meet the future voice of the customer (FVOC). The aim is to determine and prioritize only the ‘important’ QCs with a greater confidence in meeting the FVOC. It is particularly useful when the number of the potentially dominant QCs is very large so that, by using the prioritization, the size of the QFD can be effectively reduced. Some constraints, such as minimum customer satisfaction level and limitation on budget are also taken into consideration. A sensitivity analysis is suggested to give an insight to the QFD users in the change of parameters of the proposed model.     

Improved approach to quality function deployment based on Pythagorean fuzzy sets and application to assembly robot design evaluation

Quality function deployment (QFD) is an effective method that helps companies analyze customer requirements (CRs). These CRs are then turned into product or service characteristics, which are translated to other attributes. With the QFD method, companies could design or improve the quality of products or services close to CRs. To increase the effectiveness of QFD, we propose an improved method based on Pythagorean fuzzy sets (PFSs). We apply an extended method to obtain the group consensus evaluation matrix. We then use a combined weight determining method to integrate former weights to objective weights derived from the evaluation matrix. To determine the exact score of each PFS in the evaluation matrix, we develop an improved score function. Lastly, we apply the proposed method to a case study on assembly robot design evaluation.     

A fuzzy expected value-based goal programing model for product planning using quality function deployment

Product planning is one of four important processes in new product development using quality function deployment (QFD), which is a widely used customer-driven approach. In this article, a hierarchical framework for product planning using QFD is developed. To tackle the fuzziness in functional relationships between customer requirements and engineering characteristics (ECs) in product planning, the least squares method is incorporated into fuzzy regression to investigate those functional relationships, by which a more central tendency can be obtained. Furthermore, a fuzzy expected value-based goal programing model is proposed to specify target values of ECs. Different from some fuzzy product planning approaches for QFD, the proposed programing model has unambiguous interpretations. An illustrated example of a quality improvement problem of emulsification dynamite-packing machine design is given to demonstrate the application and performance of the proposed approach.     

Hesitant fuzzy integrated MCDM approach for quality function deployment: a case study in electric vehicle

Quality function deployment (QFD) is a product planning management instrument which has been used in a broad range of industries. However, the traditional QFD method has been criticised much for its deficiencies in acquiring experts’ opinions, weighting customer requirements (CRs) and ranking engineering characteristics (ECs). To overcome the limitations, an integrated analytical model is presented in this study for obtaining the importance ratings of ECs in QFD by integrating decision-making trial and evaluation laboratory (DEMATEL) technique and Vlsekriterijumska Optimizacija I Kompromisno Resenje (VIKOR) method under hesitant fuzzy environment. In particular, the hesitant fuzzy DEMATEL is used to analyse the interrelationships among CRs and determine their weights, and the hesitant fuzzy VIKOR is utilised to prioritise ECs. Finally, the feasibility and practicality of the proposed method are verified by an example regarding the product development of electric vehicle.     

CAQFD概念设计专家系统模式的研究

质量功能配置(QFD）对满足用户需求的产品概念设计提供了一种切实可行的方法。探讨了计算机辅助QFD概念设计专家系统的设计模型和计算机实现的关键技术。对用户需求信息的获取方法进行了研究,构建了用户需求知识表达的拓扑结构。从知识工程的角度,提出了基于数据库的知识表达模式和推理方式,设计了专家系统的知识推理过程。最后以高速专用磨床的主轴前支承轴承的概念设计为例,进行了系统的应用验证,取得了满意的效果。     

Multi‐response optimization in industrial experiments using Taguchi's quality loss function and principal component analysis

Many industrial experiments based on Taguchi's parameter design (PD) methodology deal with the optimization of a single performance quality characteristic. Studies have shown that the optimal factor settings for one performance characteristic are not necessarily compatible with those of other performance characteristics. Multi‐response problems have received very little attention among industrial engineers and Taguchi practitioners. Many Taguchi practitioners have employed engineering judgement for determining the final optimal condition when several responses are to be optimized. However, this approach always brings some level of uncertainty to the decision‐making process and is very subjective in nature. In order to rectify this problem, the author proposes an alternative approach using a powerful multivariate statistical method called principal component analysis (PCA). The paper also presents a case study in order to demonstrate the potential of this approach. Copyright © 2000 John Wiley & Sons, Ltd.     

Two-phase selection framework that considers production costs of suppliers and quality requirements of buyers

Buyers are faced with selecting the optimal supplier, while suppliers are left to consider production costs. In this study, we developed a two-phase selection framework that allows buyers to evaluate the performance of suppliers while taking production costs into account for value maximisation. This scheme is a win-win solution capable of promoting long-term relationships between buyers and suppliers. Under the assumption of normality, the first phase involves constructing a new Six Sigma quality capability analysis chart (SSQCAC) which takes production costs into account. The objective is to evaluate all potential suppliers using the 100?×?(1–α)% upper confidence limit (UCL) of an integrated Six Sigma quality index (SSQI) Q_PIh when dealing with products with smaller-the-better (STB), larger-the-better (LTB), or nominal-the-best (NTB) quality characteristics. According to interval estimation theory, this method can have a significant impact on the consumption of resources; i.e. the production costs of the supplier can be decreased by reducing the production quality to below that required by the buyer. The proposed method also filters out unsuitable suppliers in order to simplify the decision problem and reduce computational demands and operational risks/costs without compromising the quality of the final product. In the second phase, a detailed analysis is conducted using Euclidean distance measure to select the optimal supplier from among the remaining candidates. We conducted a real-world case study to evaluate the efficacy of the proposed method. We also conducted comparisons with existing methods to demonstrate the advantages of the proposed method and its managerial implications. Suggestions for future study are also provided.     

设计质量创新--QFD、TRIZ和田口方法的集成应用

 产品竞争归根到底是设计与制造水平的竞争,只有在设计中运用新的思想,采用新的理论、方法和原理,才能提高产品的设计质量,实现创新,从而构筑竞争优势．QFD方法以顾客需求为导向,从顾客出发寻找影响产品质量的关键技术．TRIZ理论提供了一种全新的解决创新问题的思想,实现技术创新．田口方法为创新成果转化成物美价廉的产品提供了切实可行的应用工具．在比较和分析3种方法各自特点的基础上,提出了QFD、TRIZ和田口方法的集成应用的设计思想,它将最大限度地发挥各自的优势,弥补不足,从而实现设计质量创新．     

An integrated quality function deployment and capital budgeting methodology for occupational safety and health as a systems thinking approach: The case of the construction industry

In this paper, an integrated methodology for Quality Function Deployment (QFD) and a 0–1 knapsack model is proposed for occupational safety and health as a systems thinking approach. The House of Quality (HoQ) in QFD methodology is a systematic tool to consider the inter-relationships between two factors. In this paper, three HoQs are used to consider the interrelationships between tasks and hazards, hazards and events, and events and preventive/protective measures. The final priority weights of events are defined by considering their project-specific preliminary weights, probability of occurrence, and effects on the victim and the company. The priority weights of the preventive/protective measures obtained in the last HoQ are fed into a 0–1 knapsack model for the investment decision. Then, the selected preventive/protective measures can be adapted to the task design. The proposed step-by-step methodology can be applied to any stage of a project to design the workplace for occupational safety and health, and continuous improvement for safety is endorsed by the closed loop characteristic of the integrated methodology.     

An integrated approach for machine tool selection using fuzzy analytical hierarchy process and grey relational analysis

Selecting a proper machine tool is one of the important decisions a company has to make. Companies which fail to do so face many problems which negatively affect the firm's productivity, flexibility, precision and its responsiveness capabilities. Selection of a machine tool involves a lot of criteria to be simultaneously studied and so it requires a multi-criterion decision making (MCDM) method to solve it. Also the subjectivity involved in such decisions ask for the use of theories such as fuzzy and grey which are very effective in handling subjective inputs. This paper integrates the fuzzy analytic hierarchy process (AHP) and grey relational analysis approaches for the selection of a machine tool from a given set of alternatives. Fuzzy AHP is used to calculate the priority weights of the criteria. Subsequently grey relational analysis (GRA) is employed to rank the alternatives. A well known problem existing in literature has been picked up for the numerical illustration. The results obtained in this paper are better when compared with that existing in literature.     

北京铁路地下直径线盾构选型及功能设计

根据隧道直径的大小和地质等条件,分析北京铁路地下直径线隧道工程盾构法施工中盾构设备选型考虑的因素及选择的机型,确定盾构机型配置的主要功能及对地质的适应性,并对盾构主要结构数据和配备能力进行了计算和描述。提出了盾构选型和设计中需要注意的事项和问题。     

Uncovering differences and similarities among quality function deployment-based methods in Design for X: Benchmarking in different domains

The ability for a product or a service to meet customer needs and requirements efficiently before its market launch is a key-point in design and development activities. Quality Function Deployment (QFD) represents one of the most powerful design methods to achieve such a goal. This study investigates the QFD-based methods proposed in the last two decades, whose use in different ambits of Design for X (DfX) is reported to be effective. We selected most common QFD-based methods, analyzing how designers can implement and coordinate them in design activities effectively throughout their application to an identical case study.     

Investigation and characterization of a control scheme for multivariate quality control

A new scheme for multivariate statistical quality control is investigated and characterized. The control scheme consists of three steps and it will identify any out-of-control samples, select the subset of variables that are out of control, and diagnose the out-of-control variables. A new control variable selection algorithm, the backward selection algorithm, and a new control variable diagnosis method, the hyperplane methods, are proposed. It is shown by simulation that the control scheme is useful in cases where the process variables are correlated and where they are uncorrelated.     

一种保证预设质量和过程稳态的SPC方法

提出三种过程质量指数(PQI)的过程质量指数系统,基于过程质量指数的统计公差提供了一个过程质量要求和控制图设计之间的标准化界面.通过基于过程质量指数的统计公差带增加对x--R或x--s控制图中线的约束,建立一种保证预设质量和过程稳态的统计过程控制新方法.这不仅增强了控制图的功能,也为过程质量规划、统计公差和保证预设质量的SPC相关参数的并行设计提供了指导.