A QFD framework for quality, innovation and high-tech product development dynamics

The customer mostly chooses a product on the base of its quality, which therefore arises as the main cause of its commercial success. In a nearly axiomatic drawing, it follows that the effect of innovation is the improvement of quality, which itself becomes the aim of innovation. Even though the previous statement relates quality and innovation, it still does not explain their dynamics. To stress them, the ‘quality' concept must be analyzed in more detail. In fact, in addition to the ‘perceived quality', the quality ensured through `design, manufacturing and marketing' combined domains should be dealt with. This paper enhances this issue taking advantage of principles and models made available by control theory schemes coupled with quality function development (QFD) and best practice software modeling based on unified modeling language (UML

Mapping customer needs to engineering characteristics: an aerospace perspective for conceptual design

Designing complex engineering systems, such as an aircraft or an aero-engine, is immensely challenging. Formal Systems Engineering (SE) practices are widely used in the aerospace industry throughout the overall design process to minimise the overall design effort, corrective re-work, and ultimately overall development and manufacturing costs. Incorporating the needs and requirements from customers and other stakeholders into the conceptual and early design process is vital for the success and viability of any development programme. This paper presents a formal methodology, the Value-Driven Design (VDD) methodology that has been developed for collaborative and iterative use in the Extended Enterprise (EE) within the aerospace industry, and that has been applied using the Concept Design Analysis (CODA) method to map captured Customer Needs (CNs) into Engineering Characteristics (ECs) and to model an overall ‘design merit’ metric to be used in design assessments, sensitivity analyses, and engineering design optimisation studies. Two different case studies with increasing complexity are presented to elucidate the application areas of the CODA method in the context of the VDD methodology for the EE within the aerospace secto

A fuzzy-QFD approach for the enhancement of work equipment safety: a case study in the agriculture sector

The paper proposes a design for safety methodology based on the use of the Quality Function Deployment (QFD) method, focusing on the need to identify and analyse risks related to a working task in an effective manner, i.e. considering the specific work activities related to such a task. To reduce the drawbacks of subjectivity while augmenting the consistency of judgements, the QFD was augmented by both the Delphi method and the fuzzy logic approach. To verify such an approach, it was implemented through a case study in the agricultural sector. While the proposed approach needs to be validated through further studies in different contexts, its positive results in performing hazard analysis and risk assessment in a comprehensive and thorough manner can contribute practically to the scientific knowledge on the application of QFD in design for safety activities

QFD: an interactive algorithm for the prioritization of product's technical characteristics

The paper is concerned with the problem of the ``prioritization' ' of technical design characteristic s of a product. An interactive algorithm has been developed with the aim to better support the engineering design process by means of quality function deployment (QFD). The algorithm tries to soften customer approach to QFD in those situations in which customers are not able to give a ``significant' ' evaluation of the relative importance of their requirements . The method allows determining a ranking order of design characteristic s without the artificia l conversion of symbols contained in the relationshi p matrix, and without the use of explici t information concerning the relative degree of importance of customer requirements. A simple numerical applicatio n is also provide

Intelligent systems in manufacturing: current developments and future prospects

Global competition and rapidly changing customer requirements are demanding increasing changes in manufacturing environments. Enterprises are required to constantly redesign their products and continuously reconfigure their manufacturing systems. Traditional approaches to manufacturing systems do not fully satisfy this new situation. Many authors have proposed that artificial intelligence will bring the flexibility and efficiency needed by manufacturing systems. This paper is a review of artificial intelligence techniques used in manufacturing systems. The paper first defines the components of a simplified intelligent manufacturing systems (IMS), the different Artificial Intelligence (AI) techniques to be considered and then shows how these AI techniques are used for the components of IMS

Linking design and manufacturing domains via web-based and enterprise integration technologies

The manufacturing industry faces many challenges such as reducing time-to-market and cutting costs. In order to meet these increasing demands, effective methods are need to support the early product development stages by bridging the gap of communicating early design ideas and the evaluation of manufacturing performance. This paper introduces methods of linking design and manufacturing domains using disparate technologies. The combined technologies include knowledge management supporting for product lifecycle management (PLM) systems, enterprise resource planning (ERP) systems, aggregate process planning systems, workflow management and data exchange formats. A case study has been used to demonstrate the use of these technologies, illustrated by adding manufacturing knowledge to generate alternative early process plan which are in turn used by an ERP system to obtain and optimise a rough-cut capacity plan

A framework to review performance measurement systems.

This paper describes a structured review framework for managing business performance. The framework entails the review of both business performance, including thestrategic relevance of the measures, as well as the efficiency and effectiveness of the performance measurement system itself. A range of approaches and tools are employed in the framework which features a review card providing a high level view of the review process, showing the different types of review perspectives and their interactions

A review of agricultural waste activated carbon and effect on adsorption parameters

Activated carbon is widely used in industrial wastewater treatment operation because of the effectiveness in removing the dye. As the conventional activated carbon on market nowadays is expensive, lots of research was done on agricultural materials to replace the activated carbon. Sugarcane bagasse is listed as one of the agricultural material alternatives. This review compiles the characterisation of sugarcane bagasse and several agricultural wastes-based activated carbon including proximate analysis, ultimate analysis, and activated carbon surface characteristic used to remove dye in textile wastewater. Nevertheless, the adsorption parameters are the main focus as it affecting the removal of dye. The expansion review regarding activated carbon performance implies that dye removal efficiency depends on the amount of adsorbent dosage, contact time, pH solution, dye concentration applied during the adsorption process. This review shows the need of thoughtful information on adsorption parameters with an expanded list of various types of agricultural-based activated carbon and various dye removal

AI and OR in management of operations: history and trends

The last decade has seen a considerable growth in the use of Artificial Intelligence (AI) for operations management with the aim of finding solutions to problems that are increasing in complexity and scale. This paper begins by setting the context for the survey through a historical perspective of OR and AI. An extensive survey of applications of AI techniques for operations management, covering a total of over 1200 papers published from 1995 to 2004 is then presented. The survey utilizes Elsevier's ScienceDirect database as a source. Hence, the survey may not cover all the relevant journals but includes a sufficiently wide range of publications to make it representative of the research in the field. The papers are categorized into four areas of operations management: (a) design, (b) scheduling, (c) process planning and control and (d) quality, maintenance and fault diagnosis. Each of the four areas is categorized in terms of the AI techniques used: genetic algorithms, case-based reasoning, knowledge-based systems, fuzzy logic and hybrid techniques. The trends over the last decade are identified, discussed with respect to expected trends and directions for future work suggested