Ac Aarnout Brombacher

A dynamic model for managing overlapped iterative product development

Intense competition in many industries impels firms to develop more products in less time. Overlapping of development activities is regarded as one of the most promising strategies to reduce project cycle time. However, the gain from overlapping must be weighed against the additional resource and time for rework. This paper presents a new product development (NPD) process model, termed Dynamic Development Process Model (DDPM), for managing overlapped iterative product development. We validated the model with data from a mobile phone development project. The DDPM was employed to identify appropriate policies for the overlapped iterative projects in the case study company. These identified policies were implemented in the company and led to marked improvement in project performance, thus demonstrating the viability of our model.

Quality and Reliability Problems from a Consumer's Perspective: an Increasing Problem Overlooked by Businesses?

Currently, many businesses in the consumer electronics industry are facing an increasing number of consumer complaints, despite the application of quality tools that proved to be very powerful in the past. We assessed over 20 new product development projects, to understand the reasons behind the rising number of consumer complaints. We found that businesses are developing more innovative products that are brought to the market faster, with inherently higher uncertainties on the consumer expectations of these products. Current analyses of consumer complaints solely focus on checking if the product is functioning according to the technical specification, and these analyses show a rising number of consumer complaints where no failure could be established. When looking at product quality and reliability from a consumers perspective, we found that consumers complain not only about technical product failures but also when the product does not satisfy their expectations. In this paper we will take the perspective of the consumer to analyse dissatisfaction with new products from various available sources, which were not set-up for quality and reliability purposes. We will show that analysing information from these sources gives better information, especially on the non-technical failures compared with the traditional quality and reliability sources. Copyright

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.

Managing product reliability in business processes 'under pressure'

Product reliability is often seen as a product attribute. Models with different degree of sophistication analyze and predict the reliability of a product as a function of the internal structure (such as components and their relation). The practical relevance of these models, in relation with the (business) processes in which the related products are actually used, is not often addressed. Different types of reliability issues, however, can be relevant for products in different industrial contexts. This paper will present a classification model to describe different business processes, based on the degree of product innovation. It will also propose a taxonomy that can be used to classify different types of reliability problems. As this paper will demonstrate, only certain combinations of reliability problems are relevant for certain business processes. It will also show that, given certain technology trends, some combinations will become more relevant in the future. The final part of this paper will demonstrate that especially for these combinations many of the existing reliability analysis and prediction methods can be considered inadequate.

Analysis of quality information flows in the product creation process of high-volume consumer products

It is recently realised that Quality and Reliability are not only a function of the product but also of the organisation realising the product. In spite of this very few companies are able to translate this into their business processes. The Maturity Index on Reliability (MIR) was developed to measure and improve the capability of organisations to analyse, predict and improve the reliability of current and future products. The MIR concept is based on the analysis of reliability related information flows. In this paper the MIR concept is explained and a case study of a MIR assessment is given.

Bivariate constant stress degradation model: LED lighting system reliability estimation with two-stage modelling

Light-emitting diode (LED) lamp has received great attention as a potential replacement for the more commercially available lighting technology, such as incandescence and fluorescence lamps. LED which is the main component of LED lamp has a very long lifetime. This means that no or very few failures are expected during LED lamp testing. Therefore, degradation testing and modelling are needed. Because the complexity of modern lighting system is increasing, it is possible that more than one degradation failures dominate the system reliability. If degradation paths of the systems performance characteristics (PCs) tend to be comonotone there is a likely dependence between the PCs because of the systems common usage history. In this paper, a bivariate constant stress degradation data model is proposed. The model accommodates assumptions of dependency between PCs and allows the use of different marginal degradation distribution functions. Consequently, a better system reliability estimation can be expected from this model than from a model with independent PCs assumption. The proposed model is applied to an actual LED lamps experiment data. Copyright

New quantitative safety standards : different techniques, different results?

Abstract Safety Instrumented Systems (SIS) are used in the process industry to perform safety functions. Many factors can influence the safety of a SIS like system layout, diagnostics, testing and repair. In standards like the German DIN no quantitative analysis is demanded (DIN V 19250 Grundlegende Sicherheitsbetrachtungen fur MSR-Schutzeinrichtungen, Berlin, 1994; DIN/VDE 0801 Grundsatze fur Rechner in Systemen mit Sicherheitsaufgaben, Berlin, 1990). The analysis according to these standards is based on expert opinion and qualitative analysis techniques. New standards like the IEC 61508 (IEC 61508 Functional safety of electrical/electronic/programmable electronic safety-related systems, IEC, Geneve, 1997) and the ISA-S84.01 (ISA-S84.01.1996 Application of Safety Instrumented Systems for the Process Industries, Instrument Society of America, Research Triangle Park, 1996) require quantitative risk analysis but do not prescribe how to perform the analysis. Earlier publications of the authors (Rouvroye et al., Uncertainty in safety, new techniques for the assessment and optimisation of safety in process industry, D W. Pyatt (ed), SERA-Vol. 4, Safety engineering and risk analysis, ASME, New York 1995; Rouvroye et al., A comparison study of qualitative and quantitative analysis techniques for the assessment of safety in industry, P.C. Cacciabue, I.A. Papazoglou (eds), Proceedings PSAM III conference, Crete, Greece, June 1996) have shown that different analysis techniques cover different aspects of system behaviour. This paper shows by means of a case study, that different (quantitative) analysis techniques may lead to different results. The consequence is that the application of the standards to practical systems will not always lead to unambiguous results. The authors therefore propose a technique to overcome this major disadvantage.

A Methodology to Improve Higher Education Quality using the Quality Function Deployment and Analytic Hierarchy Process

Abstract In order to formulate an effective strategic plan in a customer-driven education context, it is important to recognize who the customers are and what they want. Using Quality Function Deployment (QFD), this information can be translated into strategies to achieve customer satisfaction. Since the final strategic plan relies heavily on the way QFD is used, this paper will first describe the existing problems in its use and then propose a better way to improve it. In this paper, the customers are divided into two major parties, namely, the internal and the external customer. The internal customer comprises of the lecturers and the students, while the external customer is the employers of the graduates. After collecting the Voice of Customer (VOC), the Analytic Hierarchy Process (AHP) technique was employed to generate the priorities of the VOC for each group of customers. Then, the results were used as the input for formulating strategies or Quality Characteristics (QCs) to meet the Demanded Qualities (DQs) using QFD. A simple case study is provided to demonstrate the usefulness of the methodology. A sensitivity analysis was also conducted to anticipate the changes in the DQs that will affect the output of the QFD. This is useful for providing a better strategic planning for the education institution to meet the future needs of its customers.

Optimal overlapping and functional interaction in product development

Overlapping of development stages and interaction between different functions are regarded as important strategies for reducing development lead time. However, overlapping typically requires additional costs for rework and functional interaction increases communication time. This paper presents an analytical model to improve project performance by balancing the positive and negative effects of overlapping and functional interaction. We first investigate the progress of downstream development, which is essential to derive the optimal overlapping policies. We find that the downstream progress increases over time when the upstream evolution is fast or linear, but it is indefinite when the upstream evolution is slow. Then, we present optimal overlapping policies taking into account the complexity of downstream progress. The impact of different project properties, such as the dependency between development stages and the opportunity cost of time, on overlapping policies is discussed. Finally, we derive the optimal functional interaction strategy when the optimal overlapping is followed. The methodology is illustrated with a case study at a handset design company.

Using a failure modes, effects and diagnostic analysis (FMEDA) to measure diagnostic coverage in programmable electronic systems.

Abstract One of the key issues in the quantitative evaluation of programmable electronic systems is the diagnostic capability of the equipment. This is measured by a parameter called the Coverage Factor, C . This factor can vary widely. The range of possible values is often the subject of great debate. Within limits, the diagnostic coverage factor can be calculated by knowing which component failure modes are detected by diagnostics. An extension of the Failure Modes and Effects Analysis (FMEA) can be used to show this information. This extension, called a Failure Modes, Effects and Diagnostic Analysis can serve as a useful design verification tool as well as a means to provide more precise input to reliability and safety modeling.