Knowledge modelling for supporting decision making in optimal distributed design process

This contribution highlights the significance of support methods for the early stages of sustainable product development and culminates in the introduction of a comprehensive framework in this domain. The framework aims at assisting designers and product engineers in generating and evaluating ideas for the development of product systems with high sustainability potential. The multi-iterative framework, whose effectiveness has already been demonstrated in diverse workshops, leverages a fusion of creativity and evaluation techniques, identified through an extensive comparison of techniques.

The early stages of product development are arguably the most important in the design of successful products. This paper describes different approaches to the conceptual design phase of product development, how they are taught to undergraduate engineering students, and how they are practiced in industry both in Germany and in the United States. The authors note that teaching the early stages of product development to future engineers at German Universities is more focused on methodology and processes. In the United States teaching design is more about being creative and overcoming individual constraints in order to find good and unconventional concepts. To understand how the conceptual phase is implemented in industry, the authors interviewed 16 companies in Germany and the United States. A thematic analysis was performed on the responses. In German industry, the authors observe uncertainty about how to apply process management in the very early stage of product development where different concepts are developed and evaluated. In U.S. industry most companies do not claim to follow a process during the early stage of concept development. Observing the differences between what is taught to engineering students in school and what is practiced in industry some conclusions recommendations are drawn. The observations demonstrate a weakness in process reliability during the early stage of product development both, in German and U.S. industry that should motivate academia to adapt its pedagogy in order to enable future engineers to create successful concepts.

The quality of the design has been recognized as one of the key factors to the success of the engineering project. However, engineers need to repeatedly perform design tasks, such as processing information, to produce an appropriate design result. Such a design process involves many activities and lead into one or several iterative loops. Consequently, the sequence of performing design activities should be properly planned to avoid unnecessary loops. Design Structure Matrix (DSM) is one of the widely used methods to describe the design process. By employing DSM, the relationships and the sequence of the design activities can be identified. In this research, several principles of evaluating the design process are developed. In addition, fast messy Genetic Algorithm (fmGA) is employed along with the proposed evaluation principles and DSM to determine the optimal design process. Results show, based on the proposed evaluation principles, the impact of the iteration loops can be clearly identified. Furthermore, with the proposed optimization model and its computer implementation, engineers can find the optimal design process for the large-scale design project efficiently and effectively. the proposed evaluation principles and DSM to determine the optimal design process. Results show, based on the proposed evaluation principles, the impact of the iteration loops can be clearly identified. Furthermore, with the proposed optimization model and its computer implementation, engineers can find the optimal design process for the large-scale design project efficiently and effectively.

Decision data model in virtual product development

The objective of this investigation was: (i) to develop a model that supports sustainable product development, considering the quality aspect and the environmental impact in the product life cycle, and (ii) to establish a framework to select the proportion of the share of these aspects during product development decisions. This research concentrates on achieving products that meet customer demand and have environmentally friendly life cycles. It also supports the implementation of design activities at an early stage of product development, positioning the share of quality in relation to environmental impact. The model is based on creating hypothetical prototypes of current products, and this approach concentrated on aggregating the quality (customer satisfaction) with life cycle environmental impacts (as in ISO 14040). The model was developed in five main stages, including: (i) defining product prototypes according to the modifications of quality criteria most desired by customers, (ii) assessing the quality of prototypes according to the Q quality index, (iii) prospective assessment of the environmental impacts of the life cycles of prototypes according to the LCA environmental index, (iv) methodical integration of the above-mentioned indicators into one quality and environmental indicator QLCA, and (v) analysis of possible production solutions and setting the direction of product development, taking into account both quality and environmental aspects. This research was extended with a sensitivity analysis of the QLCA indicator, after which a framework for selecting the proportion of the Q and LCA indicator’s share in product development decisions was established. The originality of this research is the ability of the developed model to facilitate eco-innovative product design and improvements while also selecting the share of qualitative and environmental aspects needed to develop sustainable products. The results provide a dynamic and effective tool for manufacturing companies; mainly designers and managers during qualitative and environmental prototyping of products commonly used by customers. The model will provide support in predicting a product that will be manufactured that will be satisfactory for customers and environmentally friendly based on LCA.

Characteristics of food products are commonly assessed in series of sensory studies to gain insight which can be used, for instance, for product development. Sensory studies are very time‐consuming and susceptible to large sources of variation. Assessing information about (new) products by means of instrumental measurements would be very beneficial for numerous reasons, including repeatability, reproducibility and, most of all, the fact that instruments do not suffer from fatigue or adaptation. Measurements simulating sensory assessment of product properties can be performed at different stages of consumption and on different types of sensory attributes. In this study the relation between rheological parameters and creamy mouthfeel was investigated. The goal was to discover whether a model using a limited mechanical characterization, namely parameters describing bulk rheological behaviour, would suffice to describe the sensory attribute ‘creamy mouthfeel’, also called creaminess. The two main reasons for performing this study were (i) to investigate the possibility of using rheological measurements for high‐throughput screening of newly developed custard products without the need for involving sensory panels already at an early stage of product development and (ii) to gain knowledge about the correlation between rheological measurements and the multidimensional attribute creamy mouthfeel. The resulting model shows that prediction of creamy mouthfeel by means of rheological measurements is possible only to a certain extent ($Q_{\rm CV}^2=0.48$). Reasons that can be mentioned for deviations between measured creaminess and modelled creaminess are (i) variation in measured creamy mouthfeel scores (variation in y‐variable) and (ii) lack of description of surface properties of the food product by the rheological measurements used here. The results show that instrumental measurements are complementary to sensory analysis and can greatly facilitate the task for the practitioner at an early stage of product development, making high‐throughput screening of novel products feasible. Copyright © 2005 John Wiley & Sons, Ltd.

Transfer moulding is the most common process for the encapsulation of electronic packages in semiconductor manufacturing. Quality of the moulding is affected by a large number of mould design parameters and process parameters. Currently, the parameters setting is performed by experienced engineers in a trial and error manner and often the optimal setting can not be obtained. In the face of global competition, the current practice is inadequate. In this research, a process optimisation system for transfer moulding of electronic packages is described which involves design of experiments (DOE) techniques, artificial neural networks (ANNs), multiple regression analysis and the minimax method. The system is aimed to determine the optimal mould design parameters and process parameter settings of transfer moulding of electronic packages for multiobjective problem. Implementation of the optimisation system has demonstrated that the time for the determination of optimal mould design parameters and process parameters setting can be greatly reduced and the parameters setting recommended by the system can contribute to the good quality of moulded packages without relying on experienced engineers.

In this paper, an optimal design process for high-rise building structures is presented based on cost-effectiveness criterion. Then, an optimal design of a complex high-rise building based on cost-effectiveness criterion is carried out by using the design process. A minimum life cycle cost and corresponding elastic inter story drift considering initial cost and damage cost as two separate objective functions are obtained by using genetic algorithm. Finally, fitting curves of life cycle cost, initial cost, damage cost and corresponding performance indexes are interpolated by using one-dimensional linear interpolation considering elastic inter story drift ratio as control performance indexes. And lots of life cycle cost designs and corresponding performance indexes of the separated objective function are given. The results show that the optimal design process is practical and optimal results are diverse, and can be chosen flexibly by owners.

Photogrammetry-based 3D scanning for supporting design activities and testing in early stage product development

Earthquake protection of structures with nonlinear viscous dampers optimized through an energy-based stochastic approach

This paper gives an overview of research that is expanding the domain of design for manufacturing (DFM) into new and important areas. DFM and assembly is widely used in industry, especially in product design and development process. to meet customer needs, companies are struggling with competitive markets to produce low cost products with high quality and faster to market. It becomes an important concept as the best time to find cost reductions, at design stage, rather than during manufacturing. The paper concludes with some general guidelines that suggest how manufacturing firms can develop useful, effective DFM. Overall goal with the paper is to aid designers, manufacturers, process planners in the practical industries on the ground and researchers in the mentioned area of study.

Product development has become a focus of competition in many industries. Due to decreasing product life cycle, it is important to reduce the time and cost of product development. The product development process includes six main phases: product planning, concept development, system-level design, detailed design, testing and refinement, and production ramp-up [34]. Concept development process consists of four stages: identifying customer needs, establishing product specifications, and generating and selecting product concepts. Recent efforts have been made to improve the product development decisions [20], especially at the early stages of product development, since it has been recognized that nearly 75% of product life-cycle cost is committed by the end of concept development [26]. However, it is difficult to make product design decisions at the early development stages, because decision makers have to consider all life cycle issues [21, 22] with vague project information available.

Tolerancing decisions can profoundly impact the quality and cost of electro-mechanical assemblies. Existing approaches to tolerance analysis and synthesis in design entail detailed knowledge of geometry of the assemblies and are mostly applicable during advanced stages of design, leading to a less than optimal design process. During the design process of assemblies, both the assembly structure and associated tolerance information evolve continuously. Therefore, significant gains can be achieved by effectively using this information to influence the design of the assembly. Motivated by this, we identify and explore two goals for future research that we believe can enhance the scope of tolerancing for the entire design process. The first goal is to advance tolerancing decisions to the earliest possible stages of design. This issue raises the need for effective representation of tolerancing information during different stages of design and for effective assembly modeling. The second goal addresses the appropriate, synergistic use of available methods and best practices for tolerance analysis and synthesis, at successive stages of design. Pursuit of these goals leads to the definition of a multilevel approach that enables tolerancing to be addressed at successive stages of design in an incremental fashion. The resulting design process, which we call the design for tolerance process, integrates three important domains: (1) design activities at successive stages of design; (2) assembly models that evolve continuously through the design process; (3) methods and best practices for tolerance analysis and synthesis. We demonstrate major steps of our proposed approach through a simple, yet illustrative, example.

This study proposes a systematic process of a multi‐objective optimal design of an axial‐flux permanent‐magnet motor for electric scooters. The preliminary design uses a zero‐dimensional (0D) model to determine the number of slots and poles and initial sizes of the motor according to the driving requirements of the scooter. The optimal design process uses a 1D magnetic circuit model with an effective air‐gap distribution function, whereas searching for a set of motor parameters that minimise or maximise motor performance indices such as torque, torque density and torque ripple. The final design is verified and refined by the 3D finite element method. The resulting prototype motor features high torque density of 8.94 Nm/kg and electronic gearshifts between low and high gears. According to their efficiency maps, the driving‐cycle efficiency is estimated as 57% for the electric scooter to operate on the driving cycle ECE‐40.

Mass Customization and Beyond – Application of Co-Creation & Postponement