Driving in the wrong lane: towards a longer life-span of cars

Within the context of product longevity, one especially impactful and ubiquitous product demands further research: the car. Car longevity has been addressed in the context of product life extension and product lifetime optimisation but there have been a few studies on car longevity in the context of business and none specifically from an industrial design context. This paper presents initial findings from preliminary interviews with key industry representatives such as car designers and engineers. It discusses the barriers to and opportunities for designing a car with a longer life-span. This and further data will later be analysed in order to produce a design framework to inform car designers on life-span and usage optimization through design. Strategies such as increased longevity or use-intensity can potentially reduce the throughput - and thereafter the consumption - of cars. Such a shift in the automotive sector would support the transition from a linear economy to a more sustainable one. The initial findings, however, suggest that a longer life car is not an uncompromised solution and important concessions would have to be made in order to make this an acceptable product

Bicriteria Product Design Optimization: An Efficient Solution Procedure Using AND/OR Trees

Abstract: Competitive imperatives are causing manufacturing firms to consider multiple criteria when designing products. However, current methods to deal with multiple criteria in product design are ad hoc in nature. In this paper we present a systematic procedure to efficiently solve bicriteria product design optimization problems. We first present a modeling framework, the AND/OR tree, which permits a simplified representation of product design optimization problems. We then show how product design optimization problems on AND/OR trees can be framed as network design problems on a special graph-a directed series-parallel graph. We develop an enumerative solution algorithm for the bicriteria problem that requires as a subroutine the solution of the parametric shortest path problem. Although this parametric problem is hard on general graphs, we show that it is polynomially solvable on the series-parallel graph. As a result we develop an efficient solution algorithm for the product design optimization problem that does not require the use of complex and expensive linear/integer programming solvers. As a byproduct of the solution algorithm, sensitivity analysis for product design optimization is also efficiently performed under this framework

Novel models and algorithms for systems reliability modeling and optimization

Recent growth in the scale and complexity of products and technologies in the defense and other industries is challenging product development, realization, and sustainment costs. Uncontrolled costs and routine budget overruns are causing all parties involved to seek lean product development processes and treatment of reliability, availability, and maintainability of the system as a true design parameter . To this effect, accurate estimation and management of the system reliability of a design during the earliest stages of new product development is not only critical for managing product development and manufacturing costs but also to control life cycle costs (LCC). In this regard, the overall objective of this research study is to develop an integrated framework for design for reliability (DFR) during upfront product development by treating reliability as a design parameter. The aim here is to develop the theory, methods, and tools necessary for: 1) accurate assessment of system reliability and availability and 2) optimization of the design to meet system reliability targets. In modeling the system reliability and availability, we aim to address the limitations of existing methods, in particular the Markov chains method and the Dynamic Bayesian Network approach, by incorporating a Continuous Time Bayesian Network framework for more effective modeling of sub-system/component interactions, dependencies, and various repair policies. We also propose a multi-object optimization scheme to aid the designer in obtaining optimal design(s) with respect to system reliability/availability targets and other system design requirements. In particular, the optimization scheme would entail optimal selection of sub-system and component alternatives. The theory, methods, and tools to be developed will be extensively tested and validated using simulation test-bed data and actual case studies from our industry partners

Design and Core Competency, The Missing Links.

International audienceDesigning in an industrial context is a very complex activity. It needs the integration of heterogeneous knowledge or skills, to transform a set of ill-defined requirements into an artefact that satisfies esthetical, functional, technical, economical criteria. Design process optimization with methods like system engineering and core competency building are key issues for managers of product development process, design skills networks, communities of design practices... In the literature, these issues have been dealt with separately. In this paper, we propose a framework of reference that helps us to explicit the content of the core design competency. This framework is a first step beyond an efficient compentency based management of design structures

AN INTEGRATED SYSTEMS ENGINEERING METHODOLOGY FOR DESIGN OF VEHICLE HANDLING DYNAMICS

The primary objective of this research is to develop an integrated system engineering methodology for the conceptual design of vehicle handling dynamics early on in the product development process. A systems engineering-based simulation framework is developed that connects subjective, customer-relevant handling expectations and manufacturers\u27 brand attributes to higher-level objective vehicle engineering targets and consequently breaks these targets down into subsystem-level requirements and component-level design specifications. Such an integrated systems engineering approach will guide the engineering development process and provide insight into the compromises involved in the vehicle-handling layout, ultimately saving product development time and costs and helping to achieve a higher level of product maturity early on in the design phase. The proposed simulation-based design methodology for the conceptual design of vehicle handling characteristics is implemented using decomposition-based Analytical Target Cascading (ATC) techniques and evolutionary, multi-objective optimization algorithms coupled within the systems engineering framework. The framework is utilized in a two-layer optimization schedule. The first layer is used to derive subsystem-level requirements from overall vehicle-level targets. These subsystem-level requirements are passed on as targets to the second layer of optimization, and the second layer derives component-level specifications from the subsystem-level requirements obtained from the first step. The second layer optimization utilizes component-level design variables and analysis models to minimize the difference between the targets transferred from the vehicle level and responses generated from the component-level analysis. An iterative loop is set up with an objective to minimize the target/response consistency constraints (i.e., the targets at the vehicle level are constantly rebalanced to achieve a consistent and feasible solution). Genetic Algorithms (GAs) are used at each layer of the framework. This work has contributed towards development of a unique approach to integrate market research into the vehicle handling design process. The framework developed for this dissertation uses Original Equipment Manufacturer\u27s (OEM\u27s) brand essence information derived from market research for the derivation and balancing of vehicle-level targets, and guides the chassis design direction using relative brand attribute weights. Other contributions from this research include development of empirical relationships between key customer-relevant vehicle handling attributes selected from market survey and the various scenarios and objective metrics of vehicle handling, development of a goal programming based approach for the selection of the best solution from a set of Pareto-optimal solutions obtained from genetic algorithms and development of Vehicle Handling Bandwidth Diagrams

SQG-Differential Evolution for difficult optimization problems under a tight function evaluation budget

In the context of industrial engineering, it is important to integrate efficient computational optimization methods in the product development process. Some of the most challenging simulation-based engineering design optimization problems are characterized by: a large number of design variables, the absence of analytical gradients, highly non-linear objectives and a limited function evaluation budget. Although a huge variety of different optimization algorithms is available, the development and selection of efficient algorithms for problems with these industrial relevant characteristics, remains a challenge. In this communication, a hybrid variant of Differential Evolution (DE) is introduced which combines aspects of Stochastic Quasi-Gradient (SQG) methods within the framework of DE, in order to improve optimization efficiency on problems with the previously mentioned characteristics. The performance of the resulting derivative-free algorithm is compared with other state-of-the-art DE variants on 25 commonly used benchmark functions, under tight function evaluation budget constraints of 1000 evaluations. The experimental results indicate that the new algorithm performs excellent on the 'difficult' (high dimensional, multi-modal, inseparable) test functions. The operations used in the proposed mutation scheme, are computationally inexpensive, and can be easily implemented in existing differential evolution variants or other population-based optimization algorithms by a few lines of program code as an non-invasive optional setting. Besides the applicability of the presented algorithm by itself, the described concepts can serve as a useful and interesting addition to the algorithmic operators in the frameworks of heuristics and evolutionary optimization and computing

A Large Neighborhood Search heuristic for Supply Chain Network Design

24 pagesMany exact or approximate solution techniques have been used to solve facility location problems and more generally supply chain network design problems. Yet, the Large Neighborhood Search technique (LNS) has almost never been proposed for solving such problems, although it has proven its efficiency and flexibility in solving other complex combinatorial optimization problems. In this paper we propose an LNS framework for solving a four-layer single period multi-product supply chain network design problem involving multimodal transport. Location decisions for intermediate facilities (e.g. plants and distribution centers) are made using the LNS while transportation modes and product flow decisions are determined by a greedy heuristic. As a post-optimization step, we also use linear programming to determine the optimal product flows once the logistics network is fixed. Extensive experiments based on generated instances of different sizes and characteristics show the effectiveness of the method compared with a state-of-the-art solver

From design optimization systems to geometrical contradictions

AbstractWithin the framework of the Research Project PROSIT [1] aimed at the development of an integrated product design platform capable to link Computer-Aided Innovation (CAI) with PLM/EKM systems, the authors have approached the analysis of the contradictions emerging during the design embodiment phase. In this case, since the functional architecture of the product is already fixed, design conflicts arise due to contradictory geometrical requirements. Design Optimization systems can play a relevant role for the identification of these “geometrical contradictions”, even if with modified criteria of usage. The present paper first describes how Design Optimization can be adopted as a means to link CAI and PLM/EKM systems; then a detailed analysis of geometrical contradictions is reported together with the criteria proposed for their categorization. Finally, the discussion is focused on the adoption of the proposed classification of geometrical contradictions as a pointer to the most suitable inventive principles and geometrical effects to overcome the design conflicts