François Cluzel

Using evolutionary design to interactively sketch car silhouettes and stimulate designer's creativity

An Interactive Genetic Algorithm is proposed to progressively sketch the desired side-view of a car profile. It adopts a Fourier decomposition of a 2D profile as the genotype, and proposes a cross-over mechanism. In addition, a formula function of two genes discrepancies is fitted to the perceived dissimilarity between two car profiles. This similarity index is intensively used, throughout a series of user tests, to highlight the added value of the IGA compared to a systematic car shape exploration, to prove its ability to create superior satisfactory designs and to stimulate designers creativity. These tests have involved six designers with a design goal defined by a semantic attribute. The results reveal that if friendly is diversely interpreted in terms of car shapes, sportive denotes a very conventional representation which may be a limitation for shape renewal.

Exploitation scenarios in industrial system LCA

PurposeThis paper considers the variabilities that exist in the exploitation of a complex industrial system. Our scenario-based LCA model ensures the reliability of results in situations where the system life cycle is very uncertain, where there is substantial lack of data, and/or where time and resources available are limited. It is also an effective tool to generate exploitation recommendations for clients.MethodsExisting quantitative uncertainty methods in LCA require a huge amount of accurate data. These data are rarely available in simplified and upstream LCA for complex industrial systems. A scenario-based approach is the best compromise between acceptable quality of results and resources required. However, such methods have not yet been proposed to improve the environmental knowledge of the system in the case of exploitation scenarios. The method proposed here considers a limited number of scenarios (three or four) that are defined using the Stanford Research Institute matrix. Using results from past projects, relevant parts of the system are listed, and expert knowledge and parameters are associated with these parts and quantified. A classical LCA process then provides the results for the different scenarios.Results and discussionThe method was applied to an Alstom Grid AC/DC conversion substation for the primary aluminum industry. A previous study had limited scope, as the life cycle was poorly understood. Relevant parts were, thus, clearly identified as follows: spare parts program, transport failures, preventive and corrective maintenance, updates and revampings, lifetime modulation, and end-of-life. Four scenarios were considered as follows: best case, worst case, baseline (expected future), and a highly different alternative. Results show the pertinence of considering several exploitation scenarios when the life cycle is not predictable, as the environmental impacts may vary widely from one case to another. A sensitivity analysis also shows that some relevant parts such as updates and revampings will need to be carefully considered in futures studies.ConclusionsThe consideration of three exploitation scenarios (best case, baseline, and worst case) appears to be extremely pertinent when considering simplified LCA of industrial systems with high uncertainties and limited time and resources. This model is also very useful to generate good practice and recommendations towards clients, thus initiating a dialog centered on eco-design and continuous improvement.

Managing the Complexity of Environmental Assessments of Complex Industrial Systems with a Lean 6 Sigma Approach

The integration of environmental concerns into the product design process has highlighted a new problem that arises when confronted with complex systems. Indeed environmental assessment methodologies like Life Cycle Assessment (LCA) become in this case particularly heavy to implement. Considering aluminium electrolysis substations as a complex industrial system, we propose a new eco-design methodology based on a Lean Six Sigma approach. Including the environmental parameter as the fourth dimension of the Quality, Costs, Time triangle this methodology has the advantage to cover and systematize the entire eco-design process. It answers to most of the limits raised in our study and allows managing a part of the complexity that appears in particular during the goal and scope definition and the inventory phases of LCA. An application of aluminium electrolysis substations is mentioned.

Proposition for an adapted management process to evolve from an unsupervised Life Cycle Assessment of complex industrial systems towards an eco-designing organisation

The integration of environmental concerns into the product design process is not trivial when dealing with complex industrial systems. Actually, environmental assessment methodologies like Life Cycle Assessments reach, in this case, methodological and organisational limits. More generally, the complexity inherent in the design process may put off eco-design initiatives from a lack of organisational management, methods and tools. In this article, we propose a project management methodology to facilitate the integration of eco-design into the design process of complex industrial systems. This methodology is based on continuous improvement and a Define, Measure, Analyse, Improve, Control (DMAIC) process. It is then structured around precise team definition, precise milestones, deliverables and phases. A first stage ensures a reliable environmental assessment of the full system and the identification of environmental improvement projects. A second stage allows the independent execution of the most promising improvement projects. A first application is proposed on the Alstom Grid AC/DC (alternative current/direct current) conversion substations for the aluminium industry. A Life Cycle Assessment has been performed with limited resources and has provided rich findings and promising perspectives. It shows in particular that the best environmental configuration of such a complex industrial system depends on external parameters like the implantation site.

The DSM Value Bucket Tool

The Dependency Structure Modelling Value Bucket (DSM-VB) tool is integrated to Radical Innovation Design (RID) methodology for exploring the front end of innovation in need seeker mode. The determination of value buckets has been automated by matrix representations of dependencies between problems or pain points, usage situations and existing solutions. Three matrices are built along the problem setting stage of a RID process. The first matrix expresses which problems occur during usage scenarios, the second how much existing solutions cover problems and the third how much existing solutions are useful in usage situations. Combining these three matrices results in a matrix of value buckets as being the combinations of important problems occurring during characteristic usage situations and for which few existing solutions are useful or efficient. This outcome allows to perform focused creativity workshops and to result in “blue ocean” innovations with high likelihood to be successful on the market.

In Vivo In Situ Experimentation Projects by Innovative Cleantech Start-Ups in Paris

Cities play an essential role in facilitating and supporting the real-world experimentations (for instance in public spaces with real users) of innovative products and services in the field of clean technologies. In this respect, the City of Paris has implemented an experimentation mechanism to help innovative start-ups improving their solutions and robustifying their business models in a multi-stakeholder ecosystem. Nonetheless, a primary investigation demonstrated that the efficiency of these in vivo in situ experimentations have means of being improved. To deal with this issue, the current paper proposes a critical review and a characterization of the existing projects related to clean technology and sustainability themes. A study over 25 experimentation projects results in identifying matches and mismatches between the expectations and the obtained results of tests by innovative start-ups. We have statistically demonstrated that the most important purpose of running experimentation projects by start-ups is to test and build a relevant stakeholders network around their businesses. Furthermore, we have assessed the influence of these experimentations on the design of innovative products.

Comparing Sustainable Performance of Industrial System Alternatives by Integrating Environment, Costs, Clients and Exploitation Context

Life Cycle Assessment (LCA) is a methodology to assess environmental performances of products throughout their life cycles. Traditionally, LCA-based decision-making focuses on environmental impacts, excluding customer expectations and economic considerations. Moreover, it usually uses generic data while environmental performances of industrial systems often depend on local contexts. The aim of this paper is to provide a comprehensive framework to identify the solution most adapted to a specific context, considering environmental, economic and commercial aspects. First, environmental performances of competing products are compared thanks to LCA. A sensitivity analysis highlights influential parameters on which operational scenarios are built. Costs are then incorporated into a set of exploitation scenarios.Second, matrix-based approach is used. Products are ranked according to several client profiles. The most suitable solution for a given context is identified.This framework is applied on three burners for forge furnaces. Results show that client profiles and operational contexts (namely client expectations, location and resources availability and costs) affect choices.Copyright