Jean Marc Le Lann

Eco-innovative design method for process engineering

Due to the environmental issues, innovation is one way to challenge eco-friendly technologies, create new process options which are needed to meet the increasing demands for sustainable production. To accelerate and improve eco-innovative design, there is a need for the computer aided eco-innovation tools to support engineers in the preliminary design phase. Currently, several computer aided innovation tools with a clear focus on specific innovation tasks exist but very few of them deal with the eco-innovation issues. Therefore the purpose of this paper is to present the development of a computer aided model based preliminary design methodology focused on technological eco-innovation for chemical engineering. This methodology is based on modified tools of the structured TRIZ theory. The general systematic framework gives the same level of importance, to the technological and environmental requirements during the conceptual design phase. Integrating environment oriented design approach at the earliest, in the design phase, is essential for product effectiveness and future development. The methodology employs a decomposition based solution approach in hierarchical steps by analysing the problem faced, formulation of the problem and the generation of possible and feasible ideas. At each step, various methods and tools will be needed. In this paper some existing tools are adapted to chemical engineering and some tools of the structured TRIZ theory are modified and improved to build a specific methodology oriented towards the increasing technological complexity and environmental issues of current designs. Undoubtedly, the selection of materials and substances for a particular generated concept, mainly affects the structure, mechanical factors (processability and dimensions) and the environmental impact. In order to deal with these environmental criteria, the resources and their impacts are considered in the upstream phase of the design process and are introduced as constraints in our model. To highlight its capabilities, the methodology is illustrated through a case study dedicated to tars and ashes issues in biomass gasification.

Model based fault diagnosis for hybrid systems : application on chemical processes

The complexity and the size of the industrial chemical processes induce the monitoring of a growing number of process variables. Their knowledge is generally based on the measurements of system variables and on the physico-chemical models of the process. Nevertheless, this information is imprecise because of process and measurement noise. So the research ways aim at developing new and more powerful techniques for the detection of process fault. In this work, we present a method for the fault detection based on the comparison between the real system and the reference model evolution generated by the extended Kalman filter. The reference model is simulated by the dynamic hybrid simulator, PrODHyS. It is a general object-oriented environment which provides common and reusable components designed for the development and the management of dynamic simulation of industrial systems. The use of this method is illustrated through a didactic example relating to the field of Chemical Process System Engineering.

The extended resource task network: a framework for the combined scheduling of batch processes and CHP plants

The issue of energy has emerged as one of the greatest challenges facing mankind. In an industrial perspective, the development of site utility systems (generally combined heat and power (CHP) systems) for the generation and management of utilities provides a great potential source for energy savings. However, in most industrial sites, a master–slave relationship usually governs this kind of system and limits the potential operating capacity of CHP. To improve the decision-making process, Agha et al. (2010. Integrated production and utility system approach for optimising industrial unit operation. Energy, 35, 611–627) have proposed an integrated approach that carries out simultaneous and consistent scheduling of batch production plants and site utility systems. The modelling of the problem relies on a mixed integer linear programming (MILP) formulation. Nevertheless, although it is a powerful mathematical tool, it still remains difficult to use for non-expert engineers. In this framework, a graphical formalism based on existing representations (STN, RTN) has been developed: the extended resource task network (ERTN). Combined with an efficient and generic MILP formulation, it permits various kinds of industrial problems, including production and consumption of utility flows to be modelled homogenously. This paper focuses on the semantic elements of the ERTN formalism and illustrates their use through representative examples.

Innovation and knowledge management: using the combined approach TRIZ-CBR in process system engineering

In this article, a TRIZ based model is proposed to support the innovation and knowledge capitalization process. This model offers a knowledge base structure, which contains several heuristics to solve problems, synthesized from a large range of domains and industries and, also, the capacity to capture, store and make available the experiences produced while solving problems.

Constraint Satisfaction Problem for Case-Based Reasoning Adaptation: Application in Process Design

Abstract Process design represents a complex domain where past experiences are often used to solve new design problems. Currently in the Artificial Intelligence field and more particularly in Knowledge Management some techniques arise in order to accelerate the entire design process. Among these methods Case Based Reasoning is emerging as an efficient approach to deal with this challenge, allowing to store previous design cases to help for solving new problems and reducing considerably the design time. However existing cases must be adapted to new problem situation. In this article we deal with the case adaptation problem and we propose an improvement of CBR using a Constraints Satisfaction Problem approach applied to the early phase of process design.

Process Innovation through bio-inspired design

Abstract In process system engineering, we often adopt a constructivist approach to answer the question “How can we go from parts to a whole system?” To answer to this question we need to propose approach that, based on the knowledge of phenomena at small-scale, allows going up the different scales in order to design process but also to innovate thanks to the creation of new knowledge. In this paper, a bio inspired design approach is presented. It is based on two main principles which intervene repetitively to understand and analyze the passage between scales for living organisms: the juxtaposition of foundational blocks that assemble, and then differentiation. The goal of this paper is to demonstrate that these principles can find a more widespread use and in particular they can be integrated into a process system engineering constructivist approach for innovative design. After defining the fundamental building blocks to initiate the process of juxtaposition and integration, an example on distillation and reactive distillation is used to illustrate the method capabilities in process synthesis.

Collaboration Framework for TRIZ-Based Open Computer-Aided Innovation

In the current industrial context, there is an increasing interest in the collective resolution of creative problems during the conceptual design phase. With collaboration, companies can expect to facilitate aggregation of multi-intelligence and knowledge for the proposal of new inventive solutions. Recent advances in theoretical approaches to innovation management as well as in information and communication technologies provide a more structured knowledge-driven environment for inventors, designers, and engineers. As a result, a new category of tools known as computer-aided innovation (CAI) is emerging, with the goal of assisting designers in their creative performance and of effectively implementing a complete innovation process. This chapter proposes a next evolutionary step for CAI, arising from two major recent developments: one coming from the advances in information and communication technology possibilities commonly referred to as “Web 2.0” and the other coming from a strategic paradigm shift from closed to open innovation. To go further, in this work we introduce an information-based software framework to collaborate for inventive problem solving. This framework proposes the implementation of techniques from the collective intelligence research field in combination with the systematic methods provided by the TRIZ theory. While collective intelligence focuses on the intelligent behavior that emerges in collaborative work, the TRIZ theory concentrates its attention in the individual capacity to solve problems systematically. The framework’s objective is to improve the individual creativity provided by the TRIZ methods and tools, with the value created by the collective contributions. This contribution highlights the importance of knowledge acquisition, capitalization, and reuse as well as the problem formulation and resolution in collaboration.

Management of «Systematic Innovation»: A kind of quest for the Holy Grail!

In this paper, authors propose a contribution for improving the open innovation processes. It shows the necessity to get an efficient methodology for open innovation in order to build a computer aided tool for inventive design in Process Systems Engineering (PSE). The proposed methodology will be evocated to be fully used in the context of the “revolutionary” concepts around the so-called factory for the future, also called integrated digital factory, innovative factory… As a result the main contribution of this paper is to propose a software prototype for an Open Computer Aided Innovation 2.0. By definition this open innovation relies on collaboration. This collaboration should enable a community, with a very broad spectrum of skills, to share data, information, knowledge and ideas. As a consequence, a first sub objective is to create a methodological framework that takes advantages of collaboration and collective intelligence (with its capacity to join intelligence and knowledge). Furthermore, the raise of the digital company and more particularly the breakthroughs in information technologies is a powerful enabler to extend and improve the potential of collective intelligence. The second sub objective is to propose a problem resolution process to impel creativity of expert but also to develop, validate and select innovative solutions. After dealing with the importance of Process Innovation and Problem solving investigation in PSE, the proposed approach originally based on an extension of the TRIZ theory (Russian acronym for Theory of Inventive Problem Solving), has been improved by using approach such as case-based reasoning, in order to tackle and revisit problems encountered in the PSE. A case study on biomass is used to illustrate the capabilities of the methodology and the tool.

A multiobjective genetic algorithm optimization framework for batch plant design

Abstract This paper presents a MultiObjective Genetic Algorithm (MOGA) optimization framework for batch plant design. For this purpose, two MOGAs are implemented with respect to three criteria, i.e., investment cost, equipment number and a flexibility indicator based on Work In Process (the so-called WIP) computed by use of a Discrete-Event simulation model. The performances of the two procedures are studied for a large-size problem.