Coupling system design and project planning: discussion on a bijective link between system and project structures

This article discuss the architecture of an integrated model able to support the coupling between a system design process and a project planning process. The project planning process is in charge of defining, planning and controlling the system design project. A benchmarking analysis carried out with fifteen companies belonging to the world competitiveness cluster, Aerospace Valley, has highlighted a lack of models, processes and tools for aiding the interactions between the two environments. We define the coupling as the establishment of links between entities of the two domains while preserving their original semantic, thus allowing information to be collected. The proposed coupling is recursive. It enables systems to be decomposed into subsystems when designers consider complexity to be too high, and can also decompose projects into sub-projects. The coupling enables systematically links to be drawn between project entities and system entities. In this paper, we discuss the different possibilities of linking system and project structures during the design and the planning processes. Firstly, after presenting the results of the industrial analysis, the different entities are defined and the various coupling modes are discussed

Improvement of retrieval in Case-Based Reasoning for system design

The problematic addressed in this article is dealing with the improvement of retrieval in Case-Based Reasoning for system design. The retrieval activity is based on the evaluation of similarities between requirements (target) and the solutions (sources). However, similarities between features is often a subjective kind of knowledge difficult to formalize within companies. Based on an ontology of domain, the approach permits to retrieve compatible solutions rather than similar ones using a model of designer preferences. The requirements are modeled by means of constraints. When constraints are confronted to solutions in order to evaluate a compatibility measure, missing information within solutions with regard to requirements are taken into account using semantic similarities between concepts. A case study validates the proposals

How to take into account general and contextual knowledge for interactive aiding design: Towards the coupling of CSP and CBR approaches

The goal of this paper is to show how it is possible to support design decisions with two different tools relying on two kinds of knowledge: case-based reasoning operating with contextual knowledge embodied in past cases and constraint filtering that operates with general knowledge formalized using constraints. Our goals are, firstly to make an overview of existing works that analyses the various ways to associate these two kinds of aiding tools essentially in a sequential way. Secondly, we propose an approach that allows us to use them simultaneously in order to assist design decisions with these two kinds of knowledge. The paper is organized as follows. In the first section, we define the goal of the paper and recall the background of case-based reasoning and constraint filtering. In the second section, the industrial problem which led us to consider these two kinds of knowledge is presented. In the third section, an overview of the various possibilities of using these two aiding decision tools in a sequential way is drawn up. In the fourth section, we propose an approach that allows us to use both aiding decision tools in a simultaneous and iterative way according to the availability of knowledge. An example dealing with helicopter maintenance illustrates our proposals

Some experimental results relevant to the optimization of configuration and planning problems.

This communication deals with mass customization and the association of the product configuration task with the planning of its production process while trying to minimize cost and cycle time. We consider a two steps approach that first permit to interactively (with the customer) achieve a first product configuration and first process plan (thanks to non-negotiable requirements) and then optimize both of them (with remaining negotiable requirements). This communication concerns the second optimization step. Our oal is to evaluate a recent evolutionary algorithm (EA). As both problems are considered as constraints satisfaction problems, the optimization problem is constrained. Therefore the considered EA was selected and adapted to fit the problem. The experimentations will compare the EA with a conventional branch and bound according to the problem size and the density of constraints. The hypervolume metric is used for comparison

Configuration knowledge modeling: How to extend configuration from assemble/make to order towards engineer to order for the bidding process

The bidding process is one of the most important phases for system contractors. A successful bid implies defining and implementing attractive and realistic systems solutions that fulfil customer expectations. An additional challenge arises with the increase in systems diversity resulting from growing customization needs. As a result, for standard customizing offers, bidders find good quality support with configuration software for assemble/make-to-order situations. But when requirements exceed the standard offers, bidders need extended support to fulfil Engineering-to-Order requirements. In this context, this article shows how configuration knowledge models, which support configuration in assemble/make-to-order situations (AMTO), can be extended and used in engineer-to-order situations (ETO). Modeling is achieved assuming that the configuration problem is considered as a constraint satisfaction problem. Six key requirements that differentiate ETO from AMTO are identified and modeling extensions are proposed and discussed. An example illustrates all the contributions

Readiness, feasibility and confidence: how to help bidders to better develop and assess their offers

In a bidding process, the bidder must define and evaluate potential offers in order to propose the most suitable one to the potential customer. Proposing attractive but also realistic offers to various potential customers is a key factor for the bidder to stay competitive. In order to achieve this, the bidder needs to be very sure about the technical specifications and the constructability of the proposal. However, performing a detailed design is resource and time-consuming. This article proposes the foundation of a new framework which can help bidders to define the right offer: (i) in the context of a non-routine design process, while avoiding a detailed design and (ii) taking into account two new indicators that reflect the bidder’s confidence that they can meet the commitments once the offer is accepted. The first indicator (OCS) characterises the Overall Confidence in the technical System, while the second one (OCP) gives the Overall Confidence in the delivery Process. Both OCS and OCP are based firstly on two factual objective indicators, Technology Readiness Level (TRL) for OCS and Activity Feasibility Level (AFL) for OCP, and secondly on two human-based subjective indicators, Confidence In System (CIS) for the OCS and Confidence In Process for the OCP. An illustrative application shows how this framework can really help bidders define an offer, while avoiding detailed design and enable them to evaluate the confidence level in each potential offe

Product v Service system configuration: a generic knowledge-based model for commercial offers

At a time when modes of consumption are rapidly evolving, consumer attitudes and expectations are changing. Today, customers want more and more products and services that can be customised to their needs. Furthermore, they are more willing to pay for usage of a product rather than ownership. On the other hand, companies are adding more and more services to the products they are bringing to market in order to create added value and differentiate themselves from their competitors. To adapt to these new market trends, companies now have to offer their customers a more sophisticated catalog of solutions, in both product and services, including all conceivable combinations of the two. The aim of this article is to propose a generic knowledge-based model, dedicated to commercial offer configuration which is able to cope with the whole variety of solutions a company can deliver. To our knowledge, although some works on product configuration, service and product-service system configuration exist, none of them is generic enough to support product, service and product-service configuration at the same time when defining commercial offers. In this article, after giving a state-of-the-art assessment of product and service configurations, the need for a generic model able to cover the whole range and diversity of commercial offers is established, a knowledge-based model is defined and its relevance is demonstrated on seven use-cases coming from secondary and tertiary sector companies

Aide à la conception d'opérations de traitement thermique et estimation des distortions en résultant par exploitation de connaissances expertes

Cet article présente les résultats d'un projet européen dont l’objectif est d’aider à la conception d’opérations de traitement thermique. Pour cela, de la connaissance experte a  été capitalisée et formalisée pour d'une part, aider à la définition d'une opération de traitement thermique et d'autre part, estimer les distorsions en résultant. Après une présentation du contexte de ce projet, l’extraction des connaissances et leur formalisation par des approches par contraintes seront présentées

Case-based reasoning and system design: An integrated approach based on ontology and preference modeling

This paper addresses the fulfillment of requirements related to case-based reasoning (CBR) processes for system design. Considering that CBR processes are well suited for problem solving, the proposed method concerns the definition of an integrated CBR process in line with system engineering principles. After the definition of the requirements that the approach has to fulfill, an ontology is defined to capitalize knowledge about the design within concepts. Based on the ontology, models are provided for requirements and solutions representation. Next, a recursive CBR process, suitable for system design, is provided. Uncertainty and designer preferences as well as ontological guidelines are considered during the requirements definition, the compatible cases retrieval, and the solution definition steps. This approach is designed to give flexibility within the CBR process as well as to provide guidelines to the designer. Such questions as the following are conjointly treated: how to guide the designer to be sure that the requirements are correctly defined and suitable for the retrieval step, how to retrieve cases when there are no available similarity measures, and how to enlarge the research scope during the retrieval step to obtain a sufficient panel of solutions. Finally, an example of system engineering in the aeronautic domain illustrates the proposed method. A testbed has been developed and carried out to evaluate the performance of the retrieval algorithm and a software prototype has been developed in order to test the approach. The outcome of this work is a recursive CBR process suitable to engineering design and compatible with standards. Requirements are modeled by means of flexible constraints, where the designer preferences are used to express the flexibility. Similar solutions can be retrieved even if similarity measures between features are not available. Simultaneously, ontological guidelines are used to guide the process and to aid the designer to express her/his preferences

Modularization of smart product service: A framework integrating smart product service blueprint and weighted complex network

Modularization of smart product service (SPS) emerges as a priority strategy to agilely satisfy the dynamic customization requirement and to flexibly response to the rapid market change. Compared with the traditional product service, the SPS have more complicated interactions between the service components due to the novel characteristics caused by the application of smart technologies. The SPS modularization presents great differences from the identification of service component, correlation evaluation and module partition with the traditional product service modularization. However, most the existing research mainly focuses on the context of traditional product service, while containing scant study of smart product service. Therefore, this study proposes a hybrid framework for SPS modularization. In the framework, a cyber-physical product service blueprint is firstly proposed to represent the SPS operation process and identify the SPS components. Then, a rough-fuzzy correlation matrix is presented to determine the comprehensive interdependence between all pairs of SPS components with fully considering the hybrid decision uncertainties involved in the evaluation process, i.e., intrapersonal linguistic vagueness and interpersonal preference diversity. After that, the complex network theory is used to construct the SPS network and a modified Girvan-Newman algorithm is adopted for the SPS module partition. Finally, an illustrative modularization case of smart gearbox maintenance service and some caparisons with other methods demonstrate the feasibility and validity of the proposed approach