Hybridation of Bayesian networks and evolutionary algorithms for multi-objective optimization in an integrated product design and project management context

A better integration of preliminary product design and project management processes at early steps of system design is nowadays a key industrial issue. Therefore, the aim is to make firms evolve from classical sequential approach (first product design the project design and management) to new integrated approaches. In this paper, a model for integrated product/project optimization is first proposed which allows taking into account simultaneously decisions coming from the product and project managers. However, the resulting model has an important underlying complexity, and a multi-objective optimization technique is required to provide managers with appropriate scenarios in a reasonable amount of time. The proposed approach is based on an original evolutionary algorithm called evolutionary algorithm oriented by knowledge (EAOK). This algorithm is based on the interaction between an adapted evolutionary algorithm and a model of knowledge (MoK) used for giving relevant orientations during the search process. The evolutionary operators of the EA are modified in order to take into account these orientations. The MoK is based on the Bayesian Network formalism and is built both from expert knowledge and from individuals generated by the EA. A learning process permits to update probabilities of the BN from a set of selected individuals. At each cycle of the EA, probabilities contained into the MoK are used to give some bias to the new evolutionary operators. This method ensures both a faster and effective optimization, but it also provides the decision maker with a graphic and interactive model of knowledge linked to the studied project. An experimental platform has been developed to experiment the algorithm and a large campaign of tests permits to compare different strategies as well as the benefits of this novel approach in comparison with a classical EA

Integration of experience feedback into the product lifecycle: an approach to best respond to the bidding process

Bidding process allows a client to choose a bidder to realize an embodiment of work, supply or service. From the bidder point of view, there are several obvious risks when responding because he bets on a future development that hasn’t been yet realized. We propose to assist the bidder with decision support tools based on past experiences to detect, report and minimize these potential risks. In this paper, we present the definition of a conceptual architecture to integrate experience feedback into the product lifecycle taking into account all stages of product lifecycle to best respond new bidding processes

On the use of Process Mining and Machine Learning to support decision making in systems design

Research on process mining and machine learning techniques has recently received a significant amount of attention by product development and management communities. Indeed, these techniques allow both an automatic process and activity discovery and thus are high added value services that help reusing knowledge to support decision-making. This paper proposes a double layer framework aiming to identify the most significant process patterns to be executed depending on the design context. Simultaneously, it proposes the most significant parameters for each activity of the considered process pattern. The framework is applied on a specific design example and is partially implemented.FUI GONTRAN

Towards an integration of systems engineering and project management processes for a decision aiding purpose

This article proposes an integrated process that combine Systems engineering processes and project management ones. These processes are defined according to the industrial standard processes existing in the literature. The main idea is to define a common information model enabling the federation of all the points of view of the different actors with regards to systems engineering, project time management, project cost management and project risk management. The resulting integrated project graph encompasses all the scenarios established after defining all the coupling points between those processes. The definition of the graph is based also on the available knowledge and the capitalized experiences resulting from experience feedback on previous projects. The scenario selection optimization is then performed using a decision-aided tool that aims to build a panel of pareto-optimal solutions taking into account uncertainties on project objectives (cost and duration). This tool will also enable the decision-maker to select one scenario according to an acceptable level of risks. The integrated process, the optimization tool based on ant colony optimization (ACO) and the method for decision making are described in the paper

A Multi-Skilled Approach to Property Maintenance Considering Temporal, Spatial and Resource Constraints

With the continued increase in age of the United States housing and building stock, as well as the continued need to maintain properties across the U.S., the need for timely, cost-optimal maintenance is ever more critical. This paper proposes the application of a mathematical model to aid in the scheduling and assignment of construction and maintenance tasks, considering the multi-skilled workforce. The benefit of this approach is to take advantage of the economies of scale that can be developed using cross-functional skilled workers with varying levels of competence and efficiency. This approach schedules and assigns tasks using data from maintenance task software datasets, using the least-cost, competent worker available for the job while also considering the trade-off between skilled labor cost and travel costs, both in terms of travel wage and vehicle wear and tear. The model is enhanced to include pairing between a mentor and an apprentice, where combined efficiency and pairing costs are considered at the same time as travel costs. Due to the practical nature of this research, a case organization was used and data from that firm was analyzed so that operational insights into the necessity of such a model could be considered. The mathematical backbone of the optimization approach to multi-skilled resource allocation considers the temporal and spatial demands of a geographically dispersed property management program. Actual, as opposed to sample, data allows us to evaluate the real financial implications on the case firm, if such an approach to scheduling is used. The generalization of this data provides excellent fit for a model that can be used to assign the best capable worker to the most cost-efficient task, considering deadlines, priorities and availability. Results of this scheduling approach provide significant cost and resource reductions over the historical firm performance, though practical considerations should temper that expectation. The above approach offers exceptional scalability and adaptability with the continued advancement of algorithm approaches to network-distribution and peer-to-peer work platforms

Vers un couplage des processus de conception de systèmes et de planification de projets : formalisation de connaissances méthodologiques et de connaissances métier

Les travaux présentés dans cette thèse s'inscrivent dans une problématique d'aide à la conception de systèmes, à la planification de leur projet de développement et à leur couplage. L'aide à la conception et à la planification repose sur la formalisation de deux grands types de connaissances : les connaissances méthodologiques utilisables quel que soit le projet de conception et, les connaissances métier spécifiques à un type de conception et/ou de planification donné. Le premier chapitre de la thèse propose un état de l'art concernant les travaux sur le couplage des processus de conception de systèmes et de planification des projets associés et expose la problématique de nos travaux. Deux partie traitent ensuite, d'une part, des connaissances méthodologiques et, d'autre part, des connaissances métier. La première partie expose trois types de couplages méthodologiques. Le couplage structurel propose de formaliser les entités de conception et de planification puis permet leur création et leur association. Le couplage informationnel définit les attributs de faisabilité et de vérification pour ces entités et synchronise les états de ces dernières vis-à-vis de ces attributs. Enfin, le couplage décisionnel consiste à proposer, dans un même espace et sous forme de tableau de bord, les informations nécessaires et suffisantes à la prise de décision par les acteurs du projet de conception. La seconde partie propose de formaliser, d'exploiter et de capitaliser la connaissance métier. Après avoir formalisé ces connaissances sous forme d'une ontologie de concepts, deux mécanismes sont exploités : un mécanisme de réutilisation de cas permettant de réutiliser, en les adaptant, les projets de conception passés et un mécanisme de propagation de contraintes permettant de propager des décisions de la conception vers la planification et réciproquement. ABSTRACT : The work presented in this thesis deals with aiding system design, development project planning and its coupling. Aiding design and planning is based on the formalization of two kind of knowledge: methodological knowledge that can be used in all kind of design projects and business knowledge that are dedicated to a particular kind of design and/or planning. The first chapter presents a state of the art about coupling system design process and project planning process and gives the problem of our work. Then, two parts deal with design and planning coupling thanks to, on one hand, methodological knowledge, and on the other hand, business knowledge. The first part presents three types of methodological coupling. The structural coupling defines design and planning entities and permits its simultaneous creation of and its association. The informational coupling defines feasibility and verification attributes for these entities and synchronizes its attribute states. Finally, the decisional coupling consists in proposing, in a single dashboard, the necessary and sufficient information to make a decision by the design project actors. The second part proposes to formalize, to exploit and to capitalize business knowledge. This knowledge is formalized with ontology of concepts. Then, two mechanisms are exploited: a case reuse mechanism that permits to reuse and adapt former design projects and a constraint propagation mechanism that allows propagating decisions from design to planning and reciprocally