The project management team has to respect contractual commitments, in terms of deadlines and budgets, that are often two antagonistic objectives. At the same time, the market becomes more and more demanding as far as costs and delays are concerned while expecting a high quality level. Then, the project management team has to continuously consider novelty and a risk management strategy in order to determine the best balance between benefits and risks. Based on the principles of a synchronized process between risk management and project management, and on the concepts of risk scenario, we propose a decision-making tool to help the project manager choose the best way to improve project success rate while controlling the level of risks. As a finding, the project manager would be able to evaluate and compare different novelties or development strategies taking into account their repercussions on potential risks and risk treatment strategies. Finally, a case study in the aerospace industry and specifically on satellite integration and tests is developed to validate this approach.

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To cite this version:François Marmier, Ioana Filipas Deniaud, Didier Gourc. Strategic decision-making in NPD projects according to risk: Application to satellites design projects. Computers in Industry, Elsevier, 2014, 65 (8) Abstract:In this paper we present a method for making strategic decisions in New Product Development (NPD) projects based on risks. In NPD the complexity of the process depends both on the nature of the design problem and the difficulties associated with managing the project (activities, risks). To design a complex product several different teams, having different competencies, work on the project. Not one among them controls the entire process. The interactions between product subsystems in NPD often lead to technological arbitration between alternative solutions In selecting one solution over another, the risk management concerns and the overall project plan are affected. Therefore, the objective is to give the project manager the means to evaluate the effects of strategic decisions, including those that influence the selection of technological solutions for the project plan as well as those for risk treatment strategies. We propose an integrated process that comprises design, project management and risk management. It takes into consideration the design activities and risk activities to generate a design project planning where design activities and risk activities are folded into the overall design project plan. During the process of project design two different types of strategies are required: one relates to the problem design, the other to the assessment of project risks. Each strategy leads to different possible scenarios. We present a decision tree that shows the decision steps and possible project scenarios. A generic decision support system is proposed. We demonstrate its applicability by applying it to a satellite design project.

Demand forecasting consists of using data of the past demand to obtain an approximation of the future demand. Mathematical approaches can lead to reliable forecasts in deterministic context through extrapolating regular patterns in time-series. However, unpredictable events that do not appear in the historical data can make the forecasts obsolete. Since forecasters have a partial knowledge of the context and of the future events (such as strikes, promotions) with some probability, the idea presented in this work is on structuring the implicit as well as the explicit knowledge in order to easily and fully integrate it in final forecasts. This paper presents a judgemental-based approach in forecasting where mathematical forecasts are considered as a basis and the structured knowledge of the experts is provided to adjust the initial forecasts. This is achieved using the identification and classification of four factors characterising events that could not be considered in the initial forecasts. Validation of the approach is provided with two case studies developed with forecasters from a plastic bag manufacturer and a distributor acting in the food market. The results show that structuring the expert knowledge through the identification of factor-related events lead to high improvements of forecasts accuracy.

a b s t r a c tMathematical forecasting approaches can lead to reliable demand forecast in some environments by extrapolating regular patterns in time-series. However, unpredictable events that do not appear in historical data can reduce the usefulness of mathematical forecasts for demand planning purposes. Since forecasters have partial knowledge of the context and of future events, grouping and structuring the fragmented implicit knowledge, in order to be easily and fully integrated in final demand forecasts is the objective of this work. This paper presents a judgemental collaborative approach for demand forecasting in which the mathematical forecasts, considered as the basis, are adjusted by the structured and combined knowledge from different forecasters. The approach is based on the identification and classification of four types of particular events. Factors corresponding to these events are evaluated through a fuzzy inference system to ensure the coherence of the results. To validate the approach, two case studies were developed with forecasters from a plastic bag manufacturer and a distributor belonging to the food retailing industry. The results show that by structuring and combining the judgements of different forecasters to identify and assess future events, companies can experience a high improvement in demand forecast accuracy.

In maintenance services skills management is directly linked to the performance of the service. A good human resource management will have an effect on the performance of the plant. Each task which has to be performed is characterised by the level of competence required. For each skill, human resources have different levels. The issue of making a decision about assignment and scheduling leads to finding the best resource and the correct time to perform the task. To solve this problem, managers have to take into account the different criteria such as the number of late tasks, the workload or the disturbance when inserting a new task into an existing planning. As there is a lot of estimated data, the managers also have to anticipate these uncertainties. To solve this multi-criteria problem, we propose a dynamic approach based on the kangaroo methodology. To deal with uncertainties, estimated data is modelled with fuzzy logic. This approach then offers the maintenance expert a choice between a set of the most robust possibilities.

International audienceQuality control lead times are one of most significant causes of loss of time in the pharmaceutical and cosmetics industries. This is partly due to the organization of laboratories that feature parallel multipurpose machines for chromatographic analyses. The testing process requires long setup times and operators are needed to launch the process. The various controls are non-preemptive and are characterized by a release date, a due date and available routings. These quality processes lead to significant delays, and we therefore evaluate the total tardiness criterion. Previous heuristics were defined for the total tardiness criterion, parallel machines, and setup such as ATC (Apparent Tardiness Cost) and ATCS (ATC with setups). We propose new rules and a simulated annealing procedure in order to minimize total tardiness

In a complex innovative project, an organisation is often not able to manage all aspects alone, due to the lack of all required competencies, skills or resources. Hence, alliance formation can be a solution. To decrease the risk of potential collaboration inefficiency, partner selection happens among firms before collaboration starts. This paper proposes hypotheses based on a systematic literature review. These hypotheses consider the needs of the project and allow to characterise partner selection using a new typology. Finally, a novel framework is proposed to help decision-makers of partner selection in alliance formation. Potentials for future studies are also developed.