New product development process include several activities and decisions. It starts with idea stage and ends when product enters market stage. Concurrent engineering is a product development approach that helps improving the performance of companies by reducing costs, increasing quality, creating new knowledge, and having a shorter product development time. In this research, the evolution of Concurrent engineering in space projects and issues related to the implementation of Concurrent engineering in Design facilities were examined. For this reason, European Space Agency's Concurrent Design Facility and NASA Integrated Mission Design Center have been studied. The implementation of Concurrent engineering in Instituto Superior Té cnico's Concurrent Design Facility has also been studied.

Network location models comprise one of the main categories of location models. These models have various applications in regional and urban planning as well as in transportation, distribution, and energy management. In a network location problem, nodes represent demand points and candidate locations to locate the facilities. If the links network is unchangeably determined, the problem will be an FLP (Facility Location Problem). However, if links can be added to the network at a reasonable cost, the problem will then be a combination of Facility location and NDP (Network Design Problem). In previous studies, capacity of facilities was considered to be a constraint while capacity of links was not considered at all. The proposed MIP model considers capacity of facilities and links as decision variables. This approach increases the utilization of facilities and links, and prevents the construction of links and Facility locations with low utilization. Furthermore, Facility location cost (link construction cost) in the proposed model is supposed to be a function of the associated Facility (link) capacity. Computational experiments as well as sensitivity analyses performed indicate the efficiency of the model.

A supply chain is a set of facilities connected together in order to provide products to customers. The supply chain is subject to random failures caused by different factors which cause the unavailability of some sites. Given the current economic context, the management of these unavailabilities is becoming a strategic choice to ensure the desired reliability and availability levels of the different supply chain facilities. In this work, we treat two problems related to the field of supply chain, namely the Design and unavailabilities management of logistics facilities. Specifically, we consider a stochastic distribution network with consideration of suppliers' selection, distribution centres location (DCs) decisions and DCs’ unavailabilities management. Two resolution approaches are proposed. The first approach called non-integrated consists on define the optimal supply chain structure using an optimization approach based on genetic algorithms (GA), then to simulate the supply chain performance with the presence of DCs failures. The second approach called integrated approach is to consider the Design of the supply chain problem and unavailabilities management of DCs in the same model. Note that, we replace each unavailable DC by performing a reallocation using GA in the two approaches. The obtained results of the two approaches are detailed and compared showing their effectiveness.

This paper presents a decision-making methodology based on a simple nonlinear programming model, which uses both quantitative and qualitative criteria, for evaluating Facility layout Design. A computer-aided layout-planning tool, Spiral, is adopted to facilitate the layout alternative Design process as well as to collect quantitative. Analytic hierarchy process (AHP) is then applied to collect qualitative data related to quality and flexibility. A non-linear programming (NLP) model is proposed to solve the layout Design problem by simultaneously considering both the quantitative and qualitative data. The purposed integrated procedure is applied to a real data.

We consider a family of problems that combine network Design and Facility location. Such problems arise in many practical applications in di, erent , elds such as telecommunications, transportation networks, logistic, and energy supply networks. In Facility location problems, we want to decide which facilities to open and how to assign clients to the open facilities so as to minimize the sum of the Facility opening costs and client connection costs. These problems typically do not involve decisions concerning the routing of the clients' demands to the open facilities,once we decided on the set of open facilities, each client is served by the closest open Facility. In network Design problems, on the other hand, we generally want to Design and dimension a minimum-cost routing network providing su, cient capacities to route all clients' demands to their destinations. These problems involve deciding on the routing of each client's demand. But, in contrast to Facility location problems, demands' destinations are predetermined. In many modern day applications, however, all these decisions are interdependent and a, ect each other. Hence, they should be taken simultaneously. The aim of this work is to survey models, algorithmic approaches and methodologies concerning such combined network Design Facility location problems.

This paper proposes a novel Facility location model for health service network Design by considering different key elements including the reliability aspects, service capacity, congestion, service quality, surrounding public infrastructures, geographical accessibility and several types of cost such as investment, transportation and operational costs. We formulate the problem as a robust scenario-based stochastic programming model to deal with different categories of uncertainty associated with reliability, demand, service and geographical accessibility such that the minimization of expected costs under all disruption scenarios will be attained. To illustrate the applicability of the proposed model, a real-life case study based on the health service network of Sistan and Baluchestan province is presented. The findings of this research enable the system Designers to investigate different strategic and operational decisions in the Design and management of the health service networks from both cost and risk perspectives.

In recent years, managing the interface between Design and other activities has received considerable attention. Effective coordination among these areas is therefore vital for effectiveness of the organization. The ideal situation would be continuous interdepartmental contact with well-developed channels of communication. In this study, the best strategy for product Design department has been chosen using the strategic formulation framework with fuzzy approach. Subsequently, alignment of each functional Design strategy with SAPCO business strategies has been explained. Findings indicate that developing partnerships with global automotive and engineering Design companies and building strategic alliances with rival firms to achieve competitive advantages have maximum alignment with business strategies. In addition, findings provide a basis for firms in evaluating the Concurrent Design strategies and a reference for them to strengthen their Concurrent capabilities. There are few reports on sustained use of Concurrent Design as an on-going strategic process in an organization. This study aims at contributing to the Concurrent Design solutions.