Abstract
A product development framework called LeanDfX has been conceived at INEGI, aiming at organizing the product design and development process benefitting from lean thinking and DfX paradigms. The design of the metallic structure for an automated guided vehicle (AGV) focusing on its static, dynamic and fatigue characteristics was a recent opportunity to enhance and further develop the framework through the consideration and integration into the process of several existing tools such as FMEA (failure mode and effect analysis), QFD (quality function deployment) or fuzzy logic. This paper describes the integration of those tools in the LeanDfX framework and an application to the design of an AGV structure. The methodology presented involves systematic consideration of a substantial number of design requirements and more detailed product specification characterization. Such a number might be seen as delaying the development process, but the present case study showed that the inverse was true, thanks to the structured systematic approach and timely elimination of less desirable alternatives.

Abstract
This study focuses on the characterization of the production process of a composite sandwich panel for an aircraft structure. Two curing alternatives were compared, namely hot-press and autoclave. A holistic assessment was conducted applying the Total Efficiency Framework, which combines both process efficiency and environmental performance analyses into a single index score to support manufacturing decision. The study provides inventory data, collected at laboratory scale regarding materials, energy consumption, and process operation for composite panel production, which are seldom available. This foreground data was used to quantify the process efficiency, based on lean design tool, and to estimate the potential environmental impacts, using Life Cycle Assessment methodology to determine the eco-efficiency of the production process. The results suggested that the autoclave curing outperforms the hot-press alternative in terms of efficiency, eco-efficiency, and environmental perfor-mance. Regarding the total efficiency index results for maximum productivity, the results show a difference of 12% between the two alternatives, indicating potential competitive advantages in an industrial setting.

Abstract

Abstract

Abstract
This paper presents an effective Dual-RAMP algorithm for solving the Capacitated Single Allocation p-Hub Location Problem (CSApHLP). This problem aims to determine the set of p hubs in a network that minimizes the total cost of allocating all the non-hub nodes to the p hubs. The algorithm effectively explores the primal-dual relationship, combining adaptive memory concepts and metaheuristic techniques with principles of mathematical relaxation under the Relaxation Adaptive Memory Programming (RAMP) framework, covering the dual and primal solution spaces. The proposed algorithm incorporates Lagrangean Relaxation and Subgradient Optimization in the dual side and a simple Improvement Method on the primal side. The results' quality on a standard testbed shows that the RAMP approach is a very effective approach for the CSApHLP.

Abstract
Facility Location Problems are widely studied problems in the literature with several practical applications, reaching areas such as telecommunications, design of a supply chain management, transport utilities and water distribution networks. In this paper, we address the Capacitated Facility Location Problems (CFLP), whose general goal is to determine where to locate a set of facilities to serve a particular set of customers with minimum cost. The CFLP problem has been widely studied for the past decades with the development of exact and heuristics methods. We propose a new heuristic algorithm for the Capacitated Facility Location Problem (CFLP) based on the RAMP (Relaxation Adaptive Memory Programming) framework. In the dual side of the method, the RAMP framework uses a Dual-Ascent procedure and a simple improvement method based on Tabu Search was used to explore the primal side, making this algorithm a very robust RAMP approach. The RAMP algorithm for the CFLP obtained excellent results, demonstrating its potential for new applications to other extensions and variations of Facility Location Problems. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.