Models for Improvement Management and Operational Performance

Achieving high levels of performance in the manufacturing environment requires an increase in speed, quality and reliability of existing technologies. This is inherently related with the need to develop adequate process monitoring and modelling/simulation approaches, along with innovative optimization and maintenance strategies. The purpose of this dissertation is to provide a framework that can be used as a tool by decision makers when evaluating and controlling the performance of a system. To achieve this, a structured conceptual model should be developed, which should not be tied to any particular model. The idea with this framework is to assess information obtained during production and use it to generate relevant KPIs for monitoring and evaluating the system?s performance. This information should then be fed into a DSS that can provide suggestions or even actively influence simulation parameters to apply the identified improvement measures. Finally, the proposed framework is to be applied in a case-study to evaluate its relevance in the improvement of manufacturing operations in a real-world context

Fuzzy control in manufacturing systems

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Energy efficiency in discrete-manufacturing systems: insights, trends, and control strategies

Since the depletion of fossil energy sources, rising energy prices, and governmental regulation restrictions, the current manufacturing industry is shifting towards more efficient and sustainable systems. This transformation has promoted the identification of energy saving opportunities and the development of new technologies and strategies oriented to improve the energy efficiency of such systems. This paper outlines and discusses most of the research reported during the last decade regarding energy efficiency in manufacturing systems, the current technologies and strategies to improve that efficiency, identifying and remarking those related to the design of management/control strategies. Based on this fact, this paper aims to provide a review of strategies for reducing energy consumption and optimizing the use of resources within a plant into the context of discrete manufacturing. The review performed concerning the current context of manufacturing systems, control systems implemented, and their transformation towards Industry 4.0 might be useful in both the academic and industrial dimension to identify trends and critical points and suggest further research lines.Peer ReviewedPreprin

Proceedings of the third International Workshop of the IFIP WG5.7

Contents of the papers presented at the international workshop deal with the wide variety of new and computer-based techniques for production planning and control that has become available to the scientific and industrial world in the past few years: formal modeling techniques, artificial neural networks, autonomous agent theory, genetic algorithms, chaos theory, fuzzy logic, simulated annealing, tabu search, simulation and so on. The approach, while being scientifically rigorous, is focused on the applicability to industrial environment