A creative solution for rapid and inexpensive model-making in product design processes

Innovative Developments in Virtual and Physical Prototyping

A creative solution for rapid and inexpensive model-making in product design processes

Rapid prototyping (RP) is an approach for automatically building a physical object through solid freeform fabrication. Nowadays, RP has become a vital aspect of most product development processes, due to the significant competitive advantages it offers compared to traditional manual model making. Even in academic environments, it is important to be able to quickly create accurate physical representations of concept solutions. Some of these can be used for simple visual validation, while others can be employed for ergonomic assessment by potential users or even for physical testing. However, the cost of traditional RP methods prevents their use in most academic environments on a regular basis, and even for very preliminary prototypes in many small companies. That results in delaying the first physical prototypes to later stages, or creating very rough mock-ups which are not as useful as they could be. In this paper we propose an approach for rapid and inexpensive model-making, which was developed in an academic context, and which can be employed for a variety of objects.

Dashboard services for pragmatics-based interoperability in cloud and ubiquitous manufacturing

The real Cloud and Ubiquitous Manufacturing systems require effectiveness and permanent availability of resources, their capacity and scalability. One of the most important problems for applications management over cloud based platforms, which are expected to support efficient scalability and resources coordination following SaaS implementation model, is their interoperability. Even application dashboards need to easily incorporate those new applications, their interoperability still remains a big problem to override. So, the possibility to expand these dashboards with efficiently integrated communicational cloud based services (cloudlets) represents a relevant added value as well as contributes to solving the interoperability problem. Following the architecture for integration of enriched existing cloud services, as instances of manufacturing resources, this paper: a) proposes a cloud based web platform to support dashboard integrating communicational services, and b) describe an experimentation to sustain the theory that the effective and efficient interoperability, especially in dynamic environments, could be achieved only with human intervention.

Computational evaluation of hydraulic system behaviour with entrapped air under rapid pressurization

The pressurization of hydraulic systems containing entrapped air is considered a critical condition for the infrastructure's security due to transient pressure variations often occurred. The objective of the present study is the computational evaluation of trends observed in variation of maximum surge pressure resulting from rapid pressurizations. The comparison of the results with those obtained in previous studies is also undertaken. A brief state of art in this domain is presented. This research work is applied to an experimental system having entrapped air in the top of a vertical pipe section. The evaluation is developed through the elastic model based on the method of characteristics, considering a moving liquid boundary, with the results being compared with those achieved with the rigid liquid column model.

Computational evaluation of hydraulic system behaviour with entrapped air under rapid pressurization

The pressurization of hydraulic systems containing entrapped air is considered a critical condition for the infrastructure's security due to transient pressure variations often occurred. The objective of the present study is the computational evaluation of trends observed in variation of maximum surge pressure resulting from rapid pressurizations. The comparison of the results with those obtained in previous studies is also undertaken. A brief state of art in this domain is presented. This research work is applied to an experimental system having entrapped air in the top of a vertical pipe section. The evaluation is developed through the elastic model based on the method of characteristics, considering a moving liquid boundary, with the results being compared with those achieved with the rigid liquid column model.

Intelligent Bio-Inspired system for manufacturing scheduling under uncertainties

A novel approach to scheduling resolution by combining Autonomic Computing (AC), Multi-Agent Systems (MAS), Case-based Reasoning (CBR), and Bio-Inspired Optimization Techniques (BIT) will be described. AC has emerged as a paradigm aiming at incorporating applications with a management structure similar to the central nervous system. The main intentions are to improve resource utilization and service quality. In this paper we envisage the use of MAS paradigm for supporting dynamic and distributed scheduling in Manufacturing Systems with AC properties, in order to reduce the complexity of managing manufacturing systems and human interference. The proposed CBR based Intelligent Scheduling System was evaluated under different dynamic manufacturing scenarios.

Self-optimization for dynamic scheduling in manufacturing systems

Scheduling is a critical function that is present throughout many industries and applications. A great need exists for developing scheduling approaches that can be applied to a number of different scheduling problems with significant impact on performance of business organizations. A challenge is emerging in the design of scheduling support systems for manufacturing environments where dynamic adaptation and optimization become increasingly important. In this paper, we describe a Self-Optimizing Mechanism for Scheduling System through Nature Inspired Optimization Techniques (NIT).

MASDSheGATS – Scheduling System for Dynamic Manufacturing Environments

This chapter addresses the resolution of scheduling in manufacturing systems subject to perturbations. The planning of Manufacturing Systems involves frequently the resolution of a huge amount and variety of combinatorial optimisation problems with an important impact on the performance of manufacturing organisations. Examples of those problems are the sequencing and scheduling problems in manufacturing management, routing and transportation, layout design and timetabling problems.

Self-organization for scheduling in agile manufacturing

Agility refers to the manufacturing system ability to rapidly adapt to market and environmental changes in efficient and cost-effective ways. This paper addresses the development of self-organization methods to enhance the operations of a scheduling system, by integrating scheduling system, configuration and optimization into a single autonomic process requiring minimal manual intervention to increase productivity and effectiveness while minimizing complexity for users. We intend to conceptualize real manufacturing systems as interacting autonomous entities in order to build future Decision Support Systems (DSS) for Scheduling in agile manufacturing environments.

Collective intelligence on dynamic manufacturing scheduling optimization

Swarm Intelligence (SI) is a growing research field of Artificial Intelligence (AI). SI is the general term for several computational techniques which use ideas and get inspiration from the social behaviours of insects and of other animals. This paper presents hybridization and combination of different AI approaches, like Bio-Inspired Techniques (BIT), Multi-Agent systems (MAS) and Machine Learning Techniques (ML T). The resulting system is applied to the problem of jobs scheduling to machines on dynamic manufacturing environments.

Autonomic computing for scheduling in manufacturing systems

We describe a novel approach to scheduling resolution by combining Autonomic Computing (AC), Multi-Agent Systems (MAS) and Nature Inspired Optimization Techniques (NIT). Autonomic Computing has emerged as paradigm aiming at embedding applications with a management structure similar to a central nervous system. A natural Autonomic Computing evolution in relation to Current Computing is to provide systems with Self-Managing ability with a minimum human interference. In this paper we envisage the use of Multi-Agent Systems paradigm for supporting dynamic and distributed scheduling in Manufacturing Systems with Autonomic properties, in order to reduce the complexity of managing systems and human interference. Additionally, we consider the resolution of realistic problems. The scheduling of a Cutting and Treatment Stainless Steel Sheet Line will be evaluated. Results show that proposed approach has advantages when compared with other scheduling systems.

Cooperative intelligent system for manufacturing scheduling

Hybridization of intelligent systems is a promising research field of computational intelligence focusing on combinations of multiple approaches to develop the next generation of intelligent systems. In this paper we will model a Manufacturing System by means of Multi-Agent Systems and Meta-Heuristics technologies, where each agent may represent a processing entity (machine). The objective of the system is to deal with the complex problem of Dynamic Scheduling in Manufacturing Systems.