Conceptual modeling architecture and implementation of object-oriented simulation for automated guided vehicle (AGV) systems

Traditional simulation languages and simulators do not fully support the need to design, modify, and extend simulation models of manufacturing systems, especially, material handling systems. Since AGV systems, one type of automated material handling systems, require complicated control logic, flexible job routings, and frequent layout modifications and extensions to correspond to production requirements, the time consumption and efforts to achieve the above tasks in traditional paradigms are significant. However, such difficulties can be overcome by the use of object-oriented simulation. This research develops an object-oriented modeling architecture for the simulation of AGV (automated guided vehicle) systems by extending Beaumariage's object-oriented modeling environment (1990) which is originally designed for the simulation of job shop type manufacturing systems. For this extension, several classes required to comprise an AGV system are created into the original environment which include AGV, limited size queue, control point, track segment, machine cell, AGV system control classes, and so on. This architecture provides a flexible environment that enables the modeling of traditional and tandem AGV system layouts. A best-first search approach, one artificial intelligence search algorithm, is employed to direct AGVs to determine the shortest path from all possible travel paths. The computerized modeling system with this conceptual architecture is easy to use, especially compared with traditional simulation tools. In addition, the extended object-oriented architecture used for the simulation of AGV systems is program independent and may be implemented in any object-oriented language. The prototype system implemented as a portion of this research is performed in Smalltalk/V. Two case examples are presented for verification and validation

A Model-Centric Framework for Advanced Operation of Crystallization Processes

Crystallization is the main physical separation process in many chemical industries. It is an old unit operation which can separate solids of high purity from liquids, and is widely applied in the production of food, pharmaceuticals, and fine chemicals. While industries in crystallization operation quite rely on rule-of-thumb techniques to fulfill their requirement, the move towards a scientific- and technological- based approach is becoming more important as it provides a mechanism for driving crystallization processes optimally and in more depth without increasing costs. Optimal operation of industrial crystallizers is a prerequisite these days for achieving the stringent requirements of the consumer-driven manufacturing. To achieve this, a generic and flexible model centric framework is developed for the advanced operation of crystallization processes. The framework deploys the modern software environment combined with the design of a state-of-the-art 1-L crystallization laboratory facility. The emphasis is on developing an economically and practically feasible implementation which can be applied for the optimal operation of various crystallization systems by pharmaceutical industries. The key developments in the framework have occurred in three broad categories: i. Modeling: Using an advanced modeling tool is intended for accurate representation of the behavior of the physical system. This is the cornerstone of any simulation, optimization or model-based control approach. ii. Monitoring: Applying a novel image-based technique for online characterization of the particulate processes. This is a promising method for direct tracking of particle size and size distribution with high adaptability for real-time application iii. Control: Proposing numerous model-based strategies for advanced control of the crystallization system. These strategies enable us to investigate the role of model complexity on real-time control design. Furthermore, the effect of model imperfections, process uncertainty and decision variables on optimal operation of the process can be evaluated. Overall, results from this work presents a robust platform for further research in the area of crystal engineering. Most of the developments described will pave the way for future set of activities being targeted towards extending and adapting advanced modeling, monitoring and control concepts for different crystallization processes

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

Plasma sprayed titanium coatings with/without a shroud

Abstract: Titanium coatings were deposited by plasma spraying with and without a shroud. The titanium coatings were then assessed by scanning electron microscopy. A comparison in microstructure between titanium coatings with and without the shroud was carried out. The results showed that the shroud played an important role in protecting the titanium particles from oxidation. The presence of the shroud led to a reduction in coating porosity. The reduction in air entrainment with t he shroud resulted in better heating of the particles, and an enhanced microstructure with lower porosity in the shrouded titanium coatings were observed compared to the air plasma sprayed counterpart

Intelligent systems in manufacturing: current developments and future prospects

Global competition and rapidly changing customer requirements are demanding increasing changes in manufacturing environments. Enterprises are required to constantly redesign their products and continuously reconfigure their manufacturing systems. Traditional approaches to manufacturing systems do not fully satisfy this new situation. Many authors have proposed that artificial intelligence will bring the flexibility and efficiency needed by manufacturing systems. This paper is a review of artificial intelligence techniques used in manufacturing systems. The paper first defines the components of a simplified intelligent manufacturing systems (IMS), the different Artificial Intelligence (AI) techniques to be considered and then shows how these AI techniques are used for the components of IMS

A distributed knowledge-based approach to flexible automation : the contract-net framework

Includes bibliographical references (p. 26-29)

Mechatronics of a ball screw drive using a N degrees of freedom dynamic model

High performance position control in machine tools can only be achieved modelling the dynamic behavior of the mechatronic system composed by the motor, transmission and control during the design stage. In this work, a complex analytical model of a ball screw drive is presented and integrated in a mechatronic model of the actuator to predict the dynamic behaviour and analyze the impact of each component of the transmission. First, a simple 2 degrees of freedom model is presented, and is analysis sets the basis for the development of a more complex model of several degrees of freedom, whose resulting fundamental transfer functions are represented using natural and modal coordinates. The modeling in modal coordinates carries a reduction of the transfer function that reduces computational work. The two models are compared and experimentally validated in time and frequency domain by means of experimental tests carried out on a specifically developed ball screw drive test benchMinisterio de Economía y Competitividad: Project DPI2015-64450-R (MINECO/FEDER, UE) University of the Basque Country (UPV/EHU) under the program UFI 11/29 Departamento de Educación, Política Lingüística y Cultura” of the regional government of the Basque Country (IT949-16

Heuristic Solutions for Loading in Flexible Manufacturing Systems

Production planning in flexible manufacturing system deals with the efficient organization of the production resources in order to meet a given production schedule. It is a complex problem and typically leads to several hierarchical subproblems that need to be solved sequentially or simultaneously. Loading is one of the planning subproblems that has to addressed. It involves assigning the necessary operations and tools among the various machines in some optimal fashion to achieve the production of all selected part types. In this paper, we first formulate the loading problem as a 0-1 mixed integer program and then propose heuristic procedures based on Lagrangian relaxation and tabu search to solve the problem. Computational results are presented for all the algorithms and finally, conclusions drawn based on the results are discussed