Uses and applications of artificial intelligence in manufacturing

The purpose of the THESIS is to provide engineers and personnels with a overview of the concepts that underline Artificial Intelligence and Expert Systems. Artificial Intelligence is concerned with the developments of theories and techniques required to provide a computational engine with the abilities to perceive, think and act, in an intelligent manner in a complex environment. Expert system is branch of Artificial Intelligence where the methods of reasoning emulate those of human experts. Artificial Intelligence derives it\u27s power from its ability to represent complex forms of knowledge, some of it common sense, heuristic and symbolic, and the ability to apply the knowledge in searching for solutions. The Thesis will review : The components of an intelligent system, The basics of knowledge representation, Search based problem solving methods, Expert system technologies, Uses and applications of AI in various manufacturing areas like Design, Process Planning, Production Management, Energy Management, Quality Assurance, Manufacturing Simulation, Robotics, Machine Vision etc. Prime objectives of the Thesis are to understand the basic concepts underlying Artificial Intelligence and be able to identify where the technology may be applied in the field of Manufacturing Engineering

Introduction to IntelliSIM 1.0

IntelliSIM is a prototype for a new generation of knowledge-based simulation tool that has been developed by the Systems Simulation Laboratory at Arizona State University. This tool is a computer environment that allows non-simulation trained modelers to predict the performance of a manufacturing system for which the necessary data is available. The system provides predictive data on such items as throughput time, queue levels, equipment utilization, reactions to machine failures, etc. With IntelliSIM, the benefits of discrete-event simulation can be exploited without requiring the high level of expertise necessary to successfully conduct a sound simulation study. The approach offered with IntelliSIM is one which will offer substantial savings over currently available simulation tools. This document is Version 1 (1992) of the user manual for the IntelliSIM software

Introduction to IntelliSIM 1.0

IntelliSIM is a prototype for a new generation of knowledge-based simulation tool that has been developed by the Systems Simulation Laboratory at Arizona State University. This tool is a computer environment that allows non-simulation trained modelers to predict the performance of a manufacturing system for which the necessary data is available. The system provides predictive data on such items as throughput time, queue levels, equipment utilization, reactions to machine failures, etc. With IntelliSIM, the benefits of discrete-event simulation can be exploited without requiring the high level of expertise necessary to successfully conduct a sound simulation study. The approach offered with IntelliSIM is one which will offer substantial savings over currently available simulation tools. This document is Version 1 (1992) of the user manual for the IntelliSIM software

Advances in Computer Science and Engineering

The book Advances in Computer Science and Engineering constitutes the revised selection of 23 chapters written by scientists and researchers from all over the world. The chapters cover topics in the scientific fields of Applied Computing Techniques, Innovations in Mechanical Engineering, Electrical Engineering and Applications and Advances in Applied Modeling

Analysis of CIM performance using different LAN structures a simulation approach

This research illustrates a systematic procedure for modeling and performance analysis of the integration effect of communication network to the physical system. The concept is to model different layouts of Computer Integration Manufacturing (CIM) using different Local Area Network(LAN) structures. The steps to accomplish this concepts are, a) To determine the performance measures for physical layouts and the communication network, in order to obtain a performance analysis. b) Modeling the physical layout using Promodel simulation package. c) Extracting results from the outcome of the simulation of the physical layout and using this as input to the communication network simulation. d) Modeling the communication network using LNET simulation package. e) Comparing the output of each simulation run and determine which is most acceptable. Having different performance measures for both physical layout and networks, the proposed research objective is to illustrate the effectiveness of network structures on physical systems performance. Throughput, utilization, and delay are used as measures for both the physical layouts and network structures. Using these measures the optimum layout and network is selected

Bidirectional Electric Vehicles Service Integration in Smart Power Grid with Renewable Energy Resources

As electric vehicles (EVs) become more popular, the utility companies are forced to increase power generations in the grid. However, these EVs are capable of providing power to the grid to deliver different grid ancillary services in a concept known as vehicle-to-grid (V2G) and grid-to-vehicle (G2V), in which the EV can serve as a load or source at the same time. These services can provide more benefits when they are integrated with Photovoltaic (PV) generation. The proper modeling, design and control for the power conversion systems that provide the optimum integration among the EVs, PV generations and grid are investigated in this thesis. The coupling between the PV generation and integration bus is accomplished through a unidirectional converter. Precise dynamic and small-signal models for the grid-connected PV power system are developed and utilized to predict the system’s performance during the different operating conditions. An advanced intelligent maximum power point tracker based on fuzzy logic control is developed and designed using a mix between the analytical model and genetic algorithm optimization. The EV is connected to the integration bus through a bidirectional inductive wireless power transfer system (BIWPTS), which allows the EV to be charged and discharged wirelessly during the long-term parking, transient stops and movement. Accurate analytical and physics-based models for the BIWPTS are developed and utilized to forecast its performance, and novel practical limitations for the active and reactive power-flow during G2V and V2G operations are stated. A comparative and assessment analysis for the different compensation topologies in the symmetrical BIWPTS was performed based on analytical, simulation and experimental data. Also, a magnetic design optimization for the double-D power pad based on finite-element analysis is achieved. The nonlinearities in the BIWPTS due to the magnetic material and the high-frequency components are investigated rely on a physics-based co-simulation platform. Also, a novel two-layer predictive power-flow controller that manages the bidirectional power-flow between the EV and grid is developed, implemented and tested. In addition, the feasibility of deploying the quasi-dynamic wireless power transfer technology on the road to charge the EV during the transient stops at the traffic signals is proven

A line-balancing strategy for designing flexible assembly systems

We present a rough-cut analysis tool that quickly determines a few potential cost-effective designs at the initial design stage of flexible assembly systems (FASs) prior to a detailed analysis such as simulation. It uses quantitative methods for selecting and configuring the components of an FAS suitable for medium to high volumes of several similar products. The system is organized as a series of assembly stations linked with an automated material-handling system moving parts in a unidirectional flow. Each station consists of a single machine or of identical parallel machines. The methods exploit the ability of flexible hardware to switch almost instantaneously from product to product. Our approach is particularly suitable where the product mix is expected to be stable, since we combine the hardware-configuration phase with the task-allocation phase.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/45513/1/10696_2004_Article_BF00167513.pd

Production Systems with Deteriorating Product Quality : System-Theoretic Approach

Manufacturing systems with perishable products are widely seen in practice (e.g., food, metal processing, etc.). In such systems, the quality of a part is highly dependent on its residence time within the system. However, the behavior and properties of these systems have not been studied systematically, and, therefore, is carried out in this dissertation. Specifically, it was assumed that the probability that each unfinished part is of good quality is a decreasing function of its residence time in the preceding buffer. Then, in the framework of serial production lines with machines having Bernoulli and geometric reliability models, closed-form formulas for performance evaluation in the two-machine line case were derived, and develop an aggregation-based procedure to approximate the performance measures in M\u3e2-machine lines. In addition, the monotonicity properties of these production lines using numerical experiments were studied. A case study in an automotive stamping plant is described to illustrate the theoretical results obtained. Also, Bernoulli serial lines with controlled parts released was analyzed for both deterministic and stochastic releases. Finally, bottleneck analysis in Bernoulli serial lines with deteriorating product quality were studied