Introduction of programmable logic controller in industrial engineering curriculum

Recent trends in process control and industrial automation scenarios have resulted in the emergence of many pioneering techniques that have revolutionized the manufacturing industry. In order to maintain quality and precision, advances have been associated with the increasing use of microprocessors in process control applications. Most of the industrial process control systems utilize Programmable Logic Controllers (PLC). Also due to the increase in internet usage and recent innovations in PLC software, remote monitoring and PLC control of process through the internet is also a recent trend. This thesis presents course/lab material for integration in the Industrial Engineering curriculum. The course/lab content was designed to improve the student\u27s knowledge and to broaden the industrial engineering curriculum at West Virginia University (WVU). This thesis proposes the use of inexpensive T100MD+ PLCs. A traffic light control system was developed to introduce the fundamental concepts of Boolean algebra and real-time control. A series of control exercises can be carried on the traffic light system. A temperature sensitive system was also developed. Students can test various PID control strategies on this hardware/software platform. Students will also have the ability to control the process via the internet

FPGA fuzzy controller design for magnetic ball levitation

this paper presents a fuzzy controller design for nonlinear system using FPGA. A magnetic levitation system is considered as a case study and the fuzzy controller is designed to keep a magnetic object suspended in the air counteracting the weight of the object. Fuzzy controller will be implemented using FPGA chip. The design will use a high-level programming language HDL for implementing the fuzzy logic controller using the Xfuzzy tools to implement the fuzzy logic controller into HDL code. This paper, advocates a novel approach to implement the fuzzy logic controller for magnetic ball levitation system by using FPGA

Internet based data logging and supervisory control of boiler drum level using LabVIEW

This work describes a framework of a Internet based data logging and supervisory control of boiler drum level system. The design and implementation of this process is done by the LabVIEW software. The data of the process variables (Temperature and Level) from the boiler system need to be logged in a database for further analysis and supervisory control. A LabVIEW based data logging and supervisory control program simulates the process and the generated data are logged in to the database as text file with proper indication about the status of the process variable (normal or not normal. Three different types of boiler drum level control system are designed in the Circuit Design and Simulation toolkit of LabVIEW. This work provides the knowledge about the Fuzzy Adaptive PID Controller and the various PID controller design methods such as Zeigler-Nichol method, Tyreus-Luyben method, Internal Model Control (IMC). Comparative study is made on the performance of the PID and Fuzzy Adaptive PID controller for better control system design. The internet plays a significant and vital role in the real time control and monitoring of the industrial process. Internet based system control and monitor the plant system remotely from anywhere without any limitation to any geographical region. Internet based boiler control system is developed by a Web Publishing tool in LabVIEW. The use of internet as a communication medium provides the flexible and cost- effective solution. Now, to analyse the performance of boiler drum level control system, Internet based data logging and supervisory control system is designed. Hence, anyone can control and monitor the boiler plant globally

A novel hierarchical clustering algorithm for the analysis of 3D anthropometric data of the human head

In recent years, the use of 3D anthropometry for product design has become more appealing because of advances in mesh parameterisation, multivariate analyses and clustering algorithms. The purpose of this study was to introduce a new method for the clustering of 3D head scans. A novel hierarchical algorithm was developed, in which a squared Euclidean metric was used to assess the head shape similarity of participants. A linkage criterion based on the centroid distance was implemented, while clusters were created one after another in an enhanced manner. As a result, 95.0% of the studied sample was classified inside one of the four computed clusters. Compared to conventional hierarchical techniques, our method could classify a higher ratio of individuals into a smaller number of clusters, while still satisfying the same variation requirements within each cluster. The proposed method can provide meaningful information about the head shape variation within a population, and should encourage ergonomists to use 3D anthropometric data during the design process of head and facial gear