Accretion Control in Sponge Iron Production Kiln using Fuzzy Logic

Sponge iron is the product generated by direct reduction of iron ore with aid of either carbon or natural gas under controlled temperatures and pressures within a rotary kiln. However the performance of rotary kilns is usually adversely affected by the formation of accretion. This accumulation of sintered solid particles which form rings along the length of the kiln hinders material flow, lowers productivity and life span of the kiln. To maintain the quality of sponge iron and improve on performance of rotary kilns, there is need to minimize accretion build up in the kiln. However due to the nonlinear nature of the reduction process dynamics, it is difficult to control accretion build up in the kiln. This paper proposes the control of accretion build up through the application of Fuzzy Logic control. The controller receives partial and imprecise data from field instruments and is able to maintain product quality under dynamic process conditions. MATLAB Fuzzy-Toolbox was used to model and simulate the design. A comparison is made between the designed Fuzzy system and the PID controller. Simulation results show that it is possible to reduce accretion build up from 27 % when using PID controller to 14.6 % with the use of Fuzzy control. Keywords: Accretion, Fuzzy Logic, Kiln, Sponge iro

Modelling and design of the eco-system of causality for real-time systems

This thesis was submitted for the award of Doctor of Philosophy and was awarded by Brunel University London.The purpose of this research work is to propose an improved method for real-time sensitivity analysis (SA) applicable to large-scale complex systems. Borrowed from the EventTracker principle of the interrelation of causal events, it deploys the Rank Order Clustering (ROC) method to automatically group every relevant system input to parameters that represent the system state (i.e. output). The fundamental principle of event modelling is that the state of a given system is a function of every acquirable piece of knowledge or data (input) of events that occur within the system and its wider operational environment unless proven otherwise. It therefore strives to build the theoretical and practical foundation for the engineering of input data. The event modelling platform proposed attempts to filter unwanted data, and more importantly, include information that was thought to be irrelevant at the outset of the design process. The underpinning logic of the proposed Event Clustering technique (EventiC) is to build causal relationship between the events that trigger the inputs and outputs of the system. EventiC groups inputs with relevant corresponding outputs and measures the impact of each input variable on the output variables in short spans of time (relative real-time). It is believed that this grouping of relevant input-output event data by order of its importance in real-time is the key contribution to knowledge in this subject area. Our motivation is that components of current complex and organised systems are capable of generating and sharing information within their network of interrelated devices and systems. In addition to being an intelligent recorder of events, EventiC could also be a platform for preliminary data and knowledge construction. This improvement in the quality, and at times the quantity of input data, may lead to improved higher level mathematical formalism. It is hoped that better models will translate into superior controls and decision making. It is therefore believed that the projected outcome of this research work can be used to predict, stabilize (control), and optimize (operational research) the work of complex systems in the shortest possible time. For proof of concept, EventiC was designed using the MATLAB package and implemented using real-time data from the monitoring and control system of a typical cement manufacturing plant. The purpose for this deployment was to test and validate the concept, and to demonstrate whether the clusters of input data and their levels of importance against system performance indicators could be approved by industry experts. EventiC was used as an input variable selection tool for improving the existing fuzzy controller of the plant. Finally, EventiC was compared with its predecessor EventTracker using the same case study. The results revealed improvements in both computational efficiency and the quality of input variable selection

Effect of Fuel Mixture on Cement Production: A Case Study of BUA Plant. Cement Production Optimization with change in Specific surface area (0.35cm2/g and 0.38cm2/g). Using Particle Swarm Optimization model.

Ordinary Portland cement industries have been using co-processing from industrial waste. These paper present opportunities of using both Conventional fuel and Agricultural waste for cement production optimization an in-depth analysis on effect of using conventional fuel (mineral coal, pet-coke, Heavy oil and Natural gas) and Agricultural waste (sugar waste and ground nut shell). This mixture is intended for use in a rotary kiln of clinker production, dry process. The optimization model used was Particle Swarm Optimization (PSO). The change in the specific surface area(S) from 0.35cm2/g to 0.38cm2/g of the final product (cement), this  resulted into slight increased the energy consumption, more retention time, reduction in production output, increased wear rate on mill liners. Keywords: Fuel mixture, Cement quality, Environmental effect

Green Technologies for Production Processes

This book focuses on original research works about Green Technologies for Production Processes, including discrete production processes and process production processes, from various aspects that tackle product, process, and system issues in production. The aim is to report the state-of-the-art on relevant research topics and highlight the barriers, challenges, and opportunities we are facing. This book includes 22 research papers and involves energy-saving and waste reduction in production processes, design and manufacturing of green products, low carbon manufacturing and remanufacturing, management and policy for sustainable production, technologies of mitigating CO2 emissions, and other green technologies

Performance Targets in Production Processes (PT-PRO)

One of the main actions of the European Environmental Technologies Action Plan (ETAP) is: ¿Setting ambitious targets to improve the environmental performance of technologies within a given timeframe. This should encourage technological development while preparing the markets to accept and prepare for these high standard environmental technologies¿. On request of DG Environment, the JRC-IPTS launched a project on Performance Targets for Industry Processes (PT-PRO project), with the objective to further define concepts and to identify the conditions necessary to implement the concept of Performance Targets. The project was carried out with the help of ITA, ÖAW, GMV/IVL, FEA and TNO. This report provides a definition of the main elements of Performance Targets and an overview of the general principles for their implementation. Based on four case study sectors (the iron & steel, cement, pulp & paper and the textile industries), an illustration of these different elements is provided in relation with a range of industry sectors and their environmental challenges, existing regulations, technical potentials, market situations and organisational structure. The report also discusses the best conditions and limitations of setting Performance Targets for the industry and the possible value-added.JRC.J.2-Competitiveness and Sustainabilit

Design of Fuzzy Controllers for Embedded Systems With JFML

Fuzzy rule-based systems (FRBSs) have been successfully applied to a wide range of real-world problems. However, they suffer from some design issues related to the difficulty to implement them on different hardware platforms without additional efforts. To bridge this gap, recently, the IEEE Computational Intelligence Society has sponsored the publication of the standard IEEE Std 1855-2016 which is aimed at providing the fuzzy community with a well-defined approach to model FRBSs in a hardwareindependent way. In order to provide a runnable version of an FRBS that is designed in accordance with the IEEE Std 1855-2016, the open source library Java Fuzzy Markup Language (JFML) has been developed. However, due to hardware and/or software limitations of embedded systems, it is not always possible to run an IEEE Std 1855-2016 FRBS on this kind of systems. The aim of this paper is to overcome this drawback by developing a new JFML module that assists developers in the design and implementation of FRBSs for open hardware–embedded systems. In detail, the module supports several connection types (WiFi, Bluetooth, and USB) in order to make feasible running FRBSs in a remote computer when, due to hardware limitations, it is not possible that they run locally in the embedded systems. The new JFML module is ready for ArduinoTM and Raspberry Pi, but it can be easily extended to other hardware architectures. Moreover, the new JFML module allows to automatically generate runnable files on ArduinoTM or Raspberry Pi in order to support nonexpert users, that is, users without specific knowledge about embedded systems or without strong programming skills. The use of the new JFML module is illustrated in two case studies.This paper has been supported in part by the Spanish Ministry of Economy and Competitiveness (Projects TIN2017-89517-P, TIN2015-68454-R, TIN2017-84796-C2-1-R, and TIN2017-90773-REDT) and the Andalusian Government. In addition, Jose M. Alonso is Ramon y Cajal Researcher (RYC-2016-19802). Financial support from the Galician Ministry of Education (grants ED431F 2018/02, GRC2014/030 and accreditation 2016-2019, ED431G/08), co-funded by the European Regional Development Fund (ERDF/FEDER program), is also gratefully acknowledged

HR Selection Distortions: A theoretical framework for the Fiji Public Service

Despite being frequently perceived as a pertinent issue necessary to critically examine how incumbents are selected on merit, HR selection distortions is typically illdefined and poorly explained in much debate, hence, more precision in terms of contextualization of practice is needed. Through explaining and synthesizing the work of a number of scholars from different disciplines, the paper develops a theoretical framework for a meta- analysis, which begins with an exploration of the relationship between HR selection, networking and relational ties, employee’s justice perceptions, group heterogeneity and worker performance in Fiji’s public service institutions. The theoretical framework provides the leeway for the research questions to be answerable and the postulated hypotheses testable. However, more needs to be done to explain not only the nature and emergence of HR selection distortions but also the very real problems it faces in sustaining itself, let alone transforming the hiring processes in Fiji’s public service. The value of the paper lies in its theoretical innovation, drawing on a range of disciplines, and its attempt to situate HR selection distortions precisely, conceptually, theoretically, and practically