Assessment of the Hunter Valley Coal Export Supply Chain

We develop a decision support tool that assesses the throughput of a coal export supply chain for a given level of demand. The tool can be used to rapidly evaluate a number of infrastructures for several future demand scenarios in order to identify a few that should be investigated more thoroughly using a detailed simulation model. To make the natural model computationally tractable, we exploit problem structure to reduce the model size, and we employ aggregation as well as disaggregation to strengthen the structure of model. We use the tool in a computational study in which we analyze system performance for different levels of demand to identify potential bottlenecks

Coal Handling System-Its Performance Monitoring & Suggestive Measures for Improvements

The coal handling process involves a number of activities from loading and unloading to stockpile. This procedure can be carried out by coal conveying system which includes a large number of mechanical equipment. The important activities under coal handling include loading/unloading, dumping, transporting etc. which are done with the help of various mechanical equipment. Every organization wants to profit as much as possible and increases their production rate by using maximum effort for care and maintain. And it is possible if the equipment is running in good condition with zero breakdowns, zero accident, and zero wastage. This research work presents a practical analysis for monitoring the operational performance of equipment, which shows the two additional objectives: the first one is the identification of major causes of production losses which are born from malfunctions, breakdowns, and bad operating programme. And the second one is the implementation of a suitable and appropriate methodology for improvement of coal handling systems, which handling the coal from bunker to stockyard within an industry. The data are analyzed and compared with World class to Obtained OEE. During the operation, many reasons are there, which affect the production rate called six big losses. To minimize the six big losses and improve productivity, an accurate effective estimation of equipment is necessary and offers a suitable methodology. For the purpose of the study, a case study methodology is applied in order to analyze in the depth of maintenance in a real context. The primary focus of this research work is to monitor the equipment performance in coal handling plants and its contribution to the company for overall operation. The OEE data are recorded through tables and compared to world class OEE considering the operational losses and also performance reports are briefly analyzed through figures in terms of equipment failures in different locations, idle time for materials, operators and speed loss time for minor stoppages like sensor blocked, cleaning/checking or component jamming. For minimizing the downtime and promote productivity, a suitable methodology is developed through tables for determining the status of coal handling equipment viz. Tippler, Side arm charger, Reversible apron feeder, Belt conveyor system, Stacker, Reclaimer. This research work deals with the quantitative measurement of equipment performance in coal handling plant, which defines losses for many reasons. As a result, valuable information is provided concerning the performance monitoring of production equipment and implementing a suitable methodology for improvement of coal handling machinery operations viz tippler, side arm charger, reversible apron feeder, belt conveyor, stacker, reclaimer. Introduce the estimation and evaluation of OEE procedure which is highly valid and accurate performance indicator and has become very popular in all the industries starting from mining area for excavation of material to harbour area for material handling. OEE shows a right metrics to analyze the ordinary issue and improving the whole process. There are many formulas, systems and metrics being used to improve the whole production process, but one and only OEE reduces complex problem into easy. The biggest advantage of OEE allows companies to have separate business functions by applying a single easy to understand the formula. OEE is by far the most effective benchmarking tool in making sound management and maintenance decisions. The dissertation concludes with a summary of the contribution and the scope of further work

Factors affecting vessel turnaround time at the port of Richards Bay dry bulk terminal.

Masters Degree. University of KwaZulu-Natal, Durban.Abstract available in PDF

Application of the Lean Philosophy to reduce Carbon Emissions in the Precast Concrete Industry of Singapore

Ph.DDOCTOR OF PHILOSOPH

Historia, evolución y perspectivas de futuro en la utilización de técnicas de simulación en la gestión portuaria: aplicaciones en el análisis de operaciones, estrategia y planificación portuaria

Programa Oficial de Doutoramento en Análise Económica e Estratexia Empresarial. 5033V0[Resumen] Las técnicas de simulación, tal y como hoy las conocemos, comenzaron a mediados del siglo XX; primero con la aparición del primer computador y el desarrollo del método Monte Carlo, y más tarde con el desarrollo del primer simulador de propósito específico conocido como GPS y desarrollado por Geoffrey Gordon en IBM y la publicación del primer texto completo dedicado a esta materia y llamado the Art of Simulation (K.D. Tocher, 1963). Estás técnicas han evolucionado de una manera extraordinaria y hoy en día están plenamente implementadas en diversos campos de actividad. Las instalaciones portuarias no han escapado de esta tendencia, especialmente las dedicadas al tráfico de contenedores. Efectivamente, las características intrínsecas de este sector económico, le hacen un candidato idóneo para la implementación de modelos de simulación con propósitos y alcances muy diversos. No existe, sin embargo y hasta lo que conocemos, un trabajo científico que compile y analice pormenorizadamente tanto la historia como la evolución de simulación en ambientes portuarios, ayudando a clasificar los mismos y determinar cómo estos pueden ayudar en el análisis económico de estas instalaciones y en la formulación de las oportunas estrategias empresariales. Este es el objetivo último de la presente tesis doctoral.[Resumo] As técnicas de simulación, tal e como hoxe as coñecemos, comezaron a mediados do século XX; primeiro coa aparición do computador e o desenvolvemento do método Monte Carlo e máis tarde co desenvolvemento do primeiro simulador de propósito específico coñecido como GPS e desenvolvido por Geoffrey Gordon en IBM e a publicación do primeiro texto completo dedicado a este tema chamado “A Arte da Simulación” (K.D. Tocher, 1963). Estas técnicas evolucionaron dun xeito extraordinario e hoxe en día están plenamente implementadas en diversos campos de actividade. As instalacións portuarias non escaparon desta tendencia, especialmente as dedicadas ao tráfico de contenedores. Efectivamente, as características intrínsecas deste sector económico, fanlle un candidato idóneo para a implementación de modelos de simulación con propósitos e alcances moi variados. Con todo, e ata o que coñecemos, non existe un traballo científico que compila e analiza de forma detallada tanto a historia como a evolución da simulación en estes ambientes portuarios, clasificando os mesmos e determinando como estes poden axudar na análise económica destas instalacións e na formulación das oportunas estratexias empresariais. Este é o último obxectivo da presente tese doutoral.[Abstract] Simulation, to the extend that we understand it nowadays, began in the middle of the 20th century; first with the appearance of the computer and the development of the Monte Carlo method, and later with the development of the first specific purpose simulator known as GPS developed by Geoffrey Gordon in IBM. This author published the first full text devoted to this subject “The Art of Simulation” in 1963. These techniques have evolved in an extraordinary way and nowadays they are fully implemented in different fields of activity. Port facilities have not escaped this trend, especially those dedicated to container traffic. Indeed, the intrinsic characteristics of this economic sector, make it a suitable candidate for the implementation of simulation with very different purposes and scope. However, to the best of our knowelegde, there is not a scientific work that compiles and analyzes in detail both, the history and the evolution of simulation in port environments, contributing to classify them and determine how they can help in the economic analysis of these facilities and in the formulation of different business strategies. This is the ultimate goal of this doctoral thesis

Adding multi-objective optimisation capability to an electricity utility energy flow simulator

Thesis (MEng)--Stellenbosch University, 2016.ENGLISH ABSTRACT: The energy flow simulator (EFS) is a strategic decision support tool that was developed for the South African national electricity utility Eskom. The advanced set of algorithms incorporated into the EFS enables various departments within Eskom to simulate and analyse the Eskom value chain from primary energy to end-use over a certain study horizon. The research in this thesis is aimed at determining whether multi-objective optimisation (MOO) capability can be added to the EFS. The study forms part of a series of research projects. This project builds on the work of Hatton (2015) in which the focus was on single-objective optimisation capability for the EFS. Inventory management at Eskom's coal- red power stations was identified as the most suitable area for the formulation of an MOO model. It was also identified that certain modifications to the existing EFS architecture can possibly improve its potential as an optimisation tool. The architecture of the EFS is studied and modifications to it are proposed. A multi-objective inventory model is then formulated for Eskom's network of coal- red power stations using the simulation outputs of the EFS. The model is based on the movement of coal between the various power stations in an attempt to maintain an optimal inventory level at each station as far as possible. To solve the model, a suitable MOO algorithm is selected and integrated with the simulation component of the EFS. Several experiments are conducted to validate the MOO model and test the e effectiveness of the algorithm in solving the optimisation problem.AFRIKAANSE ABSTRACT: Die energievloei-simulator (EVS) is 'n strategiese besluitondersteuningsinstrument wat ontwikkel is vir die Suid-Afrikaanse nasionale elektrisiteitsverskaffer, Eskom. Die gevorderde stel algoritmes waaruit die EVS bestaan stel verskeie departemente binne Eskom in staat om die Eskom-waardeketting te simuleer en te analiseer, vanaf prim^ere energie tot eindgebruik, oor 'n sekere studie tydperk. Die navorsing in hierdie tesis is daarop gemik om te bepaal of meerdoelige optimeringsvermo e tot die EVS bygevoeg kan word. Die studie vorm deel van 'n reeks navorsingsprojekte. Hierdie projek bou voort op die werk van Hatton (2015) waarin die fokus op enkeldoel-optimeringsvermo e vir die EVS was. Voorraadbestuur by Eskom se steenkoolaangedrewe kragstasies is geidentifiseer as die mees geskikte gebied vir die formulering van 'n meerdoelige optimeringsmodel. Daar is ook geidentifiseer dat sekere veranderinge aan die bestaande argitektuur van die EVS moontlik die model se potensiaal as 'n optimeringsinstrument kan verbeter. Die argitektuur van die EVS word bestudeer en veranderinge daaraan word voorgestel. 'n Meerdoelige voorraadbestuursmodel word daarna vir Eskom se netwerk van steenkoolaangedrewe kragstasies geformuleer deur die simulasie-uitsette van die EVS te gebruik. Die model is gebaseer op die beweging van steenkool tussen die verskillende kragstasies om 'n optimale voorraadvlak by elke stasie te probeer handhaaf. Om die model op te los word 'n geskikte meerdoelige optimeringsalgoritme gekies en met die EVS se simulasie komponent geintegreer. Verskeie eksperimente word uitgevoer om te bevestig dat die meerdoelige optimeringsmodel korrek is en om die doeltreffendheid van die algoritme as oplossingsmetode vir die probleem te toets

Business improvement through a structured approach to sustainability in the precast concrete flooring industry

Different production and business procurement systems in the precast flooring industry have traditionally been designed to offer products/services with high quality, within shorter delivery times, and with the lowest cost and expense possible. However, these systems do not account for the different environmental impacts arising from its operations. This thesis explores the environmental performance of precast concrete production systems and evaluates how precast organisations can maintain their business cases within a healthy and sustainable approved practice. A Life Cycle Assessment (LCA) study was carried out for five Hollowcore and pre-stressed beams manufacturers (members of the Precast Flooring Federation—PFF) to identify the main environmental impacts arising from the production of precast flooring. It was found that mineral extraction, carbon dioxide emissions, waste disposal, and transportation are the main sources of environmental impact in the sector. [Continues.

13th International Conference on Modeling, Optimization and Simulation - MOSIM 2020

Comité d’organisation: Université Internationale d’Agadir – Agadir (Maroc) Laboratoire Conception Fabrication Commande – Metz (France)Session RS-1 “Simulation et Optimisation” / “Simulation and Optimization” Session RS-2 “Planification des Besoins Matières Pilotée par la Demande” / ”Demand-Driven Material Requirements Planning” Session RS-3 “Ingénierie de Systèmes Basées sur les Modèles” / “Model-Based System Engineering” Session RS-4 “Recherche Opérationnelle en Gestion de Production” / "Operations Research in Production Management" Session RS-5 "Planification des Matières et des Ressources / Planification de la Production” / “Material and Resource Planning / Production Planning" Session RS-6 “Maintenance Industrielle” / “Industrial Maintenance” Session RS-7 "Etudes de Cas Industriels” / “Industrial Case Studies" Session RS-8 "Données de Masse / Analyse de Données” / “Big Data / Data Analytics" Session RS-9 "Gestion des Systèmes de Transport” / “Transportation System Management" Session RS-10 "Economie Circulaire / Développement Durable" / "Circular Economie / Sustainable Development" Session RS-11 "Conception et Gestion des Chaînes Logistiques” / “Supply Chain Design and Management" Session SP-1 “Intelligence Artificielle & Analyse de Données pour la Production 4.0” / “Artificial Intelligence & Data Analytics in Manufacturing 4.0” Session SP-2 “Gestion des Risques en Logistique” / “Risk Management in Logistics” Session SP-3 “Gestion des Risques et Evaluation de Performance” / “Risk Management and Performance Assessment” Session SP-4 "Indicateurs Clés de Performance 4.0 et Dynamique de Prise de Décision” / ”4.0 Key Performance Indicators and Decision-Making Dynamics" Session SP-5 "Logistique Maritime” / “Marine Logistics" Session SP-6 “Territoire et Logistique : Un Système Complexe” / “Territory and Logistics: A Complex System” Session SP-7 "Nouvelles Avancées et Applications de la Logique Floue en Production Durable et en Logistique” / “Recent Advances and Fuzzy-Logic Applications in Sustainable Manufacturing and Logistics" Session SP-8 “Gestion des Soins de Santé” / ”Health Care Management” Session SP-9 “Ingénierie Organisationnelle et Gestion de la Continuité de Service des Systèmes de Santé dans l’Ere de la Transformation Numérique de la Société” / “Organizational Engineering and Management of Business Continuity of Healthcare Systems in the Era of Numerical Society Transformation” Session SP-10 “Planification et Commande de la Production pour l’Industrie 4.0” / “Production Planning and Control for Industry 4.0” Session SP-11 “Optimisation des Systèmes de Production dans le Contexte 4.0 Utilisant l’Amélioration Continue” / “Production System Optimization in 4.0 Context Using Continuous Improvement” Session SP-12 “Défis pour la Conception des Systèmes de Production Cyber-Physiques” / “Challenges for the Design of Cyber Physical Production Systems” Session SP-13 “Production Avisée et Développement Durable” / “Smart Manufacturing and Sustainable Development” Session SP-14 “L’Humain dans l’Usine du Futur” / “Human in the Factory of the Future” Session SP-15 “Ordonnancement et Prévision de Chaînes Logistiques Résilientes” / “Scheduling and Forecasting for Resilient Supply Chains